Methodological manual for statistics on the information society.
Date: 2006-12-11
Institutions: Eurostat
Subjects: EU statistics, industrial statistics, information society, statistical method

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Methodological
manual for
statistics on the
nformation Society
l

E U R O P E A N
C O M M I S S I O N

THEME
Industry, trade
and services

 
 
 
 
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ISBN 92-79-02645-3
ISSN 1725-0099

© European Communities, 20 60

Methodological Manual 
for statistics on the  
Information Society 

Survey year 2006, v2.0 

E U R O P E A N  

C O M M I S S I O N  

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Methodological manual for statistics on the Information Society 

implementation  of  Art.  5  of  Regulation  (EC)  No  808/2004  of 

the  European  Parliament  and  of  the  Council  of  21  April  2004 

concerning Community statistics on the information society (OJ 

L143, 30.04.2004, p. 49) 

Published by Eurostat 

Version 2.0, April 2006 

This  publication  has  been  prepared  by  Unit  F6  “Information  Society  Statistics  and 

Services” of Eurostat. The opinions expressed are those of the authors alone and do 

not necessarily reflect the position of the European Commission. 

Eurostat would like to thank the national statistical institutes who contributed to this 

publication: 

Part I:  Wolfgang Hauschild (Statistisches Bundesamt, DE), Martin Lundo (Danmarks 

Statistik,  DK),  Alessandra  Nurra  and  Adolfo  Nascia  (ISTAT, IT),  Andries 

Kuipers  (Centraal  Bureau  voor  de  Statistiek,  NL),  Aarno  Airaksinen 

(Statistikcentralen,  FI),  Eric  Hellsing  (Statistiska  centralbyrån,  SE),  Mark 

Pollard  (Office for  National  Statistics,  UK),  Geir  Martin  Pilskog  (Statistisk 

sentralbyrå, NO), Sheridan Roberts (OECD). 

Part II: Henrik Lynge Hansen (Danmarks Statistik, DK), Adolfo Morrone (ISTAT, IT), 

Andreas  Schiefer  (Bundesanstalt  Statistik  Österreich,  AT),  Anders  Hintze 

(Statistiska  centralbyrån,  SE),  Elaine  Chamberlain  (Office for  National 

Statistics, UK), Håkon Rød (Statistisk sentralbyrå, NO). 

Contact 

Part I:  Fernando Reis (Eurostat, Unit F6), - General enterprise survey 

+352 4301 36568 

fernando.reis@cec.eu.int 

Heidi Seybert (Eurostat, Unit F6), - Financial sector 

+352 4301 37416 

Heidi.seybert@cec.eu.int 

Part II: Christophe Demunter (Eurostat, Unit F6),  

+352 4301 36565 

christophe.demunter@cec.eu.int 

Reproduction is authorised, except for commercial purposes, provided the source is acknowledged 

Methodological manual for Information Society Statistics 

2  

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Table of contents 

Table of contents .................................................................................................................. 3 

Preface ................................................................................................................................ 7 

Part I 

Enterprise survey .................................................................................................. 9 

I.1. 

Statistical product .................................................................................................11 

I.1.1. 

I.1.2. 

I.1.3. 

I.1.4. 

I.1.5. 

I.1.6. 

Statistical unit ...........................................................................................11 

Target population.......................................................................................12 

Periodicity .................................................................................................13 

Observation variables .................................................................................13 

Summary measures, aggregated variables, indicators and tabulation ...............15 

Explanatory notes ......................................................................................16 

I.1.6.1  Module A: Access to Information and Communication Technologies ...16 

I.1.6.2  Module B: Use of Internet ............................................................24 

I.1.6.3  Module C: e-commerce via Internet...............................................35 

I.1.6.4  Module D: e-commerce via computer networks other than Internet...41 

I.1.6.5  Module X: Background Information ...............................................43 

I.1.7. 

Enterprises of the financial sector ................................................................50 

I.1.7.1 

Observation variables for the financial sector..................................50 

I.1.7.2 

Explanatory notes .......................................................................50 

I.1.7.2.1.  Module  A:  Access  to  Information  and  Communication 
Technologies ..............................................................................51 

I.1.7.2.2.  Module C: E-Commerce via Internet .............................51 

I.1.7.2.3.  Module  D:  E-Commerce  via  computer  mediated  networks 
other than Internet (optional).......................................................57 

I.1.7.2.4.  Module X: Background Information ..............................59 

I.2. 

Production methodology.........................................................................................62 

I.2.1. 

I.2.2. 

I.2.3. 

Timetable – Survey period ..........................................................................62 

Frame population .......................................................................................63 

Sampling design ........................................................................................64 

Methodological manual for Information Society Statistics 

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I.2.4. 

I.2.5. 

I.2.6. 

I.2.7. 

I.2.3.1 

Stratification...............................................................................69 

I.2.3.2 

Sample size................................................................................71 

I.2.3.3  Weighting – Grossing up methods .................................................73 

Survey type ..............................................................................................77 

Questionnaire – Data collection tool .............................................................80 

Quality control systems ..............................................................................81 

Data processing .........................................................................................84 

I.2.7.1  Misclassification treatment ...........................................................84 

I.2.7.2 

Non-response treatment ..............................................................85 

Unit non-response.......................................................................86 

Item non-response......................................................................88 

I.2.7.3 

Computing accuracy measures......................................................89 

I.2.8. 

Survey execution reports ............................................................................90 

I.3. 

Annexes ...............................................................................................................91 

I.3.1. 

I.3.2. 

I.3.3. 

I.3.4. 

Model questionnaire for non-financial economic activities ................................91 

Model questionnaire for the financial sector ...................................................95 

Transmission format.................................................................................101 

Reporting template ..................................................................................102 

Part II 

Household survey ...............................................................................................103 

II.1.  Statistical product ...............................................................................................105 

II.1.1. 

II.1.2. 

II.1.3. 

II.1.4. 

II.1.5. 

II.1.6. 

Statistical unit .........................................................................................105 

Target population.....................................................................................106 

Periodicity ...............................................................................................107 

Observation variables ...............................................................................107 

Summary measures, aggregated variables, indicators and tabulation .............107 

Explanatory notes ....................................................................................108 

II.1.6.1  Module A: Access to Information and Communication Technologies .109 

II.1.6.2  Module B: Use of mobile phone and computers, location and frequency 
of use 

114 

II.1.6.3  Module C: Use of the Internet.....................................................118 

II.1.6.4  Module D: e-Government ...........................................................126 

II.1.6.5  Module E: Internet commerce details: activities and barriers ..........131 

II.1.6.6  Module F: e-Skills .....................................................................136 

II.1.6.7  Module G: Socio-demographic background variables .....................139 

Methodological manual for Information Society Statistics 

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II.2. 

Production methodology.......................................................................................151 

II.2.1. 

II.2.2. 

II.2.3. 

II.2.4. 

II.2.5. 

II.2.6. 

II.2.7. 

Timetable – Survey period ........................................................................151 

Frame population .....................................................................................153 

Sampling design ......................................................................................156 

II.2.3.1  Stratification.............................................................................162 

II.2.3.2  Sample size..............................................................................162 

II.2.3.3  Weighting – Grossing up methods ...............................................164 

Survey type ............................................................................................164 

Questionnaire – Data collection tool ...........................................................168 

Quality control systems ............................................................................169 

Data processing .......................................................................................171 

II.2.7.1  Misclassification treatment .........................................................171 

II.2.7.2  Non-response treatment ............................................................171 

Unit non-response.....................................................................172 

Item non-response....................................................................174 

I.1.1.1 

Computing accuracy measures....................................................178 

II.2.8. 

Survey execution reports ..........................................................................181 

II.3.  Annexes .............................................................................................................183 

II.3.1. 

II.3.2. 

II.3.3. 

Model questionnaire .................................................................................183 

Transmission format.................................................................................194 

Reporting template ..................................................................................195 

Part III 

EU Legislation ....................................................................................................197 

III.1.  Regulation  (EC)  No  808/2004  of  the  European  Parliament  and  of  the  Council  of  21  April 
2004 concerning Community statistics on the information society .............................199 

III.2.  Commission Regulation (EC) No 1099/2005 of 13 July 2005 implementing Regulation (EC) 
No  808/2004  of  the  European  Parliament  and  of  the  Council  concerning  Community 
statistics on the information society ......................................................................200 

Methodological manual for Information Society Statistics 

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Preface 

Information  and  Communications  Technologies  (ICT)  are  still  the  main  drivers  of  the  economy 

and of changes within society. Official statistics are indispensable for an informed understanding 

of the implications of the transformations underway. However, the right set of variables is crucial. 

The measurement of the Information Society by statistics on society, on business processes and 

productivity is an area for continuous revision and improvement. 

From  2002  the  European  Commission  established  annual  Information  Society  surveys  to 

benchmark the ICT-driven development in enterprises and by individuals. Eurostat developed two 

model surveys, one on enterprises, one on individuals, in close collaboration with Member States 

and  the  OECD,  which  have  been  regularly  adapted  to  the  changing  needs  of  users  and  policy 

makers.  These  model  surveys  are  composed  of  model  questionnaires  and  accompanying 

methodological  guidelines  for  their  implementation.  In  2004  the  European  Parliament  and  the 

Council  adopted  Regulation  (EC)  No  808/2004  covering  the  above  mentioned  surveys.  That 

regulation  is  a  framework  regulation:  it  allows  flexibility  to  adapt the  surveys  to  newly  evolving 

needs  by  users  and  decision  makers.  Annual  implementing  measures  such  as  Commission 

Regulation  (EC)  No  1099/2005  for  the  survey  year  2006  are  forming  the  basis  for  the  Eurostat 

model surveys and will ensure harmonized data for all EU-25 Member States until 2010. 

The  current  version  of  the  methodological  manual  is  drawn  up  as  a  tool  for  helping  national 

statistical  institutes  (NSI)  to  translate  the  two  Eurostat  model  questionnaires  into  national 

languages  and  to  implement  the  national  surveys  following  a  harmonised  methodology.  It  is  a 

hands-on tool with recommended guidelines and does not replace statistical handbooks. Its main 

focus is on explanatory notes to the variables and attributes of the model questionnaires for the 

year  2006.  Colleagues  from  the  NSI  and  from  OECD  contributed  substantially  and  helped 

Eurostat  to  finish  it.  Annexes  with  the  model  questionnaires,  the  transmission  formats  and  the 

reporting templates as well as the legal background documents are included. 

The concept of this methodological manual is to use it as a rolling document.  Certain areas are 

covered  at  length,  others  would  need  some  additional  input,  so  it  is  far  from  being  exhaustive. 

Nevertheless we went public to provide this tool to those who are struggling with data collection 

and interviewing for the 2006 survey wave. Any proposal to the authors to improve the manual is 

welcome, also from interested readers outside the European Community, in view of reaching for 

harmonized information society statistics at global level. 

Hartmut Buchow 

Information Society Statistics 

Methodological manual for Information Society Statistics 

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Part I 

Enterprise survey 

Methodological manual for Information Society Statistics 

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I.1. 

STATISTICAL PRODUCT 

The  statistical  product  is  the  clear  and  precise  definition  of  the  statistical  information  to  be 

produced. It distinguishes itself from the production methodology. The production methodology is 

the  way  or  method  of  doing,  while  the  statistical  product  is  its  direct  result.  Different  statistical 

methodologies  can  produce  the  same  statistical  product,  being  only  different  ways  of  doing  the 

same  thing.  This  means  that  as  long  as  we  guarantee  that  two  figures  concern  the  same 

statistical  product,  for  instance  for  two  different  countries,  they  are  comparable.  This  way,  this 

distinction  between  the  statistical  product  and  the  statistical  methodology  helps  us  to  focus  on 

those  elements  more  important  to  assure  comparability  between  the  several  national  statistics 

and produce new ones at the EU level, i.e. the statistical product, while leaving to the discretion 

of the national statistical institutes the choice of the better statistical methodology to be applied 

in its own country taking into consideration its own specificities. 

The elements that make up the statistical product, at an input level, are the statistical unit, the 

target population and the observation variables, and at the output level, the periodicity and the 

summary  measures,  aggregate  variables  and  tabulation.  Covering  all  the  elements  of  the 

statistical  product,  the  statistical  concepts  and  the  nomenclatures  are  the  additional  needed 

element to assure harmonization and comparability of statistics. 

I.1.1. Statistical unit 

The  statistical  unit  is  the  base  type  of  the  elements  of  a  group  (also  called  population)  that  we 

want  to  observe  or  analyse.  The  basic  statistical  operations  of  classification,  aggregation  and 

ordering are done on the statistical unit. 

The  choice  of  the  statistical  unit  is  a  matter  of  both  the  data  collection  process  (namely  the 

operational  restrictions  associated  to  collecting  data  from  each  type  of  statistical  unit)  and  the 

conceptual framework chosen to observe and analyse the phenomenon. The statistical unit is the 

bearer of statistical characteristics or attributes, which we ultimately want to measure. 

There are several types of statistical units, according to its usage. An observation unit represents 

an identifiable entity, about which data can be obtained. During the collection of data, this is the 

unit for which data is recorded. It should be noted that this may, or may not be, the same as the 

reporting  unit.  The  reporting  unit  is  the  unit  that  reports  to  the  survey  authority.  It  reports 

information for the observation unit(s). In certain cases it may be different from the observation 

unit. A reporting unit is a unit that supplies the data for a given survey instance. 

The  observation  statistical  unit  in  the  “Community  Survey  on  ICT  usage  and  e-Commerce  in 

Enterprises” is the enterprise, as defined in the Council Regulation (EEC) No 696/93 of 15 March 

1993  on  the  statistical  units  for  the  observation  and  analysis  of  the  production  system  in  the 

Community defines a list of statistical units: 

“The  enterprise  is  the  smallest  combination  of  legal  units  that  is  an  organizational  unit 

producing goods or services, which benefits from a certain degree of autonomy in decision-

making, especially for the allocation of its current resources. An enterprise carries out one 

or more activities at one or more locations. An enterprise may be a sole legal unit.” 

The  enterprise  thus  defined  is  an  economic  entity  which  can  therefore,  under  certain 

circumstances, correspond to a grouping of several legal units. Some legal units, in fact, perform 

Methodological manual for Information Society Statistics 

11  

 
 
activities  exclusively  for  other  legal  units  and  their  existence  can  only  be  explained  by 

administrative  factors  (e.  g.  tax  reasons),  without  them  being  of  any  economic  significance.  A 

large  proportion  of  the  legal  units  with  no  persons  employed  also  belong  to  this  category.  In 

many cases, the activities of these legal units should be seen as ancillary activities of the parent 

legal  unit  they  serve,  to  which  they  belong  and  to  which  they  must  be  attached  to  form  an 

enterprise used for economic analysis. 

However,  the  definition  of  the  enterprise  as  the  appropriate  statistical  unit  poses  some 

limitations.  Some  enterprises,  especially  the  larger  ones,  are  composed  of  several  local  units 

(establishment). Because of this, a geographical breakdown of the results (although still possible 

using  the  local  of  the  main  headquarters  of  the  enterprise)  is  of  limited  use.  Nevertheless,  ICT 

usage is not easy to attribute to the different establishments of an enterprise, and for this reason 

the enterprise is the statistical unit adopted. 

I.1.2. Target population 

A population is a collection of objects of the same class, which in statistical terms means a group 

of  elements  of  the  same  statistical  unit.  There  are  two  types  of  populations  to  be  considered 

when producing statistics: the target population and the frame population. 

The target  population is the population of interest. It is defined by delimiting clearly the group 

of  statistical  elements  for  which  some  information  concerning  the  all  group  we  want  to  know. 

That delimitation is based on one or more attributes of the statistical unit. For example, for the 

enterprise,  some  commonly  used  attributes  to  delimit  the  target  population  are  the  size  (e.g. 

number  of  persons  employed),  the  economic  activity  and  its  location.  An  example  of  a  target 

population  could  be  “enterprises  with  10  or  more  persons  employed,  classified  in  Group  72  of 

NACE, localised in the EU”. 

The  frame  population  is  an  operationalisation  of  the  target  population,  consisting  ideally  in  a 

complete list of the elements of the target population. Although a target population can be easily 

defined, in practise a list of all its elements is needed for its complete or partial (in case a sample 

is  used)  observation,  and  that  can  be  very  difficult  to  obtain.  That  list  should  be  complete  and 

include only and every element of the target population only once. However, most of the times it 

will  suffer  from  both  under-coverage  and  over-coverage.  Usually  files  of  statistical  elements 

(registers)  are  maintained  and  updated,  containing  lists  of  statistical  elements  and  also 

information on some attributes, usually used for delimiting target populations. Frame populations 

are  usually  extracted  from  those  registers.  The  frame  population  will  be  further  explained  in 

chapter 2.2. 

The target population of the “Community Survey on ICT usage and e-Commerce in Enterprises” 

is the group of enterprises delimited by the following attributes: 

•  Economic activity: 

Enterprises classified in the following categories of NACE-Rev.1: 

- Section D – “Manufacturing”; 

- Section F – “Construction”; 

- Section  G  –  “Wholesale  and  retail  trade;  repair  of  motor  vehicles,  motorcycles  and 

personal and household goods”; 

Methodological manual for Information Society Statistics 

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- Groups  55.1  and  55.2  –  “Hotels”  and  “Camping  sites  and  other  provision  of  short-

stay accommodation”; 

- Section I – “Transport, storage and communication”; 

- Section K – “Real estate, renting and business activities”; 

- Groups  92.1  and  92.2  –  “Motion  picture  and  video  activities”  and  “Radio  and 

television activities”. 

Optionally the target population can be extended to the following categories: 

- - Section E – “Electricity, gas and water supply”; 

- - Groups from 55.3 to 55.5 inclusive; 

- - Groups from 92.3 to 92.7 inclusive; and 

- - Division 93 – “Other service activities”. 

•  Enterprise size: 

Enterprises with 10 or more persons employed; 

Optionally the target population can be extended to enterprises with number of persons 

employed between 1 and 9. 

•  Geographic scope: 

Enterprises located in any part of the territory of the Country. 

I.1.3. Periodicity 

The  periodicity  is  annual,  meaning  the  data  is  collected  and  compiled  once  per  year.  However, 

some  variables  can  be  observed  with  a  lower  frequency,  e.g.  variables  which  tend  to  be  stable 

over time. 

An annual survey should  be a compromise or trade-off between response and collection burden 

and  the  need  for  relevant  and  recent  information  on  a  “fasting  moving”  study  domain  like  the 

information society.  

This periodicity is laid down in paragraph c) of Annex II of Regulation 808/2004 and in section 5 

of Regulation 1099/2005 (see also Part III – EU Legislation). 

I.1.4. Observation variables 

The attributes of the statistical unit are what in the end we want to observe and the observation 

variables  hold  numerical  measures  of  those  attributes.  Attributes  and  observation  variables 

shouldn’t be confused. An attribute is some property of the statistical unit and each attribute may 

have one or more observation variables which hold numerical measures of that attribute. 

For example, for the statistical unit “Individual” an attribute is his “Monthly Salary”. We want to 

measure  this  attribute  and  can  just  use  a  variable  to  hold  the  monetary  value  of  the  monthly 

salary. But collecting the monetary value of an individual’s monthly salary might not be feasible. 

Methodological manual for Information Society Statistics 

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In  this  case  we  can  use  another  variable  which  is  feasible,  like  a  categorical  variable  with  4 

different ranges of monthly salary, which information individuals are willing to give. In this case 

two different observation variables can be used to measure the same attribute. 

There are many ways of classifying observation variables, but the most relevant one for the ICT 

usage surveys is the distinction between qualitative and quantitative variables. 

Qualitative variables contain non-numeric information. They serve merely as labels or names for 

identifying special attributes of the statistical unit. An example is the Gender of employees with 

the values  Male or Female. Sometimes qualitative variables can be rendered  numeric by coding 

the  non-numeric  values.  An  important  type  of  qualitative  variables  is  that  of  binary  variables. 

Binary  variables  assume  only  two  different  values,  which  usually  are  rendered  numeric  by 

attributing the values “0” and “1” in a meaningful way. 

Quantitative variables contain information as to how much or how many. Hence they are always 

numeric. An example is the Salary or Experience (in years) of an employee. 

The observation variables in the “Community Survey on ICT usage and e-Commerce” are mainly 

qualitative, namely binary. 

The following table list the observation variables. 

A1 
A2 
A3 
A4a 
A4b 
A4c 
A4d 
A5 
A6a 
A6b 
A6c 
A7a 
A7b 
A7c 
A7d 
A8 
A9a 
A9b 
A9c 
A9d 
A9e 
A10 

B1 
B2 
B3a 
B3b 
B3c 
B3d 
B3e 
B4 
B5a 
B5b 
B5c 
B5d 
B5e 

Variable 

Computer usage 
Percentage of persons employed using computers at least once a week 
Existence of remote working 
Remote working by type: working at home 
Remote working by type: at external business partners’ premises 
Remote working by type: geographically dispersed loca. of the enterprise 
Remote working by type: during business travel 
Difficulties in recruiting personnel with ICT skills 
ICT user skills not available or not entirely suitable 
ICT specialist skills not available or not entirely suitable 
High cost of ICT specialists 
ICT usage: wireless LAN  
ICT usage: wire based LAN 
ICT usage: Intranet 
ICT usage: Extranet 
Existence of IT system to manage the placing and/or receipt of orders 
Orders management IT sys. linked to internal sys. for re-ordering supplies 
Orders management IT system linked to invoicing and payment systems 
Orders management IT sys. linked to system for managing production, logistics 
Orders management IT system linked to suppliers' business systems 
Orders management IT system linked to customers' business systems 
Extent of substitution of postal mail by electronic communication 

Access to Internet 
Percentage of persons employed using computers connected to the WWW 
Internet connection: Traditional modem 
Internet connection: ISDN 
Internet connection: DSL 
Internet connection: Other fixed Internet connection 
Internet connection: Mobile connection 
Maximum download speed of Internet connection 
Internet usage for banking and financial services 
Internet usage for training and education 
Internet usage for market monitoring 
Internet usage for receiving digital products 
Internet usage for obtaining after-sales services 

Methodological manual for Information Society Statistics 

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B6 
B7a 
B7b 
B7c 
B7d 
B8 
B9a 
B9b 
B9c 
B10a 
B10b 
B10c 
B10d 
B11a 
B11b 
B11c 
B12 

C1 
C2 
C3 
C4 
C5a 
C5b 
C6a 
C6b 
C6c 
C7 

D1 
D2 
D3 
D4 

X1 

X2 

X3 

X4 

X5 

Internet usage for interaction with public authorities 
Internet usage for obtaining information from public authorities’ websites 
Internet usage for obtaining forms from public authorities’ websites 
Internet usage for returning filled in forms to public authorities 
Internet usage for submitting a proposal in an electronic tender system 
Existence of own website 
Website for marketing own products 
Website for facilitating access to catalogues and price lists 
Website for providing after-sales support 
Security facilities usage: Virus checking or protection software 
Security facilities usage: Firewalls 
Security facilities usage: Secure servers 
Security facilities usage: Off-site data backup 
Security facilities usage: Electronic digital signature 
Security facilities usage: Other authentication mechanism 
Security facilities usage: Data encryption for confidentiality 
ICT-related problems encountered 

Have ordered via Internet 
Percentage of purchases resulting from orders placed via Internet 
Have received orders via Internet 
Percentage of turnover resulted from orders received via Internet 
Internet e-sales by type of client: B2B and B2G 
Internet e-sales by type of client: B2C 
Internet e-sales by destination: Own country 
Internet e-sales by destination: Other EU countries 
Internet e-sales by destination: Rest of the world 
Have sold products via specialised B2B market places 

Have ordered via non-Internet computer networks 
Percentage of purchases from orders placed via non-Internet computer networks 
Have received orders via non-Internet computer networks 
Percentage of turnover from orders received via non-Internet computer networks 

Main economic activity of the enterprise 

Average number of persons employed 

Purchases of goods and services 

Turnover 

Location (Objective 1/ non-Objective 1 region) 

I.1.5. Summary  measures,  aggregated  variables,  indicators  and 

tabulation 

Summary  measures  are  numerical  values  defined  by  a  statistical  measure  that  is  used  to 

summarize  the  values  for  a  specific  variable  for  all  statistical  units  in  a  specific  group.  Such 

measures  can  take  the  form  of  aggregates  (e.g.  total  number  of  yes-answers  on  a  specific 

question) or indicators (e.g. percentage of yes-answers). 

Aggregates can be compiled for the total population or for the different subpopulations defined by 

the background  variables (e.g. NACE  category or size) or for  subpopulations  defined conditional 

on the answers of other study variables (e.g. Internet users versus non users). 

E.g.: 

-  number of enterprises with Internet access 

-  number of enterprises with between 10 and 49 persons employed with Internet access 

-  number of enterprises having a LAN and an Intranet 

Methodological manual for Information Society Statistics 

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To  obtain  the  indicators  (proportions,  percentages,  etc.),  the  aggregates  need  to  be  divided  by 

the total population or subpopulation. 

The denominator of such ratio can for instance be: 

- 

total population of enterprises in the selected strata (e.g. “proportion of enterprises with between 10 and 

49 persons employed with access to the Internet” = the number of enterprises with between 10 and 49 

persons employed with access to the Internet divided by the total number of enterprises with between 10 

and 49 persons employed) 

The  detailed  transmission  format  for  sending  the  aggregated  data  to  Eurostat,  can  be  found  in 

I.3.3 Transmission format. 

I.1.6. Explanatory notes 

The explanatory notes in this chapter refer to the questions in the 2006 model questionnaire (see 

I.3.1 Model questionnaire, p. 183). The structure of this chapter follows the model questionnaire, 

i.e. the explanatory notes are grouped per module and per question. It is recommended to have 

the model questionnaire at hand while reading this section. 

I.1.6.1  MODULE A: ACCESS TO INFORMATION AND COMMUNICATION TECHNOLOGIES 

A1:  Did your enterprise use computers, during January 2006? 

[ Scope: all enterprises ] 

[ Type: one single answer needed, i.e. Tick only one ; binary (Yes/No); filter question ] 

A  computer  is  a  programmable  device  or  machine  capable  of  receiving,  processing  and 

outputting  various  types  of  data,  performing  calculations  and  other  manipulations  on  it, 

under  the  control  of  a  stored  set  of  instructions.  A  computer  typically  consists  of  one  or 

more processing units, memory units, and associated peripheral input and output devices.  

Depending  on  size  and  power,  computers  can  be  generally  divided  in  the  following 

categories: 

(cid:1)  Supercomputer: An extremely fast computer that can perform hundreds of millions 

of instructions per second. 

(cid:1)  Mainframe:  A powerful  multi-user computer capable of supporting many  hundreds 

or thousands of users simultaneously. 

(cid:1)  Minicomputer:  A  multi-user  computer  capable  of  supporting  from  10  to  hundreds 

of users simultaneously. 

(cid:1)  Workstation:  A  powerful,  single-user  computer....like  a  personal  computer,  but  it 

has a more powerful microprocessor and a higher-quality monitor. 

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(cid:1)  Personal  computer:  A  small,  single-user  computer  based  on  a  microprocessor 
....has  a  keyboard  for  entering  data,  a  monitor  for  displaying  information,  and  a 

storage device for saving data. 

Amongst personal computers one can find: 

(cid:1)  Desktop  computers:  A  desktop  computer  can  be  defined  as  a  computer  that 
usually remains fixed in one place. Normally the user is placed in front of it, behind 

the keyboard with the monitor placed on top. 

(cid:1)  Portable computers (laptop): A portable computer (or laptop) can be defined as a 
computer that is small enough to carry. A portable computer (or laptop) can usually 

carry  out  the  same  tasks  as  a  desktop  computer.  Includes  notebooks  but  not 

handheld computers, although portable. 

(cid:1)  Handheld  computers  (palmtop):  A handheld computer is a computer that can be 
used while you are holding it and stored in a small bag or for instance in a pocket. 

Personal Digital Assistants (PDAs) are another term for handheld computers. A PDA 

uses a pen rather than a keyboard. 

All  the  above  types  of  computers  are  in  the  scope  of  this  question.  On  the  other  hand, 

electronic  tills  which  are  only  used  for  monetary  transactions  (EPOS)  and  computer 

controlled machinery are not considered for this question. 

Use of computers doesn’t refer to ownership. The computers might belong to the enterprise, 

be leased or shared with another organisation. 

A2:  How many persons employed used computers at least once a week, 

during January 2006? 
or 
Please indicate an estimate of the percentage of the number of persons 
employed used computers at least once a week, during January 2006. 

[ Scope: enterprises which use computers, i.e. A1 = Yes] 

[ Type: numerical, in real or percentage values ] 

The  concept  of  computer  to  be  used  in  this  question  is  the  same  as  the  one  for  question 

A1. 

This question refers not to access only, but to effective use of computers by the personnel 

in the enterprise activities. It intends also to capture only the relevant use of computers by 

workers, setting a minimum level of frequency: at least once a week. Although there was in 

the  past  reference  to  the  use  of  computers  by  persons  employed  in  their  normal  work 

routine, this concept shouldn’t be used as it would, for instance, include those which routine 

includes  using  a  computer  every  three  months  when  this  wouldn’t  be  a  relevant  use  of 

computers by the enterprise personnel. 

This  variable  can  be  collected  in real  or  in  percentage  values.  The  variable  in  real  values 

might  be  more  appropriate  for  smaller  enterprises,  while  the  one  in  percentage  terms 

indicated for bigger ones. When the number of persons employed is small it’s easier for the 

respondent  just  to  identify  which  ones  work  with  computers,  instead of  having  to  calculate 

the  percentages  afterwards.  The  collection  in  percentage  terms  might  even  introduce 

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measurement errors in those cases, because of the rounding that is necessary to provide an 

answer  in  percentages  made  of  integer  numbers  between  1  and  100.  The  collection  in 

percentage terms can also introduce other measurement errors as it induces the respondent 

to make an educated guess of its value introducing the bias usually associated to this type of 

answer. On the other hand, for bigger enterprises, with a high number of persons employed, 

the  identification  of  every  worker  using  (and  not  just  having  access)  a  computer  can  be 

burdensome  or  not  possible  and  result  in  non-response.  In  this  case  the  collection  of  this 

information in percentage terms inducing to an educated guess may be preferable. 

Eurostat in its model questionnaire (annex I.3.1) recommends to use a combination of both 

giving to the respondent the opportunity to choose to answer in real or percentage values. 

Independently on how this variable is collected, in real or percentage values, the background 

variable “number of persons employed” is needed for grossing up the overall percentage of 

persons  employed  using  computers.  In  order  to  compute  the  overall  percentage  both  the 

total number of persons employed and the total number of persons using computers need to 

be  grossed  up.  If  collected  in  percentage  terms,  the  corresponding  real  value  needs  to  be 

calculated afterwards multiplying the answer with that background variable to gross up the 

number of persons employed using computers. 

A3:  Did your enterprise have persons employed who regularly work part of 
their time (half a day per week or more) away from the enterprise's 
regular work site while having access to the enterprise’s computer 
system, during January 2006? 

[ Scope: enterprises which use computers, i.e. A1 = Yes] 

[ Type: one single answer needed, i.e. Tick only one; binary (Yes/No); filter question] 

The  purpose  of  this  variable  is  to  capture  the  use  by  the  enterprise  of  information  and 

communication  technology  to  improve  the  mobility  of  its  workforce  and  enhance  the 

flexibility of its business processes. 

Persons employed who regularly work part of their time away from the enterprise's regular 

worksite  include  persons  working  at  home,  at  locations  belonging  to  a  third  party  (e.g. 

customer  premises),  on  the  move  (i.e.  while  travelling),  at  other  places  different  from 

traditional  workplaces  (hotels,  conferences,  etc…)  and  in  another  location  belonging  to  the 

enterprise (and not being the regular place of work). 

Access  to  the  enterprise's  computer  system  is  usually  done  through  an  extended  LAN. 

Extended  LAN  infrastructure  is  set  up  for  employees  to  access  the  business  internal 

computer-mediated network infrastructure from outside the usual working premises (remote 

access). 

Remote  access  is  the  ability  to  log  onto  the  internal  business  computer  network  from  a 

distant  location.  Generally,  this  implies  a  computer,  a  modem,  and  some  remote  access 

software  to  connect  to  this  network  via  a  telecommunications  link  or  other  networks 

(proprietary computer-mediated networks, Internet including VPN).  

Remote access means that the remote computer actually becomes a full-fledged host on the 

internal computer network. An office worker away from their desk, perhaps the other side of 

the  world  on  a  business  trip  or  a  holiday,  can  open  a  remote  desktop  session  into  their 

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normal  office  PC  using  a  secure  Virtual  Private  Network  (VPN)  connection  via  the  Internet. 

This gives him or her completely normally access to all their normal files and data, including 

e-mail and other applications, while they are away. 

A  virtual  private  network  (VPN)  is  a  way  to  use  a  public  telecommunication  infrastructure, 

such as the Internet, to provide remote offices or individual users with secure access to their 

organization's  network.  A  virtual  private  network  can  be  contrasted  with  an  expensive 

system  of  owned  or  leased  lines  that  can  only  be  used  by  one  organization.  The  goal  of  a 

VPN is to provide the organization with the same capabilities, but at a much lower cost.  A 

VPN  works  by  using  the  shared  public  infrastructure  while  maintaining  privacy  through 

security  procedures  and  tunnelling  protocols  such  as  the  Layer  Two  Tunnelling  Protocol 

(L2TP). In effect, the protocols, by encrypting data at the sending end and decrypting it at 

the receiving end, send the data through a "tunnel" that cannot be "entered" by data that is 

not properly encrypted. An additional level of security involves encrypting not only the data, 

but also the originating and receiving network addresses. 

A4:  Did any of those persons access the enterprise's computer system from 

the following places, during January 2006? 

[ Scope: enterprises with persons employed remotely acceding the enterprise's computer 

system, i.e. A3 = Yes] 

[ Type: one single answer needed, i.e. Tick only one; binary (Yes/No)] 

For  enterprises  having  personnel  acceding  remotely  to  its  computer  system,  the  following 

places of access are measured: 

a) From home 

This includes the access by the employee to the enterprise computer system from its own 

home. 

b) From customers or other external business partners’ premises 

c) From other geographically dispersed locations of the same enterprise or enterprise group 

d) During business travel, e.g. from hotel, airport etc 

A5:  Did your enterprise have difficulties in recruiting personnel with ICT skills 

(from basic to professional), during 2005? 

[ Scope: enterprises which use computers, i.e. A1 = Yes] 

[ Type: one single answer needed, i.e. Tick only one; binary (Yes/No); filter question] 

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ICT  specialist  skills  include  specifying,  designing,  developing,  installing,  operating, 

supporting, maintaining, managing, evaluating and researching ICT systems 

ICT  user  skills  include  skills  on  the  application  of  systems  to  support  own  work,  use  of 

generic  software  tools  and  use  of  specialised  tools  supporting  business  functions  within 

industry 

e-Business skills in clued skills on the exploitation of opportunities provided by ICT notably 

the Internet. 

A6:  Did your enterprise face the following problems when trying to recruit 

personnel, during 2005? 

[ Scope: enterprises which use computers, i.e. A1 = Yes] 

[ Type: one single answer needed, i.e. Tick only one; binary (Yes/No); filter question] 

For  enterprise  having  found  difficulties  in  recruiting  personnel  with  ICT  skills,  the  following 

reasons are colleted. 

a) Personnel with required skills in the use of  ICT  applications not available or not entirely 

suitable 

This item includes all those situations where the enterprise tried to recruit personnel with 

ICT user skills, and found difficulties in doing so. These difficulties can be either because 

there  was  a  lack  of  candidates  or  it  was  difficult  to  find  a  candidate  with  the  right 

knowledge in the use of ICT which the enterprise needs. 

b) ICT specialists with the required skills not available or not entirely suitable 

This item includes all those situations where the enterprise tried to recruit personnel with 

ICT specialist skills, and found difficulties in doing so, because either there was a lack of 

candidates or it was difficult to find a candidate with the right knowledge in the ICT field 

the enterprise needs. 

c) High remuneration costs of ICT specialists 

This  item  includes  all  those  situations  where  the  enterprise  found  difficulties  in  doing  in 

recruiting  personnel  with  ICT  specialist  skills,  because  either  the  remuneration  required 

by  the  candidates  was  more  than  what  the  enterprise  could  afford,  or  it  was  difficult  to 

find a candidate who would accept what the enterprise was offering. 

A7:  Did your enterprise have the following information and communication 

technologies, during January 2006? 

[ Scope: enterprises which use computers, i.e. A1 = Yes] 

[ Type: one single answer needed, i.e. Tick only one; binary (Yes/No); filter question] 

All  enterprises  with  internal  computer-mediated  network  (LAN  or  set  of  enterprise’s  LANs) 

infrastructure  in  January  2006.  Variable  refers  to  the  availability  regardless  property  and 

purposes of the internal computer-mediated network infrastructure within the enterprise at 

whatever moment during January. 

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A LAN is a network for communication between computers confined to a single building or in 

closely  located  group  of  buildings,  permitting  users  to  exchange  data,  share  a  common 

printer or master a common computer, etc. 

a) Wireless LAN 

A  wireless  LAN  is  a  local  network  which  uses  wireless  technologies  such  as  radio-

frequency,  infrared,  microwave,  or  other  types  of  electromagnetic  or  acoustic  waves  for 

the  last  internal  link  connecting  employees’  devices  (computers,  printers  etc)  to  the 

business  computer-mediated  network.  to  transmit  signals  or  data  between  stationary 

(fixed) points (connecting employees’ devices such as computers, printers etc) and a LAN 

backbone line(s) within the enterprise’s working premises. 

“Backbone  is  a  line  or  set  of  lines  that  local  area  networks  connect  to  span  distances 

efficiently (for example, between buildings).” 

b) Wire based LAN 

A wire based LAN uses wires, cables, or fibre optics for the last internal links to transmit 

signals or data between stationary (fixed) points (connecting employees’ devices such as 

computers,  printers  etc)  and  a  LAN  backbone  line(s)  within  the  enterprise’s  working 

premises. 

c) Intranet 

Intranet  refers  to  the  use  of  Internet  protocols  (TCP/IP  and  others)  to  share  and 

exchange company information in the same way as over the Internet (web site interface) 

but with access restricted to the internal users  via internal business computer-mediated 

network  (LAN  or  set  of  enterprise’s  LANs)  infrastructure,  accessible  only  by  authorised 

users (organisation’s members, employees, or others with authorisation). 

Typically  the  term  intranet  refers  to  the  internal  web  site  (an  intranet’s  Web  sites  look 

and act just like any other Web sites). The same concepts and technologies of the World 

Wide  Web  such  as  web  browsers  and  servers  running  on  the  internet  protocol  suite  are 

used to build an intranet. Other internet protocols are commonly used as well, especially 

ftp and email. Intranet in general looks like a private version of the Internet (web sites). 

It  may  consist  of  many  interlinked  local  area  networks  and  also  use  leased  lines  in  the 

wide  area  network.  There  does  not  necessarily  have  to  be  any  access  from  the 

organisation's internal network to the internet itself (world wide web).  However, usually 

larger enterprises allow users within their intranet to access the public  Internet through 

firewall  servers  with  a  gateway  through  which  all  access  takes  place.  Company  security 

very often has the ability to screen messages in both directions so that company security 

is  maintained.  This  means  that  organisations  that  allow  their  staff  internet  access  can 

normally  determine  which  internet  web  sites  are  being  viewed,  block  access  to  specific 

sites  they  don't  want  them  to  see  (such  as  pornographic  sex,  sites),  and  even  trace 

offenders  who  persistently  attempt  to  view  them.  They  can  also  block  certain  types  of 

web content (such as objects) which they consider a particular security risk.” 

When part of an intranet is made accessible to customers, partners, suppliers, or others 

outside the company, that part becomes part of an extranet. 

c) Extranet 

A secure extension of an  Intranet that allows external users to access some  parts of an 

organisation’s Intranet. 

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A8:  Did your enterprise have IT systems to manage the placing or receipt of 

orders, during January 2006? 
If Yes, 

A9:  Did your enterprise's IT systems for managing orders link automatically 

with any of the following IT systems, during January 2006? 

[ Scope: enterprises which use computers, i.e. A1 = Yes] 

[ Type: one single answer needed, i.e. Tick only one; binary (Yes/No); filter question] 

The purpose of these variables is to provide a measure of the integration of business processes. 

Implicitly, we are identifying that integration with automatic links. That is, something changes in 

the IT system supporting a business process and automatically (i.e. without human intervention) 

that  change  is  reflected  in  the  IT  system  supporting  another  business  process.  The  next  issue 

then is which business processes we are interested in (as we can't cover all business processes in 

the  enterprises,  and  as  they  actually  differ  between  enterprises  from  different  economic 

activities).  One  solution  is  to  start  with  two  business  processes  that  exist  in  every  enterprise: 

selling  and  buying.  (That's  why  we  start  with  a  question  on  the  existence  of  IT  system  for 

managing orders, received and placed.) 

As  the  final  purpose  of  these  questions  is  to  identify  the  existence  of  automatic  links  between 

different business processes, the definition of the starting point (IT system for managing orders) 

should  be  as  broad  as  possible.  That  is  IT  system  would  mean  basically  just  some  software 

application. 

At the same time, the definition of IT system is restricted by the specific software used or even 

its level of sophistication. The level of sophistication of a software application or a system is not 

directly correlated to its effectiveness or efficiency, and therefore correlated to a positive impact 

in the enterprise, which ultimately that's what we want to identify. 

So,  in  conclusion,  even  an  excel  worksheet  or  an  access  database  where  orders  are  inserted 

manually can be considered as an IT system for managing orders. 

A10: In your communication with customers and other enterprises, to what 

extent has your enterprise substituted traditional postal mail (e.g. for 
sending invoices, direct mail, etc.) by electronic means of communication 
(Intranet, Extranet, Internet, e-mail messages), in the last 5 years? 

[ Scope: enterprises which use computers, i.e. A1 = Yes] 

[ Type: one single answer needed, i.e. Tick only one; binary (Yes/No)] 

The purpose of this variable is to obtain insight in the real level of substitution and to better 

understand the interface between the use of e-communication and more traditional means, 

like postal mail. 

This variable includes two types of relationships the enterprise may have: with customers or 

potential  customers;  and  with  enterprises  that  are  business  partners  but  not  customers  or 

potential  customers  –  which  is  more  related  to  automation  of  business  processes  and  e-

business. 

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In the model questionnaire, the different levels of substitution are indicated in ‘words’, not in 

percentage  ranges.  The  four  categories  used  are  No  substitution,  Minor  substitution, 

Significant  substitution  and  Most  or  all  substituted.  As  the  meaning  of  the  different 

categories in the question may be troublesome when translating into the national languages 

or when carrying out the interviews, the following guidelines can be kept in mind: 

-  No substitution means that the overall postal mail was not reduced because of electronic 

means of communication; 

-  Minor  substitution  means  that  electronic  means  are  now  used  instead  of  post  mail  in  a 

few situations, but postal mail is still the most important; 

-  Significant  substitution  means  that  electronic  became  the  main  mean  of  business 

communication; 

-  Most  or  all  substituted  means  that  postal  mail  was  used  before,  but  it's  rarely  used 

nowadays. 

A category Non-applicable has been added for respondents who have never made significant 

use of traditional postal mail, e.g. new companies. 

The purpose of the choice of the reference period "in the last 5 years" is to restrict the period for 

which  we want to measure the variation. If it had been left open, then for older enterprises we 

could be capturing a different phenomenon than for newer enterprises. For older enterprises, we 

would  be  measuring  the  long-term  situation:  have  enterprises  being  substituting  postal  mail  in 

the last, e.g., in the last 20 years. For newer enterprises, we would be measuring the short term 

substitution  of  the  last  years.  What  we  want  to  capture  is  the  second  phenomenon.  We  don't 

want to capture the effect of the new technologies (ICT) on the older ones (postal mail), but the 

effect of the adoption of ICT in the postal market. 

The intention is not to exclude enterprises with less than five years, but to exclude the variation 

over longer periods. Foe enterprises with less than 5 years, they still may have seen a decrease 

in  postal  mail  or  not.  In  the  situation  of  an  enterprise  which  is  very  new  (e.g.  one  year),  the 

expected answer would be option v) - non-applicable. 

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I.1.6.2  MODULE B: USE OF INTERNET 

B1.  Did your enterprise have access to Internet, during January 2006? 

[ Scope: enterprises which use computers, i.e. A1 = Yes] 

[ Type: one single answer needed, i.e. Tick only one; binary (Yes/No); filter question] 

This  variable  refers  to  the  access  availability  regardless  of  property  and  purposes  of  the 

connection at whatever moment during January 2006. The term “Internet access” means having 

an external connection to the Internet through an Internet access ‘service’ provider (ISP). 

The  technologies  used  to  connect  to  the  Internet  are  physical  based  or  wireless.  So  we  can 

distinguish  wire  based  connections  from  wireless  connections.  Another  important  distinction  is 

between fixed connections and mobile connections. Access via fixed line refers to the connection 

between  to  stationary  points,  while  mobile  connections  are  performed  via  mobile  phone 

networks.  The  distinctions  wire/wireless  and  fixed/mobile  are  not  the  same,  as  wireless 

connections  can  be  used  to  connect  two  fixed  points,  as  is  the  case  of  satellite  connections. 

Another  breakdown  of  the  Internet  access  is  between  temporary  (dial-up  on  demand)  and 

permanent connection (always on-line). 

The  Internet  is  a  world-wide  open  computer  mediated  system  (network)  that  transmits  data  by 

packet  switching  using  a  standardised  Internet  Protocol  (IP)  and  many  other  related  protocols 

(Internet protocol suit). 

The  Internet  is  made  up  of  thousands  of  smaller  commercial,  academic,  and  government 

networks. It carries (provides access) to  various information and communication services, such 

as  electronic  mail  and  the  interlinked  web  pages  and  other  documents  of  the  World  Wide  Web. 

Internet refers to following Internet Protocol (IP) based networks and systems: WWW; Extranet 

over the Internet; EDI over the Internet; Internet accessed by mobile phones; Internet email.”  

The  Internet  protocol  suite  is  the  set  of  communications  protocols  that  implement  the  protocol 

stack on which the Internet runs. It is sometimes called the TCP/IP protocol suite, after the two 

most important protocols in it: the Transmission Control Protocol (TCP) and the Internet Protocol 

(IP), which were also the first two to be defined. 

An  Internet  access  ‘service’  provider  (ISP)  is  a  company  that  provides  individuals  and  other 

companies  access  to  the  Internet  and  related  services.  An  ISP  has  the  equipment  and  the 

telecommunication  line  access  required  to  have  a  point-of-presence  on  the  Internet  for  the 

geographic area served. The larger ISPs have their own high-speed leased lines so that they are 

less  dependent  on  the  telecommunication  providers  and  can  provide  better  service  to  their 

customers. Most telecommunications operators are ISPs. 

Generally, an ISP charges a monthly access fee to the consumer. The consumer then has access 

to  the  Internet  for  an  ulimited  number  of  hours,  although  the  speed  at  which  this  data  is 

transferred varies widely and depends on the type of the Internet connection. 

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B2:  How many persons employed used computers connected to the World 

Wide Web at least once a week, during January 2006? 
or 
Please indicate an estimate of the percentage of the number of persons 
employed used computers connected to the World Wide Web at least once 
a week, during January 2006. 

[ Scope: enterprises with Internet access, i.e. B1 = Yes] 

[ Type: numerical, in real or percentage values ] 

This  variable  refers  to  persons  employed  who  have  access  to  the  World  Wide Web  (WWW) 

from their workstation or from a computer to which he/she has free access. In principal, any 

person employed in an enterprise with access to the Internet can access it from a computer 

in the enterprise. However, here only persons employed to whom it was granted access are 

counted. The criteria in this variable to identify Internet access is WWW access. The reason 

for its usage is that from the several services that can be run in the Internet the WWW is the 

most common one, together with e-mail. A mere access to the Internet through the e-mail 

service is not considered in this variable, because it's very already very common in Europe 

and it doesn't provide the same potentialities in terms of access to information as the WWW. 

Just  like  with  persons  employed  using  computers  (question  A2),  this  variable  can  be 

collected in real or in percentage values. Eurostat in its model questionnaire (annex I.3.1) 

recommends  using  a  combination  of  both,  giving  to  the  respondent  the  opportunity  to 

choose to answer in real or percentage values. 

Independently on how this variable is collected, in real or percentage values, the background 

variable “number of persons employed” is needed for grossing up the overall percentage of 

persons employed using computers. 

B3.  Did your enterprise have the following types of external connection to the 

Internet, during January 2006? 

[ Scope: enterprises with Internet access, i.e. B1 = Yes] 

[ Type: binary (Yes/No)] 

By  external  connection  it is  meant  the  type of  the "last  mile"  connection  of  the  enterprise  (e.g. 

enterprise’s computer-mediated network) to the network of the Internet access service provider 

"ISP". The last mile is the final leg of delivering communications connectivity to the enterprise. 

Type of external Internet connection: 

a) Traditional Modem (dial-up access over normal telephone line) 

Dial-up is a temporary connection to the Internet via an analogue (standard) modem and 

standard  telephone  line  (public  switched  telephone  network  PSTN),  which  requires  that 

the  modem  dial  a  phone  number  when  Internet  access  is  needed  (to  dial  the  Internet 

service provider’s node to establish a modem-to-modem link, which is then routed to the 

internet). 

Dial-up  pertains  to  a  telephone  connection  in  a  system  of  many  lines  shared  by  many 

users.  A  dial-up  connection  is  established  and  maintained  for  limited  time  duration.  A 

Methodological manual for Information Society Statistics 

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dial-up  connection  can  be  initiated  manually  or  automatically  by  the  computer's  modem 

or  other  device.  This  type  of  the  Internet  connection  is  capable  of  carrying  up  to  56 

kilobits per second (Kbit/s) and is considered as the typical example of the low capacity 

‘speed’ connection (narrowband). 

b) ISDN connection 

ISDN (Integrated Services Digital Network) connection is a temporary connection to the 

Internet  using  a  type  of  circuit  switched  telephone  network  system  (a  set  of  CCITT/ITU 

standards), designed to allow digital (as opposed to analogue) transmission of voice and 

data  over  ordinary  telephone  copper  wires  (enables  digital  transmission  over  the  public 

switched telephone network), resulting in better quality and higher speeds, than available 

with analogue systems. 

Enterprises that install an ISDN adapter (in place of a telephone modem) receives up to 

128 Kbps compared with the maximum 56 Kbps rate of an analogue (standard) modem 

connection.  ISDN  services  can  simultaneously  transmit  voice,  data  and  video.  ISDN  is 

also considered as a low capacity ‘speed’ connection (narrowband). 

This category includes Basic Rate Interface (BRI) consisting of two B channels, each with 

bandwidth of 64 Kbit/s, and one D channel with a bandwidth of 16 Kbit/s. 

This  category  does  not  include  Primary-Rate  Interface,  a  type  of  ISDN  service  designed 

for  larger  organizations.  PRI  includes  23  B-channels  (30  in  Europe)  and  one  D-Channel. 

PRI service is generally transmitted through an E1 line in Europe. This type of connection 

belongs under alternative e). 

c) DSL (xDSL, ADSL, SDSL etc) connection 

xDSL  (Digital  Subscriber  Line)  refers  to  a  family  of  a  high-bandwidth  (broadband),  local 

loop  technologies  that  provide  a  digital  permanent  Internet  connection  over  the  copper 

wires of the local telephone network.  

Asymmetric  Digital  Subscriber  Line  (ADSL)  where  more  bandwidth  is  allocated  to 

download  than  upload  and  High  Rate  Digital  Subscriber  Line  (HDSL)  are  considered 

dominant  DSL  technologies.  Typically,  individual  connections  will  provide  from  1.544 

Mbps to 512 Kbps downstream and about 128 Kbps upstream. A DSL line can carry both 

data  and  voice  signals  and  the  data  part  of  the  line  is  continuously  connected.  DSL 

connection  is  considered  as  one  of  the  high  capacity  ‘speed’  permanent  ‘fixed’  Internet 

connection (broadband). 

d) Other fixed internet connection 

Other  high  capacity  ‘speed’  fixed  (wire  or  wireless)  connection  includes  the  following 

types  of  the  Internet  connection:  Cable  modem  ‘cable  TV  network  connection’;  High 

capacity  leased  lines  ‘Frame  Relay,  ATM,  Digital  Multiplex’;  Ethernet  LANs  connection; 

Optical  fibre  connection;  Satellite  connection;  Wi-fi  connection,  other  FWA  connections 

etc.. 

Cable  modem  uses  modems  attached  to  cable  television  networks  (cable  TV  lines)  for 

permanent ‘fixed’ access to the Internet. The term cable internet (or simply cable) refers 

to the delivery of internet service over this infrastructure. A cable modem is a device that 

enables  you  to  hook  up  your  PC  to  a  local  cable  TV  line  and  receive  data  at  about  1.5 

Mbps.  It  is  considered  as  one  of  the  high  capacity  ‘speed’  permanent  ‘fixed’  Internet 

connection (broadband). 

Methodological manual for Information Society Statistics 

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High capacity leased line is a permanent telephone connection between two points set up 

by a telecommunications common carrier. Typically, leased lines are used by businesses 

to connect geographically distant offices. Unlike normal dial-up connections, a leased line 

is  always  active.  Because  the  connection  doesn't  carry  anybody  else's  communications, 

the  carrier  can  assure  a  given  level  of  quality.  For  example,  a  T-1  channel  is  a  type  of 

leased line that provides a maximum transmission  speed of 1.544 Mbps. You can divide 

the  connection  into  different  lines  for  data  and  voice  communication  or  use  the  channel 

for  one  high  speed  data  circuit.  Dividing  the  connection  is  called  multiplexing. 

Increasingly, leased lines are being used by companies, and even individuals, for Internet 

access because they afford faster data transfer rates and are cost-effective if the Internet 

is used heavily. 

A leased line is a telephone line that has been leased for private use. In some contexts, 

it's called a dedicated line. A leased line is usually contrasted with a switched line or dial-

up line”. Leased lines are usually available at speeds of 64k, 128k, 256k, 512k, 2Mb and 

provided to the customer on X.21 presentation. Frame relay protocol and T-1 and T-3 (in 

Europe called E-1 and E-3) lines are used for the Internet connection via a leased lines.  

Higher speeds are available on alternative interfaces. 

Frame  relay  is  an  efficient  data  transmission  technique  used  to  send  digital  information 

quickly and cheaply to one or many destinations from one point. It is a packet-switching 

protocol for connecting devices on a Wide Area Network (WAN). Frame Relay networks in 

the U.S. support data transfer rates at T-1 (1.544 Mbps) and T-3 (45 Mbps) speeds.  In 

fact, you can think of Frame Relay as a way of utilizing existing T-1 and T-3 lines owned 

by  a  service  provider.  Most  telephone  companies  now  provide  Frame  Relay  service  for 

customers  who  want  connections  at  56  Kbps  to  T-1  speeds.  (In  Europe,  Frame  Relay 

speeds vary from 64 Kbps to 2 Mbps. Frame relay is being displaced by ATM and native 

IP based products, including IP virtual private networks. 

Fixed  wireless  Internet  connection  (FWA)  is  a  technology  which  uses  radio-frequency, 

infrared,  microwave,  or  other  types  of  electromagnetic  or  acoustic  waves  in  place  of 

wires,  cables,  or  fibre  optics  to  transmit  signals  or  data  (provide  Internet  access) 

between  stationary  (fixed)  points.    It  includes  e.g.  a  satellite  Internet  connection  (long 

range wireless transmission) or Wi-fi (medium range wireless transmission).   

Wi-Fi  (or  Wi-fi,  WiFi,  Wifi,  wifi),  short  for  "Wireless  Fidelity",  is  a  set  of    Ethernet 

standards  for  wireless  local  area  networks  (WLAN)  currently  based  on  the  IEEE  802.11 

specifications.  New  standards  beyond  the  802.11  specifications,  such  as  802.16  are 

currently  in  the  works,  they  offer  many  enhancements,  anywhere  from  longer  range  to 

greater transfer speeds. Wi-Fi was intended to be used for wireless devices and LANs, but 

is  now  often  used  for  Internet  access  (one  of  the  main  international  standards  for 

wireless  broadband  Internet  access  and  networking,  with  widespread  use  in  business, 

homes and public spaces). It is based on radio signals with a frequency of 2.4 GHz and 

capable  of  speeds  of  up  to  11  Mbps.    It  enables  a  person  with  a  wireless-enabled 

computer or personal digital assistant to connect to the Internet when in proximity of an 

access point called a hotspot. 

Under  this  category  it's  not  included  the  Internet  connection  via  high  capacity  ‘speed’ 

mobile phone networks, which are included in alternative e) instead. 

e) Mobile connection 

This variable includes connections to the Internet via mobile phone networks and includes 

connections via low capacity ‘speed’ mobile phone networks (HSCSD, GPRS etc) - mobile 

Methodological manual for Information Society Statistics 

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Internet narrowband - and connections via high capacity ‘speed’ mobile phone networks  

(UMTS ‘W-CDMA’; EDGE ‘EGPRS’; CDMA 2000x etc) - mobile Internet broadband. 

A  Connection  via  low  capacity  ‘speed’  mobile  phone  networks  is  an  access  to  the 

Internet  using  a    long  range  wireless  transmission of    the  mobile  network    technologies  

as  High-Speed  Circuit-Switched  Data  (HSCSD)  or    General  Packet  Radio  Service  (GPRS) 

that is sometimes  called as  2,5 mobile generation technology (2,5 G). 

Access to the Internet  via mobile phone networks should be considered as low capacity 

‘speed’ mobile connection (narrowband) if it is being equal to, or greater than 256 kbit/s, 

as the sum of the capacity in both directions (download or upload). 

HSCSD  is  a  development  of  Circuit  Switched  Data,  the  original  data  transmission 

mechanism of the  GSM mobile phone system. As  with the CSD channel the allocation is 

done  in  circuit  switched  mode.  The  difference  comes  from  the  ability  to  use  different 

coding  methods  and  even  multiple  time  slots  to  increase  data  throughput.  HSCSD  is  a 

temporary mobile connection. 

2.5G is a stepping stone between 2G and 3G cellular (mobile) wireless technologies. The 

term  "second  and  a  half  generation"  is  used  to  describe  2G-systems  that  have 

implemented a packet switched domain in addition to the circuit switched domain.  While 

the terms "2G" and "3G" are officially defined, "2.5G" is not. 2.5G provides some of the 

benefits  of  3G  (e.g.  it  is  packet-switched)  and  can  use  some  of  the  existing  2G 

infrastructure in GSM and CDMA networks. The most commonly known 2.5G technique is 

GPRS. 

GPRS is a 2.5G mobile standard typically adopted by GSM operators as a migration step 

towards  3G  (W-CDMA).  GPRS  is  based  on  packet-switched  technology  enabling  high-

speed data transmission.  

Examples  of  some  most  common  spread  standards  of  low  capacity  ‘speed’  mobile 

network connection and their bandwidth (can be different between the countries and also 

within the same country): 

download        

upload 

GPRS 4+1    57.6 kbit/s    

14.4 kbit/s  

GPRS 3+2    43.2 kbit/s    

28.8 kbit/s  

CSD          9.6 kbit/s    

9.6 kbit/s 

HSCSD       28.8 kbit/s   

14.4 kbit/s  

HSCSD       43.2 kbit/s   

14.4 kbit/s  

A  connection  via high  capacity  ‘speed’  mobile  phone  networks  is  an  access  to  the 
Internet  using  a  long  range  wireless  transmission  of  the  3rd  generation  (3G)  mobile 
network  technologies  based  on  the  CDMA  (Code  Division  Multiple  Access)  as  UMTS 

(Universal Mobile Telephone System - Wideband ‘W’-CDMA); CDMA2000x; CDMA 2000 1x 

EV-DO; CDMA 2000 1x EV-DV) or some other high capacity mobile technologies based on 

the GPRS as EDGE (Enhanced Data rates for Global Evolution - EGPRS) etc. 

3G  (or  3-G)  is  short  for  third-generation  mobile  telephone  technology.  The  services 

associated with 3G provide the ability to transfer both voice data (a telephone call) and 

non-voice  data  (such  as  downloading  information,  exchanging  email,  and  instant 

messaging).  It  includes  high-speed  mobile  networks  (e.g.,  CDMA2000  1X,  WCDMA, 

CDMA2000 1xEV-DO, etc.). 

Methodological manual for Information Society Statistics 

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Universal Mobile Telecommunications System (UMTS) is one of the third-generation (3G) 

mobile phone technologies. It uses W-CDMA as the underlying standard, is standardized 

by the 3GPP, and represents the European answer to the ITU IMT-2000 requirements for 

3G Cellular radio systems. It presently delivers packet switched data transmission speeds 

up to 384 kbps and up to 2 Mbps when fully implemented. 

CDMA2000  1x  is  an  IMT-2000  3G  mobile  network  technology,  based  on  CDMA  that 

delivers packet switched data transmission speeds of up to 144 kbps. It is also referred 

to as 1XRTT. 

CDMA2000 1xEV-DO is an IMT-2000 3G mobile network technology, based on CDMA that 

delivers packet switched data transmission speeds of up to 2.4 Mbps. 

Enhanced  Data  rates  for  Global  Evolution  (EDGE)  is  an  intermediate  technology  that 

brings  second-generation  GSM  closer  to  third-generation  capacity  for  handling  data 

speeds  up  to  384  Kbits/s.  The  standard  is  based  on  the  GSM  standard  and  uses  TDMA 

multiplexing technology. 

Narrowband  is  defined  by  the  type  of  the  Internet  connection  and  includes:  1)  Dial-up 

(connection via standard telephone line ‘PSTN using analogue modem); and 2) ISDN (Integrated 

Services Digital Network) 

Broadband  is  defined  by  the  type  of  the  Internet  connection  and  includes:  1)  xDSL  (Digital 

Subscriber  Line)  technologies  as  ADSL,  HDSL,  SDSL,  VDSL  that  form  core  broadband;  and  2) 

Other high capacity ‘speed’ fixed (wire or wireless) connection (Cable modem ‘cable TV network 

connection’;  Leased  lines  ‘Frame  Relay,  ATM,  Digital  Multiplex’;  Ethernet  LANs  connection; 

Optical fibre connection; Satellite connection; Wi-fi connection etc) – extendend fixed wire based 

and wireless broadband. 

B4.  What was the maximum speed for download contractually provided to 

your fastest Internet connection, as of January 2006? 

[ Scope: enterprises with Internet access, i.e. B1 = Yes] 

[ Type: one single answer needed, i.e. Tick only one; Categorical] 

In computer networks, bandwidth is often used as a synonym for data transfer rate - the amount 

of data that can be carried from one point to another in a given time period (usually a second). 

This  kind  of  bandwidth  is  usually  expressed  in  bits  (of  data)  per  second  (bps).  For  example,  a 

modem  with  a  bandwidth  of  56  kilobits  per  second  (Kbps)  can  transmit  a  maximum  of  about 

56,000 bits of digital data in one second. 

If 

the 

capacity 

is  asymmetric 

(i.e.  more  downloading/downstream/incoming 

that 

uploading/downstream/outgoing  or  opposite),  downloading/downstream/incoming  capacity 

should  be  provided.  Real  capacity  can  differ  significantly  depending  on  a  number  of  different 

factors which is why contractual bandwidth should be provided. 

In telecommunications generally, a transmission from an information server toward an end user 

is referred to as downstream and a transmission toward the server is referred to as upstream. In 

some  transmission  technologies,  such  as  ADSL  and  Cable  modems  are  asymmetric,  thereby 

rendering  the  upstream  speed  to  be  much  lower  than  that  of  its  downstream.  Symmetric 

connections  such  as  SDSL  and  T1,  however,  offer  identical  upstream  and  downstream  speeds. 

Methodological manual for Information Society Statistics 

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Whereas  downstream  is  important  to  the  average  home  user  or  enterprise  for  purposes  of 

downloading content, uploads are used mainly for web server applications and similar processes 

where the sending of data is critical (e-commerce). 

Downstream refers to the transfer speed (usually that of an internet connection) by  which data 

can be sent from the server to the client. The process by which downstream is utilized is known 

as downloading. 

Upstream  refers  to  the  transfer  speed  at  which  data  can  be  transferred  from  the  client  to  the 

server (uploading). 

B5.  Did your enterprise use the Internet for the following purposes, during 

January 2006? 

[ Scope: enterprises with Internet access, i.e. B1 = Yes] 

[ Type: one single answer needed, i.e. Tick only one] 

This variable intends to measure the adoption of the Internet by the enterprise as a user or 

consumer of several services. These services may be paid or not. This does not include the 

provision of these services in the Internet. For example, for "banking and financial services" 

this variable measures the use of the Internet to use the services provided by banks and not 

the use of the Internet by banks to provide financial services. 

This  variable  includes  the  use  of  the  Internet  in  general  and  is  not  restricted  to  the  World 

Wide Web. 

The following Internet uses are measured: 

a) Banking and financial services 

This  includes  the  use  of  web-banking,  the  consultation  of  financial  information  (like 

exchange  rates,  interest  rates,  etc.)  and  the  use  of  the  Internet  for  automatic  data 

interchange  between  the  enterprise  and  other  financial  organisations  (for  instance 

through the use of XML or EDIFACT). 

b) Training and education 

This includes the use of online education programs by the employees. 

c) Market monitoring (e.g. prices) 

This  includes  the  use  of  the  World  Wide  Web  to  look  for  information  on  current  or 

potential suppliers, clients or competitors. 

d) Receiving digital goods or services 

This  includes  the  use  of  the  Internet  to  download  files  or  to  receive  it  (e.g.  by  e-mail) 

when they were paid for. 

e) Obtaining after-sales service 

This includes the use of the Internet to receive support from suppliers. This can be done 

by  e-mail  or  through  the  use  of  the  website  of  the  supplier.  It  also  includes  the  use  of 

automatic data interchange, via Internet. 

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B6.  Did your enterprise use the Internet for interaction with public 

authorities, during 2005? 

[ Scope: enterprises with Internet access, i.e. B1 = Yes] 

[ Type: one single answer needed, i.e. Tick only one; binary (Yes/No); filter question] 

As  the  competence  of  the  government  or  the  ‘public  authorities’  differs  strongly  from  one 

country to another, the concept has been kept as wide as possible: public authorities refer to 

both  public  services  and  administration  activities.  While  ‘administration’  refers  to  obligation 

and  rights  one  has  as  a  citizen  or  as  an  enterprise  in  activity  in  the  country  (the  so-called 

red  tape),  public  services  can  refer  to  non-administrative  tasks  or  competences  of 

government bodies, e.g. offering the public library’s catalogue on-line. 

The  service  providers  can  be  at  national  or  regional  level,  but  also  at  the  level  of  cities  or 

municipalities. The service providers can even be ‘semi-governmental’, e.g. public libraries, 

hospitals, universities, etc. 

B7.  Did your enterprise interact with public authorities in the following ways, 

during 2005? 

[ Scope: enterprises having interacted with public authorities, i.e. B6 = Yes] 

[ Type: one single answer needed, i.e. Tick only one; binary (Yes/No)] 

a) For obtaining information 

Includes  searching  to  obtain  any  type  of  information  from  public  authority  web  sites. 

Public  authorities’  web  sites  include  local  or  central  government  offering  information  or 

services.  It  would  be  helpful  to  provide  a  list  of  local/central  government  web  sites  to 

facilitate  respondents  to  recall  public  authority  web  sites  that  they  have  used.  For 

example  respondents  may  not  realise  some  public  information  sites  are  run  by  public 

authorities, e.g. a meteorological office offering weather forecast services.  

b) For obtaining forms, e.g. tax forms 

Includes  downloading  official  forms  for  any  purpose  of  use  (e.g.  for  information  or  for 

requesting a service). The downloaded files could be in formats such as PDF or Microsoft 

Word. 

c) For returning filled in forms, e.g. provision of statistical information to public authorities 

Includes filled in forms sent via internet only, either . Forms downloaded, printed, filled in 

and sent by post should not be included in this category. 

d) Submitted a proposal in an electronic tender system (e-procurement) 

Includes  the  submission  of  proposals  in  Internet  based  systems  (either  based  on  web 

interfaces or any other architecture). 

This question makes use  of the conceptual  framework for the levels of interaction between 

enterprises  or  citizens  and  public  authorities,  used  by  DG  INFSO.    The  framework  of  four 

levels  of  interaction  was  developed  to  measure  the  level  of  sophistication  offered  by 

Methodological manual for Information Society Statistics 

31  

websites  supplying  basic  public  services.  That  way,  one  can  distinguish  websites  that  only 

provide  information  on  a  public  service  (1st  level)  from  websites  that  allow  to  download 

forms (2nd level) or to submit information in an online form (3rd level) up to websites that  

allow to completely treat the public service or administrative obligation without the need for 

any paperwork whatsoever (4th level of sophistication). The first three levels are considered 

in the enterprise survey, as the last one has proved to be very difficult to collect. 

It is expected or logical that a particular website that reaches a certain level of sophistication 

also  include  all  lower  levels,  for  instance  a  website  offering  the  possibility  to  download  a 

form  should  certainly  provide  information  on  the  particular  public  service  that  form  would 

refer to. The concept of the four levels of sophistication was adopted for the measurement of 

the usage of e-government by enterprises (and the 3 first levels for citizens). However, the 

interpretation  of  the  results  will  have  to  differ  slightly  from  the  interpretation  done  for  the 

sophistication  of  the  public  websites.  At  usage  level,  it  is  natural  to  assume  that  a  user 

(enterprise  or  citizen),  before  knowing  which  form  to  download  (2nd  level),  will  obtain 

information  on  the  public  service  he  is  interested  in  (1st  level),  but  he/she  will  only  do  it 

once  or  twice  and  not  every  time  it  downloads  the  form.  Therefore,  when  measuring  the 

usage  every  year,  it  is  perfectly  possible  that  there  are  users  who  have  downloaded  forms 

with  obtaining  information  in  those  cases  in  which  the  user  already  had  all  the  information 

he needed (although not very probable, as users may well constantly search for information 

on several different issues). In this sense, it is possible that the respondents answers Yes to 

item  b  without  having  answered  Yes  to  a  (or  Yes  to  c  without  having  answered  Yes  to  a 

and/or b). 

B8.  Did your enterprise have a Web Site / Home Page, during January 2006? 

[ Scope: enterprises with Internet access, i.e. B1 = Yes] 

[ Type: one single answer needed, i.e. Tick only one; binary (Yes/No); filter question] 

This observation variable doesn't refer specifically to the ownership of the website, but to the 

use of a website by the enterprise. It includes not  only the existence of  a  website which is 

located  in  servers  which  belong  to  the  enterprise  or  are  located  at  one  of  the  enterprise's 

sites,  but  also  third  party  web-sites  (e.g.  one  of  the  group  of  enterprises  to  which  it 

belongs). 

However, it doesn't include any web presence of the enterprise. That would be too broad, as 

it would include the presence of the enterprise (e.g. its name or its contact information) in 

directories and online yellow pages. These cases are not included in this variable. 

Finally,  this  variable  includes  any  website,  independently  of  its  sophistication  or  services 

provided. 

B9.  Did the Web Site of your enterprise provide the following facilities, during 

January 2006? 

[ Scope: enterprises with a website, i.e. B8 = Yes] 

[ Type: one single answer needed, i.e. Tick only one; binary (Yes/No)] 

Methodological manual for Information Society Statistics 

32  

 
a) Marketing the enterprise’s products 

It includes providing information on the enterprise's products in its website. 

b) Facilitating access to product catalogues and price lists 

It  includes  the  provision  of  product  catalogues,  including  prices,  in  the  enterprise's 

website. 

c) Providing after sales support 

It includes the use of the website to provide support to clients, for example with a web-

form where clients can pose questions. 

B10. Did your enterprise use the following internal security facilities, during 

January 2006? 

[ Scope: enterprises with Internet access, i.e. B1 = Yes] 

[ Type: one single answer needed, i.e. Tick only one; binary (Yes/No)] 

a) Virus checking or protection software 

Includes computer programs that attempt to identify and eliminate computer viruses and 

other malicious software. 

b) Firewalls (software or hardware) 

A  firewall  is  a  hardware  or  software  solution  which  controls  and  filters  communication 

between  a  computer  or  a  computer  network  and  the  Internet.  It  filters  incoming 

communication, or access, disallowing unauthorized or potentially dangerous material. It 

filters  also  outgoing  communication,  in  order  to  limit  access  only  to  some  Internet 

resources.  It  also  logs  all  communication  between  the  computer  or  computer  network 

and the Internet. 

c) Secure servers (support secured protocols such as shttp) 

It  includes  the  use  of  secure  protocols  (e.g.  shttp  or  https)  by  the  enterprise  in  its 

servers.  https  is  a  URI  scheme  equivalent  to  the  http  scheme,  originally  intended  to  be 

used  with  the  HTTP  protocol,  but  with  added  encryption  layer.  The  URI  structure  is  the 

same,  except  that  URIs  begins  with  "https:"  rather  than  "http:".  The  scheme  provides 

authentication  and  encrypted  communication  and  is  widely  used  on  Web  for  security-

sensitive  communication,  such  as  payment  transactions.  Instead  of  using  plain  text 

socket communication, the session data is encrypted either using the SSL (Secure Socket 

Layer) protocol or the TLS (Transport Layer Security) protocol. 

d) Off-site data backup 

Backing  up is a security  measure which consists in making copies of computer files in a 

different  location  from  where  they  are  originally  located.  The  backup  copy  can  then  be 

used to restore the original data in case it was damaged or lost. 

Methodological manual for Information Society Statistics 

33  

B11. Was it possible to communicate with your enterprise using the following 

security facilities, during January 2006? 

[ Scope: enterprises with Internet access, i.e. B1 = Yes] 

[ Type: one single answer needed, i.e. Tick only one; binary (Yes/No)] 

a) Electronic digital signature as customer's authentication mechanism 

An  electronic  signature  is  some  kind  of  electronic  information  attached  to  or  associated 

with  a  contract  or  another  message  used  as  the  legal  equivalent  to  a  written  signature. 

Electronic signature is often used to mean either a signature imputed to a text via one or 

more  of  several  electronic  means,  or  cryptographic  means  to  add  non-repudiation  and 

message  integrity  features  to  a  document.  Electronic  digital  signature  refers  specifically 

to a cryptographic signature, either on a document, or on a lower-level data structure. 

b) Other authentication mechanism (e.g. PIN code) 

A  personal  identification  number  (PIN)  is  a  secret  code  shared  between  a  user  and  a 

system  that  can  be  used  to  authenticate  the  user  to  the  system.  Typically,  the  user  is 

required to provide a non-confidential user identifier and a confidential PIN to gain access 

to the system. Upon receiving the User  ID and PIN, the system looks up the  PIN based 

upon the User ID and compares the looked-up PIN with the received PIN. If they match, 

then  the  user  is  granted  access.  If  they  do  not  match,  then  the  user  is  not  granted 

access.  PINs  are  often  4-digit  numbers  in  the  range  0000-9999  resulting  in  10,000 

possible numbers, so that an attacker would need to guess an average of 5000 times to 

get the correct PIN. 

c) Data encryption for confidentiality 

Encryption is the process of obscuring information to make it unreadable without special 

knowledge. It can be used to ensure confidentiality, but other techniques are still needed 

to make communications secure, particularly to verify the integrity and authenticity of a 

message; for example, a message authentication code (MAC) or digital signatures. 

B12. Did your enterprise encounter ICT related security problems during 2005 
(e.g. computer virus, worms or trojan attack, unauthorised external 
access to the computer system), that resulted in a loss of information or 
working time? 

[ Scope: enterprises with Internet access, i.e. B1 = Yes] 

[ Type: one single answer needed, i.e. Tick only one; binary (Yes/No)] 

An  ICT  related  security  problem  is  any  event  which,  posing  a  threat  to  the  availability, 

integrity or confidentiality of the enterprise's computer system, resulted in the destruction or 

disclosure  of  information,  or  even  if  recovered  resulted  in  the  loss  of  working  time  due 

resolving the problem. 

Methodological manual for Information Society Statistics 

34  

 
I.1.6.3  MODULE C: E-COMMERCE VIA INTERNET 

In order to assure the broadest international comparability of the enterprise ICT usage statistics, 

the OECD definition of e-commerce is used throughout this module. According to this definition: 

An  electronic  transaction  is  the  sale  or  purchase  of  goods  or  services,  whether  between  businesses, 
households,  individuals  or  private  organisations,  conducted  over  computer-mediated  networks.  The 
goods and services are ordered over those networks, but the payment and the ultimate delivery of the 
good or service may be conducted on or off-line. 

Source: OECD Guide to Measuring the Information Society 

This module covers only orders which are transmitted via Internet, while orders transmitted via 

other computer networks are covered in module D. 

One  important  difference  in  this  module  compared  with  most  of  the  questionnaire  is  that  the 

reference  period  is  the  previous  calendar  year,  instead  of  January  of  the  survey  year.  Flux 

economic variables like turnover and purchases, the main  variables to measure in e-commerce, 

need to be measured for a period longer than 1 month. In order to keep comparability with the 

main business statistics a calendar year is taken as reference period. 

The concept of Internet is the same as the one taken in module B. That is, it refers to the public 

open worldwide network known as Internet and not to the use of the Internet protocol in closed 

networks. 

e-Commerce  consists  on  a  business  process  which  is  conducted  via  computer  networks,  in  this 

case the Internet. The role of the computer network is very important. It doesn't include the use 

of the Internet merely as a human-to-human communication tool. For this reason conventional e-

mails manually typed by humans are excluded from this definition. In this case the computer and 

the  network  are  being  used  only  as  a  communication  device,  just  like  a  telephone  and  its 

network.  However,  if  the  e-mail  system  is  just  used  for  the  transmission  of  an  automatic 

message, i.e. computer-to-computer without human intervention, which represents an order for 

a product or service, then it is considered an e-commerce transaction. 

Therefore orders transmitted from a human to another human in a manual manner through the 

Internet  are  not  considered  e-commerce.  The  typical  ways  in  which  e-commerce  orders  are 

placed  via  the  Internet  is:  1)  through  a  web-site,  which  typically  characterises  business-to-

consumer  e-commerce;  2)  through  automatic  data  interchange,  i.e.  using  XML,  which 

characterises  business-to-business  e-commerce;  and  3) 

through  B2B  e-marketplaces. 

Nevertheless, any other automatic use of the Internet to transmit orders is included. 

Methodological manual for Information Society Statistics 

35  

 
C1.  Did your enterprise order products/services via the Internet, during 2005 

(excluding manually typed e-mails)? 

[ Scope: enterprises with Internet access, i.e. B1 = Yes] 

[ Type: one single answer needed, i.e. Tick only one; binary (Yes/No); filter question] 

C2.  Please indicate for 2005 the percentage of the Internet orders in relation 

to the total purchases (in monetary terms, excluding VAT). 

or 
Please state the value of the purchases resulted from orders placed via 
Internet (in monetary terms, excluding VAT), in 2005. 

If you can't provide this value, 
Please indicate an estimate of the percentage of the total purchases 
resulted from orders placed via Internet, in 2005. 

[ Scope: enterprises which have ordered via Internet, i.e. C1 = Yes] 

[ Type: numerical] 

The value of the purchases made over the Internet can be collected in 3 different ways. The 

first  one,  with  the  lowest  level  of  measurement,  is  to  collect  it  in  terms  of  classes  of 

percentage  of  the  total  purchases.  This  is  the  minimum  level  of  measurement  required  for 

this variable. The reason is that in several countries the collection of any other information 

on this value is not feasible. In this case, the 5 response categories used are: 

• 

Less than 1% 

•  1% or more and less than 5% 

•  5% or more and less than 10% 

•  10% or more and less than 25% 

•  25% or more 

The  main  disadvantage  of  collecting  the  information  in  this  way  is  that  it  doesn't  allow  to 

aggregate the value of Internet purchases. 

As the aggregated value of Internet purchases is one indicator of policy and general interest, 

alternative  ways  of  collecting  this  data  are  recommended  when  such  is  possible.  Internet 

purchases should in alternative be collected with a numerical value, either in real terms or in 

percentage terms. 

Internet purchases collected in percentage values 
Please indicate an estimate of the percentage of the total purchases 
resulted from orders placed via Internet, in 2005.

%

Collecting  Internet  purchases  in  percentage  values  has  the  advantage  of  allowing  us  to 

obtain an approximate estimate from respondents which don't have in the enterprise records 

which can provide this value. Field experience has shown that enterprise purchases are done 

in a decentralised way. Therefore, unless specific records of all these transactions are kept in 

a  centralised  form,  it  may  be  difficult  for  the  enterprise  to  provide  the  value  of  Internet 

purchases. 

Methodological manual for Information Society Statistics 

36  

 
However,  the  disadvantage  of  collecting  this  variable  in  percentage  values  is  that  for  the 

majority of enterprises this is still a small value. For most of the enterprises it is actually less 

than 1%. The problem is that this question doesn't allow the respondent to provide such an 

answer. The answer in this case would have to be either 0% or 1%. 

Also, even when making educated estimates the respondents have the tendency to round it 

to  multiples  of  10%  and  5%.  For  very  small  numbers  there  is  evidence  that  respondents 

round significantly around 1%. Therefore, when collected in this form, a large proportion of 

the  values  collected  are  1%.  This  has  to  be  taken  into  account  when  the  results  are 

tabulated in percentage classes. If 1% is at the limit of the classes used (e.g. [ 0% - 1% [; [ 

1%  -  5%  [),  then  in  which  class  the  1%  is  included  will  have  a  significant  impact  on  the 

results. 

Another disadvantage of this method is that for big enterprises a value of less than 1% can 

still be a significant amount. If collected in percentages, Internet purchases of less than 1% 

can  either  not  be  taken  into  account  if  the  respondent  answers  0%  or  be  over-estimated. 

When answers from big enterprises are involved this can bring a significant instability to the 

results. 

Internet purchases collected in real values 
Please state the value of the purchases resulted from orders placed via 
Internet (in monetary terms, excluding VAT), in 2005.

(National Currency)

Therefore, the preferable  way to collect Internet purchases is in real values.  Unfortunately, 

for a large number of enterprises this value is not available and to make educated estimates, 

percentage values are better then real values. 

Internet purchases collected in real and percentage values 
Please state the value of the purchases resulted from orders placed via 
Internet (in monetary terms, excluding VAT), in 2005.

(National Currency)

If you can't provide this value,
Please indicate an estimate of the percentage of the total purchases 
resulted from orders placed via Internet, in 2005.

%

Therefore, currently the recommended method is to give the alternative to the enterprise to 

answer in real values if it  has the information or, in case such information is  not available, 

ask for an estimation of its percentage in relation to the turnover. 

This  intends  first  to  reflect  what  the  practice  in  several  national  surveys  is  already:  some 

countries ask for the real value, while others ask for the percentage value. Second, it intends 

to provide an alternative to avoid the bias that might exist from asking in each of this ways: 

underestimation in the case of the real  value  and overestimation in the case  of percentage 

values, by giving the enterprises the option of using the one for which they can provide more 

accurate answers. 

The grossing-up of results will be different depending on how enterprise's Internet purchases 

are collected. If collected in percentage classes, then only the proportion of enterprises per 

class  can  be  grossed-up.  If  collected  in  real  or  percentage  values  then  real  or  the  overall 

percentage can be grossed-up. Eurostat practice has been to get the grossed-up value of the 

percentage, i.e. the overall percentage of purchases made via Internet. 

Methodological manual for Information Society Statistics 

37  

 
 
 
When  grossing-up,  the  values  collected  as  percentages  need  to  be  weighted  by  the  total 

purchases  of  goods  and  services  (variable  X2).  Please  refer  to  chapter  I.2.3.3  for  more 

information on the weighting. 

C3.  Did your enterprise receive orders via the internet, during 2005 

(excluding manually typed e-mails)? 

[ Scope: enterprises with Internet access, i.e. B1 = Yes] 

[ Type: one single answer needed, i.e. Tick only one; binary (Yes/No); filter question] 

C4.  Please state the value of the turnover resulted from orders received via 

Internet (in monetary terms, excluding VAT), in 2005. 

If you can't provide this value, 
Please indicate an estimate of the percentage of the total turnover 
resulted from orders received via Internet, in 2005. 

[ Scope: enterprises which have received orders via Internet, i.e. C3 = Yes] 

[ Type: numerical] 

Contrary to purchases, sales are usually centralised in enterprises. For this reason, Internet 

sales are collected in value (percentage or real) and not in percentage classes like it is the 

case for Internet purchases. 

The problematic of collecting Internet sales in real or percentage terms are the same as for 

collecting Internet purchases. As in that case the recommended method is to collect it giving 

the  possibility  to  the  respondent  to  answer  in  real  values  and  if  that  is  not  possible  to 

provide an educated estimate in percentage of the total turnover. 

C5.  Please provide a percentage breakdown of all Internet sales in 2005, by 

type of client. (Estimates in percentage of the monetary values) 

[ Scope: enterprises which have received orders via Internet, i.e. C3 = Yes] 

[ Type: numerical] 

For respondents having received orders via Internet, a percentage breakdown of the Internet 

sales by type of client is requested. The types of clients used are: 

a) B2B (Sales to other enterprises) and B2G (Sales to public authorities) 

The  B2B  abbreviation  stands  for  business-to-business  and  refers  to  relations  between 

enterprises,  opposed  to  relations  between  enterprises  and  other  groups,  like  consumers 

and  the  Government.  In  this  variable  it  refers  to  commercial  transactions  between  the 

respondent  enterprise  and  other  enterprises.  Business-to-business  electronic  commerce 

typically  takes  the  form  of  automated  processes  between  trading  partners  and  is 

performed in higher volumes than business-to-consumer applications. 

Methodological manual for Information Society Statistics 

38  

 
B2G  stands  for  business-to-government  and  includes  in  this  variable  the  commercial 

transactions  between  the  respondent  enterprise  and  public  authorities,  which  are 

conducted via Internet. 

b) B2C (Sales to private consumers) 

B2C  stands  for  business-to-consumer  and  refer  to  relations  between  enterprises  the  end 

consumer.  In  this  variable,  it  refers  orders  received  by  the  enterprise  from  individuals. 

Business-to-consumer electronic commerce typically takes the form of web-pages that offer 

the possibility to order products. 

C6.  Please provide a percentage breakdown of all Internet sales in 2005, by 

destination. (Estimates in percentage of the monetary values) 

[ Scope: enterprises which have received orders via Internet, i.e. C3 = Yes] 

[ Type: numerical] 

For respondents having received orders via Internet, a percentage breakdown of the Internet 

sales  by  destination  of  the  delivery  is  requested.  In  the  case  of  the  delivery  of  a  digital 

product the localisation of the client is taken as the destination. The destination categories of 

the clients used are: 

a) Own country 

The all territory of the country is considered, either inside the EU or not. 

b) Other EU countries 

The territory of all the Member-States of the EU is considered, except the country where 

the survey is conduct if it is one of the EU Member-States. 

c) Rest of the world 

This item includes all the remaining turnover resulted from orders placed via Internet. 

C7.  Did your enterprise sell any products to other enterprises via a presence 

on specialised Internet market places, during 2005? 

[ Scope: enterprises which have received orders via Internet, i.e. C3 = Yes] 

[ Type: one single answer needed, i.e. Tick only one; binary (Yes/No)] 

e-Marketplaces,  or  electronic  marketplaces,  are  business-to-business  portals,  web-based 

trading  systems,  where  goods  or  services  are  transacted.  These  portals  integrate  a 

community  of  many  suppliers  and  many  buyers,  and  function  as  brokers  between  the  two 

(function as an intermediary without taking possession of the goods or services). 

Methodological manual for Information Society Statistics 

39  

 
 
e-Marketplaces  provide  additional  services  such  as  catalogues  (e.g.  list  of  all  the  products 

available from all supplier members), directory listing (list of suppliers per product category, 

with  links  to  respective  web-sites  and  additional  details  about  the  companies  and  product 

offer), auctions, support to several languages, industry news, bulletin boards, etc. 

If the enterprise is member of an e-marketplace and sold any product or service through this 

system then should answer "Yes" to the question. 

Methodological manual for Information Society Statistics 

40  

I.1.6.4  MODULE D: E-COMMERCE VIA COMPUTER NETWORKS OTHER THAN INTERNET 

D1.  Did your enterprise order products/services via external computer 

networks other than Internet, during 2005? 

[ Scope: enterprises which use computers, i.e. A1 = Yes] 

[ Type: one single answer needed, i.e. Tick only one; binary (Yes/No); filter question] 

D2.  Please indicate for 2005 the percentage of the orders placed or 

transmitted via computer networks other than Internet, in relation to the 
total purchases (in monetary terms, excluding VAT). 

or 
Please state the value of the purchases resulted from orders placed via 
computer networks other than Internet (in monetary terms, excluding 
VAT), in 2005. 

If you can't provide this value, 
Please indicate an estimate of the percentage of the total purchases 
resulted from orders placed via computer networks other than 
Internet, in 2005. 

[ Scope: enterprises which have ordered via other computer networks than Internet, i.e. D1 

= Yes] 

[ Type: numerical] 

Just  like  with  orders  placed  via  Internet,  the  value  of  the  purchases  made  over  computer 

networks other than Internet can be collected in 3 different ways: 1) in terms of classes of 

percentage  of  the  total  purchases;  2)  in  percentage  value;  and  3)  in  real  value.  The 

advantages  and  disadvantages  of  collecting  this  information  in  the  several  ways  are  the 

same as in the case of Internet purchases. Please refer to the explanatory note of question 

C2 for more in-depth information. 

When collected in classes of percentages, the 5 response categories used are: 

• 

Less than 1% 

•  1% or more and less than 25% 

•  25% or more and less than 50% 

•  50% or more and less than 75% 

•  75% or more 

The  classes  are  not  the  same  as  the  ones  used  for  Internet  purchases,  because  although 

other computer networks are used by fewer enterprises, they are used more intensively. 

Just like Internet purchases, currently the recommended method is to give the alternative to 

the enterprise to answer in real values if it has the information or, in case such information 

is not available, ask for a estimation of its percentage in relation to the turnover. 

Methodological manual for Information Society Statistics 

41  

Equally,  the  grossing-up  of  results  will  be  different  depending  on  how  enterprise's  Internet 

purchases  are  collected.  If  collected  in  percentage  classes,  then  only  the  proportion  of 

enterprises per class can be grossed-up. If collected in real or percentage values then real or 

the overall percentage can be grossed-up. Eurostat practice has been to get the grossed-up 

value of the percentage, i.e. the overall percentage of purchases made via Internet. 

When  grossing-up,  the  values  collected  as  percentages  need  to  be  weighted  by  the  total 

purchases  of  goods  and  services  (variable  X2).  Please  refer  to  chapter  Error!  Reference 

source not found. for more information on the weighting. 

D3.  Did your enterprise receive orders via external computer networks other 

than Internet, during 2005? 

[ Scope: enterprises which use computers, i.e. A1 = Yes] 

[ Type: one single answer needed, i.e. Tick only one; binary (Yes/No); filter question] 

D4.  Please state the value of the turnover resulted from orders received via 

computer networks other than Internet (in monetary terms, excluding 
VAT), in 2005. 

If you can't provide this value, 
Please indicate an estimate of the percentage of the total turnover 
resulted from orders received via computer networks other than Internet, 
in 2005. 

[ Scope: enterprises which have received orders via computer networks other than Internet, 

i.e. D3 = Yes] 

[ Type: numerical] 

Contrary to purchases, sales are usually centralised in enterprises. For this reason, sales via 

computer networks other than Internet are collected in value (percentage or real terms) and 

not in percentage classes like it is the case for the purchases. 

The problematic of collecting sales in real or percentage terms are the same as for collecting 

purchases. As in that case the recommended method is to collect it giving the possibility to 

the  respondent  to  answer  in  real  values  and  if  that  is  not  possible  to  provide  an  educated 

estimate in percentage of the total turnover. 

Methodological manual for Information Society Statistics 

42  

 
I.1.6.5  MODULE X: BACKGROUND INFORMATION 

The  background  variables  have  several  purposes.  First,  they  are  used  to  breakdown  the  results 

from the main characteristics. That's the case of the "Main economic activity of the enterprise", 

"Average number of persons employed" and "Location". 

Second, they are needed to weight the percentages of turnover and purchases from e-commerce. 

The background variables "Total purchases of goods and services" and "Total turnover" are used 

for  that.  The  variable  "Average  number  of  persons  employed"  is  similarly  used  to  weight  the 

percentage of persons employed using computers. The number of persons employed is also used 
to weight the qualitative variables.1 

Third,  the  background  variables  are  used  in  the  sampling  design.  Namely,  the  "Main  economic 
activity" and the "Average number of persons employed" are used to stratify the sample.2 

The  background  variables  may  be  collected  through  the  ICT  survey  questionnaire  or  obtained 

from alternative sources. The alternative sources are mainly the registers and one main business 

survey,  usually  used  to  produce  the  structural  business  statistics.  It  is  very  important  that  the 

background information is at least consistent with the structural business statistics. 

X1.  Main economic activity of the enterprise 

[ Scope: all enterprises] 

[ Type: categorical] 

The main (or principal) economic activity is identified as the activity which contributes most 

to  the  total  value  added  of  the  enterprise.  The  principal  activity  so  identified  does  not 

necessarily account for 50% or more of the enterprise’s total value added. The classification 

of principal activity is determined by reference to NACE Rev. 1.1, first at the highest level of 

classification and then at more detailed levels ("top-down" method). 

The nomenclature NACE Rev. 1.1 is available in Eurostat's RAMON database: 

http://europa.eu.int/comm/eurostat/ramon  

The  main  economic  activity  of  the  enterprise  should  be  classified  by  NACE  Rev.  1.1  at  its 

highest level of detail (4 digits). Nevertheless, only the following level of detail which is used 

in the breakdown is strictly necessary. 

NACE groupings 

1 

DA + DB + DC + DD + DE  Manufacture  of  products  based  on:  food,  beverages,  tobacco, 

textile, leather, wood, pulp and paper; publishing and printing 

2 

DF + DG + DH 

3 

DI + DJ 

4 

DK + DL + DM + DN 

Manufacture  of  coke,  refined  petroleum  products,  chemical 
products, man-made fibres, rubber and plastics 

Manufacture  of  other  non-metallic  mineral  products,  basic  metals 
and fabricated metal products 

Manufacture  of  machinery  and  electrical,  optical  and  transport 
equipment and other manufacturing n.e.c. 

1 For more information on the weighting refer to chapter I.2.????. 
2 For more information on the sampling refer to chapter I.2.????. 

Methodological manual for Information Society Statistics 

43  

 
 
                                                
5 

6 

45 

50 

7 

51 

Construction 

Sale,  maintenance  and  repair  of  motor  vehicles  and  motorcycles; 
retail sale of automotive fuel 

Wholesale  trade  and  commission  trade,  except  of  motor  vehicles 
and motorcycles 

8 

9 

52 

Retail trade and repair of personal and household goods 

55.1 + 55.2 

Hotels and other provision of short-stay accommodation 

10  60 + 61 + 62 + 63 

Transport and storage 

11  64 

12  72 

Post and telecommunications 

Computer and related activities 

13  70 + 71 + 73 + 74 

Real  estate,  renting  and  business  activities  except  computer 
activities 

14  92.1 + 92.2 

Motion picture, video, radio and television activities 

F1  65.12 + 65.22 

Monetary  intermediation  and  other  credit  granting,  except  central 
banking 

F2  66.01 + 66.03 

Insurance, except compulsory social security 

Optional: 

17  22 

Publishing, printing and reproduction of recorded media 

18  40 + 41 

Electricity, gas and water supply 

19  55.3 + 55.4 + 55.5 

Restaurants, bars, canteens and catering 

20  92.3 to 92.7 

21  93 

News  agencies,  sporting  and  libraries,  archives,  museums  and 
other cultural and recreational activities  

Textile  washing  and  dry-cleaning,  hairdressing  and  other  beauty 
treatment, funeral activities, physical well-being activities, etc. 

F3  67.12 + 67.13 + 67.2 

Activities auxiliary to financial intermediation, except administration 
of financial markets 

Level 0

Level 1

Level 2

These  NACE  categories  are  grouped 

together  for  dissemination  purposes 

into  several  aggregates  organised  in  3 

hierarchal levels. At the first level there 

are 

3 

categories 

distinguishing 

"Manufacturing, 

Energy 

and 

Construction",  "Non-financial  services" 

and "Financial Services". At the second 

Total

level,  activities  are  grouped  at  the 

Section level of NACE Rev. 1.1, making 

9  categories.  Level  3  is  the  most 

detailed one, composed of the 21 NACE 

groupings described above. 

Total

Manufacturing, 
Energy and 
Construction

Non-financial 
Services

Section D

Section E

Section F

Section G

Section H

Section I

Section K

Section O

Financial 
Services

Section J

Level 3
DA+DB+DC+DD+DE

DF+DG+DH

DI+DJ

DK+DL+DM+DN

40 + 41

45

50

51

52

55.1 + 55.2

55.3 - 55.5

60 - 63

64

72

70 +71 +73 +74

92.1 + 92.2

92.3 - 92.7

93

65.12 + 65.22

66.01 + 66.03

67.12 + 67.13 + 67.2

Legend:

Optional category

Non-optional category

Manufacturing, Energy 
and Construction

Non-financial services

Financial Services

Section D

Section E

Section F

Section G

Section H

Section I

Section K

92 + 93

Section J

DA+DB+
DC+DD+
DE

DF+DG + 
DH

DI + DJ

DK+DL+D
M +DN

40 + 41

45

50

51

52

55.1 + 
55.2

55.3 - 
55.5

60 - 63

64

72

70 + 71 + 
73 + 74

92.1 + 
92.2

92.3 -
92.7

93

65.12 + 
65.22

66.01 + 
66.03

Methodological manual for Information Society Statistics 

67.12 + 
67.13 + 

67.2  

44  

 
 
 
X2.  Average number of persons employed 

[ Scope: all enterprises] 

[ Type: numerical] 

For  purposes  of  general  harmonisation  of  enterprise  ICT  usage  statistics  and  the  more 

general  field  of  business  statistics,  the  concept  of  persons  employed  used  here  is  the  one 

from the Structural Business Statistics (SBS). 

The  number  of  persons  employed  is  defined  as  the  total  number  of  persons  who  work  in  the 
observation unit (inclusive of working proprietors, partners working regularly in the unit and unpaid 
family workers), as well as persons who work outside the unit who belong to it and are paid by it 
(e.g. sales representatives, delivery personnel, repair and maintenance teams). It includes persons 
absent for a short period (e.g. sick leave, paid leave or special leave), and also those on strike, but 
not  those  absent  for  an  indefinite  period.  It  also  includes  part-time  workers  who  are  regarded  as 
such  under  the  laws  of  the  country  concerned  and  who  are  on  the  payroll,  as  well  as  seasonal 
workers, apprentices and home workers on the payroll. 

The  number  of  persons  employed  excludes  manpower  supplied  to  the  unit  by  other  enterprises, 
persons  carrying  out  repair  and  maintenance  work  in  the  enquiry  unit  on  behalf  of  other 
enterprises, as well as those on compulsory military service. 

Unpaid family workers refer to persons who live with the proprietor of the unit and work regularly 
for the unit, but do not have a contract of service and do not receive a fixed sum for the work they 
perform.  This  is  limited  to  those  persons  who  are  not  included  on  the  payroll  of  another  unit  as 
their principal occupation. 

Source: Structural Business Statistics Regulation (variable 16 11 0) 

The  number  of  persons  employed  should  be  measured  as  the  yearly  average  during  the 

previous calendar year. However, if the seasonal effect is not significant, the last day of the 

previous calendar year can be used. 

The average number of persons employed is coded into 5 size categories. For the tabulation 

of  the  results,  the  size  categories  are  grouped  in  a  hierarchal  way  into  3  levels.  The  first 

level  distinguishes  micro-enterprises  from  the  others.  The  second  and  thirds  levels  further 

breakdown these two groups. 

Size Categories (persons employed) 

Level 0

Level 1

1  10 to 49 

Small enterprises 

2  50 to 249 

Medium enterprises 

3  250 or more  

Big enterprises 

Optional: 

4  Less than 5 

Small micro-enterprises 

5  5 to 9 

Big micro-enterprises 

Total

Micro-
Enterprises

Small, Medium 
and Large 
Enterprises

Total

Level 2
Small Micro-
Enterprises
Big Micro-
Enterprises

Small and 
Medium 
Enterprises

Large 
Enterprises

Level 3
Small Micro - 
Enterprises
Big Micro - 
Enterprises

Small Enterprises

Medium Enterprises

Large Enterprises

Legend:

Optional category

Non-optional category

Micro-Enterprises

Small, Medium and Large Enterprises

Small Micro-Enterprises

Big Micro-Enterprises

Small and Medium 
Enterprises

Large Enterprises

1  to  4 perso ns 
emplo yed

5 to 9 persons 
employed

10 to 49 perso ns 
employed

50 to  249 persons 
emplo yed

250 or more persons 
emplo yed

Methodological manual for Information Society Statistics 

45  

 
 
 
 
X3.  Total purchases of goods and services 

[ Scope: all enterprises] 

[ Type: numerical] 

This variable is not to be collected for the financial enterprises, i.e., enterprises which main 

economic  activity  is  classified  in  Section  J  of  NACE  Rev.  1.1,  because  the  concept  is  only 

applicable to non-financial economic activities. 

This  variable  is  needed  to  weight  the  percentage  of  purchases  resulted  from  orders  placed 

via  Internet  and  other  computer  networks.  However,  if  these  variables  are  collected  in 

classes,  instead  of  percentage  (or  real)  values,  then  this  background  variable  is  not 

necessary. 

As for the number of persons employed and turnover, the SBS definition is to be used: 

Purchases  of  goods  and services  include  the  value of  all  goods  and  services purchased during  the 
accounting period for resale or consumption in the production process, excluding capital goods the 
consumption  of  which  is  registered  as  consumption  of  fixed  capital.  The  goods  and  services 
concerned may be either resold with or without further transformation, completely used up in the 
production process or, finally, be stocked. 

Included  in  these  purchases  are  the  materials  that  enter  directly  into  the  goods  produced  (raw 
materials,  intermediary  products,  components),  plus  non-capitalised  small  tools  and  equipment. 
Also  included  is  the  value  of  ancillary  materials  (lubricants,  water,  packaging,  maintenance  and 
repair  materials,  office  materials)  as  well  as  energy  products.  Included  in  this  variable  are  the 
purchases of materials made for the production of capital goods by the unit. 

Services  paid  for  during  the  reference  period  are  also  included  regardless  of  whether  they  are 
industrial or non-industrial. In this figure are payments for all work carried out by third parties on 
behalf  of  the  unit  including  current  repairs  and  maintenance,  installation  work  and  technical 
studies.  Amounts  paid  for  the  installation  of  capital  goods  and  the  value  of  capitalised  goods  are 
excluded. 

Also  included  are  payments  made  for  non-industrial  services  such  as  legal  and  accountancy  fees, 
patents and licence fees (where they are not capitalised), insurance premiums, costs of meetings of 
shareholders and governing bodies, contributions to business and professional associations, postal, 
telephone, electronic  communication,  telegraph  and  fax charges,  transport  services  for  goods  and 
personnel,  advertising  costs,  commissions  (where  they  are  not  included  in  wages  and  salaries), 
rents, bank charges (excluding interest payments) and all other business services provided by third 
parties.  Included  are  services  which  are  transformed  and  capitalised  by  the  unit  as  capitalised 
production. 

Expenditure classified as financial expenditure or extraordinary expenditure in company accounts is 
excluded from the total purchases of goods and services. 

Purchases  of  goods  and  services  are  valued  at  the  purchase  price  excluding  deductible  VAT  and 
other deductible taxes linked directly to turnover. 

All  other  taxes  and  duties  on  the  products  are  therefore  not  deducted  from  the  valuation  of  the 
purchases  of  goods  and  services.  The  treatment  of  taxes  on  production  is  not  relevant  in  the 
valuation of these purchases. 

Specific calculation methods are needed for NACE Rev.1 classes 66.01 and 66.03 

Source: Structural Business Statistics Regulation (variable 13 11 0) 

Methodological manual for Information Society Statistics 

46  

X4.  Total turnover 

[ Scope: all enterprises] 

[ Type: numerical] 

Just like the total purchases of goods and services, this variable is not to be collected for the 

financial  enterprises,  i.e.  enterprises  which  main economic  activity  is  classified  in  Section  J 

of  NACE  Rev.  1.1,  because  the  concept  is  only  applicable  to  non-financial  economic 

activities. 

As  for  the  number  of  persons  employed  and  purchases  of  goods  and  services,  the  SBS 

definition is to be used: 

Turnover comprises the totals invoiced by the observation unit during the reference period, and this 
corresponds to market sales of goods or services supplied to third parties. 

Turnover  includes  all  duties  and  taxes  on  the  goods  or  services  invoiced  by  the  unit  with  the 
exception of the VAT invoiced by the unit vis-à-vis its customer and other similar deductible taxes 
directly linked to turnover. 

It  also  includes  all  other  charges  (transport,  packaging,  etc.)  passed  on  to  the  customer,  even  if 
these charges are listed separately in the invoice. Reduction in prices, rebates and discounts as well 
as the value of returned packing must be deducted. 

Income  classified  as  other  operating  income,  financial  income  and  extraordinary  income  in 
company accounts is excluded from turnover. Operating subsidies received from public authorities 
or the institutions of the European Union are also excluded. 

For  NACE  Rev.  1  classes  66.01  and  66.03,  the  corresponding  title  of  this  characteristic  is  ‘Gross 
premiums written’. 

Source: Structural Business Statistics Regulation (variable 12 11 0) 

X5.  Location (Objective 1/ non-Objective 1 region) 

[ Scope: all enterprises] 

[ Type: categorical] 

 “Objective  1”  promotes  the  development  and  structural  adjustment  of  regions  whose 

development  is  lagging  behind,  i.e.  whose  average  per  capita  GDP  is  below  75%  of  the 

European Union average. 

The  NUTS  regions  (statistical  demarcation)  eligible  for  support  from  the  Structural  Funds 

under  Objective  1  -  including  transitional  or  phasing-out  Objective  1  regions  until 

31/12/2006 which are marked in italic - are listed below. 

Please note that the list is different  for the one used in the 2005 survey as regions are no 

longer under transitional support as of 31/12/2005. 

Countries entirely covered by Objective 1: 

Estonia (the whole country counts as one single region at NUTS2-level) 

Greece 

Latvia (the whole country counts as one single region at NUTS2-level) 

Lithuania (the whole country counts as one single region at NUTS2-level) 

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Hungary 

Malta (the whole country counts as one single region at NUTS2-level) 

Poland 

Slovenia (the whole country counts as one single region at NUTS2-level) 

Countries partially covered by Objective 1: 

Belgium: 

The following communes of the province of Hainaut: Bernissart, 
Chapelle-lez-Herlaimont, Charleroi (with the exception of former 
commune of Mont-sur-Marchienne), Châtelet, Courcelles, Farciennes, 
Fontaine-l'Evêque, Manage, Boussu, Dour, Frameries, Hensies, Mons 
(only the communes of Jemappes, Flenu et Cuesmes), Quaregnon, 
Quiévrain, Colfontaine, La Louvière (with the exception of the former 
commune of Boussoit), Anderlues, Morlanwelz 

(note: as of 31/12/2005, the rest of the province of Hainaut is no longer 
eligible for transitional support) 

Czech Republic: 

Střední Čechy, Jihozápad, Severozápad, Severovýchod, Jihovýchod, 
Střední Morava, Moravskoslezsko (i.e. the whole country except Praha) 

Germany: 

Spain: 

France: 

Brandenburg Nord-Ost, Brandenburg Süd-West, Mecklenburg-
Vorpommern, Chemnitz, Dresden, Leipzig, Dessau, Halle, Magdeburg, 
Thüringen 

(note: as of 31/12/2005, Berlin (part: former East Berlin, i.e. Kreis 
Berlin-Ost, Stadt) is no longer eligible for transitional support)  

Galicia, Principado de Asturias, Castilla y León, Castilla-La Mancha, 
Extremadura, Comunidad Valenciana, Andalucía, Región de Murcia, 
Ceuta, Melilla, Canarias, Comunidad Autonoma Cantabria 

Guadeloupe, Martinique, Guyana, Réunion, Corse, Nord - Pas-de-Calais 
(parts: arrondissements Avesnes, Douai, Valenciennes) 

Ireland: 

Border, Midlands, Western, South-East 

(note: as of 31/12/2005, Dublin, Mid-East, Mid-West, South-West are 
no longer eligible for transitional support) 

Italy: 

Campania, Puglia, Basilicata, Calabria, Sicilia, Sardegna, Molise 

Austria: 

Burgenland 

Portugal: 

Slovakia: 

Finland: 

Sweden: 

Norte, Centro, Alentejo, Algarve, Açores, Madeira (i.e. the whole 
country except Lisboa) 

Západné Slovensko, Stredné Slovensko, Východné Slovensko (i.e. the 
whole country except Bratislavsky kraj) 

Itä-Suomi (all), Länsi-Suomi (part: northern part of Keski-Suomi), 
Pohjois-Suomi (parts: all of Lappi, part of Pohjois-Pohjanmaa, eastern 
part of Keski-Pohjanmaa) 

[see also: Annex I to Protocol 6 annexed to the Act of Accession of 
Austria, Finland and Sweden (http://europa.eu.int/eur-lex/en/ 
treaties/dat/AU_FI_SV_accession.html#0355010034)]  

Norra Mellansverige (parts: northwestern part of Gävleborgs län, 
northern and western parts of Dalarnas län, northern part of Värmlands 
län), Mellersta Norrland (all, but coastal part is under the "Special 
Programme") and Övre Norrland (all, but coastal part is under the 
"Special Programme") 

[see also: Annex I to Protocol 6 annexed to the Act of Accession of 
Austria, Finland and Sweden (http://europa.eu.int/eur-lex/en/ 

Methodological manual for Information Society Statistics 

48  

 
 
 
 
 
 
 
 
 
 
 
 
United Kingdom: 

treaties/dat/AU_FI_SV_accession.html#0355010034)] 

South Yorkshire, West Wales and the Valleys, Cornwall and Isles of 
Scilly, Merseyside, Highlands and Islands (only Islands – 1995 NUTS III 
boundaries) 

(note: as of 31/12/2005, Northern Ireland and Highlands and Islands 
(except Islands) are no longer eligible for transitional support) 

Countries with no Objective 1 regions: 

Denmark (the whole country counts as one single region at NUTS2-level) 

Cyprus (the whole country counts as one single region at NUTS2-level) 

Luxembourg (the whole country counts as one single region at NUTS2-level) 

The Netherlands (note: as of 31/12/2005, Provincie Flevoland is no longer eligible for 

transitional support) 

The list of Objective 1 regions was published in O.J.  L194 p. 53 of 27/07/1999, Annexes I 

and II (http://europa.eu.int/eur-lex/pri/en/oj/dat/1999/l_194/l_19419990727en00530057.pdf). 

The  list  of  Objective  1  regions  in  the  Member  States  who  entered  the  EU  in  2004  can  be 

found in Annex  II to the Act concerning the conditions of accession of these countries. The 

list is valid from 01/05/2004 until 31/12/2006 

(http://www.europa.eu.int/eur-lex/en/treaties/dat/L_2003236EN/L2003236EN.065803.htm). 

The list of NUTS regions as of 2003 was published in O.J. L154 p. 1 of 21/06/2003; see also 

the RAMON-database on Eurostat’s website (http://europa.eu.int/comm/eurostat/ramon/nuts). 

Methodological manual for Information Society Statistics 

49  

 
 
 
 
I.1.7. Enterprises of the financial sector  

I.1.7.1  OBSERVATION VARIABLES FOR THE FINANCIAL SECTOR 
In  addition  to  the  economic  activities  described  in  section  I.1.2  above,  the  enterprise  survey 

targets  the  collection  of  statistical  information  from  the  financial  sector,  i.e.  banks  and  other 

credit institutions as well as insurance services relating to NACE Rev. 1.1 section J classes 65.12, 

65.22, 66.01, 66.03. Optional NACE activities are 67.12, 67.13, 67.2.  

The  importance  of  the  use  of  ICT  and  eCommerce  in  the  financial  sector  has  been  widely 

recognised.  However,  measurement  of  eCommerce  poses  certain  difficulties.  In  particular  the 

measurement  of  eCommerce  in  monetary  terms  of  the  value  or  percentage  of  turnover  which 

resulted  from  orders  received  via  Internet  or  other  computer  networks  was  not  found 

appropriate.  Following  a  pilot  phase  and  testing  of  a  set  of  alternate  variables  by  various  NSIs, 

the methodology regarding the observation variables has been modified for the financial sector.  

The  changes  in  the  observation  variables  mainly  concern  questions  related  to  eCommerce. 

Particular emphasis is put on Internet eCommerce and Business-to-consumer eCommerce.   

A  specific  model  questionnaire  and  transmission  format  has  been  issued  and  is  attached  in 

chapters  1.3.1  and  1.3.2,  respectively.  The  reporting  of  results  is  integrated  in  the  template  in 

chapter 1.3.3.  

I.1.7.2 
The explanatory notes in this chapter refer to the questions in the 2006 model questionnaire for 

EXPLANATORY NOTES 

enterprises  in  the  financial  services  sector.  The  structure  of  this  chapter  follows  the  model 

questionnaire,  i.e.  the  explanatory  notes  are  grouped  per  module  and  per  question,  but  only 

those questions which are different compared to the general model questionnaire for enterprises 

are  addressed.  Regarding  the  remaining  questions,  reference  is  made  to  chapters  I.1.6.1  and 

I.1.6.2. It is recommended to have the model questionnaire for the financial sector at hand while 

reading this section. 

Methodological manual for Information Society Statistics 

50  

I.1.7.2.1.  MODULE A: ACCESS TO INFORMATION AND COMMUNICATION TECHNOLOGIES 

Question A1 of the general enterprise survey is not addressed. It was found that computer use is 

widespread  in  the  financial  sector.  The  questionnaire  starts  with  asking  the  percentage  of 

personnel using a computer. The numbering of questions in module A is thus slightly different. 

A7:  Did your enterprise have IT systems to manage the receipt of orders, 

during January 2006? 
If Yes, 

A8:  Did your enterprise's IT systems for managing orders link automatically 

with any of the following IT systems, during January 2006? 

[ Scope: all enterprises] 

[ Type: one single answer needed, i.e. Tick only one; binary (Yes/No); filter question] 

As for other enterprises (see explanatory notes for questions A8 and A9 in chapter I.1.6.1), 

the  purpose  of  these  variables  is  to  provide  a  measure  of  the  integration  of  business 

processes. For the financial sector, we are in particular interested in IT systems for managing 

the receipt of orders from customers. The question is thus limited to two dimensions: 

a)  Existence  of  automatic  link  to  (any)  internal  IT  system  of  the  enterprise  or  enterprise 

group, and 

b)  Existence  of  automatic  link  to  customers’  business  systems  (for  customers  outside  the 

enterprise group). 

I.1.7.2.2.  MODULE C: E-COMMERCE VIA INTERNET 

The  module  on  e-commerce  via  the  Internet  for  financial  sector  enterprises  addresses  first  in  a 

more general sense the provision of on-line financial services via the Internet to consumers, i.e. 

business-to-consumer  e-commerce,  and  then  more  in  particular  the  provision  of  services  to 

consumers through a website.  

The  module  takes  into  account  that  in  e-commerce,  services  can  be  ordered  over  Internet 

Protocol  based  networks  but  the  payment  and  the  ultimate  delivery  of  the  service  may  be 

conducted on- or off-line. Orders received via telephone, facsimile, or manually typed e-mails are 

not counted as electronic commerce. E-commerce means transactions conducted over computer-

mediated  networks.  Orders  from  customers  are  the  critical  issues.  The  simple  provision  of 

information  on  the  enterprise  and  its  available  services  which  can  be  accessed  by  a  customer 

from the website is excluded here. 

Financial  transactions  are  the  business  of  banking  and  credit  granting  services  and  insurances 

which  transact  in  financial  markets  on  the  customer’s  behalf.  Transactions  in  banking  services 

include  the  transfer  of  money  via  bank  accounts  following  orders  from  customers  to  pay  for 

purchases  etc.,  the  transfer  of  money  to  a  savings  deposit,  the  provision  of  a  loan,  or  the 

purchase  or  sale  of  a  security.  Transactions  of  insurance  firms  involve  the  sales  of  insurance 

policies.  Traditionally, orders from customers have been done at the bank counter by completing 

more  or  less  simple  paper  forms,  or  by  completing  insurance  policy  application  forms  with  the 

assistance  of  agents  working  independently  or  not  for  insurance  companies.  Today,  electronic 

Methodological manual for Information Society Statistics 

51  

 
orders  for  these  services  via  Internet  applications  have  grown  but  the  proportions  are  not  yet 

exactly known and are expected to differ among countries.  

C1. Did your enterprise provide on-line financial services to customers via the 
information  services,  excluding 

Internet,  during  2005  (other  than 
manually typed e-mails)?  

[ Scope: enterprises with Internet access, i.e. B1 = Yes] 

[ Type: one single answer needed, i.e. Tick only one; binary (Yes/No); filter question] 

As  mentioned  in  chapter  I.1.6.2,  the  Internet  is  a  world-wide  open  computer  mediated 

system  (network)  that  transmits  data  by  packet  switching  using  a  standardised  Internet 

Protocol (IP) and related protocols (Internet protocol suit). Questions C1 and C2 (C2a, C2b) 

of  this  module  refer  to  the  Internet  Protocol  (IP)  based  networks  and  systems  such  as 

WWW, Extranet over the Internet, EDI over the Internet, virtual private network (VPN) over 

the  Internet  and  Internet  enabled  by  mobile  phones.  The  provision  of  on-line  financial 

services by manually typed e-mails via the Internet is excluded. 

The following question C2a is closely related with question C2b. 

C2a.  Which  of  the  following  products/services  did  you  provide  to  customers, 

during 2005? 

C2b.  For  which  of  these  products/services  did  you  receive  orders  from 

customers via the Internet, during 2005? 

[ Scope: enterprises which provide on-line financial services via the Internet, i.e. C1 = Yes] 

[ Type: multiple answers possible, i.e. one or more; binary (Yes/No)] 

For  enterprises  with  Internet  access  that  are  providing  on-line  financial  services  to 

customers, information is requested on the type of financial services offered (question C2a). 

That  information  will  allow  to  check  if  all  services  or  a  part  of  them  is  offered  on-line 

(question C2b).  

Should  none  of  the  services  mentioned  be  put  on  offer  on-line,  the  following  questions  in 

Module  C  can  be  skipped  and  the  respondents  can  continue  with  the  next  module  in  the 

questionnaire.    

Usual and possible services provided by banks and credit institutions for traditional and on-

line  internet  transactions  are  listed  as  answer  possibilities  a)  to  d).  Insurance  services  are 

distinguished  as 

life 

insurances  and  non-life 

insurances.  Compared  to  traditional 

transactions, on-line transactions via the Internet can be done anytime and from anywhere. 

Some on-line financial services may update the account and other transaction information in 

real time, others daily or less frequent. 

Major  services  are  listed  by  function:  enabling  payments,  savings,  loans,  investments, 

insurance. 

Methodological manual for Information Society Statistics 

52  

 
 
 
 
 
 
 
 
a) Payment services 

Payment  services  enable  customers  to  perform  orders  for  payment  of  invoices  or  for 

transfers from the customers' current account to other accounts or to apply for a credit card.  

b) Savings deposits 

Services offering savings deposits allow the customer to make deposits (and withdraw them) 

in a savings account. Deposits on savings accounts enable customers to save money and to 

earn  interest  rates  that  are  higher  than  on  a  current  (or  checking)  account.  The  customer 

can  make  deposits  by  opening  a  savings  account  at  the  bank.    An  order  regarding  savings 

deposits  is  for  example  to  instruct  the  bank  to  place  money  on  (directly,  or  indirectly  by 

transfer  from  other  accounts)  a  savings  account.    On-line  savings  deposits  may  be  less 

demanded  and  offered  if  offices  are  absent  and  the  account  holder  cannot  make  direct 

deposits in person.  

c) Loans  

Loans can be offered by credit institutions in a traditional manner or on-line via the Internet. 

The order for a loan involves the completion of an application for a loan. For the purpose of 

managing loan transactions, dept accounts may be opened by the bank.  

d) Investment services 

Services  rendered  by  a  bank,  stock  broker  or  an  issuing  house  in  placing  shares  and/or 

debentures  or  buying  and  selling  securities  (stock,  bonds,  shares  in  mutual  funds)  without 

subscribing  for  them  and  without  having  to  take  the  shares  and/or  debentures  onto  own 

books. The relations with the customers usually involve the opening of deposits for securities 

transactions.   As an example, an order from a customer is to request buying a security on 

his/her behalf from the bank. 

e) Life insurances 

f) Non-life insurances 

In  general  an  insurance  is  a  contract  whereby  a  person  or  legal  entity,  the  insurer, 

guarantees to indemnify wholly or partially another person, the insured, in consideration of a 

lump  sum  payment  or  payments  at  regular  intervals  known  as  premiums,  for  loss  suffered 

by the insured due to the occurrence of the hazard specified in the contract. 

An insurance policy is the contractual document setting out the signed and dated agreement 

between the insurer and the insured, which confirms the existence of the insurance contract 

between these parties and serves as proof thereof.  

An order for insurance, life or non-life, is to apply for an insurance policy. Examples for non-

life insurances are car insurance, health insurance, disability insurance, travel insurance and 

business insurance. 

Methodological manual for Information Society Statistics 

53  

 
C3.  Please  indicate  for  2005  and  for  the  following  groups  of  customers  the 
percentage  of  account/deposit  holders  who  used  interactive  ordering  via 
your  website (for banking  services,  if ticked 'yes'  in C2b  a), b), c) and/or 
d)) 

[ Scope: enterprises which provide on-line financial services via the Internet, i.e. C1 = Yes, 

and which provide banking services via the Internet,  
i.e. C2b a), b), c) and/or d) = Yes] 

[ Type: categorical/numerical] 

a) All account/deposit holders using interactive ordering via your website related to the total 

number of account/deposit holders 

 b) Private holders of accounts/deposits using interactive ordering via your website related to 

the total number of private account/deposit holders  

 c) Corporate holders of accounts/deposits using interactive ordering via your website related 

to the total number of private account/deposit holders 

 Banks and other credit institutions offering payment services, savings deposits, loans and/or 
investment  services  are  requested  to  indicate  the  percentage  of  customers  in  terms  of 

account/deposit  holders  ordering  via  the  website.  Since  the  percentage  of  customers  is 

viewed to be difficult to address, the percentage of holders of accounts or deposits should be 

considered. Addressing the amount of account/deposit holders in this context is perceived to 

be more simple and better recorded.  The percentage of website accounts/deposits according 

to different types of account/deposit holders (all, private, corporate) will serve as a possible 

alternative.  

Focus is laid on business-to-consumer eCommerce and types of consumers as subjects being 

of special interest in the area of financial services.  In particular, the possibility to separate 

private holders of accounts or deposits will support the monitoring of developments towards 

creating an integrated retail financial service market in Europe for which cross-border trade 

facilitated by eCommerce has received attention in European policy.  

Another focus concerning receiving orders from customers via the Internet is laid on the use 

of interactive ordering via the  website. This means  that the question is restricted to orders 

received  through  the  enterprise'  publicly  accessible  website  and  does  not  address  other 

possible  forms  of  ordering  via  the  Internet,  e.g.  EDI  over  Internet.  The  use  of  the  web 

interface  to  banks  and  other  credit  institutions  is  perceived  to  be  more  understood  and  to 

reflect increasing common practice by private and corporate customers of financial services. 

The web application facilitating the orders is usually interactive, by checking and informing of 

any  missing  details  to  be  completed  in  the  order  and  providing  notifications  to  the 

customers, e.g. when the order has been registered.  

The collection of information with a numerical value either in absolute terms or in percentage 

terms  is  not  considered  feasible  by  various  countries.  Therefore,  the  value  of  receiving 

orders  from  account/deposit  holders  is  stratified  by  six  classes  of  percentage  of 

account/deposit  holders  using  interactive  ordering  via  the  website  in  relation  to  the  total 

number of account/deposit holders.  The response categories are:  

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54  

 
 
 
 
• 

Less than 1% 

•  1% or more and less than 5% 

•  5% or more and less than 10% 

•  10% or more and less than 25% 

•  25% or more and less than 50% 

•  50% or more 

Alternatively,  respondents  have  two  possibilities  to  indicate  numerical  values:  They  can 

provide  an  estimated  percentage;  or  they  can  provide  the  absolute  values  in  terms  of 

numbers  of  account/deposit  holders.  The  more  countries  providing  numerical  values  in 

relation  to  the  total  number  the  better.  Finally  however,  the  aim  is  to  obtain  a  certain 

minimum level of measurement by using the percentage classes.  

The following question C4 is optional. 

C4.  Please  indicate  for  2005  the  importance  of  Internet  enabled  financial 
transactions  for  your  business  by  providing  percentages  or  absolute 
figures for the following values (for banking services, if ticked 'yes' in C2b 
a), b), c) and/or d)) 

[ Scope: enterprises which provide on-line financial services via the Internet, i.e. C1 = Yes, 

and which provide banking services via the Internet,  
i.e. C2b a), b), c) and/or d) = Yes] 

[ Type: categorical/numerical] 

a) Value of payment orders via Internet related to the total value of payment orders 

b)  Value  of  revenues  (commissions,  margins,  fees,  interest)  from  orders  via  the  Internet 

related to the total value of revenues (in monetary terms, excluding VAT)  

Compared  to  the  enterprise  survey  on  other  economic  activities,  variables  on  turnover  and 

production  value  have  not  proved  feasible  for  banking  services  and  insurances.  Therefore, 

the characteristics to be collected concentrate on the value of payment orders and the value 

of  revenues  from  commissions,  margins,  fees,  and/or  interest  which  are  perceived  to  be 

more  simple  measures.  The  question  is  optional,  meaning  that  the  results  should  be 

assessed in terms of possible future use in the survey.  

Following  the  same  ways  of  collecting  information  as  described  in  question  C3  above,  the 

value  of  payment  orders via  the  Internet  related  to  the  total  value  of  payment  orders,  and 

the value of revenues from orders via the Internet related to the total value of revenues are 

collected in terms of classes of percentage of the Internet related values on the total values. 

The use of percentage classes is related to expected difficulties in providing exact values and 

should increase response rates.   

Alternatively,  respondents  have  two  possibilities  to  indicate  numerical  values:  They  can 

provide  an  estimated  percentage.  They  can  also  provide  the  absolute  values  in  terms  of 

value  of  payment  orders and  value  of  revenues  received  via  the  Internet  together  with  the 

total values for grossing up purposes.  

Methodological manual for Information Society Statistics 

55  

 
 
 
 
 
C5.  Please  indicate  for  the  following  groups  of  customers  the  percentage  of 
insurance  policies  ordered  via  your  website  and  related  revenues,  during 
2005. (for insurances, if ticked 'yes' in C2b e) and/or f)) 

[ Scope: enterprises which provide on-line financial services via the Internet, i.e. C1 = Yes, 
and which provide insurance services via the Internet, i.e. C2b e) and/or f) = Yes] 

[ Type: categorical/numerical] 

a)  Insurance policies ordered by private customers/individuals via your website related 

to the total number of insurance policies  

b)  Insurance  policies  ordered  by  corporate  customers/enterprises  via  your  website 

related to the total number of insurance policies  

c)  Value  of  Gross  Premiums  Written  from  private  and  corporate  insurance  policies 

ordered  via  your  website  related  to  the  total  value  of  Gross  Premiums  Written,  (in 

monetary terms, excluding VAT)  

This  question  is  collecting  information  on  customers  ordering  insurance  services  via  the 

website.  In  detail,  the  question  will  measure  the  receipt  of  orders  or  applications  for 

insurance  policies  via  the  website,  the  two  different  types  of  insurance  policy  holders 

(private,  corporate),  and  a  monetary  value,  i.e.  gross  premiums  written.  As  recognised  in 

insurance  service  statistics,  the  variable  "gross  premiums  written"  should  replace  and 

provide an equivalent to turnover.  

Following  the  same  ways  of  collecting  information  as  in  the  previous  two  questions,  values 

are collected in terms of classes of percentages, in this case of insurance policies ordered via 

the website by private customers as well as ordered by corporate customers and of the value 

of gross premiums written resulting from website orders for insurance policies.  

Alternatively,  respondents  have  two  possibilities  to  indicate  numerical  values:  They  can 

provide an estimated percentage; or they can provide the absolute values, here in terms of 

numbers  of  insurance  policies  and  value  of  gross  premiums  written  in  national  currency, 

excluding VAT. The minimum aim is to obtain data on the different percentage classes.  

The  number  of  classes  and  the  range  of  values  for  each  of  the  classes  are  the  same  for 

questions C3, C4, and C5.  Percentage bases are the total number of insurance policies. 

C6.  Please  provide  a  percentage  breakdown  of  all  Internet  sales  of  retail 
financial  services  in  2005,  by  destination  (estimates  in  percentage  of  the 
total retail customers who ordered via the Internet) 

 [ Scope: enterprises which provide on-line financial services to customers via the Internet, 

i.e. C1 = Yes] 

[ Type: numerical] 

For  respondents  providing  on-line  financial  services  to  customers  via  the  Internet,  a 

percentage breakdown of the Internet sales of retail financial services by destination, i.e. in 

terms  of  considering  the  residence  of  the  private  customer  or  individual  as  client  is 

requested.  Normally,  the  customers  of  financial  services  must  indicate  their  address  of 

residence  including  the  country  of  residence  when  opening  bank  accounts  or  purchasing 

Methodological manual for Information Society Statistics 

56  

 
 
 
 
insurance  policies.  The  respondents  should  give  estimates  in  percentages  of  the  total 

number of retail customers who ordered or purchased via the Internet. 

If  the  number  of  retail  customers  in  banking  and  insurance  services  as  such  is  not  known, 

the information to be collected should consider the total number of private account/deposit 

holders and private holders of insurance policies.  The countries of residence  of the private 

customers  (individuals)  or  private  holder  of  accounts,  deposits,  and  insurance  policies  who 

ordered  or  purchased  via  the  Internet  (usually  using  the  www,  Internet  enabled  mobile 

phones  and  not  EDI  over  Internet)  should  be  reflected  in  the  breakdown.  The  breakdown 

should sum up to 100 %.   

The destination categories of the retail customers used are: 

a) Own country 

All territory of the country is considered, either inside the EU or not. 

b) Other EU countries 

The territory of all the Member-States of the EU is considered, except the country where 

the survey is conducted if it is one of the EU Member-States. 

c) Rest of the world 

This  item  includes  all  the  remaining  countries  of  residences  of  retail  customers  who 

placed orders via the Internet. 

The  question  is  aimed  to  contribute  to  monitoring  advances  towards  an  integrated  retail 

financial services market in Europe facilitated by e-Commerce via Internet. 

I.1.7.2.3.  MODULE  D:  E-COMMERCE  VIA  COMPUTER  MEDIATED  NETWORKS  OTHER  THAN 

INTERNET (OPTIONAL) 

The  module  on  e-commerce  via  other  computer  mediated  networks  has  been  marked 

optional,  reflecting  certain  difficulties  faced  during  the  pilot  testing  to  understand  other 

networks  used  in  financial  services  in  the  right  way.  However,  the  two  questions  of  the 

module  are  considered  to  be  much  less  complex  than  earlier  versions  of  the  questionnaire 

for the financial sector. 

As in Module C, the provision of on-line financial services via other networks to consumers, 

i.e. business-to-consumer e-commerce is addressed. The first question is held more general 

not  distinguishing  types  of  customers  while  the  second  question  takes  into  account  the 

certain networks used by certain types of customers. 

D1. Did your enterprise receive orders from customers via networks other than 

Internet, during 2005? 

[ Scope: all enterprises] 

[ Type: one single answer needed, i.e. Tick only one; binary (Yes/No); filter question] 

Networks other than Internet are those that are used for communication between computers 

but  that  are  not  publicly  accessible  'Wide  area  Networks'  such  as  the  Internet.  They  are 

usually  proprietary  networks  made  up  of  leased  lines  and  can  cover  local  and  wide 

Methodological manual for Information Society Statistics 

57  

 
 
geographical  areas.  They  exclude  all  IP/Internet  Protocol  based  networks  mentioned  under 

question C1 above.  

Respondents are requested to indicate if they receive orders from any customer over other 

computer  mediated  networks.  Orders  can  concern  any  type  of  financial  transaction. 

Examples  are  the  transfer  of  money  between  bank  accounts,  the  application  for  a  loan  or 

purchase  of  an  insurance  policy,  or  cash  payment  orders  at  points  of  sale  or  self-service 

zones using proprietary networks linked to cash dispensers.  

D2.  Did  your  enterprise  use  the  following  electronic  networks  other  than 

Internet to receive orders from customers? 

[  Scope:  enterprises  receiving  orders  from  customers  via  networks  other  than  Internet,  i.e. 

D1 = Yes] 

[ Type: multiple answers possible, i.e. Tick one or more; binary (Yes/No)] 

To  increase  the  understanding  of  respondents,  the  question  provides  some  detailed 

examples  of  other  computer-mediated  networks  used  by  financial  services  and  their 

customers.  

The use of other computer-mediated networks in the financial services sector and especially 

in banking is quite widespread, both in terms of managing relations with customers as well 

as  in  inter-banking  relationships.  We  focus  all  questions  in  module  D  on  relationships  with 

customers, retail customers (private, individuals) and corporate customers. 

a)  Network  to  receive  payment  batch  orders  from  corporate  customers'  computer 

applications 

Banks  and  other  credit  institutions  can  receive  batch  orders  for  payments  from  corporate 

customers'  computer  system.  Payment  batch  orders  are  a  collection  of  payment  orders 

which  should  be  processed  as  a  group  and  at  a  certain  time.  It  may  concern  payment  of 

recurring or non-recurring invoices to suppliers or salary payments for companies' personnel.  

b)  Self-service  zones  with  cash  dispensers  (e.g.  bancomats)  and/or  credit  card  payment 

orders from retail customers/individuals 

Retail customers (private customers, individuals) have received cards from their banks and 

other  credit  institutions  to  make  electronic  payments.  The  category  refers  to  any  payment 

card, such as credit, debit, or charge card; the term credit card is sometimes used for other 

payment cards. Debit cards (debiting the current account) are often used for cash dispensers 

which can offer more facilities than receiving cash money, e.g. paying bills by giving order to 

transfer  money  from  the  own  current  account  to  another,  displaying  account  information. 

Credit  cards  enable  to  pay  for  purchases  up  to  certain  credit limit.  Debit  cards  are  used  as 

alternative  to  make  payments  for  purchases  at  shops  with  the  difference  that  they  directly 

deduct  the  amount  from  the  purchaser's  account.  Cards  can  combine  credit  and  debit  card 

properties.  

Payment cards are often used by retail customers of banks in so-called self-service zones or 

at points of sales which have a cash dispenser (also called bancomat, 'Geldautomat', or ATM, 

Methodological manual for Information Society Statistics 

58  

 
 
 
 
i.e.  automatic  teller  machines).  These  are  computing  machines  connected  to  proprietary 

networks and provide links to the banks' computer systems.   

Similar,  card  payment  orders  can  be  placed  by  retail  customers  at  points  of  sales  or 

supermarkets and retail stores. The devices used are sometimes called EFTOS, i.e. electronic 

funds  transfer  at  point  of  sale,  or  payment  terminal,  which  uses  card  or  chip  readers  and 

require entering of the amount of payment and PIN number.  

c) Network to receive orders from sales agents computer systems linked to your enterprise 

computer system 

This  example  can  concern  both  banks  and  insurance  companies  which  often  maintain 

relationships  to  agents  (insurance  agents,  brokerage)  to  sell  their  products  (e.g.  insurance 

policies, investment fonds).  

d) Other  

This option is given to evaluate the extent of any other networks in use. Respondents may 

use other networks for other purposes than the possibilities listed above.  

I.1.7.2.4.  MODULE X: BACKGROUND INFORMATION 

The background variables in the model questionnaire for the financial sector allow to breakdown 

the results from the main characteristics, to weight certain variables, or to stratify the sample.  

Since  module  C  and  D  in  the  model  questionnaire  for  the  financial  sector  do  not  address 

monetary  variables  or  the  same  type  of  monetary  variables  as  compared  to  the  general 

enterprise survey for the other economic activities, the background variables "Total purchases of 

goods and services" and "Total turnover" are not addressed.  

The questionnaire is limited to the following background variables: 

X1:  Main activity of the enterprise 

The main activities of the financial sector addressed according to NACE Rev. 1.1 are either  

-  monetary  intermediation  of  monetary  institutions other  than  central  banks  (class  65.12); 

postal giro and postal savings bank activities are included in this class.  

- other credit granting (class 65.22); this includes granting of consumer credit, provision of 

long-term  finance  to  industry,  money  lending  outside  the  banking  system,  credit  granting  by 

mortgage credit institutions 

- life insurance (class 66.01) 

- non-life insurance (class 66.03); class 66.02 relates to pension funding and is excluded. 

Voluntary or optional activities for which the model questionnaire for the financial sector can be 

used are the following activities auxiliary to financial intermediation: 

-  class 67.12: Security broking and fund management 

Methodological manual for Information Society Statistics 

59  

 
 
 
 
 
 
 
-  class  67.13:  Activities  auxiliary  to  financial  intermediation  not  elsewhere  classified; 

examples are mortgage brokers, 'bureaux de change', etc. 

-  group  67.2  (class  67.20):  Activities  auxiliary  to  insurance  and  pension  funding;  e.g. 

insurance agents. 

X2:  Average number of persons employed  

(or if not available "number of persons employed") 

As  stated  for  the  general  enterprise  survey,  efforts  should  be  made  to  obtain  the  average 

value from the most recent SBS survey. However, information from SBS concerning the financial 

sector  may  not  be  available.  In  this  case,  the  number  of  persons  employed  in  December  2005 

should be collected. 

X3:    Location  (objective 1/non-objective 1 region) 

For further information on the background variables X1, X2 and X3, including location and list of 

objective 1 regions, reference is made to chapter I.1.6.5. 

Methodological manual for Information Society Statistics 

60  

 
 
 
 
 
I.2. 

PRODUCTION METHODOLOGY 

I.2.1. Timetable – Survey period 

The survey period of the Community Survey on ICT Usage and e-Commerce in Enterprises is the 

first  quarter  of  calendar  year  t.  The  variables  in  the  questionnaire  are  predominantly  of  a 

qualitative  nature  (yes-or-no-questions  or  tick-box-questions).  The  answers  to  these  questions 

refer  to  the  situation  in  January  of  year  t.  The  answers  to  the  quantitative  questions  -  for 

example  the  percentage  of  total  turnover  realised  by  sales  over  the  Internet  -  refer  to  the 

calendar year t-1. 

In  order  to  minimize  the  recall-bias  of  the  respondent  the  collection  should  occur  just  after  the 

reference period, after January during the first quarter. However, some countries have difficulties 

in collecting monetary data (turnover and purchases) right in the beginning of the year. In these 

cases, the collection should start as soon as possible. Preferably still during the first quarter. 

To  maximize  the  level  of  harmonization  between  the  national  surveys  in  the  different  Member-

States, it is important that this survey period is respected as much as possible. 

Table: Overview of the survey periods (2005 survey) 
Source: Final reports for the Community Survey on ICT Usage and e-Commerce in Enterprises (2005) 

Belgium 

Second half of March 2005 – Mai 2005 

Czech Republic 

Second quarter 2005 

Denmark 

Germany 

Estonia 

Greece 

Spain 

Ireland 

Italy 

Cyprus 

Latvia 

February-April 2005.  

First quarter 2005 

The questionnaires were sent out in March 2005. The deadline was the 1 of May 2005 

The survey started on March 2005. 

Data collection was carried out on the second quarter 2005 

April 2005 

April-September 2005. 

Data collection period: 28/1/2005 – 18/3/2005 

Survey period was May 2005 

Lithuania 

First quarter 2005 

Luxembourg 

April-May 2005 

Hungary 

Malta 

First quarter of 2005. 

February to March 2005 as planned. 

Netherlands 

February 2005: sending out the questionnaires, general survey 

Austria 

Poland 

Portugal 

Slovenia 

Started on 2nd February 2005; Last questionnaire received on 23rd May 2005 

From 1st April till 30th April 

Data collection started in April and finished in November. 

7th March 2005 – 31st May 2005 

Slovak Republic 

Questionnaires sent in March. Required date of questionnaire return was April 2005 

Finland 

Sweden 

Mailing started beginning of February; Most responses received in May at the latest. 

Questionnaires sent 23rd March 2005. Data collection lasted until the beginning of July. 

United Kingdom 

The survey was conducted during 2005 

Norway 

Paper questionnaires sent and web questionnaire available 9 March 2005. Returned paper 
questionnaires no longer accepted, Web questionnaire taken off Internet 21 May 2005. 

Methodological manual for Information Society Statistics 

62  

I.2.2. Frame population 

Normally, the enterprise ICT survey will be carried out in the form of a sample survey. The frame 

population  (or  sampling  population)  is  the  list  of  enterprises  from  which  the  sample  will  be 

drawn.  Ideally,  this  list  of  enterprises  should  be  equivalent  to  the  target  population  as  both 

over-coverage and under-coverage can induce bias and affect the reliability of the survey results. 

E.g.  over-coverage due  to  inclusion  of  enterprises  which  main  economic  activity  is  agriculture  (outside 
the  scope  of  the  Community  Survey)  in  the  sampling  frame:  if  this  sector  presents  below  the 
average adoption of ICT, the population total may show a downwards bias due to inclusion of this 
group. 

E.g.  under-coverage  due  to  the  fact  that  some  remote  areas  are  not  covered  in  the  register:  as  such 
areas  usually  have  a  lower  penetration  of  ICTs,  the  overall  indicators  may  be  relatively 
overestimated for such country. 

The  sample  for  the  Community  Survey  should  be  drawn  from  the  business  register  in  the 

different Member-States as defined in Council Regulation (EEC) No 2186/93. Part of this register 

is  the  activity  code  at  the  four-digit  (class)  level  of  NACE  Rev.1,  the  size  measured  by  the 

number  of  persons  employed  and  the  geographical  location  code  (territorial  units)  of  the 

enterprises. 

The  choice  to  comply  with  the  enterprise  as  the  appropriate  statistical  unit  and  the  business 

register and its enterprise’ characteristics as the framework population, is inspired by the wish to 

keep  a  certain  level  of  consistency  with  the  Structural  Business  Statistics.  On  a  meso-level  as 

well as on a micro-level results of the Structural Business Statistics will be combined with data on 

the  ICT  usage  of  enterprises  for  analysis  and  for  weighting-purposes  (for  the  latter:  see 

paragraph 2.3.3). 

To allow for an assessment, it is important to include the coverage and the sampling frame when 

reporting metadata (see Chapters 3 and 5 in the reporting template, Annex I.3.4). 

The  table  below  presents  the  sampling  frames  used  in  the  national  statistical  institutes  for  the 

2005 survey.  

Table: Overview of the sampling frames (2005 survey) 
Source: Quoted from the Final reports for the Community survey on ICT usage and e-commerce in enterprises 

(2005) 

Belgium 

Frame population is derived from SBS frame population: elimination of enterprises with 
<  5  persons  employed  or  NACE  different  from  ICT-frame.  Some  SBS  reporting  units 
coupled if they belong to the same enterprise in the business register.  

Czech Republic 

The frame population is the same as the one for the Structural Business Survey (SBS). 

Denmark 

Germany 

Estonia 

Greece 

The frame population corresponds with SBS. 

The sampling base of our survey is the active enterprise register. 

The frame is the same as for short term business statistics as main questions are about 
January  2005.  The  same  frame  is  also  used  for  SBS,  the  only  difference  is  that 
enterprises, which were active only part of 2004 and are not active in 2005 are included 
in 2004 SBS survey but not in the ICT survey. 

The  sampling  frame  used  was  based  on  data  coming  from  the  Business  Register  of 
NSSG.  This  Business  Register  was  set  up  from  data  coming  from  tax  authorities  and 
social security funds. Moreover, this register was updated with data obtained by recent 
statistical surveys of NSSG. The frame population is the one used for the SBS. 

Methodological manual for Information Society Statistics 

63  

 
Spain 

Ireland 

Cyprus 

Latvia 

The  frame  population  of  the  ICT  survey  is  the  same  as  the  one  used  for  the  SBS: 
DIRCE. The Central Businesses Directory (DIRCE) collects all Spanish businesses in a 
single directory. Its basic objective is to enable business-targeted sample surveys to be 
conducted,  and  consequently,  it  registers  information  such  as  identity  data,  location, 
main  activity  or  number  of  employees. This  information is  obtained  from  administrative 
sources  (Inland  Revenue  and  Social  Security)  and  complemented  with  data  from 
common statistical operations. Moreover, this directory is annually updated.  

The  CSO  Central  Business  Register  provides  the  frame  population.  The  Central 
Business Register is also used by the SBS surveys. 

The  frame  population  is  the  Registration  of  Establishments  2000  which  is  updated  on 
the  basis  of  the  Employment  Survey  and  other  resources  so  as  to  take  into  account 
changes  in  the  structure  of  employment  by  industry,  occupation  and  size  of 
establishment. The frame population is used for the Structural Business Statistics too. 

The statistical business register holds information on all enterprises that are registered 
in the administrative Enterprise Register of the Republic of Latvia. In the sampling frame 
only economically active enterprises from the business register are included and it is the 
same as used for the Structural Business Statistics. 

Lithuania 

The  statistical  unit  of  survey  are  economically  active  enterprise  as  defined  in  the 
Statistical Business Register. 

Luxembourg 

For the sample design, the enterprises register was used. 

Hungary 

The  frame  population  is  almost  the  same  as  the  one  used  for  the  Structural  Business 
Statistics.  The  underlying  register  concerning  the  target  population  is  the  Business 
Register of Enterprises. The observation and sampling units consist of those enterprises 
that have an obligatory data provider status in December 2004 concerning the following 
surveys:  "Simplified  monthly  report  on  the  industrial  activities”,  “Simplified  monthly 
report  on  the  construction  activities”,  “Simplified  monthly  report  on  the  agricultural, 
trading and service activities”. All these enterprises build up the frame of the survey, i.e. 
the sampling frame. The observation units of the survey consist of the enterprises that 
belong to the chosen sample elements concerning the above mentioned surveys. 

Malta 

The frame population is taken from the Business Register section of the NSO. 

Netherlands 

Austria 

Poland 

Portugal 

Slovenia 

The  population  described  in  the  ICT-survey  is  drawn  from  the  same  business-register 
as the survey for the Structural Business Statistics and at the same reference date i.c 1-
12-2004. 

Frame  population  is  the  enterprises  in  the  National  Business  Register.  SBS  use  the 
same source for sampling. 

- 

The frame population of this survey is the reference universe of the Structural Business 
Statistics, which is taken from the national business registers. 

The  sampling  frame  was  made  by  using  the  data  from  the  Business  Register  of  the 
Republic of Slovenia and the data from some other surveys. 

Slovak Republic 

Frame  population  was  based  on  the  same  Register  of  statistical  units  as  in  case  of 
structural business statistics. 

Finland 

Sweden 

The  frame  population  is  drawn  from  the  production  database  of  Structural  Business 
Statistics. 

The sampling frame is the Swedish Business Register. 

United Kingdom 

Whole UK economy taken from the ONS business register, based on SBS. 

Norway 

The frame population is based on the Structural Business Statistics. 

I.2.3. Sampling design 

The  survey  should  be  based  on  a  probability  sample  from  which  results  representative  of  the 

population could be derived, considering the agreed breakdowns defined in the questionnaire. 

The  sampling  design  and  the  resulting  sample  size  (see  below)  should  be  appropriate  for 

obtaining  accurate,  reliable  and  representative  results  on  the  survey  characteristics  and 

breakdowns specified in the Regulation and the model questionnaire. 

Methodological manual for Information Society Statistics 

64  

 
 
This  objective  should  be  achieved  for  the  overall  proportions  as  well  as  for  the  proportions 

relating  to  the  different  subgroups  of  the  population.  The  estimated  coefficient  of  variation  (or 

relative standard error) should not exceed 2% for the overall proportions and should not exceed 

4%  for  the  proportions  relating  to  the  different  subgroups  of  the  population  where  these 

subgroups constitute at least 5% of the total population in the scope of the survey. 

The aim of such requirement is to ensure the collection of a complete dataset – without empty, 

confidential or unreliable cells - for these indicators. 

Table: Overview of the sampling design and sampling methods (2005 survey) 
Source: Quoted from the Final reports for the Community Survey on ICT Usage and e-Commerce in Enterprises 

(2005) 

Belgium  

Stratified random sample: 

Czech Republic  

▪  Stratification  by  Activity  (17  categories),  Size  class  (4  categories)  and  NUTS1  region  (3 

categories), resulting in 204 strata. 

▪  Exhaustive selection in strata with less than 5 enterprises. Oversampling of smaller regions. 

Sample selection = SRS algorithm in SPSS. 
No procedures for the coordination of non-overlapping with other samples. 

Stratified  random  sampling  for  enterprises  with  5-249  and  census  for  250  and  more  employees 
with respect to Business Register was used. 
Number of enterprises and number of employees was used for stratification. GREG was used for 
sample design. The sample was designed with no reference to any other survey. 
Sample  size  was  designed  to  enable  accurate,  reliable  and  representative  results  for  breakdown 
into four size groups, 32 NACE aggregates groups and two territory groups and for main variables 
as a cross-tabulated. 

Denmark  

The sample is a stratified random sample made by use of register-based data. 
Strata was made by: 

▪  employment (10-19, 20-49, 50-99, 100+) and 
▪  activity (Nace, 2-digit) 

Germany  

Estonia  

Greece  

Germany  used  a  two-stage  stratified  random  sample.  The  stratified  variables  were  federal  states 
(first stage), economic activities (NACE) and number of employees (second stage). 

The data are collected by sample survey, using stratified simple random sampling. The sample is 
stratified by economic activity and by number of persons employed. 
By  number  of  persons  employed,  the  survey  includes  all  enterprises  with  50  and  more  persons 
employed. Stratified  simple  random sampling  is  used  for  enterprises  10  to  49  persons  employed. 
For  data  processing  the  enterprises  were  divided  by  number  of  persons  employed  into  following 
size groups: 10-19, 20-49; 50-99; 100-249; 250-499; 500-999; 1000+ 
Sample was drawn using permanent random numbers. The choice of starting point between 0 and 
1  guarantee  non-overlap  with  two  large  sample surveys:  wages survey  and  structure  of  business 
survey. 
The number of strata is 263. 

The sampling method applied was the simple stratified random sampling, employing the enterprise 
as the survey unit. 
The enterprises with 10 or more employees included in the survey were stratified as following: 

▪  By geographical region – NUTSI 
▪  By aggregations of NACE Rev.1 subsections, as defined in the relevant contract, within each 

geographical region  

▪  By size class of the enterprise. 

In each one of the major strata (major stratum = Geography x Economic Activity), the enterprises 
were  stratified  into  L=7  size  classes,  according  to  their  size,  determined  by  their  average  annual 
number of employees in the business register, as follows. 

Size Class  
Class 1  
Class 2  
Class 3  

Number of employees 
10-19 
20-49 
50-99 

Methodological manual for Information Society Statistics 

65  

 
 
 
 
 
 
Spain 

Ireland  

Cyprus  

Class 4  
Class 5  
Class 6  
Class 7  

100-249 
250-499 
500-999 
1000+ 

In  one  geographical  region,  for  one  economic  activity,  let  h  be  one  size  class.  So  h  will  take  the 
following values: h=1,2,…,7. In the initial sampling design, the size classes with h=3,4,5,6,7 were 
census  strata  (take-all),  because  they  contain  the  large  size  units  and  the  element  population 
variance  is  high.  In  each  stratum  (let  h),  a  sample  of  nh  enterprises  was  selected  from  the  total 
number  of  enterprises  Nh  with  equal  selection  probabilities,  by  applying  the  systematic  sampling 
method.  In  the  size  classes  with  h=1,2,  the  distribution  of  sampling  units  was  conducted  by 
applying the Neyman technique (optional allocation). The final sample size (survey in Nace Groups 
except  Nace  J)  was  4.668  enterprises  (sampling  rate  =  26,01%),  of  which  the  1.787  enterprises 
belong  to  the  first  two  size  classes  (they  were  surveyed  on  a  sample  basis)  and  the  rest  2.881 
enterprises belong to the census size classes. 
The  whole  sample  size  was  defined  so  that  the  results  to  reflect  the  true  situation  of  the  total 
population units with a sufficient degree of representativeness. 
Finally,  concerning  the  aggregations  65.12+65.22,  66.01+66.03  and  67.12+67.13+67.2  (separate 
survey for Nace J), these were also exhaustively surveyed (118 enterprises). 

According to the frame population (extracted from the DIRCE), the statistical units are stratified by 
crossing the following variables: size, economic activity and location. 
In  every  stratum,  a systematic selection  randomly started is  executed, sorting  out  the  enterprises 
by size and location. 
The categories of the variables used to stratify are: 

▪  size: 0 to 2, 3 to 9, 10 to 49, to 199, 200 or more 
▪  main activity: following the aggregation of NACE classification as follow: 

GENERAL QUESTIONNAIRE: 
1)DA+DB+DC+DD+DE 
2)DF+DG+DH 
3)DI+DJ 
4)DK+DL+DM+DN 
5)E (40+41) 
6)F (45) 
7)G (50) 
8)G (51) 
9)G (52) 
10)H (55.1+55.2) 
11)I (60+61+62+63) 
12)I (64) 
13)K (72) 
14)K (70+71+73+74) 
15)O (92.1+92.2) 
FINANCIAL SECTOR: 
1)J (65.12+65.22) 
2)J (66.01+66.03) 
3)J (67.12+67.13+67.2) 

▪  region:  all  Spanish  regions  (19)  are  covered  (except  for  the  pilot  survey  referred  to 

enterprises with less than 10 employees). 

The total number of initial strata is 1.710 (18*5*19), including empty strata.  

Stratified  random  sample.  NACE  (2  digit  level)  and  employment  size  class  (10-49,  50-249  and 
250+) were the variables that were used to stratify. 
In total there were 136 strata. 
Where possible, to assist reduce the response burden on small and medium size enterprises, we 
try to minimise the possibility of these enterprises being included in both the SBS and ICT surveys. 

The  sampling  method  used  was  stratified  random  sampling.  Two  variables  were  used  for 
stratification, NACE group and size. There were 14 NACE groups and 3 size groups. 
Due  to  the  small  number  of  large  and  medium  enterprises  it  has  been  decided  to  use  all  those 
enterprises  in  the  sample.  Half  of  the  small  enterprises  were  selected  systematically  with 
probability proportional to size from a list ordered in ascending order by enterprise size. 
Sixty  additional  enterprises  were  included  in  the  sample  in  April  2005,  in  order  to  update  the 
sample and include almost all enterprises from smaller NACE groups. These enterprises belong to 
NACE groups: 23-25, 50, 64, 72, and 92.1-92.2. 
The  size  of  the  sample,  i.e.  1240  enterprises,  could  satisfactorily  serve  the  desirable  and 
acceptable confidence  limits  of the  survey  results,  taking  always  into  consideration time  and cost 
constraints. 
The total number of all financial enterprises falling in the 3 NACE groups, for the size classes 10-
49, 50-249, 250+ is small (113 enterprises), thus all enterprises are used. 

Methodological manual for Information Society Statistics 

66  

 
 
 
 
Latvia  

Lithuania  

The sample is made as stratified simple random sample. The stratification is made according to the 
main line of economic activity of enterprise (according NACE breakdown shown in general outlines 
of ICT survey), the territorial location of enterprise (6 regions) and enterprise size group (5 groups). 
Size  groups  were  defined  by  turnover,  number  of  persons  employed,  value  added  tax  paid, 
balance  and  other  variables.  The  final  number  of  strata  was  597  (considering  also  other  NACE 
activities for national needs). 
The  sample  allocation  is  made  using  proportional  allocation.  There  are  different  proportions  for 
each  size  groups  of  enterprises.  The  proportions  depend  on  population  size  of  strata.  The 
proportions are higher for strata with smaller population size. 
The sample for this survey is made as sub-sample from Structural Business Statistics survey. The 
sampling fraction for the biggest enterprises was 100%. 

It was used stratified one-stage random sampling. 
The number of employees was used to stratify population. Categories of variables:  

▪  number of employees: 10-49; 50-249; 250 and more. 

The final number of strata – 54. 
The Neyman optimal allocation was used for sample selection and determination of sample size. 
If stratum size is 20 or less then all enterprises in this stratum are included. 
All financial enterprises are covered in the survey. 

Luxembourg  

A census have been made. 

Hungary  

Malta  

The  sample  selection  was  done  with  a  stratified  sampling  scheme.  The  strata  are  formed  in  the 
following way. 
Concerning the NACE-codes all the 2-digit level branches are being treated as a different stratum. 
We  break  down  some  2-digit  level  branches  to  smaller  sub-branches,  if  there  is  a  need  for  a 
separate  treatment  considering  the  importance  or  the  size  of  these  areas.  This  is  being  done  by 
this way. 
Branch Sub-branches 
14 14.21 and others 
22 22.22 and others 
28 28.11 and others 
29 29.24 and others 
36 36.14 and others 
37 37.10 and others 
45 45.1, 45.21, 45.25, 45.22-45.24, 45.3, 45.4, 45.5 
50 50.10 and others 
51 51.70 and others 
55 55.1-55.2, 55.30, others from 55.3-55.5  
60 60.24 and others 
63 63.40 and others 
80 80.42 and others  
Concerning  the  number  of  employees  the  following  categories  are  being  treated  separately:  40 
(20-49 employees), 30 (10-19 employees), 22 (5-9 employees). 
The capitol Budapest and the provinces are forming different strata. 

The distribution of the sample among the above defined strata is being done by the following. By 
the  cooperation  with  the informatics  department  we  know  the  number  of  enterprises  belonging  to 
the sample frame in all the single strata. This information is available for the time periods January 
2002 and January 2003 (in the latter case provisional data are available). 
The  final  sample  sizes  are  determined  by  the  well-known  Neumann-type  optimal  allocation.  For 
this  procedure  we  make  use  of  the  information  available  for  the  previous  time-period  concerning 
the stratum level statistics for different variables. 
The process of sample selection is done by the following. A random number is being assigned to 
all the enterprises in the sampling frame. After that we add 1 or 2 to the value of some enterprises 
in order to give preference to some of them. Then the process of sample selection is being done by 
ordering the enterprises by the assigned values and then choosing those that possess the biggest 
values. The underlying concept of the distortion process can be described in this way. We want to 
include firstly those  enterprises  which  were  in the sample  in  2002 but  not  in  the  sample  between 
1998 and 2000. Secondly, those enterprises which were not included in the sample neither in 2002 
nor between 1998 and 2000. Thirdly those sample elements from 2002 which were in the sample 
between 1998 and 2000 too. Fourthly, those which were in the sample between 1998 and 2000 but 
not in the sample in 2002. 

For size class FTE 50-249 and 250 and over, all enterprises were covered.  For size class 10 to 49 
FTE, 4 divisions were limited to 50 respondents.   
Regarding the micro-enterprises only, that is from 1-4 FTE and from 5-9 FTE size classes, this was 
approached by a quota structure of 50 maximum, but with aggregated NACE for Manufacturing D 
as a whole, and Motor, Wholesale, Retail Trade also taken as one cluster.  See Excel file for the 
sampling scheme for this purpose. 

Methodological manual for Information Society Statistics 

67  

 
Netherlands  

The target-variables (of year t-1) used to allocate the sample are: 

▪  the number of enterprises receiving orders online (a qualitative variable); 
▪  - the number of fte’s spend on developing own account software (a quantitative variable). 
The  population/sample  was  divided  into  56  NACE-aggregates  and  7  groups  of  size-classes 
resulting in 392 cells/strata. 
Ca.  12  000  enterprises  were  allocated  in  a  way  that  on  a  national  level  the  relative  confidence-
intervals for the target-variables were as small as possible. Enterprises with 250 or more employed 
persons  were  integrally  included  in  the  sample.  By  choosing  a  maximum  number  of  12  000 
enterprises  to  be  allocated  a  response  percentage  of  50  percent  is  anticipated.  In  principle  the 
Neyman-allocation was used to allocate the 12 000 enterprises over the different strata, meaning 
that  the  allocation  is  inversely  proportional  to  the  variance  of  the  target-variable  in  the  relevant 
strata. 
A rotation-fraction of .5 was used, meaning that 50 percent of the sample – if possible – exists of 
enterprises  which  also  in  the  year  t-1  were  included  in  the  sample.  A  system  to  ‘spread’  the 
administrative burden for enterprises is used to avoid - if possible - that certain enterprises receive 
a lot of questionnaires in year t and others none or just a few. So, the overlap with other surveys in 
the same period e.g. the structural business statistics survey, is minimized. 

Austria  

Stratified random sample; 2 dimensions were used as stratification variables: 

▪  Main economic activity: 

8 strata: sections D, F, G, H (only 55.1 and 55.2), I, J, K, and 92 (only 92.1 and 92.2)  

Poland  

Portugal  

Slovenia  

Slovak Republic  

Finland  

▪  Size classes 

3  strata:  10-49  employed  persons,  50-249  employed  persons,  more  than  250  employed 
persons 

8 x 3 = 24 strata 
A full census was carried out among enterprises with 250 or more persons employed.  

Firstly, some domains of economic activity and large enterprises (with more than 249 employees) 
were taken wholly to the sample. This gave 3633 units. Secondly to start rotation, enterprises from 
the last year sample that were present in the 2005 frame were also taken to the sample. This gave 
4508 units . Thirdly some cross strata of economic activity and size that contained small number of 
enterprises  were  also  taken  wholly  to  the  sample.  They  were  118  units.  Thus  we  obtained  8259 
units  in  the  sample.  The  remaining  units  were  allocated  using  method  of  equal  precision  in  the 
domain  (of  economic  activity)  and  Neyman  allocation  among the strata  (size*won  –administrative 
unit).  This  way  5265  of  units  were  allocated.  Finally  just  before  starting  the  survey  (in  March) 
sample was corrected  by removing some not active enterprises and adding new units because of 
some small changes in population. 

The sampling method used was the stratified random sample. Two variables were used to stratify 
the sample: 

▪  NACE Rev.1.1 in the following domains: DA, DB, DC, DD, DE, DF, DG, DH, DI, DJ, DK, DL, 

DM, DN, 45, 50, 51, 52, I (60-63), I (64), K (72), K (70+71+73+74), O (921+922); 

▪  Number  of  employed  persons  in  the  following  domains:  1-4;  5-9;  10-49;  50-249;  250  and 

more. 

For large enterprises a census is adopted. 

Design of the sample was stratified systematic sample. Activity group and size class were used as 
stratification variables. 
In addition, implicit stratification by 5–digit NACE group was used. 
No procedures for coordinated samples were applied. 

The  sample  was  created  on  the  base  of  the  same  methods,  which  were  used  in  other  surveys 
organised  by  SO  SR  (short-term  surveys,  structural  business  surveys).  In  comparison  with  other 
surveys  the  boundary  between  exhaustive  and  sample  survey  was  changed  in  the  direction 
upwards.  
In  this  survey  on  enterprises  the  sample  was  organised  in  enterprises  with  1  to  249  employees, 
whereas in STS and SBS the sample concerns the enterprises with 1 to 19 employees.  
Two-stage sampling was realised: 
NACE 
Number of employees  
In the sample the level of NUTS3 was applied as well. In spite of that due to the great number of 
strata this criterion was not used for grossing-up. 

Stratified random sample (in enterprises with at least 100 employees a census). 
The  variables  for  stratification  were  the  size  of  the  enterprise  (as  number  of  persons  employed) 
and economic activity. 

▪  The categories of size were 5: 5-9, 10-19, 20-49, 50-99 and 100+. 
▪  The categories of economic activity were 26: as NACE classes 15-19, 20, 21, 22, 23, 24-25, 
26,  27-28,  29-33,  34-35,  36,  37,  40,  45,  50,  51,  52,  55.1-55.2,  55.3-55.5,  60-63,  64,  70-71, 
72, 73-74, 92.1+92.2+92.4+92.71, 93. 

All together this is 130 strata. 
All enterprises in the sample frame employing at least one hundred persons were included in the 

Methodological manual for Information Society Statistics 

68  

Sweden  

United Kingdom  

inquiry.  Sampling  was  applied  to  enterprises  with  five  to  99  employees.  As  a  starting  point  in 
constructing  the  sample,  one  half  of  the  enterprises  employing  50  to  99  persons,  one  fifth  of  the 
enterprises  with  20  to  49  employees  and  ten  per  cent  of  those  employing  5  to  9  and  10  to  19 
persons were selected by size category from the strata. This preliminary sample structure was still 
modified by strata to include more enterprises where the number of enterprises would be small and 
analytical  purposes  relating  to  economic  activity  needed  more  enterprises  to  the  sample.  Also  in 
strata  where  the  number  of  enterprises  was  regarded  large  relative  to  the  analytical  needs  the 
sample size was reduced. 
In financial sector all enterprises are covered, except in two smallest size groups in NACE 65120 a 
sample is drawn to cover 30 per cent of the enterprises with 10-19 employees and 40 per cent of 
the enterprises in enterprises with 20-49 employees. 

Stratified  random  sampling  is  used,  where  size  and  economic  activity  are  the  variables  used  for 
stratification. 
Size : 10-19, 20-49, 50-99, 100-199, 200-249, 250-499, 500-  
Economic activity : 15-22, 23-25, 26-28, 29-37, 40-41, 45, 50, 51, 52, 55.1-55.2, 55.3-55.5, 60-63, 
64,  65.12  and  65.22,  66.01  and  66.03,  67.12-67.13  and  67.2,  65.11  and  65.21  and  65.23  and 
66.02 and 67.11, 70-71 and 73-74, 72, 92.1-92.2, 93  (NACE) 
The final number of strata (containing at least one enterprise) : 149 
The  sample  size  is  determined  by  the  precision  0.07  and  “worst  case”  variances  (that’s  why  the 
precision  is  as  low  as  0.07).  As  allocation  method,  we  used  optimum  allocation  (Neyman 
allocation).  The  sample  is  positively  coordinated  with  the  sample  drawn  for  the  Survey  of  ICT 
Usage and e-Commerce in Enterprises 2004. 

Each ONS survey begins its permanent random number (PRN) selection at different points on the 
PRN  line  to  limit  overlap  with  other  surveys  as  much  as  is  possible.    By  knowing  where  each 
survey  begins  its  PRN  selection  we  can  have  information  more  readily  available  in  the  case  of 
complaints, and know where to position new surveys on the line.  However, the larger the business 
the more significant it is and therefore the more ONS questionnaires it receives. 
To minimise  burden  on the  10-49  employment  businesses we  set our  PRN start  point  to  exclude 
any businesses selected by the Annual Business Survey.  
0-9 employment businesses are only selected for 1 year  in 3 for any ONS survey. 

The  following  strata  are  used  based  on  reported  employment,  held  on  our  business  register 
(IDBR). 
0-9     random sampling 
10- 49 random sampling 
50 - 249    random sampling 
250 - 999  random sampling 
1000+ Fully enumerated strata 

Norway  

The sample was drawn from all enterprises with at least five employees in the Central Register of 
Establishments and Enterprises. 
It was stratified by industry and size of the enterprise measured by employment. 

▪  Enterprises with 5-9 employees the sample was 5 per cent, 
▪  Enterprises with 10-19 employees the sample was 7,5 per cent, 
▪  Enterprises with 20-49 employees the sample was 15 per cent, 
▪  Enterprises with 50-99 employees the sample was 50 per cent, 
▪  Enterprises with 100-249 employees the sample was 75 per cent, and 
▪  Enterprises with at least 250 employees all enterprises were included in the sample. 

The same sample percentages were used within all of the selected industries. 

I.2.3.1 

STRATIFICATION 

The recommendation is to use a stratified sample of enterprises with the aim to form groups 

of  units  characterised,  in  terms  of  the  variables  collected  in  the  survey,  by  maximum 

homogeneity within the group and maximum heterogeneity between the groups. 

The  background  variables  X1  -  "Main  Economic  Activity"  (in  terms  of  NACE)  and  X2  - 

"Average  Number  of  Persons  Employed"  (in  terms  of  size  classes)  should  be  used  for  the 

stratification of the sample. The "Location of the Enterprise" (variable X5) can also used as a 

stratification  variable  (if  an  objective  1  /  non-objective  1  breakdown  is  provided,  or  any 

other  geographical  breakdown,  than  the  stratification  by  this  variable  is  necessary).  These 

Methodological manual for Information Society Statistics 

69  

 
 
 
variables,  according  to  the  Council  Regulation  (EEC)  No  2186/93  on  business  registers  for 
statistical  purposes,  are  presented  in  the  sampling  frame  and  can,  therefore,  be  used  to 

stratify the sample à priori. 

The  purpose  of  the  stratification  by  main  economic  activity,  size  class  and  location  is  to 

assure à priori, accurate results for the breakdowns. In fact, if the sample is not stratified by 

these variables, the number of enterprises which casually end up in some NACE category or 

size class might be too small to produce accurate results. 

For the definition of the categories and level of detail of the stratification variables, the level 

of  dissemination  concerning  NACE-aggregates  and  size-class  has  to  be  taken  into  account 

(please  refer to the  explanatory  notes  of  the  background  variables  in  chapter  I.1.6.5).  The 

minimum  stratification  of  the  frame  population  has  to  be  consistent  with  this  level  of 

dissemination,  meaning  that  the  most  detailed  level  of  categories  of  all  the  breakdowns 

foreseen have to be possibly defined by adding the aggregated results of the different strata 

(cells) distinguished in the stratification. 

Given  the  level  of  dissemination,  the  minimum  level  of  stratification  concerning  NACE-

aggregates  and  size-class  is  defined  in  the  following  table.  For  reasons  of  estimation 

efficiency,  additional  stratification  by  size-class  and/or  NACE-aggregates  may  be  useful. 

Under  certain  conditions  the  efficiency  of  the  estimator  can  be  improved  by  defining  more 

detailed (homogeneous) groups of NACE-aggregates and size-classes. Efficiency means here 

a higher reliability of the estimates for the same overall sample size. 

In  the  figure  below,  the  "x"  in  bold  represent  the  minimum  level  of  stratification  for  the 

mandatory scope of the enterprise Community Survey (48 strata). The "x", in normal text, 

represents  the  minimum  level  of  stratification  for  the  optional  scope  of  the  survey  (an 

additional 57 strata). 

Micro-Enterprises

Small Micro-
Enterprises
Small Micro - 
Enterprises

Big Micro-
Enterprises
Big Micro - 
Enterprises

1  to 4 persons 
employed

5  to 9 persons 
employed

x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x

x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x

10  to 49 persons 
employed

Small 
Enterprises

Small and Medium 
Enterprises

Total
Small, Medium and Large Enterprises
Large 
Enterprises
Large 
Enterprises
250 or more 
persons 
employed
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x

Medium 
Enterprises
50  to 249 
persons 
employed
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x

x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x

Manufacturing, 
Energy and 
Construction

Total

Non-financial 
Services

Financial 
Services

Section D

DA+DB+DC+DD+DE
DF+DG+DH
DI+DJ
DK+DL+DM+DN

Section G

Section I

Section H

Section E 40 + 41
Section F 45
50
51
52
55.1 + 55.2
55.3 - 55.5
60 - 63
64
72
70 +71 +73 +74
92.1 + 92.2
92.3 - 92.7
93
65.12 + 65.22
66.01 + 66.03
67.12 + 67.13 + 67.2

Section K

Section J

Section O

Methodological manual for Information Society Statistics 

70  

 
I.2.3.2 

SAMPLE SIZE 

Calculation  of  sample  sizes  should  take  into  account  that  it  has  to  ensure  representative 

results  for  all  the  estimates  produced.  In  particular  calculation  of  sample  size  should  take 

into  account  that  each  statistic  has  to  be  tabulated  by  NACE  category,  size  class  and 

geographical location. 

As  budgets  are  limited,  the  design  of  samples  involve  making  trade-offs  along  various 

dimensions.  Larger  samples  make  it  possible  to  analyse  sub-groups  in  depth  but  every 

interview or questionnaire treated increases survey costs. 

On the basis of the previous considerations, it is suggested to adopt a mixed view, based on 

both cost and organisational criteria and on an evaluation of the sample errors of the main 

estimates  on  a  national  level  and  with  reference  to  each  of  the  territorial  domains  and  to 

each of the breakdown variables of interest. 

The  calculation  of  sample  sizes  should  be  based  on  precision  requirements  (see  I.2.3).  On 

this basis countries should decide on sample design and calculate the sample sizes in order 

to receive estimates with sufficient accuracy and within possible budgetary constraints. 

In practice, the sample size is usually calculated by applying the desirable overall reliability 

of the estimate to a target-variable. This target variable can be one of special relevance for 

the survey or one that correlates well with the majority of the variables to be collected. The 

resulting  sample  size  is  set  by  the  dispersion  of  this  target-variable.  However,  some  times 

for several reasons, e.g. the administrative burden of enterprises, often a maximum number 

of  enterprises  to  be  surveyed  is  defined.  This  number  of  enterprises  is  allocated  to  the 

different  strata  in  such  a  way  that  the  reliability  of  the  estimates  is  optimized.  An  efficient 

way  to  allocate  a  specified  number  of  enterprises  to  the  different  strata  is  the  so-called 

Neyman-allocation,  meaning  that  the  number  of  enterprises  is  allocated  to  the  relevant 

strata inversely proportional with the variance of a specified target-variable in these strata. 

n

h

·=
n

S

N
h
∑ ·
N

h

h
S

h

Where: nh is the number of units in the sample in stratum h; 

n is total sample size; 

Nh total number of units in the frame population for stratum h; 

Sh true standard deviation in stratum h for the relevant variable. 

Estimates  of  the  variance  of  the  target  variable  might  come  from  a  pilot-survey  or  the 

survey from a previous year. 

Additional  to  the  outcome  of  the  Neyman-allocation,  a  minimum  number  of  enterprises  in 

each  stratum  can  be  specified.  For  larger  enterprises  one  can  decide  to  include  them 

integrally  in  the  survey.  However,  for  qualitative  questions  this  is  less  crucial  then  for 

variables like for example production value. 

More  advanced  sampling  techniques  may  be  used  as  long  as  it  is  possible  to  calculate  the 

normal statistical variables and it meets the output specified in this manual. 

By  specifying  a  maximum  number  of  enterprises  in  the  sample  it  is  useful  to  anticipate  - 

based  on  experience  with  a  previous  survey  or  another  comparable  survey  -  a  response 

rate.  If  experience  shows  that  only  50  percent  of  the  enterprises  addressed,  actually 

respond in a usable way, the sample size should be adapted to this response rate, meaning 

should be doubled. 

Methodological manual for Information Society Statistics 

71  

 
·
 
 
 
 
The  table  below  gives  an  overview  of  the  sample  sizes  reported  by  the  national  statistical 

institutes in the Final Reports for the 2005 national surveys. Note that due to the adaptation 

of  the  sample  size  to  specific  national  needs  (e.g.  production  of  regional  estimates),  the 

sample sizes can't always be compared. For most countries, the final or net sample size was 

between 3000 and 6000 elements. The response and non-response as well as the quality (in 

terms of coefficient of variation) are discussed in more detail in the next chapters. 

Table: Overview of the sample sizes and response rates (2005 survey) 
Source: Final reports for the Community survey on ICT usage and e-commerce in enterprises (2005) 

Gross 
sample size

Number of 
eligible 
elements

Non-
response

Ineligible (out-
of-scope)

Net sample 
size

Unit 
response 
rate

Usable 
sample rate

20,467

2,255

18,212

5,135

56

5,079

32,919

1,354

31,565

14,072

17,493

Belgium

Czech Republic

Denmark

Germany

Estonia

Greece

Spain

Ireland

Italy

Cyprus

Latvia

Lithuania

Luxembourg

Hungary

Malta

Netherlands

Austria

Poland

Portugal

Slovenia

Slovak Republic

Finland

Sweden

7,529

10,325

4,261

39,229

3,440

4,786

72

529

:

28

0

209

1,353

7,398

2,512

2,472

9,677

753

8,339

4,700

14,904

6,068

1,996

4,684

4,854

4,000

28

7

65

71

0

3

0

86

429

403

17

69

167

39

United Kingdom

11,951

2,498

Norway

3,298

0

7,457

9,796

:

2,768

2,281

:

4,689

7,515

:

39,201

21,170

18,031

3,440

4,577

568

2,044

2,812

2,455

2,872

2,533

15,400

2,624

1,325

7,391

2,447

2,401

9,677

750

8,339

4,614

14,475

5,665

1,979

4,615

4,687

3,961

9,453

3,298

136

823

152

1,240

2,412

15

2,416

1,416

2,703

1,356

369

632

1,169

1,232

1,551

735

1,189

6,568

2,295

1,161

7,265

735

5,923

3,198

11,772

4,309

1,610

3,983

3,518

2,729

7,902

2,563

62.9%

76.7%

:

46.0%

83.5%

55.3%

84.6%

51.7%

55.4%

89.7%

88.9%

93.8%

48.4%

75.1%

98.0%

71.0%

69.3%

81.3%

76.1%

81.4%

86.3%

75.1%

68.9%

83.6%

77.7%

62.3%

72.8%

:

46.0%

83.5%

52.9%

75.2%

51.1%

53.1%

87.9%

88.8%

91.4%

47.0%

75.1%

97.6%

71.0%

68.0%

79.0%

71.0%

80.7%

85.0%

72.5%

68.2%

66.1%

77.7%

Note: Usable sample rate equals net sample size divided by gross sample size. 

Methodological manual for Information Society Statistics 

72  

 
 
 
I.2.3.3  WEIGHTING – GROSSING UP METHODS 

The grossing up method, or weighting procedure, to be adopted for the production of figures 

for the total target population is determined in the first place by the sampling design used. 

The  weighting  factors  are  calculated  taking  into  account  in  particular  the  probability  of 

selection of each unit in the sample. 

In  this  chapter,  the  explanation  of  the  several  weighting  methods  for  the  several  types  of 

variables  will  assume  the  selection  of  a  stratified  random  sample,  which  is  method 

recommended in this manual for the enterprise survey. The formulas have to be adapted if a 

different sampling design is used in the survey. 

In the second place, the grossing up method is determined by the type of variable collected 

and  the  statistics  produced  with  those  variables.  In  the  enterprise  ICT  usage  survey  there 

are two types of observation variables: 

1)  Qualitative / Binary variables, e.g. “Do you use Internet?”; and 

2)  Quantitative variables, e.g. “Please indicate the percentage of persons employed with 

access to the Internet.”. 

The  enterprise  ICT  Community  Survey  is  dominated  by  qualitative  questions  and  most 

results  are  published  as  percentages  of  the  number  of  enterprises  (total  number  of 

enterprises,  enterprises  with  access  to  the  Internet,  etc.).  This  leads  to  conclusions  or 

observations like ‘x percent of all enterprises have access to the Internet’ or ‘y percent of all 

enterprises with access to the internet sell online’. To produce these results the observations 

are weighted by the number of enterprises in the stratum to which they belong. 

These  conclusions  or  observations  are  usually  dominated  by  the  results  of  the  small  and 

medium-sized  enterprises  because  they  are  the  largest  group  expressed  in  number  of 

enterprises. However, the majority of the labour force may well work in bigger enterprises, 

where ICT usage is qualitatively and quantitatively different from the others. For this reason, 

when  looking  especially  at  more  employment  related  issues,  the  results  should  also  be 

additionally weighted  by  the  number  of  persons  employed. In this case the ICT usage 

of  larger  enterprises  gain  influence  on  the  overall  result.  Weighting  by  employed  persons 

leads  to  conclusions  or  observations  like  ‘x  percent  of  the  employed  persons  work  at 

enterprises with access to the Internet’. 

The quantitative questions are in general collected in percentage terms, e.g.  percentage of 

persons employed using computers, percentage of turnover resulted from sales received via 

Internet. In order to produce overall averages of these percentages for the total population 

they also have to be additionally weighted by the base variable of those percentages (i.e. by 

the number of persons employed if the variable is percentage of persons employed, by the 

total turnover if the variable is percentage of turnover, etc.). 

When  the  quantitative  variables  are  collected  in  real  terms  and  not  in  percentages,  the 

variables don't need to be additionally weighted by the base variable of the percentages. 

In the remaining of this chapter the two weighting methods are explained in detail. 

Methodological manual for Information Society Statistics 

73  

 
 
 
 
 
 
Basic weighting by number of enterprises 

Assuming  that  a  stratified  random  sampling  is  used,  the  estimator  of  a  total  in  the 

population based on the sample is: 

Y

∑=

hY

, 

=

Y
h

N
n

h

h

∑

hi

y

hi

, 

(1) 

(2) 

where Y  is the estimated total value of variable y for the total population 

hY  is the estimated value of variable y for the total population in stratum h; 
hN  total number of units in the frame population for stratum h; 
hn  is the number of units in the sample in stratum h; 
hiy  is the value of variable y of enterprise i in stratum h. 

In  the  case  of  the  quantitative  variables  in  real  terms  (not  in  percentage  terms), 

hiy is  the 
hiy  assumes  the  value  1  if 
the  answer  is  "YES"  and  0  if  the  answer  is  "NO".  This  way  the  total  of  this  variable  is  the 

value  of  that  variables.  In  the  case  of  the  qualitative  variables, 

number of enterprises having answered "YES". 

To  compute  the  percentages,  these  totals  are  divided  by  either  the  total  number  of 

enterprises,  in  the  case  of  the  qualitative  variables,  or  by  the  total  of  the  quantitative 

variable for all enterprises, in the other case. 

For the total population: 

∑

Y
h

N

p

Y

=

For each stratum: 

N
n

h

h

y

hi

∑

hi
N

h

p
Y
h

=

(3) 

(4) 

In the grossing up, each enterprise i in strata h has the following weight 

w =

hi

N

h

n

h

, 

(5) 

which gives how many enterprises in the population this sampled unit represents. 

Because the weighting factor 

hiw  is based on the number of enterprises, this is called 

weighting by number of enterprises. 

Methodological manual for Information Society Statistics 

74  

˛
 
 
˛
 
 
 
 
 
Additional  weighting  by  an  auxiliary  variable  (number  of  persons  employed, 
turnover, etc.) 

As mentioned before, the additional weighting by an auxiliary variable z has the purpose, in 

the  case  of  the  qualitative  variables,  of  computing  indicators  of  the  type  “percentage  of 

variable  z”,  instead  of  “percentage  of  enterprises”.  For  example  “percentage  of  persons 

employed”.  In  the  case  of  the  quantitative  variables  collected  in  percentage  terms,  this 

additional  weighting  by  the  base  variable  of  the  percentages  is  necessary  to  gross  up  the 

results. 

In terms of real values, and not percentages, this means that the indicators computed using 

this  additional  weighting  are  of  the  type  “number  of  persons  employed”,  “turnover”  or 

“purchases”,  instead  of  “number  of  enterprises”  and  the  percentages  are  computed 

afterwards using the totals of these variables. 

The formula for the computation of these indicators of the type “percentage of variable z” is 

actually the same in both types of variables, but the reasoning is slightly different. For this 

reason, they will be explained separately. 

Qualitative / Binary variables 

In this case we compute indicators of the type “percentage of variable z, for enterprises with 

y  equal  to  some  value”  (where  y  is  the  qualitative  /  binary  variable).  For  example 

“percentage  of  persons  employed,  for  enterprises  with  Internet  access”,  in  which  case  the 

qualitative / binary variable “Do you have Internet access” equals “Yes”. Or, in real values, 

“number of persons employed, for enterprises with Internet access”. 

One  way  of  doing  it  for  the  real  value  is  simply  to  select  the  enterprises  for  which  the 

qualitative variable equals the value of interest (in the example above, “Yes”) and gross up 

the number of persons employed in those enterprises: 

Y

∑=

hY

, 

Y
h

=

w
hi

∑

hi

yz
hi

hi

(6) 

where 

hY  is the estimated real value of persons employed in enterprises, for which the 
qualitative variable equals the value of interest, for the total population in stratum h; 
hN  total number of units in the frame population for stratum h; 
hn  is the number of units in the sample in stratum h; 
hiz  is the number of persons employed in enterprise i of stratum h. 
hiy  is a binary variable assuming 1 for the enterprises for which the qualitative 
variable equals the value of interest, and 0 otherwise.  
hiw is the weight of enterprise i in stratum h., as defined in formula (5). 

For the percentage, we divide this value by the grossed up total of persons employed in all 

enterprises: 

p
Y
h

=

w
hi

w
hi

∑
∑

hi

yz
hi

z

hi

hi

(7) 

hi

Methodological manual for Information Society Statistics 

75  

 
˛
(cid:215)
 
 
˛
˛
(cid:215)
(cid:215)
 
 
Which simplifies to: 

P
Y
h

∑
∑

hi

˛=

yz
hi

z

hi

hi

(8) 

hi

Quantitative variables 

In this case the indicators computed are of the type “percentage of variable z, in relation to 

another variable”, where the first one is a parcel of the second one. For example “percentage 

of  persons  employed  with  access  to  Internet,  in  relation  to  the  total  number  of  persons 

employed”. When defined in real values, it refers to the numerator only: “number of persons 

employed with access to Internet”. 

One way of doing it for the real value is to use the individual percentages of each enterprise 

(as it is collected), multiply it by the base of that percentage (in the example above, “total 

number  of  persons  employed”)  and  gross  it  up.  The  total  value  for  each  stratum  h  would 

then be: 

Y
h

=

w
hi

∑

hi

yz
hi

hi

(9) 

where 

hY  is the estimated real value of persons employed with access to the Internet, for 
the total population in stratum h; 
hN  total number of units in the frame population for stratum h; 
hn  is the number of units in the sample in stratum h; 
hiz  is the number of persons employed in enterprise i of stratum h. 
hiy  is a binary variable assuming 1 for the enterprises for which the qualitative 
variable equals the value of interest, and 0 otherwise.  
hiw is the weight of enterprise i in stratum h., as defined in formula (5). 

For the percentage, we divide this value by the grossed up total of persons employed in all 

enterprises of stratum h: 

p
Y
h

=

w
hi

w
hi

∑
∑

hi

hi

yz
hi

z

hi

hi

(10) 

Which simplifies to: 

P
Y
h

∑
∑

hi

˛=

yz
hi

z

hi

hi

(11) 

hi

Formulas  (6)  and  (9)  are  identical,  and  formulas  (8)  and  (11)  as  well.  Therefore,  the 

grossing  up  method  when  an  additional  weighting  by  an  auxiliary  variable  is  used  is  the 

same  for  qualitative  variables  and  quantitative  variables,  when  collected  in  percentage 

values. 

Methodological manual for Information Society Statistics 

76  

˛
 
 
˛
(cid:215)
 
 
˛
˛
(cid:215)
(cid:215)
 
 
˛
 
 
I.2.4. Survey type 

Data collection method 

Face-to-face interviews, telephone interviews and postal surveys are all possible techniques 

of collecting data. Next the main strengths and weaknesses of each method are presented. 

Postal survey 

Strengths: 

They  are relatively  inexpensive  to  administer.  You  can  send  the  exact  same  instrument  to  a  wide 

number of companies. They allow the respondent to fill it out at their own convenience. Mail survey 

doesn't  allow  personal  contact  between  the  researcher  and  the  respondent;  consequently  the 

researcher impressions can't influence the response of the respondent. 

Weakness: 

But  there  are  some  disadvantages  as  well.  Response  rates  from  mail  surveys  are  often  very  low 

and mail questionnaires are not the best vehicles for asking for detailed written responses. 

Personal interviews (face to face) 

Strengths: 

Interviews are a far more personal form of research than questionnaires. In the personal interview 

the  interviewer works directly  with  the respondent  (controlled situation).  Unlike  with mail  surveys 

the  interviewer  has  the  opportunity  to  probe  or  ask  follow-up  questions.  Interviews  are  generally 

easier  for  the  respondent,  especially  if  what  is  sought  is  opinions  or  impressions  (individual 

behaviour  can  be  observed  and  exchange  of  material/information  between  interviewer  and 

respondent is possible). They have a very good response rate. 

Weakness: 

Interviews  can  be  very  time  consuming  and  they  are  resource  intensive.  The  interviewer  is 

considered a part of the measurement instrument and interviewers have to be well trained in how 

to  respond  to  any  contingency.  They  are  very  expensive  and  consequently  inapplicable  for  global 

and big surveys.  

Telephone interviews: 

Strengths: 

Telephone  interviews  enable  a  researcher  to  gather  information  rapidly.  Like  personal  interviews 

they  allow  for  some  personal  contact  between  the  interviewer  and  the  respondent  (questions  can 

be repeated and interpreted). They allow the interviewer to ask follow-up questions. 

Weakness: 

Some small companies don't have publicity-listed telephone numbers. Some don't have telephone. 

People  often  don't  like  the  intrusion  of  a  call  to  their  homes.  Telephone  interviews  have  to  be 

relatively short or people will feel imposed upon. The inability to use visual aids is also a weakness.  

Methodological manual for Information Society Statistics 

77  

 
 
 
 
Electronic survey: 

Strengths: 

With  the  growth  of  the  Internet  (and  particular  the  World  Wide  Web)  and  the  expanded  use  of 

electronic mail for business communication, the electronic survey is becoming a more widely used 

survey method. Electronic surveys can take many forms. They can be distributed as electronic mail 

messages  sent  to  potential  respondents.  They  can  be  posted  as  World  Wide  Web  forms  on  the 

Internet. They can be distributed via publicly available computers. In some cases electronic surveys 

are placed on laptops and respondents fill out a survey on a laptop computer rather than on paper. 

It is less expensive to send questionnaires online than to pay for postage or for interviewers. It is 

easier to make changes to questionnaire, to copy and sort data. Questionnaires can be delivered to 

recipients in seconds rather than in days as with traditional mail. Research shows that respondents 

may  answer  more  honestly  with  electronic surveys  than  with  paper  surveys  or  interviews.  Due  to 

the  speed  of  online  networks  participants  can  answer  in  minutes  or  hours  and  coverage  can  be 

global.  Since  many  enterprises  prefer  to  report  information  electronically  to  more  traditional  data 

delivery, offering electronic surveys generally increase the total response rate. 

Weakness: 

Population  and  sample  is  limited  to  those  with  access  to  computer  and  online  network.  Thus,  in 

reality  electronic  surveys  can  only  be  a  supplement  to  other  survey  vehicles.  The  use  of  several 

survey  vehicles  simultaneously  may  prove  not  cost  efficient  due  to  increased  logistical  work.  The 

open natures of most online networks make it necessary to invest considerable time and expertise 

in  guaranteeing  acceptable  anonymity  and  confidentiality.  Constructing  the  format  of  a  computer 

questionnaire  can  be  more  difficult  the  first  few  times  due  to  a  researcher's  lack  of  experience. 

More instruction and orientation to the computer online systems may be necessary for respondents 

to complete the questionnaire. Electronic surveys can have a high technical problem with hardware 

and software. 

Nevertheless,  in  practice  almost  all  EU  Member-States  collect  the  data  through  self-

administered postal survey. The table below presents the information on the data collection 

methods used in the 2005 national surveys. 

Table: Overview of the data collection methods (2005 survey) 
Source: Final reports for the Community survey on ICT usage and e-commerce in enterprises (2005) 

Belgium 

Czech Republic 

Denmark 

Germany 

Estonia 

Greece 

Stand-alone survey. 
Answer was voluntary. 
Self-administered postal mail survey. 
Stand-alone survey. 
Answer was mandatory. 
Postal (self-administered mail out and mail or e-mail back) survey  
Electronic questionnaire (computer assisted program available on the web site) for 
electronic completion was developed. 
Stand-alone survey. 
Answer was mandatory. 
Self-administered mail survey. Postal questionnaire. 
Stand-alone survey. 
Answer was voluntary. 
Postal mail survey. 
Stand-alone survey. 
Answer was mandatory. 
Mail  survey  and  the  possibility  for  enterprises  to  get  the  questionnaire  from 
Statistical  Office  homepage.  Only  in  case  of  problematic  answers,  respondents 
were contacted by phone.  
Stand-alone survey. 
Answer was mandatory. 

Methodological manual for Information Society Statistics 

78  

 
Spain 

Ireland 

Cyprus 

Latvia 

Lithuania 

Luxembourg 

Hungary 

Malta 

Netherlands 

Austria 

Poland 

Portugal 

Slovenia 

The survey types used were: 

•  Face to face interviews (in Athens and in Thessaloniki) 
•  Self-administered mail survey 

Stand-alone survey. 
Answer was mandatory and enterprises can be penalized in case of no response. 
Firstly,  questionnaires  are  sent  by  mail  to  the  enterprises  in  the  sample. 
Moreover,  enterprises  may  phone  to  a  free-charge  telephone  number  to  get 
clarification  of  the  questions  and  to  be  helped  with  the  filling  out  of  the 
questionnaire 
Also, questionnaires might be filled in over the Internet. 
In all cases there is a system of reminders, including letters and phone calls. 
Stand-alone survey. 
Answer was voluntary. 
The survey is a self-administered mail survey 
Stand-alone survey. 
Answer was mandatory. 
Face-to-face interview. 
The  questionnaire  was  sent  by  mail  to  the  IT  manager  of  the  enterprise  just 
before the beginning of the data collection period. The IT manager was informed, 
from  the  covering  letter,  that  an  enumerator  would  contact  him  in  order  to 
arrange a meeting for the completion of the questionnaire. 
Stand-alone survey. 
Answer was mandatory. 
It  was  a  mail  survey  where  enterprises  also  were  able  to  submit  the  filled  in 
questionnaires electronically by e-mail and to fill questionnaires using our on-line 
submission system via Internet (in CSB web-site). 
Stand-alone survey. 
Answer was mandatory. 
Postal mail surveys 
Stand-alone survey. 
Answer was voluntary. 
Self administered.  
Stand-alone survey. 
Answer was mandatory. 
Self-administered mail survey 
Stand-alone survey. 
Answer was mandatory. 
Face-to-face interviews. 
Stand-alone survey. 
Answer was voluntary. 
The questionnaires are sent out by mail. 
Stand-alone survey. 
Answer was voluntary. 
A  paper  questionnaire  with  an  attached  glossary  and  a  stamped  addressed 
envelope  for  returning  the  questionnaire  to  Statistics  Austria  was  sent  to  the 
respondents  –  together  with  an  accompanying  letter  explaining  the  political 
background of the survey and providing basic instructions. 
Additionally,  enterprises  could  report  data  by  an  electronic  questionnaire  via 
Internet (writable pdf-file). A download of the questionnaire and the glossary was 
also possible. A telephone hot line for the respondents has been established. Two 
written reminders were  sent out  and 1.300 enterprises  were  contacted  by  phone 
(“motivation calls” by our in-house call centre). 
Stand-alone survey. 
Answer was mandatory. 
Self-administered mail survey 
Stand-alone survey. 
Answer was mandatory. 
This survey combines two techniques of data collection: postal and electronic. The 
enterprises can send the information by post or download the questionnaire from 
the NSI site and send it through the system created for the effect. 
Stand-alone survey. 
Answer was mandatory. 
Self-administered  mail  survey  –  the  questionnaires  were  sent  to  the  manager  of 
the company by mail. 

Slovak Republic  Stand-alone survey. 

Finland 

Answer was mandatory. 
The questionnaires as well as the reminders were sent to the enterprises by post. 
Some respondents were also reminded by phone. 
Stand-alone survey. 
Answer was mandatory. 
Mailed survey with possibility to respond electronically in web (Financial sector not 
in web) 

Methodological manual for Information Society Statistics 

79  

Sweden 

Stand-alone survey. 
Answer was voluntary. 
Postal mail survey. 

United Kingdom  Stand-alone survey. 

Norway 

Answer was mandatory. 
Self-administered postal mail survey. 
Stand-alone survey. 
Answer was voluntary. 
Self-administered mail survey in combination with web questionnaire. All sampled 
enterprises  were  able  to  report  either  via  paper  questionnaire  or  web 
questionnaire. 

Independent versus embedded survey 

The  ICT  usage  survey  in  enterprises  is  not  a  short  survey.  If  this  survey  is  attached  to 

another  survey  it  is  possible  that  the  complete  questionnaire  is  too  long.  The  respondent 

needs  too  much  time  to  answer  all  the  questions.  Consequently  the  quality  of  the  answers 

decrease and the rate of non-response increases. Arguments in favour of embedding the ICT 

usage  survey  into  an  existing  business  survey  are  reduction  of  its  total  cost  and  the 

possibility to cross ICT usage data with other business information. 

The  overview  table  above  indicates  that  in  2005  all  EU  national  ICT  usage  surveys  were 

stand-alone surveys. 

Mandatory survey versus voluntary survey 

Voluntary surveys are usually cheaper, quicker and easier to manage. In mandatory surveys 

it is implied to send the questionnaire several times to the respondent, you have to write a 

reminder letter and sometimes you have to send an administrative offence. You have to wait 

a long time for all responses and your costs increase. The advantage of a mandatory survey 

is that your response quote is nearly 100%. But a voluntary survey can settle this argument 

by increasing the sample size and sending reminder letters to the respondents. 

Contact person of the survey 

In  most  cases  the  IT  manager  is  the  appropriate  recipient  of  the  survey  on  ICT  usage  in 

enterprises. However, not all small enterprises have an IT manager; in theses cases either 

the  owner  or  the  general  administrator  should  answer.  In  bigger  companies  it  is  helpful  to 

send the questionnaire to the general management. They have an overview of all functions 

within the company. Sometimes you find a contact person of the company in your business 

register. In this case it is useful to send the questionnaire to this person. 

I.2.5. Questionnaire – Data collection tool 

To  enhance  the  comparability  across  countries,  Eurostat  provides  a  model  questionnaire  to  the 

NSIs. It is recommended to adopt the model questionnaire for the national survey. However, for 

practical reasons (for instance linked to the survey vehicle), this may not be appropriate. In this 

case,  the  statistical  institute  should  nevertheless  make  sure  that  the  routing  and  the  filtering is 

followed.  

Methodological manual for Information Society Statistics 

80  

 
Eurostat  designs  the  model  questionnaire  in  close  cooperation  with  the  national  statistical 

institutes,  the  main  users  and  in  coordination  with  other  organisations  such  as  the  OECD.  The 

results of previous surveys are taken into account, for instance to assess the relevance of certain 

questions or items, or to assess whether a variable needs to be collected on an annual basis. For 

reasons  linked  to  the  annually  renewed  implementing  measures  for  Regulation  808/2004,  the 

model  questionnaire  needs  to  be  finalised  9  months  before  the  survey  takes  place.  In  practice, 

this  means  that  the  questionnaire  reaches  its  final  status  in  March-April  of  the  year  preceeding 

(T-1) the reference year (T). The obvious disadvantage is that ‘last-minute’ policy needs can’t be 

included or that the results of the T-2 survey can’t be fully taken into account. The advantage is 

that  this  gives  the  NSIs  the  necessary  time  to  translate  the  questionnaire  and  implement  the 

survey. 

The  model  questionnaire  for  the  Community  Survey  on  ICT  Usage  and  e-Commerce  in 

Enterprises can be found in Annex I.3.1. 

The use of “Don’t Know” response categories 

The model questionnaire doesn’t include any “Don’t know” response category as it is considered 

that  such  an  answer  would  provide  the  same  information  as  a  blank  answer.  Concerning  the 

effect on the level and quality of the response when a “Don’t know” option is included, there are 

two factors to consider. On one hand, the inclusion of a “Don’t Know” option may provide more 

accurate answers. It is possible that the respondent doesn’t know the answer (because he forgot 

it or he never had the information) and, when faced with a question which doesn’t provide such a 

response alternative, gives a wild guess instead of leaving it blank. 

On  the  other  hand,  providing  a  “Don’t  know”  option  may  lead  to  a  decrease  in  the  number  of 

usable answers. Respondents may take it as a easy way out of the question, instead of searching 

the  memory,  refer  to  existing  records  or  ask  someone  who  may  have  the  information.  This  is 

particularly the case in self-administered questionnaires. 

Therefore,  the  “Don’t  know”  response  category  should  be  used  only  when  it  is  a  meaningful 

response  alternative  and  not  as  a  substitute  for  non-response.  The  Community  Survey  on  ICT 

Usage in Enterprises is based on national surveys which are almost all of them based on postal 

self-administered  questionnaires  and  it  is  composed  of  factual  questions  and  not  of  opinion 

questions. For this reason, it is recommended not to use “Don’t know” response categories. Even 

if the respondent doesn’t have the information, it should be possible to gather it from somewhere 

in the enterprise. 

I.2.6. Quality control systems 

Quality control systems are of course country-specific as most statistical institutes have standard 

procedures and guidelines for plausibility checks or logic tests of datasets. 

Such controls can be executed on-line, at the moment of the data capture by the interviewer or 

the data entry in the statistical institute, or after the data entry process (a program checks the 

data  and  prints  the  errors  to  be  checked  or  corrected).    On-line  tests  have  the  advantage  that 

the  errors  can  be  corrected  immediately  (a  lot  of  errors  will  be  simple  data-entry  errors,  f.i. 

typing 17773 instead of 1773), a disadvantage is that one needs data-entry staff that is familiar 

with the concepts in the survey (in case they have to decide if a certain value will be accepted or 

not).  The  latter  case  of  course  doesn’t  apply  with  CATI  or  CAPI  where  the  interviewer 

immediately enters the data. 

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Below, some of the most common errors or problems are briefly discussed. 

Measurement error 

There are a number of sources of measurement error: survey instruments (questionnaire), the 
respondent,  the  information  system,  the  mode  of  data  collection,  the  interviewer.  This 
paragraph  focuses  on  the  latter,  other  types  can  back  below.  The  first  and  probably  most 
important  step  in  the  statistical  process,  is  the  data  collection  or  field  work.  One  can  design 
excellent  questionnaires,  excellent  capture  tools,  excellent  imputation  methods  and  excellent 
data analyses, but as with any process the adagium ‘Garbage In Garbage Out’ also applies to 
statistics. If the interviewer is not well-trained, one can’t expect input data of a good quality. A 
more  important  problem  is  usually  the  reliability  of  the  interviewers.  The  interviewers  may 
have  an  interest  in  finishing  the  interviewers  in  the  shortest  possible  time.  This  can  lead  to 
interviews  where  certain  questions  are  skipped  (e.g.  the  person  looks  poor,  let’s  fill  in  he’s 
unemployed)  or  interviews  that  never  took  place  (e.g.  the  person  is  70  years  old,  let’s  put 
down  he  never  used  a  computer  nor  Internet).  Therefore  the  sensibilation  of  interviewers 
(which  can  include  threats  of  non-payment  or  exclusion  for  future  interview  rounds)  and  the 
follow-up is extremely important. The follow-up can be a check for coherence and consistency 
of  the  answers  or  follow-up  phone  calls  to  verify  with  the  respondents  whether  the  interview 
has  actually  taken  place  or  whether  the  interview  was  of  an  acceptable  quality  (e.g.  the 
respondent confirms that the interview only took 4 minutes, but on the questionnaire answers 
to 60 questions were recorded). 

Invalid response 

Relatively  unimportant  in  the  ICT  usage  survey  as  most  answers  are  limited  to  Yes  or  No. 
However,  it  is  possible  that  several  items  were  ticked  in  questions  where  only  one  answer  is 
expected. 

Relationship error 

Comparing the answers across the survey can reveal inconsistencies between the answers. The 
routing  and  filtering  should  normally  guarantee  that  respondents  are  not  presented  with 
questions  they  can’t  answer.  It  is  nevertheless  possible  that  e.g.  an  individual  aged  18 
indicates higher educational level or that an unemployed person indicates ‘place of work’ as a 
location  where  the  Internet  has  been  accessed.  In  the  first  case,  this  is  most  probably  an 
absolute error. In the latter case the combination is possible if the respondent lost his job only 
very recently (meaning he could have accessed the Internet at a place of work during the last 
3 months). 

Compulsory question left unanswered 

Again, the routing and filtering should avoid this type of errors. CATI or CAPI programs usually 
improve  the  quality  of  the  data  capture  in  this  respect.  With  traditional  interviews  or  self-
administered mail surveys, this error is more important. 

Suspicious values 

This  can  occur  when  the  individual  responses  are  compared  with  the  average  scores  within  a 
stratum and unexpected answers are found. In practice it will however be difficult to determine 
whether it concerns a mistake or an outlier. 

In terms of quality of the  survey as  such, the methodology and outcomes of  the survey can be 

benchmarked against other surveys: 

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Representativeness 

It can be useful to do an ex-post check of the representativeness of the sample, e.g. does the 
sample have a representative age distribution, is there some variability in the occupational and 
educational codes? 

Year-to-year comparison at aggregate level 

Comparing  the  results  for  the  current  year  with  the  previous  survey  can  also  reveal  quality 
problems where the growth is outside the range of the expected growth (e.g. the proportion of 
individuals  using  the  Internet  decreases  …).  In  such  cases,  it  is  of  course  possible  that  the 
problem stems from the previous survey exercise … 
For this purpose, it can be interesting to produce some simple tabulations of the survey results.  

Coherence or consistency with other surveys 

The  results  can  be  compared  with  results  from  related  survey  or  studies.  However,  in  case 
inconsistent  results  are  observed,  it  is  not  always  easy  to  identify  which  survey  gave  the 
‘wrong’ results. 

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I.2.7. Data processing 

This chapter mainly discusses the treatment of non-response. Although the grossing-up methods 

can  be  considered  as  a  part  of  the  data  processing,  this  topic  is  discussed  above  in  section 

II.2.3.3. 

I.2.7.1  MISCLASSIFICATION TREATMENT 

Misclassification occurs when an enterprise is included in the survey (because it belongs to a 

size  class  and  sector  of  activity  covered  by  the  survey,  at  least  according  to  register  data 

used for stratification) but later information indicates that it should not have been included. 

In other cases misclassification of enterprises means that enterprises that (according to the 

registers)  are  classified  in  a  size  class  or  NACE  category  should  have  been  classified  in 

another size class or NACE category. The misclassification will then possibly lead to the fact 

that the enterprises should belong to another strata than the one used for stratification. 

Such  a  situation  can  arise  due  to  frame  population imperfections.  Frame  imperfections  can 

occur  when  there  is  a  time  lag  between  the  actual  situation  for  an  enterprise  and  the 

information  available  in  the  registers.  It  often  takes  a  certain  period  of  time  to  update 

register information after a change in the number of employed persons or a change of sector 

of activity has occurred. 

This time lag in updating register information implies that there is a difference between the 

target  population  (i.e.  the  population  that  the  survey  intends  to  cover)  and  the  frame 

population (i.e. the population that the survey actually covers based on information available 

in registers). 

Recommendation in the presence of misclassification of enterprises 

There  are  different  possible  options  available  in  the  presence  of  misclassification  of 

enterprises. The options depend on the type of misclassification. 

If it is obvious that an enterprise should not have been included in the survey for example 

because the number of employed persons have decreased and falls beyond the size cut-off 

limit  during  the  reference  period,  the  enterprise  could  be  excluded  from  the  sample,  as  it 

should have never been included. 

However,  such  an  approach  could  be  hazardous  as  correction  then  only  is  made  for 

enterprises  that  fall  beyond  the  cut-off  limit  and  not  for  enterprises  that  had  less  than  10 

employed persons according to register information and that during the reference period of 

the  survey  exceeded  the  cut-off  limit.  A  more  appropriate  approach  is  in  those  cases  to 

assume  that  enterprises  where  the  number  of  persons  employed  has  decreased  below  the 

cut-off limit offset the enterprises that have increased in number of employed persons and 

that  exceed  the  cut-off  limit.  Enterprises  falling  below  the  cut-off  limit  are  then  treated  as 

respondents and not as over-coverage. 

If  the  misclassification  means  that  the  enterprise  should  belong  to  another  strata  than  the 

one used for stratification, new strata should be built and the weights used in computations 

should be changed accordingly. 

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I.2.7.2  NON-RESPONSE TREATMENT

3 

Introduction 

An  important  source  of  non-sampling  error  in  surveys  is  the  effect  of  non-response  on  the 

survey  results.  Non-response  can  be  defined  as  the  failure  to  obtain  complete 

measurements  on  the  (eligible)  survey  sample.  The  extent  of  non-response  varies  from 

partial non-response (failure to answer just one or some questions) to total non-response.  

The latter case occurs when the respondent refused to participate in the survey or when the 

questionnaire was sent back to the statistical office as returned mail (e.g. when the address 

to  the  enterprise  is  incorrect).  This  type  of  non-response  is  called  unit  non-response 

(§2.7.2.1):  the  sample  unit  does  not  provide  any  of  the  data  required  by  the  survey.  Unit 

non-response is generally handled by adjusting the weight of the enterprises that responded 

to the survey to compensate for those that did not respond. 

Partial non-response or item non-response (§2.7.2.2) occurs when the respondents did not 

answer  all  questions  because  they  did  not  understand  or  misinterpreted  a  question, 

alternatively refused to answer a question. 

Effect of non-response on the quality of the data 

Non-response (unit as well as item non-response) can seriously affect the quality of the data 

collected  in  a  survey.  Firstly,  the  characteristics  (or  answering  pattern)  of  the  non-

respondents can be different from those collected among the sample units who did provide 

eligible  answers.  If  such  difference  is  systematic,  serious  bias  can  be  introduced  in  the 

survey results. Secondly, the reduction of the sample size (overall or for certain questions) 

will increase the variance of the estimates. Thirdly, non-response can have an impact on the 

total cost of a survey exercise. Not only because  a  larger initial sample may  be necessary, 

but  also  because  of  higher  unit  costs  of  the  last  few  percentages  of  respondents  (due  to 

multiple  visits).  Finally,  non-response  can  be  an  indicator  of  poor  overall  quality  of  the 

survey and thus create an image or confidence problem. 

3 References for this chapter: 

•  Government Statistical Service (1997), Report of the Task Force on Imputation – June 1996. Government Statistical 

Service Methodology Series No. 3. London: Office for National Statistics. 

•  Statistics Canada (2003), Household Internet Use Survey, 2002 – Microdata User Guide. 
•  European Commission (2003), Household Budget Surveys in the EU: Methodology and recommendations for 

harmonisation 2003. Luxembourg: Office for Official Publications of the European Communities. 

•  National Centre for Social Research (1999), Item non-response (different contributions). Survey Methods Newsletter 

Volume 10 No.2 1999.  

•  Adjusting for Missing Data, Mohadjer, L., Choudhry, H., Studies of welfare populations: Data Collection and research 

Issues, 2001. 

•  Introduction to Survey Quality, Biemer, P., Lyberg, L., Wiley series in survey methodology, 2003. 
•  Weighting for non-response, Lynn, P., Survey and Statistical Computing, 1996. 
•  Non-response in the Norwegian Business Tendency Survey, Wang, J., Statistics Norway, 2004. 

Methodological manual for Information Society Statistics 

85  

 
                                                
Minimising non-response 

As prevention is always better than cure, attention should be given to avoiding non-response 

rather  than  treating  non-response.  The  number  (and  timing)  of  reminder  letters  or  call 

backs,  the  length  of  the  fieldwork  period,  the  survey  technique(s)  used,  the  length  of  the 

survey  (i.e.  the  response  burden),  the  use  and  structure  of  advance  letters,  the 

dissemination  of  previous  results  or    the  mandatory  nature  of  the  survey  can  all  have  an 

impact on the number of non-contacts or refusals. The length, design and complexity of the 

questionnaire, the interviewer’s training or the interviewer’s style can have an impact on the 

item non-response. 

As this issue is common to all surveys, it will not be discussed in detail in this manual. This 

chapter  is  mainly  focussed  on  the  treatment  of  non-response  in  the  specific  context  of  the 

ICT usage survey. 

UNIT NON-RESPONSE 

Introduction 

Unit  non-response  is  defined  as  enterprises  that  are  included  in  the  sample  but  that  have 

not participated in the survey and for  which information consequently is missing for all the 

questionnaire variables. 

Unit  non-response  can  introduce  bias  in  the  survey  results  especially  in  situations  in  which 

the  non-responding  units  are  not  representative  of  those  that  responded.  Non-response 

increases  both  the  sampling  error  level,  by  decreasing  the  sample  size,  and  non-sampling 

error level. 

Weighting adjustment for unit non-response 

The  principal  method  for  unit  non-response  adjustment  is  weighting.  Most  strategies  for 

weighting  for  non-response  involve  dividing  the  respondents  into  a  set  of  comprehensive 

and mutually exclusive groups, referred to as weighting classes. A weight is then applied to 

each class.  

Weighting classes 

In  order  to  implement  non-response  adjustments,  it  is  required  to  create  weighting 

classes. It is desirable to divide the sample in "response homogeneity groups/classes". 

Within these classes the response rates should be as homogeneous as possible, and the 

response  rate  should  be  different  among  the  classes.  Data  used  to  form  these  classes 

must be available to both non-respondents and respondents. Usually it is possible to get 

information on size, economic activity, legal status, location, and other variables in the 

business registers. 

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More  advanced  methods  for  creating  weighting  classes  are  methods  like  classification 

based  on  a  categorical  search  algorithm  or  a  logistic  regression  model  using  auxiliary 

variables to estimate the probability of response. 

Sample-Based Weighting Adjustment 

In sample-based weighting adjustment the weight  adjustment applied in each class, is 

equal to the reciprocal of the ratio of selected sample size to respondents within each of 

these  classes  (the  inverse  of  the  response  rate  within  each  class).  The  grossing-up 

factor should then be multiplied by the non-response adjustment factor. 

A simple example: 

Size 
Class 

Population 
(I) 

Sample 
size  
(II) 

Respondents 
(III) 

Respondent 
with 
characteristic 
(IV)  

Non-response 
adjustment 
Factor 
(V = II / III ) 

Initial 
Grossing-up 
factor 
(VI =  I / II ) 

Adjusted 
Grossing-up 
factor 
(VII = V * VI ) 

Small 

35 141 

878 

Medium 

5 362 

882 

 761 

761 

764 

821 

624 

595 

795 

543 

1.15 

1.07 

1.22 

40.0 

6.1 

1.0 

46.0 

6.5 

1.2 

Big 

Total 

41 264 

2 521 

2 209 

1 933 

Alternative  forms  of  sample-based  weighting  are  that  the  weights  are  not  inverse 

response  rates,  but  estimated  coefficients  of  a  regression  model  (where  survey 

response is the left-side variable). In this case, the weights are reciprocals of estimated 

response rate by the regression model. 

Population-Based Weighting Adjustment 

Population-based  weighting  adjustment  requires  population  estimates  and  class 

membership  of  respondents.  If  there  is  no  data  available  about  the  non-respondents, 

population-based adjustment still is possible since this uses external control counts for 

the  population  and  not  data  from  the  sample.  The  method  is  used  to  correct 

simultaneously for both non-coverage and non-respondents. The method is used similar 

to the sample-based method. 

In population-based adjustment (poststratification adjustment) the classes are  created 

based  on  variables,  which  are    known  both  for  respondents  and  for  the  population. 

Weights are then applied in proportion to the ratio of population to achieved sample, so 

that the sums of the adjusted weights are equal to population totals for certain classes 

of the population.  

A two-step procedure of first adjusting for non-response (sample-based adjusting) and 

then adjusting to known population counts is a common method that is used. However, 

this procedure is the same as a population-based weighting adjustment if the weighting 

classes in the sample-based and the population-based weighting adjustment are equal.  

If the strata used in the stratification are used as classes in the weighting adjustment, 

there  is  no  need  for  the  weighting  adjustment.  The  adjusted  weighting  procedure  is 

then equal to the final grossing up/weighting procedure. 

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ITEM NON-RESPONSE 

As already mentioned above, there are several reasons for the data being unavailable. These 

include  the  refusal  to  provide  an  answer,  the  inability  to  provide  an  answer,  inadequate 

quality  of  the  provided  answer  (e.g.  implausible,  incomplete,  inconsistent  with  answers  to 

other  questions,  etc.).  It  can  be  caused  by  either  the  respondent  (e.g.  refusal)  or  the 

interviewer  (e.g.  failure  to  record  the  answer  adequately)  but  also  by  the  survey  design 

itself (e.g. ambiguous routing or filtering).  

In case a particular questionnaire shows too many errors, or if too many data are missing, it 

can  be  assumed  that  the  enterprise  in  question  has  not  co-operated  satisfactorily  in  the 

survey. Here, the best solution is probably to remove the enterprise from the database for 

respondents  (but  not  from  the  frame)  and  adjust  the  weighting  coefficients  for  the  other 

enterprises accordingly. In other words, sampling units with a very high item non-response 

can  better  be  classified  as  total  non-response  or  unit  non-response.  However,  if  the 

enterprise  has  provided  answers  on  some  key  questions  of  the  questionnaire,  it  should 

probably be preferable to keep the answers provided by the enterprise (even though many 

questions are left blank). 

The general assumption is that item non-response means that the answer to the question is: 

- 

- 

"NO" if the question is a qualitative question (e.g. yes/no-questions) 

Zero if the question is a quantitative question (e.g. e-commerce value questions) 

The  general  recommendation  is  that  imputations  should  be  avoided,  except  logical 

imputations. 

In  principle  two  kinds  of  imputations  could  be  considered:  1)  to  use  data  from  answers 

provided  by  the  enterprise  previous  year  or  2)  to  use  data  from  the  current  survey  and 

impute the answer on the basis of answers provided by similar enterprises (e.g. enterprises 

belonging to the same strata).  

To use data from previous year is not recommended as the use of ICT can change over time. 

It is e.g. not obvious that an enterprise that sold goods or services via the Internet during 

year t-1 still did so during year t. The data provided the previous year can however be used 

in  order  to  find  enterprises  that  should  be  contacted  to  verify  the  change  from  previous 

year. 

To  use  the  data  of  current  survey  to  generate  an  imputed  value  for  a  variable  is  not 

recommended  as  there  is  a  risk  of  overestimation.  In  this  survey  possible  underestimation 

due to item non-response is preferred to possible overestimation due to imputation. 

As no imputation is recommended, it is very important that item non-response is kept as low 

as possible in order to minimise possible underestimation. 

There are different methods to attain lower item non-response rates: 

1)  Clarity  of  questions.  Unclear  questions  might  be  more  frequently  “avoided”  by  the 

respondents. The content and form of the questions must be considered carefully. Pre-tests 

can be done before sending out the questionnaires in order to check that the questions are 

clear to the respondents. 

2) After conducting the survey, item non-response can be further reduced by contacting the 

respondents in order to get answers to the missing questions. Special efforts should be put 

in order to gather answers for questions where item non-response is especially high.  

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For  e-commerce  value  questions  it  is  recommended  to  check  for  enterprises  with  non-

response  in  e-commerce  value  questions  but  having  large  e-commerce  values  in  previous 

years. These enterprises should be contacted to verify the current situation.  

For  e-commerce  value  questions  it  is  important  to  compare  the  answer  to  that  of  previous 

year.  Especially  enterprises  stating  that  they  have  e-sales  but  that  have  not  provided  an 

estimate  of  the  level  of  e-sales  should  be  contacted  to  have  an  estimate.  If  the  enterprise 

has provided an estimate of e-sales value previous year it could be checked if the value that 

was provided then can still be of use. 

I.2.7.3 

COMPUTING ACCURACY MEASURES 

The  use  of  a  sample  survey  unavoidably  leads  to  sampling  error.  To  get  an  idea  of  the 

sampling error, it is advised to compute this error for certain indicators.  Such information is 

not  only  interesting  to  decide  whether  the  indicator  is  reliable  enough  to  be published,  but 

can also help to determine whether the sample size should be increased in a next edition of 

the survey for certain strata where a large sampling error was diagnosed. 

The sampling error reflects the fact that only a particular sample was surveyed rather than 

the entire population. The (estimated) relative standard error – or (estimated) coefficient of 

variation  (CV)  –  is  the  ratio  of  the  square  root  of  the  variance  of  the  estimator  for  the 

proportion to the expected value of the proportion. It is estimated by the ratio of the square 

root of the estimate of the sampling variance to the estimated value (see also Chapter 9 of 

the Reporting template, Annex I.3.4). The estimation of the sampling variance should ideally 

take into account the sampling design (e.g. the stratification).  

Some  guidelines  for  interpretation  and  use  of  the  coefficients  of  variation  can  be  found  in 

section I.2.3 where the sampling design is discussed. 

The computed accuracy measures will also determine the reliability of the estimates. If the 

coefficient of variation for a certain proportion or absolute value is too high, the cell needs to 

be suppressed. 

To  avoid  that  the  level  of  the  estimate  has  an  extreme  impact  on  the  accuracy  measure 

(e.g.  a  proportion  of  1%  leads  to  a  denominator  of 0,01  when  calculating  the  CV,  in  other 

words, the standard deviation is multiplied by 100), the standard deviation (i.e. the square 

root of the sampling variance) could be used as a reference measure. 

In  case  the  computation  of  the  standard  deviation  or  coefficient  of  variation  for  all  cells  is 

not  feasible,  the  number  of  respondents  underlying  the  estimate  can  be  used  to  decide 

whether  a  proportion  can  be  published  (e.g.  if  based  on  less  than  10  respondents,  the 

estimate is not published). 

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I.2.8. Survey execution reports 

Drawing up reports after the execution of the survey is  not only a tool for a  self-assessment of 

the  work  carried  out  by  the  statistical  office  and  a  detection  of  possible  points  where  there  is 

space of improvement.  Survey execution reports are also a tool for assessing the comparability 

from one year to another or from one country to another. 

The methodological reports for the ICT usage surveys coordinated by Eurostat cover the following 

subjects: 

a.  General methodological information: reference period(s); survey period; survey vehicle, 

where  applicable;  survey  type;  pre-tests;  methodological  differences  compared  to 

previous data collection exercises. 

b.  Statistical  unit(s),  scope  and  target  population:  statistical  unit;  economic  activities 

covered;  size  coverage  in  terms  of  number  of  persons  employed;  and  territorial 

coverage. 

c.  Information on the national questionnaire. 

d.  Sampling  frame:  name  and  description  of  the  sampling  frame  or  register  used;  known 

shortcomings of the sampling frame, if any. 

e.  Sampling design: sampling method; additional measures taken at the time of sampling 

design to improve representativeness. 

f.  Unit non-response, by giving information on: gross sample size; number of out-of-scope 

cases,  number  of  other  ineligible  cases;  number  of  eligible  elements;  number  of  non-

contacts; number of cases unable to respond; other non-response; net sample size; unit 

response  rate.    Additionally,  the  report  discuss  the  methods  used  for  minimizing  non-

response as well as the methods used for dealing with unit non-response. 

g.  Item  non-response:  variables  or  items  with  response  rates  below  90%;  methods  used 

for dealing with item non-response. 

h.  Grossing-up procedures. 

i.  Sampling error: the report indicates the coefficient of variation (relative standard error) 

for a selected group of indicators or sub-indicators listed in the template. 

j.  Problems encountered and lessons to be learnt. 

k.  The report includes the questionnaire in national language and, if available, in English. 

The  Reporting  template  used  for  the  European  enterprise  ICT  usage  surveys,  including  some 

instructions, can be found in Annex I.3.4. 

(see document MM2006_AnnexII.3.3_ReportingTemplateENT2005.doc (20 pages)) 

This  template  covers  both  the  Metadata  report  (formerly  known  as  Interim  Report)  and  the 

Quality report (formerly known as Final Report) referred to in Article 7(4) of Regulation 808/2004 

(see Annex III.1) and in Annex II, chapter 6 of Regulation 1099/2005 (see Annex III.2). 

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I.3. 

ANNEXES 

I.3.1. Model questionnaire for non-financial economic activities 

EUROSTAT MODEL FOR A COMMUNITY SURVEY ON ICT USAGE AND E-COMMERCE IN ENTERPRISES
2006
Model Questionnaire (Version 3 of 18 March 2005)

(Questions relating to the ancient eEurope 2005 Benchmarking Indicators are marked with an asterisk *)

Module A: General information about ICT systems

A1. Did your enterprise use computers, during January 2006?

(Filter question)

Yes 

 No  ﬁ

 Go to X1

A2*. How many persons employed used computers at least once a week, during January 

2006?

If you can't provide this value,
Please indicate an estimate of the percentage of the number of persons employed used 
computers at least once a week, during January 2006.

A3*. Did your enterprise have persons employed who regularly work part of their time (half a 
day per week or more) away from the enterprise's regular work site while having access 
to the enterprise’s computer system, during January 2006?
(filter question)
Did any of those persons access the enterprise's computer system from the following 
places, during January 2006?

A4.

a) From home

b) From customers or other external business partners’ premises 

c) From other geographically dispersed locations of the same enterprise or enterprise group

d) During business travel, e.g. from hotel, airport etc

A5. Did your enterprise have difficulties in recruiting personnel with ICT skills (from basic 

to professional), during 2005?
(Filter question)
Did your enterprise face the following problems when trying to recruit personnel, 
during 2005?

A6.

a) Personnel with required skills in the use of ICT applications not available or not entirely 
suitable
b) ICT specialists with the required skills not available or not entirely suitable

c) High remuneration costs of ICT specialists

A7*.

Did your enterprise have the following information and communication technologies, 
during January 2006?

a) Wireless LAN

b) Wire based LAN

c) Intranet

d) Extranet 

A8. Did your enterprise have IT systems to manage the placing or receipt of orders, during 

January 2006?
(Filter question)
Did your enterprise's IT systems for managing orders link automatically with any of the 
following IT systems, during January 2006?

A9*.

a) Internal system for re-ordering replacement supplies

b) Invoicing and payment systems

c) Your system for managing production, logistics or service operations

d) Your suppliers’ business systems (for suppliers outside your enterprise group)

e)Your customers’ business systems (for customers outside your enterprise group)

(Number)

%

Yes 

 No  ﬁ

 Go to A5

Yes





Yes   No  ﬁ 

Go to A7

No




Didn't need 
to recruit  
 Go to A7

Yes




No




Type of skills 
not needed




Yes





No





Yes 

 No  ﬁ

 Go to 

A10

Yes






No






Methodological manual for Information Society Statistics 

91  

ﬁ
 
A10.

In your communication with customers and other enterprises, to what extent has your 
enterprise substituted traditional postal mail (e.g. for sending invoices, direct mail, etc.) by 
electronic means of communication (Intranet, Extranet, Internet, e-mail messages), in the last 
5 years?
(tick only one)

i)   No substitution (overall postal mail was not reduced because of electronic means of communication)
ii)  Minor substitution (electronic means are now used instead of post mail in a few situations, but postal 
mail is still the most important)

iii)  Significant substitution (electronic became the main mean of business communication)

iv)  Most or all substituted (postal mail was used before, but it's rarely used nowadays)

v)   Non-applicable (postal mail was never a relevant mean of communication for the enterprise)

Module B: Use of Internet
(asking enterprises with ICT)

B1*. Did your enterprise have access to Internet, during January 2006?

(Filter question)

B2*. How many persons employed used computers connected to the World Wide Web at 

least once a week, during January 2006?

If you can't provide this value,
Please indicate an estimate of the percentage of the number of persons employed used 
computers connected to the World Wide Web at least once a week, during January 2006.
Did your enterprise have the following types of external connection to the Internet, 
during January 2006?

B3*.

a) Traditional Modem (dial-up access over normal telephone line)

b) ISDN connection

c) DSL (xDSL, ADSL, SDSL etc) connection

d) Other fixed internet connection (e.g. cable, leased line (e.g. E1 or E3 at level 1 and ATM at level 
2), Frame Relay, Metro-Ethernet, PLC - Powerline comunication, etc.)
e) Mobile connection (e.g. e.g. analogue mobile phone, GSM, GPRS, UMTS, EDGE, CDMA2000 
1xEVDO)
What was the maximum speed for download contractually provided to your fastest 
Internet connection, as of January 2006?
(tick only one)

B4.

i)   Below 144 Kb/s

ii)  144 Kb/s or more and less than 2 Mb/s

iii) 2 Mb/s or more

B5*. Did your enterprise use the Internet for the following purposes, during January 2006?

(as consumer of Internet services)

a) Banking and financial services

b) Training and education

c) Market monitoring (e.g. prices)

d) Receiving digital goods or services

e) Obtaining after-sales service









Yes 

 No  ﬁ

 Go to D1

(Number)

%

 No








 No






Yes








Yes










B6*. Did your enterprise use the Internet for interaction with public authorities, during 2005?

(Filter question)
Did your enterprise interact with public authorities in the following ways, during 2005?

B7*.

Yes 

 No  ﬁ

 Go to B8

a) For obtaining information

b) For obtaining forms, e.g. tax forms 

c) For returning filled in forms, e.g. provision of statistical information to public authorities 

d) Submitted a proposal in an electronic tender system (e-procurement)

Yes





 No





Methodological manual for Information Society Statistics 

92  

 
 
 
B8*. Did your enterprise have a Web Site / Home Page, during January 2006?

B9.

(Filter question)
Did the Web Site of your enterprise provide the following facilities, during January 
2006?
(your enterprise as provider of Internet services)

a) Marketing the enterprise’s products 

b) Facilitating access to product catalogues and price lists

c) Providing after sales support 

B10*. Did your enterprise use the following internal security facilities, during January 2006?

a) Virus checking or protection software

b) Firewalls (software or hardware)

c) Secure servers (support secured protocols such as shttp)

d) Off-site data backup

B11*. Was it possible to communicate with your enterprise using the following security 

facilities, during January 2006?

a) Electronic digital signature as customer's authentication mechanism

b) Other authentication mechanism (e.g. PIN code)

c) Data encryption for confidentiality

Yes 

 No  ﬁ

 Go to 

B10

Yes




Yes





Yes




 No




 No





 No




B12*. Did your enterprise encounter ICT related security problems during 2005 (e.g. computer 

virus, worms or trojan attack, unauthorised external access to the computer system), 
that resulted in a loss of information or working time?

Yes 

 No 

Module C: e-commerce via Internet
(asking enterprises with Internet access)

Orders placed via Internet (Purchases)

C1*. Did your enterprise order products/services via the Internet, during 2005 (excluding 

manually typed e-mails)?
(Filter question)

C2*. Please indicate for 2005 the percentage of the Internet orders in relation to the total 

purchases (in monetary terms, excluding VAT).

Alternative Question:

Yes 

No  ﬁ

 Go to C3

Less than 1%

1% or more and less than 5%




5% or more and less than 10%
10% or more and less than 25% 


25% or more

Please state the value of the purchases resulted from orders placed via Internet (in 
monetary terms, excluding VAT), in 2005.

(National Currency)

If you can't provide this value,
Please indicate an estimate of the percentage of the total purchases resulted from 
orders placed via Internet, in 2005.
Orders received via Internet (Sales)

C3*. Did your enterprise receive orders via the internet, during 2005 (excluding manually 

typed e-mails)?
(Filter question)

%

Yes 

No  ﬁ

 Go to D1

C4*. Please state the value of the turnover resulted from orders received via Internet (in 

monetary terms, excluding VAT), in 2005.

If you can't provide this value,
Please indicate an estimate of the percentage of the total turnover resulted from orders 
received via Internet, in 2005.

(National Currency)

%

Methodological manual for Information Society Statistics 

93  

 
 
 
C5.

Please provide a percentage breakdown of all Internet sales in 2005, by type of client. 
(estimates in percentage of the monetary values)

a) B2B (Sales to other enterprises) and B2G (Sales to public authorities)

b) B2C (Sales to private consumers)

c) TOTAL

C6.

Please provide a percentage breakdown of all Internet sales in 2005, by destination.
(estimates in percentage of the monetary values)

a) Own country

b) Other EU countries

c) Rest of the world

d) TOTAL

%

%

%

%

%

%

%

1

0

0

1

0

0

C7*. Did your enterprise sell any products to other enterprises via a presence on specialised 

Internet market places, during 2005?

Yes 

No 

Module D: E-commerce via external computer networks other than Internet
(asking enterprises with ICT)

Orders placed via external computer networks other than Internet (Purchases)

D1*. Did your enterprise order products/services via external computer networks other than 

Internet, during 2005?
(Filter question)

D2. Please indicate for 2005 the percentage of the orders placed or transmitted via 

computer networks other than Internet, in relation to the total purchases (in monetary 
terms, excluding VAT).

Alternative Question:

Yes 

No  ﬁ

 Go to D3


Less than 1%
1% or more and less than 25% 
25% or more and less than 50% 
50% or more and less than 75% 


75% or more

Please state the value of the purchases resulted from orders placed via computer 
networks other than Internet (in monetary terms, excluding VAT), in 2005.

(National Currency)

If you can't provide this value,
Please indicate an estimate of the percentage of the total purchases resulted from 
orders placed via computer networks other than Internet, in 2005.
Orders received via external computer networks other than Internet (Sales)
D3*. Did your enterprise receive orders via external computer networks other than Internet, 

during 2005?
(Filter question)

%

Yes 

No  ﬁ

 Go to X1

D4*. Please state the value of the turnover resulted from orders received via computer 

networks other than Internet (in monetary terms, excluding VAT), in 2005.

(National Currency)

If you can't provide this value,
Please indicate an estimate of the percentage of the total turnover resulted from orders 
received via computer networks other than Internet, in 2005.

%

Module X: Background information

(X1-X5) available in some countries from SBS and thus not to be included; latest available information should be provided

X1. Main economic activity of the enterprise, during 2005

X2. Average number of persons employed, during 2005

X3.

Total purchases of goods and services (in value terms, excluding VAT), for 2005

X4.

Total turnover (in value terms, excluding VAT), for 2005

X5.

Location (Objective 1/ non-Objective 1 region), in 2005

Methodological manual for Information Society Statistics 

94  

 
 
 
I.3.2. Model questionnaire for the financial sector 

Eurostat model for a Community Survey on ICT Usage and E-Commerce in 
Enterprises of the Financial Sector 

2006 

Model questionnaire (Version 5 of 2 June 2005) 

 (Questions relating to eEurope benchmarking indicators are marked with an asterisk *)  

Module A: General information about ICT systems 

A1*. 

How many persons employed used computers at least once a week, during 
January 2006? 

If you can't provide this value, 
Please indicate an estimate of the percentage of the number of persons employed 
used computers at least once a week, during January 2006. 

A2*.  Did your enterprise have persons employed who regularly work part of their time 

(half a day per week or more) away from the regular work site while having access 
to the enterprise’s computer system, during January 2006? 
(filter question) 
Did any of those persons access the enterprise's computer system from the 
following places, during January 2006? 

A3. 

a) From home 

b) From customers or other external business partners’ premises  

c) From other geographically dispersed locations of the same enterprise or enterprise group 

A4. 

d) During business travel, e.g. from hotel, airport etc 
Did your enterprise have difficulties in recruiting personnel with ICT skills (from 
basic to professional), during 2005? 
(Filter question) 

A5. 

Did your enterprise face the following problems when trying to recruit personnel, 
during 2005? 

a) Personnel with needed skills in the use of ICT applications not available or not 
entirely suitable 
b) ICT specialists with the needed skills not available or not entirely suitable 

c) High remuneration costs of ICT specialists 

A6*. 

Did your enterprise have the following information and communication 
technologies, during January 2006? 

a) Wireless LAN 

b) Wire based LAN 

c) Intranet 

A7. 

A8*. 

d) Extranet  
Did your enterprise have IT systems to manage the receipt of orders, during 
January 2006? 
(Filter question) 
Did your enterprise's IT systems for managing the receipt of orders link 
automatically with any of the following IT systems, during January 2006? 

a) Internal system of your enterprise or enterprise group 

b)Your customers’ business systems (for customers outside your enterprise group) 

(Number) 

  % 

Yes  

No  (cid:2) Go to 
A4 

Yes 
 
 
 
 

No 
 
 
 
 

Yes  

No  ?  
Go to 
A6 

Didn't need 
to recruit 
 (cid:2) Go 
to A6 

Yes 

 
 
 

No 

 
 
 

Type of 
skills not 
needed 

 
 
 

Yes 
 
 
 
 

Yes  

Yes 
 
 

No 
 
 
 
 
No  (cid:2) Go to 
A9 

No 
 
 

Methodological manual for Information Society Statistics 

95  

 
 
 
 
 
 
  
 
 
 
 
 
 
 
 
 
 
  
 
  
 
  
 
  
 
 
A9. 

In your communication with customers and other enterprises, to what extent has your 
enterprise substituted traditional postal mail (e.g. for sending invoices, direct mail, 
etc.) by electronic means of communication (Intranet, Extranet, Internet, e-mail 
messages), in the last 5 years? 

(tick only one)     
i)   No substitution (overall post mail was not reduced because of electronic means of 
communication) 
ii)  Minor substitution (electronic means are now used instead of post mail in a few situations, but 
post mail is still the most important) 
iii)  Significant substitution (electronic became the main mean of business communication) 

iv)  Most or all substituted (post mail was used before, but it's rarely used nowadays) 

v)   Non-applicable (postal mail was never a relevant mean of communication for the enterprise) 

 
 
 
 
 

Module B: Use of Internet 
(asking enterprises with ICT) 
Did your enterprise have access to Internet, during January 2006? 
(Filter question) 
How many persons employed used computers connected to the World Wide 
Web at least once a week, during January 2006? 

If you can't provide this value, 
Please indicate an estimate of the percentage of the number of persons 
employed used computers connected to the World Wide Web at least once a 
week, during January 2006. 
Did your enterprise have the following types of external connection to the 
Internet, during January 2006? 

B1*. 

B2*. 

B3*. 

a) Traditional Modem (dial-up access over normal telephone line) 

b) ISDN connection 

c) DSL (xDSL, ADSL, SDSL etc) connection 

d) Other fixed internet connection (e.g. cable, leased line (e.g. E1 or E3 at level 1 and ATM at 
level 2), Frame Relay, Metro-Ethernet, PLC - Powerline communication, etc.) 

B4. 

e) Mobile connection (e.g. e.g. analogue mobile phone, GSM, GPRS, UMTS, EDGE, 
CDMA2000 1xEVDO) 
What was the maximum speed for download contractually provided to your 
fastest Internet connection, as of January 2006? 

(tick only one) 

i)   Below 144 Kb/s 

ii)  144 Kb/s or more and less than 2 Mb/s 

B5*. 

B6*. 

B7*. 

B8*. 

B9. 

iii) 2 Mb/s or more 
Did your enterprise use the Internet for training and education, during January 
2006? 

(as consumer of Internet services) 

Did your enterprise use the Internet for interaction with public authorities, 
during 2005? 
(Filter question) 
Did your enterprise interact with public authorities in the following ways, during 
2005? 

a) For obtaining information 

b) For obtaining forms, e.g. tax forms  

c) For returning filled in forms, e.g. provision of statistical information to public authorities  

d) Submitted a proposal in an electronic tender system (e-procurement) 
Did your enterprise have a Web Site / Home Page, during January 2006? 
(Filter question) 

Did your enterprise use its Web Site / Home Page for marketing the 
products/services you were offering, during January 2006? (optional) 

(your enterprise as provider of Internet services) 

Yes  

No  (cid:2) Go to 
D1 

(Number) 

  % 

Yes 
 
 
 
 

 

Yes  

Yes  

Yes 
 
 
 
 
Yes  

No 
 
 
 
 

 

 
 
 

No  
No  (cid:2) Go to 
B8 

No 
 
 
 
 
No  (cid:2) Go to 
B10 

Yes  

No  

Methodological manual for Information Society Statistics 

96  

 
 
  
 
 
 
 
 
 
 
 
 
 
 
 
 
  
 
 
 
 
 
B10*. 

Did your enterprise use the following internal security facilities, during January 
2006? 

a) Virus checking or protection software 

b) Firewalls (software or hardware) 

c) Secure servers (support secured protocols such as shttp) 

B11*. 

d) Off-site data backup 
Was it possible to communicate with your enterprise using the following 
security facilities, during January 2006? 

a) Electronic digital signature as customer's authentication mechanism 

b) Other authentication mechanism (e.g. PIN code) 

c) Data encryption for confidentiality 

Yes 
 
 
 
 

Yes 
 
 
 

No 
 
 
 
 

No 
 
 
 

B12*.  Did your enterprise encounter ICT related security problems during 2005 (e.g. 

computer virus, worms or trojan attack, unauthorised external access to the 
computer system)? 

Yes  

No  

Module C: eCommerce via Internet 

(asking enterprises with Internet access) 

C1*.  Did your enterprise provide on-line financial services to 

customers via the Internet, during 2005?                                                                                                      
(other than information services, manually typed e-mails - 

including all IP/Internet Protocol based networks such as www, 
extranet/EDI over Internet/virtual private network (VPN) over 
Internet, internet enabled mobile phones 

C2a
. 

Which of the following products/services did you provide to 
customers, during 2005? 

a) Payment services 

b) Savings deposits  

c) Loans  

d) Investment services  

e) Life Insurances 

 f) Non-life insurances 
For which of these products/services did you receive orders 
from customers via the internet, during 2005?  

C2b
. 

a) Payment services 

b) Savings deposits  

c) Loans  

d) Investment services  

e) Life Insurances 

 f) Non-life insurances 

Yes  

 No  ﬁ

 Go to D 

Yes 
 
 
 
 
 
 

Yes 
 
 
 
 
 
 

 No 
 
 
 
 
 
 

 No 
 
 
 
 
 
 

Methodological manual for Information Society Statistics 

97  

 
 
 
 
 
 
 
 
 
 
  
 
 
  
  
 
 
 
C3*.  For banking services, (if ticked ‘yes’ in C2b a), b) c) and/or d)) 

Please indicate for 2005 and for the following groups of 
customers the percentage of account/deposit holders who used 
interactive ordering via your website 

Percentage 

 or estimated percentage 

(please tick) 

 or absolute value  

a) All account/deposit holders using interactive ordering via your 
website related to the total number of account/deposit holders      

(current, savings, dept accounts, savings and securities deposits, 
etc.) 

b) Private holders of accounts/deposits using interactive ordering via 
your website related to the total number of private account/deposit 
holders 

c) Corporate holders of accounts/deposits using interactive ordering 
via your website related to the total number of corporate account 
holders 

Less than 1% 

1% or more and less 
than 5% 
5% or more and less 
than 10% 
10% or more and less 
than 25% 
25% or more and less 
than 50 % 

50% or more 

Less than 1% 

1% or more and less 
than 5% 
5% or more and less 
than 10% 
10% or more and less 
than 25% 
25% or more and less 
than 50 % 

50% or more 

Less than 1% 

1% or more and less 
than 5% 
5% or more and less 
than 10% 
10% or more and less 
than 25% 
25% or more and less 
than 50 % 

50% or more 

 
 
 
 
 
 

 
 
 
 
 
 

 
 
 
 
 
 

% 

Number via Internet: 

Total number:            

% 

Number via Internet: 

Total number: 

% 

Number via Internet: 

Total number: 

C4*.  For banking services, (optional) (if ticked ‘yes’ in C2b a, b, c and/or d) 

Please indicate for 2005 the importance of Internet enabled 
financial transactions for your business by providing 
percentages or absolute figures for the following values 

Percentage 

 or estimated percentage 

(please tick) 

 or absolute value  

a) Value of payment orders via internet related to the total value of 
payment orders       

b) Value of revenues (commissions, margins, fees, interest) from 
orders via the Internet related to the total value of revenues 

(in monetary terms, excluding VAT) 

Less than 1% 

1% or more and less 
than 5% 
5% or more and less 
than 10% 
10% or more and less 
than 25% 
25% or more and less 
than 50 % 

50% or more 

Less than 1% 

1% or more and less 
than 5% 
5% or more and less 
than 10% 
10% or more and less 
than 25% 
25% or more and less 
than 50 % 

50% or more 

 
 
 
 
 
 

 
 
 
 
 
 

% 

Value via Internet: 

Total value: 

National Currency 

% 

Value via Internet: 

Total value: 

National Currency, excluding VAT 

Methodological manual for Information Society Statistics 

98  

 
  
  
  
  
  
  
  
  
  
 
  
 
  
  
  
  
 
  
  
 
  
  
  
  
  
 
  
  
  
  
  
  
  
  
  
 
  
  
  
  
  
  
  
  
  
  
  
  
  
 
  
  
  
  
  
  
 
  
  
  
  
  
 
  
  
 
  
  
  
  
  
 
  
  
  
  
  
  
  
  
  
 
  
  
  
  
  
  
  
  
  
  
  
  
  
 
  
  
  
  
  
  
 
  
  
  
  
  
 
  
  
 
  
  
  
  
  
 
  
  
  
  
  
  
  
  
  
 
  
  
  
  
  
  
  
  
  
  
  
  
  
 
 
 
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
 
  
  
  
  
  
  
  
 
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
 
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
 
 
 
C5*.  For insurances, (if ticked ‘yes’ in C2b e) and/or f)) 

Please indicate for the following groups of customers the 
percentage of insurance policies ordered via your website and 
related revenues, during 2005.  

Percentage 

 or estimated percentage 

(please tick) 

 or absolute value 

a) Insurance policies ordered by private customers/individuals via 
your website related to the total number of insurance policies 

b) Insurance policies ordered by corporate customers/enterprises 
via your website related to the total number of insurance policies 

c) Value of Gross Premiums Written from private and corporate  
insurance policies ordered via your website related to the total value 
of Gross Premiums Written 

 (in monetary terms, excluding VAT) 

C6. 

Please provide a percentage breakdown of all Internet sales of 
retail financial services in 2005, by destination. 
(estimates in percentage of the total retail customers) 

Less than 1% 

1% or more and less 
than 5% 
5% or more and less 
than 10% 
10% or more and less 
than 25% 
25% or more and less 
than 50 % 

50% or more 

Less than 1% 

1% or more and less 
than 5% 
5% or more and less 
than 10% 
10% or more and less 
than 25% 
25% or more and less 
than 50 % 

50% or more 

Less than 1% 

1% or more and less 
than 5% 
5% or more and less 
than 10% 
10% or more and less 
than 25% 
25% or more and less 
than 50 % 

50% or more 

 
 
 
 
 
 

 
 
 
 
 
 

 
 
 
 
 
 

% 

Number via Internet: 

Total number: 

% 

Number via Internet: 

Total number: 

% 

Value via Internet: 

Total Value: 

National Currency, excluding VAT 

a) Own country 

b) Other EU countries 

c) Rest of the world 

d) TOTAL 

% 

% 

% 

% 

1 

0 

0 

Methodological manual for Information Society Statistics 

99  

 
  
  
  
  
  
  
  
  
  
  
  
 
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
 
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
 
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
 
 
 
Module D: eCommerce via computer mediated networks other than Internet (optional) 

(asking enterprises with ICT) 

D1*.  Did your enterprise receive orders from customers via networks other 

than Internet, during 2005?  

(private, proprietary networks usually using leased lines - 
excluding all IP/Internet Protocol based networks such as www, 
extranet/EDI over Internet/virtual private network (VPN) over Internet, 
internet enabled mobile phones) 

Yes  

 No  ﬁ

 Go to X 

D2. 

Did your enterprise use the following electronic networks other than 
Internet to receive orders from customers? 
(corporate customers, private individuals) 
a) Network to receive payment batch orders from corporate customers’ 
computer applications  
b) Self-service zones with cash dispensers (e.g. bancomats) and/or credit 
card payment orders from retail customers/individuals   
c) Network  to receive orders from sales agents computer systems linked to 
your enterprise computer system  

d) Other  

Yes 

 

 

 
 

 No 

 

 

 
 

Module X: Background information 

If available, latest information from SBS should be provided 

X1.  Main activity of the enterprise, during 2005 

X2.  Average number of persons employed, during 2005 

(or if this is not available, please provide number of persons employed, December 2005) 

X3.  Location (Objective 1/ non-Objective 1 region), in 2005 

Methodological manual for Information Society Statistics 

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I.3.3. Transmission format 

General Enterprise Survey 

Version 1, 31 March 2006. 

Note: this transmission format refers to the 2006 survey. 

(cid:3)(cid:3)(cid:3)(cid:3) See document MM2006_AnnexI.3.2_TransmissionFormatENT2006 (35 pages) 

Financial Sector Survey 

Version 1, 31 March 2006. 

Note: this transmission format refers to the 2006 survey. 

(cid:3)(cid:3)(cid:3)(cid:3) See document MM2006_AnnexI.3.2_TransmissionFormatFIN2006 (31 pages) 

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I.3.4. Reporting template 

Note: the reporting template for interim & final methodological report refers to the 2005 surveys. 

(cid:3)(cid:3)(cid:3)(cid:3) See document MM2006_AnnexI.3.3_ReportingTemplateENT2005.doc (20 pages) 

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Part II 

Household survey 

Methodological manual for Information Society Statistics 

103  

II.1.  STATISTICAL PRODUCT 

The  statistical  product  is  the  clear  and  precise  definition  of  the  statistical  information  to  be 

produced. It distinguishes itself from the production methodology. The production methodology is 

the  way  or  method  of  doing,  while  the  statistical  product  is  its  direct  result.  Different  statistical 

methodologies  can  produce  the  same  statistical  product,  being  only  different  ways  of  doing  the 

same  thing.  This  means  that  as  long  as  we  guarantee  that  two  figures  concern  the  same 

statistical  product,  for  instance  for  two  different  countries,  they  are  comparable.  This  way,  this 

distinction  between  the  statistical  product  and  the  statistical  methodology  helps  us  to  focus  on 

those  elements  more  important  to  assure  comparability  between  the  several  national  statistics 

and produce new ones at the EU level, i.e. the statistical product, while leaving to the discretion 

of the national statistical institutes the choice of the better statistical methodology to be applied 

in its own country taking into consideration its own specificities. 

The elements that make up the statistical product, at an input level, are the statistical unit, the 

target population and the observation variables, and at the output level, the periodicity and the 

summary  measures,  aggregate  variables  and  tabulation.  Covering  all  the  elements  of  the 

statistical  product,  the  statistical  concepts  and  the  nomenclatures  are  the  additional  needed 

element to assure harmonization and comparability of statistics. 

II.1.1. 

Statistical unit 

The  statistical  unit  is  the  base  type  of  the  elements  of  a  group  (also  called  population)  that  we 

want  to  observe  or  analyse.  The  basic  statistical  operations  of  classification,  aggregation  and 

ordering are done on the statistical unit. 

The  choice  of  the  statistical  unit  is  a  matter  of  both  the  data  collection  process  (namely  the 

operational  restrictions  associated  to  collecting  data  from  each  type  of  statistical  unit)  and  the 

conceptual framework chosen to observe and analyse the phenomenon. The statistical unit is the 

bearer of statistical characteristics or attributes, which we ultimately want to measure. 

There are several types of statistical units, according to its usage. An observation unit represents 

an identifiable entity, about which data can be obtained. During the collection of data, this is the 

unit for which data is recorded. It should be noted that this may, or may not be, the same as the 

reporting  unit.  The  reporting  unit  is  the  unit  that  reports  to  the  survey  authority.  It  reports 

information for the observation unit(s). In certain cases it may be different from the observation 

unit. A reporting unit is a unit that supplies the data for a given survey instance. 

In the ICT usage survey, the following statistical units are used (depending on the variable): 

-  households; 

- 

individuals. 

Ideally,  the  data  collected  on  the  household,  should  be  reported  by  ‘the  household’.  In  most 

cases, it is of course not feasible to put the household around the table in order to collect their 

common answer, this is especially the case in a telephone interview. In general, one individual in 

the  household  will  answer  the  household  related  questions  having  the  household  perspective  in 

mind.  This  one  individual can  for  instance  be  the  head  of  the  household or  the  individual  which 

has been selected for the individual questions. 

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As the survey relates to ones usage of computers and Internet, it is necessary that the selected 

individual  answers  the  questions  personally.  Proxy  interviews  may  lead  to  errors  in  the  data 

collection. 

Different survey units, i.e. households and individuals, are used in different sections of the model 

questionnaire. The household approach is used when information on access to different electronic 

devices,  type  of  Internet  connection,  and  barriers  to  use  of  the  Internet  is  collected.  The 

individual  approach  is  used  when  information  on  use  of  computers,  use  of  the  Internet, 

e-commerce and e-skills is collected. 

The reasoning behind using a household approach when trying to describe access to ICT is that 

households are the platform for providing access for a number of individuals, i.e. the members of 

households. In order to make comparisons between European countries on household level it is 

important to take into account the differences in household demographics. One of the reasons for 

this  is  that  some  countries  might  have  bigger  household  sizes,  and  composition  than  other 

countries,  which  also  probably  is  correlated  with  the  rate  of  access.  To  be  able  to  make  fruitful 

comparisons it also important that countries deploy the same household definition. 

The individual approach is used in the context where the collected information to a larger extent 

refers to the individual’s use of ICT. Also in this case it is import to take into account structural 

differences between countries, e.g. age demographics, in order to make fruitful comparisons. The 

problem  is  however  not  as  large  as  when  it  comes  to  households  since  many  people  have  a 

better  knowledge  of  countries’  differences  in  age  structure  than  the  differences  in  household 

structure. 

II.1.2. 

Target population 

A population is a collection of objects of the same class, which in statistical terms means a group 

of  elements  of  the  same  statistical  unit.  There  are  two  types  of  populations  to  be  considered 

when producing statistics: the target population and the frame population. 

The target population is the population of interest. It is defined by delimiting clearly the group of 

statistical elements for which some information concerning the all group we want to know. That 

delimitation  is  based  on  one  or  more  attributes  of the  statistical  unit.  In  the  ICT  usage  survey, 

the target population for the different statistical units is: 

- 

individuals: target population consists of all individuals aged 16 to 74; 

-  households:  target  population  consists of  all  (private)  households  with  at  least  one  member 

aged 16 to 74. 

The  frame  population  is  an  operationalisation  of  the  target  population,  consisting  ideally  in  a 

complete list of the elements of the target population. Although a target population can be easily 

defined, in practise a list of all its elements is needed for its complete or partial (in case a sample 

is  used)  observation,  and  that  can  be  very  difficult  to  obtain.  That  list  should  be  complete  and 

include every element of the target population only once. However, most of the time it will suffer 

from both under-coverage and over-coverage. Usually files of statistical elements (registers) are 

maintained  and  updated,  containing  lists  of  statistical  elements  and  also  information  on  some 

attributes, usually used for delimiting target populations. Frame populations are usually extracted 

Methodological manual for Information Society Statistics 

106  

 
 
 
from  those  registers.  The  frame  population  will  be further  explained  in  chapter  II.2.2,  including 

an overview of the countries’ practices for the 2005 survey. 

II.1.3. 

Periodicity 

The  periodicity  is  annual,  meaning  the  data  is  collected  and  compiled  once  per  year.  However, 

some  variables  can  be  observed  with  a  lower  frequency,  e.g.  variables  which  tend  to  be  stable 

over time. 

An annual survey should  be a compromise or trade-off between response and collection burden 

and  the  need  for  relevant  and  recent  information  on  a  “fasting  moving”  study  domain  like  the 

information society.  

This periodicity is laid down in paragraph c) of Annex II of Regulation 808/2004 and in section 5 

of Regulation 1099/2005 (see also Part III – EU Legislation). 

II.1.4. 

Observation variables 

In the ICT usage survey, most of the observation variables are qualitative, i.e. the aim is not to 

collect information on quantities (“how many …”), frequencies (“how often …”) or amounts (“how 

much  …”)  but  rather  to  obtain  non-numerical  or  categorical  information.  In  most  cases,  the 

observations  variables  in  the  ICT  usage  survey  are  binary  (dichotomous),  meaning  the 

respondent answers with yes or no, e.g. Have you used the Internet for selling goods or services. 

The final statistics will then mainly be proportions (e.g. the number of yes answers divided by the 

number of respondents who answered the question).  Other observation variables are qualitative 

too, but with more then two answering categories (e.g. highest educational level).  

The  attributes  or  characteristics  for  the  Community  survey  on  ICT  usage  in  households  and  by 

individuals  are  listed  in  Part  III  of  this  document  (Annex  II  of  the  Commission  Regulation,  see 

p. 200).  

The  operational  version  of  the  observation  variables  are  the  questions  in  the  survey 

questionnaire. A model for such questionnaire can be found in Annex II.3.1. 

The definition of the observation variables or the model questions are discussed in more detail in 

the explanatory notes below, see II.1.6. 

II.1.5. 

Summary  measures,  aggregated  variables,  indicators 
and tabulation 

Summary  measures  are  numerical  values  defined  by  a  statistical  measure  that  is  used  to 

summarize  the  values  for  a  specific  variable  for  all  statistical  units  in  a  specific  group.  Such 

measures  can  take  the  form  of  aggregates  (e.g.  total  number  of  yes-answers  on  a  specific 

questions) or indicators (e.g. percentage of yes-answers). 

Methodological manual for Information Society Statistics 

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Aggregates can be compiled for the total population or for the different subpopulations defined by 

the  background  variables  (e.g.    gender  or  educational  level)  or  for  subpopulations  defined 

conditional on the answers of other study variables (e.g. Internet users versus non users).  

E.g.: 

-  number of individuals having used a computer in the last 3 months at home 

-  number of individuals aged 16-24 having used a computer in the last 3 months at home 

-  number of individuals with having used a computer in the last 3 months at home but not at work 

-  number  of Internet  users  having  used  it for downloading  official forms  (=  number of  individuals  having 

used the Internet and having downloaded official forms) 

To  obtain  the  indicators  (proportions,  percentages,  etc.),  the  aggregates  need  to  be  divided  by 

the total population or subpopulation.   

The denominator of such ratio can for instance be: 

- 

total  population  of  individuals  in  selected  strata  (e.g.  “proportion  of  persons  aged  16-24  having  used  a 

computer at home” = the number of individuals aged 16-24 having used a computer in the last 3 months 

at home divided by the total number of individuals aged 16-24) 

- 

- 

total number of computer users (individuals that used a computer at least once in last 3 months) 

total number of regular computer users (individuals that used a computer at least once a week in the last 

3 months) 

The  detailed  transmission  format  for  sending  the  aggregated  data  to  Eurostat,  can  be  found  in 

II.3.2 Transmission format. 

II.1.6. 

Explanatory notes 

The explanatory notes in this chapter refer to the questions in the 2006 model questionnaire (see 

II.3.1 Model  questionnaire,  p.  183).  The  structure  of  this  chapter  follows  the  model 

questionnaire,  i.e.  the  explanatory  notes  are  grouped  per  module  and  per  question.  It  is 

recommended to have the model questionnaire at hand while reading this section. 

For  reasons  of  continuity,  the  explanatory  notes  for  questions  that  are  not  part  of  the  2006 

model questionnaire (but were part of the 2005 model questionnaire) have been retained, at the 

end of each module. 

The statistical unit for Module A is the household while the individual is the statistical unit for the 

other modules. 

Methodological manual for Information Society Statistics 

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II.1.6.1  MODULE A: ACCESS TO INFORMATION AND COMMUNICATION TECHNOLOGIES 

(cid:4) Statistical unit: households 

A1:  Do you or anyone in your household have access to any of the following 

devices at home? 

[ Scope: all households ] 

[ Type: multiple answers allowed, i.e. Tick all that apply ] 

For  a  definition  of  a  household  see  below,  questions  G8  and  G9  of  Module  G:  Socio-

demographic background variables.  

Access at home refers to the dwelling unit where the household/individual has its address.  

a) TV 

The  main  difficulty  with  this  question  is  to  define  digital  TV.  Many  respondents 

might not know what it really is. 

If yes to a), the household is asked if it has access to the following at home: 

a1) satellite dish  

A  satellite  dish  refers  to  a  small  dish  antenna  which  is  used  to  receive  television 

programs. 

a2) cable TV 

Cable  TV  refers  to  television  services  that  are  provided  to  households  within  a 

community by  means  of  a  network.  Many  television  channels  are  allowed  via  cable 

TV through subscription. 

a3) digital TV 

Digital  TV  refers  to  television  via  digital  signals.  This  is  the  basic  difference 

compared  to  ordinary  TV  transmission  which  is  via  analogue  signals.  Improvement 

of  picture  quality  and  Internet  access  are  some  of  the  features  that  characterize 

digital TV.  

Today’s analogue TV needs e.g. a set top box, which is a device that sits on top of 

the TV set and is the interface between the home TV and the cable TV company. The 

set  top box  changes  the  digital  signal  from  the  cable  TV  company  so  the  home  TV 

(which is analogue) can read the signal. 

c) Fixed telephone line 

A  fixed  telephone  line  connects  the  subscribing  household  to  the  switching  exchange  of 

the  providing  phone  company,  via  a  copper  wire  or  more  advanced  means  such  as  a 

coaxial  cable.  Certain  broadband  connections  (cf.  infra)  such  as  DSL,  make  use  of  fixed 

telephone lines.  

Methodological manual for Information Society Statistics 

109  

c) Mobile phone 

A mobile phone is a communication system that permits telephone communication to and 

from  mobile  users  and  to and  from  fixed  networks.  Other  terms  for  a  mobile phone  are 

gsm, handy, cellular phone and cell phone.  

d) Internet enabled mobile phone 

If  yes  to  c),  the  household  is  asked  if  it  is  an  Internet  enabled  mobile  phone  via  WAP, 

GPRS  or  UMTS  (defintions:  see  below).  This  should  be  regardless  whether  it  is  used  or 

not. Internet can be defined as a networking infrastructure, where any computer or other 

device  can  communicate  with  each  other  as  long  as  they  are  both  connected  to  the 

Internet. The  Internet is used for access to the World Wide Web and is also used for e-

mail correspondence, instant messaging etc.  During an interview, questions such as 'do 

you use picture messaging' or 'does your mobile phone have a built-in camera' can help 

to detect whether a respondent has an Internet enabled mobile phone. 

The terms WAP (Wireless Application Protocol) and GPRS (General Packet Radio Systems) 

stand for 2nd generation mobile technologies (though GPRS is sometimes referred to as 

2,5  generation)  while  UMTS  (Universal  Mobile  Telephone  System)  is  the  term  for  3rd 

generation  mobile  technology.  Both  give  access  to  the  Internet  but  3rd  generation  at  a 

much higher speed.  

e) Games console 

A  games  console  is  an  electronic  device  designed  to  play  games.  Examples  are  Sony 

playstation, Nintendo GameCube and Microsoft Xbox. 

f) Desktop computer 

A  desktop  computer  can  be  defined  as  a  computer  that  usually  remains  fixed  in  one 

place.    Normally  the  user  is  placed  in  front  of  it,  behind  the  keyboard  with  the  monitor 

placed on top. 

g) Portable computer (laptop) 

A  portable  computer  (or  laptop)  can  be  defined  as  a  computer  that  is  small  enough  to 

carry. A portable computer (or laptop) can usually carry out the same tasks as a desktop 

computer. Includes notebooks but not handheld computers, although portable. 

h) Handheld computer (palmtop) 

A handheld computer is a computer that can be used while you are holding it and stored 

in a small bag or for instance in a pocket. Personal Digital Assistants (PDAs) are another 

term for handheld computers. A PDA uses a pen rather than a keyboard. 

As  some  PDAs  can  also  be  used  for  mobile  telephony  (e.g.  hi-tech  mobile  phones  with 

some kind of integrated PDA, such as Sony  Ericsson P800 and P900 series), there is an 

overlap with item b) of this question, i.e. these PDAs can be counted for as both a mobile 

phone (item b) and a handheld computer (item f). 

i) None of the above 

Applies  where  the  household  does  not  have  access  to  the  above  mentioned  devices  at 

home. 

Methodological manual for Information Society Statistics 

110  

A2:  Does any member of the household have access to the Internet at home, 

regardless of whether it is used? 

[ Scope: all households ] 

[ Type: one single answer needed, i.e. Tick only one ; binary (Yes/No) + Don’t know ; 

filter question] 

‘Access’  does  not  refer  to  the  “connectability”  (i.e.  can  connections  be  provided  in  the 

households’ area or street), but to whether anyone in the household could use the Internet 

at home if desired, even if just to send an e-mail.  

The  clause  ‘regardless  of whether  it  is  used’  will in  most  cases  be  irrelevant as  households 

will  normally  make  use  of  a  service  they  have  subscribed  to  (and  are  paying  for).  It  is 

however  possible  that  the  connection  was  installed  by  one  of  the  household  members’ 

employer    or  is  a  default  facility  in  the  building where  the  family  is  living  (without  actually 

being used). 

The Don’t know answering category should be avoided by asking the respondent additional 

questions.  However,  in  some  cases  the  household  member  selected  for  the  interview  may 

not be aware what other members are doing with e.g. the household’s computer. 

A3:  On which of these devices is the Internet accessed at home? 

[ Scope: all households with Internet access at home, i.e. A2 = Yes ] 

[ Type: multiple answers allowed, i.e. Tick all that apply ] 

Which items are presented to the respondent, will depend on the answers given in question 

A1 (which can thus be seen as a filter question). 

The question focuses on devices already defined in question A1. In most cases it is obvious, 

that the device in question can provide access to the Internet. Regarding d) games console, 

some of them have built-in modems and thus give access to the Internet, e.g. Playstation 2.  

Item e) Other means in the 2006 model questionnaire lists two optional sub-items, namely: 

e1) via Internet enabled mobile phone 

e2) via handheld computer (palmtop, PDA) 

These  items  have  been  rendered  optional  as  they  come  back  in  the  individual  part  of  the 

questionnaire (see Module C, question C4).  

A4:  What types of Internet connection are used? 

[ Scope: all households with Internet access at home, i.e. A2 = Yes ] 

[ Type: multiple answers allowed, i.e. Tick all that apply ] 

Below  is  given  an  explanation  of  the  most  commonly used  technologies.  If  the  NSI  finds  it 

more appropriate to use the brand  names or company names than using the  references to 

the technologies (ADSL, cable, etc.), this is also a possibility (of course under the condition 

the  brand  names  can  be  recoded  to  the  different  technologies  based  on  a  one-to-one 

relationship). 

Methodological manual for Information Society Statistics 

111  

a) Modem (dial-up access over normal telephone line) or ISDN 

Connects  the  household  via  dial-up  either  through  an  analogue  modem  or  ISDN 

(Integrated Services Digital Network). Both types can be categorised as narrowband. 

 b) DSL (e.g. ADSL, SHDSL etc.) 

DSL  (Digital  Subscriber  Line)  stands  for  technology  that  transports  data  at  high  speeds 

(i.e.  equal  to  or  higher  than  144  kbit/s)  over  the  existing  copper  network.  DSL 

technology  is  a  type  of  Internet  connection  which  is  significantly  faster  than  dial-up 

access and therefore designated as broadband. 

Important DSL technologies include: 

ADSL: This term is used for DSL where more bandwidth is allocated to download than upload 

(Asymmetric DSL). 

SHDSL: Single pair high-speed DSL covers symmetric high speed DSL.  

c) Other broadband connection (e.g. cable, UMTS, etc.) 

This  question  sums  up  all  other  types  of  Internet  connection  which  is  not  provided  via 

DSL but still can be designated as broadband.  

The technologies in question are: 

Cable modem: This technology allows high-speed Internet access to be delivered over a cable 

TV network or communal aerial systems. Like DSL technologies the data is transported over 

the existing copper network. 

LAN  (Local  Area  Network):  High-speed  Internet  connections  via  housing  networks 

(connections common to several households, e.g. residents in a college). 

Fibre optic cable: A technology which is not based on copper wire. The technology uses lasers 

or light emitting diodes and can provide unlimited bandwith potential. 

Fixed  wireless  technologies  (FWA):  Technologies  in  this  group  are  all  wireless  technologies 

that provide access between fixed points. 

Satellite technologies: Provides wireless access and are predominantly used in remote areas 

not reached by cable or DSL networks. 

UMTS: For a definition, see question A1 d). 

d) Mobile phone over narrowband (WAP, GPRS, etc.) 

Broadband over the mobile phone is still limited and 2nd generation mobile technologies 

such as WAP and GPRS (see question A1 for a definition) are designated as narrowband 

connection.    

A5:  What are the reasons for not having access to the Internet at home? 

[ Scope: all households without Internet access at home, i.e. A2 = No ] 

[ Type: multiple answers allowed, i.e. Tick all that apply ] 

The  question  gives  an  idea  of  the  household  reasons  or  barriers  for  not  having  access  at 

home. Respondents should indicate all reasons that are relevant to them, not only the main 

reason(s). 

Methodological manual for Information Society Statistics 

112  

a) Have access to the Internet elsewhere 

All other places, e.g. workplace, but not at the home address. 

b) Don’t want Internet  

May  apply  to  people  that  find  content  on  the  Internet  harmful  or  have  a  principle 

objection towards Internet use. 

c) Don’t need Internet 

May apply to people that do not find it useful or interesting.  

d) Equipment costs too high 

People  in  this  category  find  equipment  costs  too  high,  that  is,  the  previously  defined 

devices in question A1 (including the set-up costs, e.g. the cost of a modem for internet 

connection). 

e) Access costs too high (telephone, etc.) 

Access costs can be telephone charges, subscription fees for broadband use etc. 

f) Lack of skills 

The  respondent  does  not  have  sufficient  knowledge  to  use  or  to  get  access  to  the 

Internet. 

g) Physical disability 

h) Privacy or security concerns 

The respondent is worried about giving personal details over the Internet due to private 

or  security  reasons.  Respondents  might  also  be  worried  about  virus  attacks  and  similar 

security problems even without giving personal details over the Internet. In this respect, 

the  spreading of  spyware  is  a  major  concern  (spyware  is  a  program  which  has  installed 

itself on the computer to monitor and report on the respondent’s computer activity; the 

development of spyware has also led to numerous anti-spyware tools to prevent spyware 

activity on the computer). 

i) None of the above, but other 

This  category  is  included  to  close  the  question.  Assuming  that  respondents  that  do  not 

have Internet at home must have a reason for not having it, the respondent is supposed 

to  tick  at  least  one  of  the  options  a  to  h  or  option  i.    In  cases  where  the  respondents 

states not to have any particular reason (not even after having heard the options in the 

questionnaire) None of the above, but other can be ticked. 

Methodological manual for Information Society Statistics 

113  

II.1.6.2  MODULE  B:  USE  OF  MOBILE  PHONE  AND  COMPUTERS,  LOCATION  AND 

FREQUENCY OF USE 

(cid:4) Statistical unit: individuals 

B1:   When did you most recently use a computer? 

[ Scope: all individuals ] 

[ Type: one single answer needed, i.e. Tick only one ; filter question ] 

A computer should be defined as multi purpose machine, a personal computer, powered by 

one of the major operating systems, i.e. Macintosh (Apple), Linux or Microsoft (Windows, XP 

or NT). PDA’s (handheld computers or palmtops) should also be included. Other equipment 

with  embedded  computing  abilities,  e.g.  cell  phones,  VCR’s,  TV  sets,  washing  and  dishing 

machines should be excluded. 

B2:   How often on average have you used a computer in the last 3 months? 

[ Scope: all individuals having used a computer in the last 3 months, i.e. 1st option in B1] 

[ Type: one single answer needed, i.e. Tick only one ] 

For definition of a computer see above, B1. 

Persons who use a computer at work on a daily basis during the week but who don’t use a 

computer at home during the weekend should tick option a) Every day or almost every day. 

B3:   Where have you used a computer in the last 3 months? 

[ Scope: all individuals having used a computer in the last 3 months, i.e. 1st option in B1] 

[ Type: multiple answers allowed, i.e. Tick all that apply ] 

For definition of a computer see above, B1.  

Concerning alternative b) At place of work (other than home), this should be interpreted as 

any place where work is usually conducted excepting at home. The usual place of work can 

be much wider than just the premises of the employer.  

Alternative  c)  At  place  of  education,  should  be  interpreted  as  the  institution  where  the 

education  takes  place  (“within  the  school  walls”). Teachers  using  computers  in  their  school 

should tick alternative b) At place of work as alternative c) rather refers to the point of view 

of pupils or students. 

See also C3 (location of Internet use). 

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B4: Do you use a mobile phone? 

[ Scope: all individuals ] 

[ Type: one single answer needed, i.e. Tick only one ; binary (Yes/No) ; filter question for B4 ] 

This question serves both as a stand-alone study variable and as a filter question for B5. 

For definition of a mobile phone see above, A1c. 

‘Use’  refers  to  the  actual  use  of  this  device.  Whether  the  respondents  owns  the  mobile 

phone is irrelevant to this question. In most cases, it will be a personal mobile phone but in 

some  households  a  ‘collective’  mobile  phone  may  be  shared  by  several  members  –  this  is 

especially the case for households that are ‘new’ to mobile telephony.  The mobile phone can 

be owned by the respondent or can e.g. be provided by the respondent’s employer. 

B5: To what extent have you substituted private traditional mail (e.g. birthday 

wishes, season’s greetings, contacts with companies or administration) 
by mobile messages (text or picture)? 

[ Scope: all individuals using a mobile phone, i.e. B4 = Yes ] 

[ Type: one single answer needed, i.e. Tick only one ] 

This  question  has  been  introduced  in  Eurostat’s  model  questionnaire  for  2006  following  a 

specific  request  by  Directorate-General  Internal  Market  and  Services  (DG  MARKT).  An 

analogue question on substitution by Internet or e-mail messages can be found in Module C 

(question C5). 

The  question  on  substitution  of  traditional  mail  by  mobile  messages  needs  to  be  inserted 

before  non  Internet  users  are  filtered  out,  i.e.  before  Module C.  To  filter  out  non  mobile 

phone users, a question on mobile phone use can be inserted, see B4.   

Sending mobile messages (SMS) via the Internet (i.e. one goes to the website of a 
telephone  company  and  sends  an  SMS  through  that  website),  is  not  to  be 
considered as a mobile message. Indeed, from the point-of-view of the respondent, 
the  Internet  was  used  to  send  the  message,  and  not  a  mobile  phone  and  such 
message falls under the scope  of question C5  (if it substituted a traditional postal 
mail). 

Please note that the discussion below covers both questions B5 and C5. Therefore reference 

is  not  only  made  to  mobile  text  messages  but  also  to  Internet  or  e-mail  messages.  The 

examples include situations from both an enterprise and a household/individual perspective. 

In the model questionnaire, the different levels of substitution are indicated in ‘words’, not in 

percentages  ranges.    The  four  categories  used  are  No  substitution,  Minor  substitution, 

Significant  substitution  and  Most  or  all  substituted.  As  the  meaning  of  the  different 

categories in the question may be troublesome when translating into the national languages 

or when carrying out the interviews, the following guidelines can be kept in mind:  

-  No  substitution  means  that  postal  mail  (resp.  Internet  or  e-mail  messages)  has  not 

reduced (0%);  

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-  Minor substitution means that mobile text messages (resp. Internet or e-mail messages) 

are  now  used  instead  of  postal  mail in  a  few  situations  but  not  in  general  (up  to  about 

one third of communication);  

-  Significant  substitution  means  that  mobile  text  messages  (resp.  Internet  or  e-mail 

messages) have substantially replaced postal mail (about 35-40% to 70-75%, or roughly 

1/3 up to 2/3);  

-  Most or all substituted means that mobile text messages replaced the majority of former 

postal mail and postal mail is now only used in a few situations. 

A category Not applicable has been added for respondents who have never made significant 

use of traditional postal mail, e.g. younger respondents or new companies. 

Although  alternative  coding  schemes  can  be  used,  e.g.  a  0-to-10 scale  or  additional 

categories, it is recommended to use the categories proposed in the model questionnaire for 

several  reasons.  First,  the  final  output  needs  to  be  recoded  into  4  categories  (+  non-

applicable) before submitting the data to Eurostat. Second,  such scaling probably shifts the 

dilemma  on  the  borderline  cases  from  the  respondents  to  the  NSI  (e.g.  is  'minor'  reflected 

by '1 up to 3' or rather by '1 up to 4' ?). Third, using harmonised questions at the input level 

can help in obtaining harmonised statistics at the end of the production line.  

Concerning  the  meaning  of  'substitution',  the  main  interest  is  to  know  to  which  extent 

traditional mail (letters, etc) is decreasing because of replacement by mobile text messages 

(resp.  Internet  or  e-mail  messages).  Not  the  additional  communication  via  e.g.  sms  is 

relevant, but that part of mobile text messages that is replacing traditional mails. 

E.g. a ‘short message service’ or SMS to wish someone a happy birthday will most probably 

replace a letter (as such wishes used to be sent with a card via post) ; an SMS to make an 

appointment  for  the  evening  will  most  probably  not be  replacing  a  traditional  letter  (would 

rather have been a phone call before the 'SMS era'). 

Or,  if  a  company  is  now  sending  500  e-mail  messages  a  day,  these  are  not  necessarily 

replacing traditional postal mail, but probably mainly additional communication. 

The following 'case studies' may clarify what kind of information is needed: 

a.  A person used to send 5 letters per week on average, now this person (still in a similar situation) 

sends  5  letters  and  additionally  some  200  e-mails  and  10  mobile  text  messages.    The  extent  of 
postal mail has not changed → No substitution. 

b.  Before the "Internet era" started, a phone company had about 1 million customers and sent each 

of them a monthly bill, an annual overview sheet and an annual letter on miscellaneous issues. A 

total of 14 million letters per year. Nowadays, the company still has 1 million customers but they 

now  have  the  opportunity  to  receive  their  bills  per  e-mail.  Half  of  them  prefers  to  do  so.  This 

means:  in  the  new  situation,  2  million  'annual  letters'  are  sent,  but  only  6  million  (500.000 

customers x 12 monthly bills) invoices. The other 6 million invoices are now sent by e-mail. In this 

case, their would be a substitution of 6 of the 14 million letters, approximately 43%, which could 

be considered as a significant substitution. 

c.  Same situation as the previous example, but due to a booming economy, the number of customers 

has  increased  to  1.75  million.  In  this  configuration,  the  company  now  sends:  3.5  million  'annual 

letters', 10.5 million invoices (875.000 customers x 12 monthly bills) and additionally 10.5 million 

invoices  by  e-mail.  One  could  say  that  the  company  is  still  sending  14  million  letters  per  year 

meaning no substitution has taken place. However, this is only a structural effect. With the same 

increase  in  business  'in  the  past'  (i.e.  before  the  use  of  e-mail),  the  company  would  have  sent 

1.750.000  x  (2  +  12)  letters,  a  total  of  24.500.000.  Meaning  that  in  this  case  about  10  million 

Methodological manual for Information Society Statistics 

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extra  letters  would  have  been  sent  if  e-mail  had  not  existed,  or  a  substitution  of  10.5  /  24.5  or 

43% (significant substitution). In other words, the question could be explained as: in your current 

business situation, how much more extra letters (or packages) would you have sent if e-mail didn't 

exist. 

d.  Take the example of Eurostat grant agreements. Every country receives a registered letter as a call 

for proposals.  Additionally,  e-mails  are sent  to  the  directors  and  to  the  Working  Group members. 

These e-mails are only in addition, the paper version is still existing. So in this case, no substitution 

took  place.  Further  communication  mainly  takes  place  via  e-mail,  but  this  is  rather  replacing  fax 

messages or phone calls, so this part of the proces is not 'threatening' postal mail either. For this 

simplified example, we could say that no substitution took place from the point of view of Eurostat. 

e.  Same  example  (grants),  but  from  the  point  of  view  of  the  Member  States.  Assume  the  applying 

Member  State  used  to  send  an  initial  proposal  plus  on  average  three  additional  letters  giving 

further  technical  or  budgetary  details.  Now,  only  the  initial  proposal  is  dealt  with  via  postal  mail, 

the  additional  letters  are  replaced  by  e-mail  communication.  In  this  (again  simplified)  case,  their 

would be a substitution of 3/4 or most or all substituted. 

f.  Years ago, a person used to send only a few postcards when going on holidays. Let's assume: 1 for 

the  parents,  1  for  the  brother,  2  for  the  grandmothers.  Now,  the  same  person  deals  with  sunny 

greetings by SMS (e.g. because these arrives immediately and are not more expensive). Because 

this  is  easy,  the  person  makes  12  people  jealous  with  a  sunny  message.  However,  parents  and 

grandmothers are still not using the Internet nor mobile phones, in other words: 3 traditional cards 

+  9  text  messages  (of  which  one  to  the  brother  who  always  got  some  card  +  8  to  'new' 

addressees). The additional 8 are not relevant in the discussion. Only the SMS replacing the card to 

the brother counts, so 1 in 4 substituted or minor substitution. 

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II.1.6.3  MODULE C: USE OF THE INTERNET 

(cid:4) Statistical unit: individuals 

C1: When did you most recently use the Internet? 

[ Scope: all individuals (even those who reported never having used a computer in B1 as they may 

have accessed the Internet via other means, though this may be very exceptional) ] 

[ Type: one single answer needed, i.e. Tick only one ; filter question ] 

This questions covers any use of the internet - whether at home, at work or from anywhere 

else and whether for private or professional purposes.  

The time breakdowns are self explanatory: Within the last 3 months; Between 3 months and 

a year ago; More than one year ago; Never used it. 

C2: On average how often did you use the Internet in the last 3 months?  

[ Scope: individuals who used the Internet in the last 3 months, i.e. 1st option (Within the 

last 3 months) in C1 ] 

[ Type: one single answer needed, i.e. Tick only one ] 

The  response  categories  to  this  question  could  be  slightly  ambiguous.  Respondents  should 

therefore be presented with all four options and should select which one best describes their 

behaviour. 

a) Every day or almost every day 

If asked this should refer to more than 4 days each week. As in question B2, persons who 

use the Internet at work on a daily basis during the week but who don’t use it at home 

during the weekend should tick option a) Every day or almost every day. 

b) At least once a week (but not every day) 

If asked this should refer to between 1 and 4 days each week 

c) At least once a month but not every week 

d) Less than once a month 

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C3: Where have you used the Internet in the last 3 months (using a computer 

or any other means)? 

[ Scope: individuals who used the Internet in the last 3 months (i.e. 1st option in C1) ] 

[ Type: multiple answers allowed, i.e. Tick all that apply ] 

The  question  is  to  be  answered  regardless  of  the  device  used  or  type  of  connection  used. 

E.g.  if  a  person  uses  a  portable  computer  with  a  wireless  data  card  (to  be  inserted  in  the 

card slot) at several locations, he or she should tick all those locations. 

a) At home 

This should be ticked if the respondent has  used the Internet at  home for any purpose, 

private or work-related.  

b) At place of work (other than home) 

This should be defined as  usual place of work.  If the respondent usually works at home 

then a) should be coded. If the respondent’s work is usually based in a number of places 

then any of these places count as their place of work. However, use of mobile technology 

in  places  such  as  hotels  etc.  even  for  work  related  purposes,  should  be  coded  as  e)  At 

other places. 

c) At place of education 

This should refer to the respondent’s own place of education. If the respondent works at 

an educational establishment – e.g. a teacher - then b) should be coded. 

d) At another person’s home 

This should not be used if the respondent’s place of work is another person’s home. 

e) At other places 

This includes ANY places not already coded above. The further responses are a subset of 

places which might be included in At other places but is NOT a comprehensive list. On the 

other hand, not all items of the list may be relevant to each country.  

Ideally the respondent should be presented with the further list only after they have said 

“other place” 

of which:  

e1) Public  library:  some  public  libraries  offer  the  possibility  to  access  the  Internet, 

whether it be a free service or if a charge is made. 

e2) Post office: see definition below. 

e3) Public office, town hall, government agency: The wording to be used in each member 

state should reflect titles of public offices which respondents would recognise. 

e4) Community or voluntary organisation: see definition below. 

e5) Internet  café:  Commercial  places  that  provide  Internet  access  services  under 

payment.  There  is  usually  a  charge  for  using  the  Internet.  This  charge  is  normally 

calculated on the basis of the amount time spent on-line. An Internet Café may also 

charge for usage not related to the internet (e.g. use of word processing software). 

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Post  offices,  Public  offices  (town  hall,  government  agencies),  Community  or  voluntary 

organisations are all public places capable of providing access to the Internet. The access 

to the Internet in these public places can be free or under payment of a fee. 

C4: Do you use any of the following mobile devices to access the Internet? 

[ Scope: individuals who used the Internet in the last 3 months (i.e. 1st option in C1) ] 

[ Type: multiple answers allowed, i.e. Tick all that apply ] 

This question refers to the actual use as a means of access not to the ‘theoretical’ possibility 

of access. Question C4 is not limited to Internet access at home, but can refer to all possible 

locations (as is in general the case for Module C).  

Via Mobile phone has been split into two items in order to separate UMTS (see item a) from 

WAP  or  GPRS  (see  item b).  First,  because  of  a  high  interest  from  users  of ICT  statistics  in 

the  take-up  and  usage  of  UMTS.  Second,  because  this  also  enables  to  distinguish  between 

mobile phone access over broadband versus mobile phone access over narrowband. 

For  additional  information  on  WAP,  GPRS,  UMTS  or  Handheld  computer,  see  Module  A, 

question A1 (items d and h). 

C5: To what extent have you substituted private traditional postal mail (e.g. 

birthday wishes, season’s greetings, contacts with companies or 
administration) by Internet or e-mail messages? 

[ Scope: individuals who used the Internet in the last 3 months (i.e. 1st option in C1) ] 

[ Type: one single answer needed, i.e. Tick only one ] 

This  question  has  been  introduced  in  Eurostat’s  model  questionnaire  for  2006  following  a 

specific  request  by  Directorate-General  Internal  Market  and  Services  (DG  MARKT).  An 

analogue  question  on  substitution  by  mobile  text  or  picture  messages  can  be  found  in 

Module B (question B5). 

For  a  detailed  discussion  of  the  meaning  or  interpretation  of  the  different  levels  of 

substitution, the purpose of the category Not applicable or for some practical illustrations of 

what is meant by ‘substitution’, please see the explanatory notes for question B5 (page 115 

and following). 

C6: Do you use a personal e-mail address (private or office)? 

[ Scope: individuals who used the Internet in the last 3 months (i.e. 1st option in C1) ] 

[ Type: one single answer needed, i.e. Tick only one ; binary (Yes/No) ] 

This  question  asks  whether  the  respondent  has  his/her  own  or  personal  e-mail  address. 

‘Personal’  address  means  that  the  respondent  is  the  only  person  who  can  access  the 

mailbox. It’s an address where the respondent could receive confidential message (e.g. reply 

from  tax  authorities)  when  necessary.  In  this  sense,  an  address  which  is  used  by  several 

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members in the household (e.g. Jones_Family@internet.eu) can be taken into account while 

a general work address (e.g. info@companyname.com) will not be considered as a personal 

address. 

The personal e-mail address can be a personal e-mail address at work, a personal address 

offered  by  the  provider  of  the  home  Internet  connection  or  web-based  accounts  such  as 

Yahoo!, Hotmail or Gmail. 

C7: For which of the following activities did you use the Internet in the last 3 

months for private purposes?  

[ Scope: individuals who used the Internet in the last 3 months (i.e. 1st option in C1) ] 

[ Type: multiple answers allowed, i.e. Tick all that apply ] 

This  set  of  responses  refers  to  personal  or  private  use  only  (ie.  NOT  for  work  related 

purposes) but access could have been from anywhere – including place of work. 

Communication  

a) Sending / receiving e-mails 

It includes the use of e-mail for sending messages to friends or for getting information on 

goods/services.  

b) Telephoning over the Internet / videoconferencing 

Telephoning over the Internet is a relatively inexpensive method to communicate and is 

often the method used by companies offering reduced cost telephone charges. Users may 

not  be  aware  that  they  are  communicating  using  such  Internet-based  telephony,  Voice-

over-IP or VoIP.  

Next  to  VoIP,  peer-to-peer  telephony  is  becoming  more  important.  The  user  needs  to 

install a little program (such as Skype) for making free calls over the internet to anyone 

else  who  also  has  this  software.  Usually,  one  can  also  make  calls  to  normal  fixed  or 

mobile lines via a pre-paid credit. 

Videoconferencing includes audio and visual communication between two or more groups 

or  persons.  Videoconferencing  is  more  widely  used  by  organisations  and  replaces  the 

need for face to face meetings. It should be remembered that this question is concerned 

with private purpose only. 

c) Other (use of chat sites, etc.) 

Chat  sites  can  be  used  by  two  or  more  persons  for the  purpose  of  communication.  This 

communication is by written word (similar to email). The identity of the person ‘chatting’ 

does  not  have  to  be  divulged  to  other  users  (e.g.  a  username  can  be  created).  Users 

must  be  ‘logged-on’  to  a  chat  site  to  use  it.  Users  that  are  logged  on  to  a  specific  chat 

site can see all correspondence between all users on that site. Correspondence is updated 

in real time.  

This item also covers instant messaging. 

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Information search and on-line services 

d) Finding information about goods or services 

Using the Internet to seek for information about any household good, for example, films, 

music, video-games, books, e-learning material, clothes, electronic equipment computer 

software  or  services  for  example  banking,  financial  or  health  services.  It  should  not 

include  transactions,  e.g.  purchases  of  any  goods  or  services  (although  one  will  usually 

look up information on a good or services before actually purchasing it). 

e) Using services related to travel and accommodation 

Includes  using  the  Internet  for  ascertaining  information  or  to  purchase  goods  and 

services in relation to travel and accommodation, for example travel tickets, hotels or any 

other type of accommodation or web sites containing information for tourists.  

f) Listening to web radios / watching web television 

This covers both live streaming (real-time) and radio or TV ‘on demand’ (batch, i.e. the 

user  can  listen/watch  programs  later  on).  This  does  not  result  in  any  saving  of 

information to, for example, the respondents computer.  

g) Playing or downloading games, images or music 

This refers to actually downloading games, images for use or music for listening.  

h) Downloading software 

Includes downloading software either free of charge or under payment.  

i) Reading or downloading online newspapers / news magazines 

This should include all types of online newspapers and magazines either free of charge or 

under payment.  

j) Looking for a job or sending a job application 

Includes searching specific web sites for job ‘hunting’ or for sending an application for a 

job.  Sending  a  job  application  should  be  included  in  this  category  only  if  it  was  sent 

on-line.   

k) Seeking health-related information (e.g. injury, disease, nutrition, improving health, etc.) 

This  item  refers  to  Internet  use  for  health  related  activities.  The  scope  is  limited  to 

private purpose, professional use is not to be taken into account. Private should however 

not  be  limited  to  own  personal  use,  but  can  also  include  internet  use  for  health  related 

activities on behalf of other family members or friends. 

Includes general searches via a search engine (Google, Yahoo!, …) using keywords in one 

of  the  mentioned  fields.  This  item  also  includes  more  specific  searches  on  specialised 

websites such as the Ministry of Health, non-governmental bodies or interest groups. The 

respondent may have obtained the website’s address from a folder or an article. 

Although  not  yet  available  in  most  countries,  this  item  also  includes  activities  such  as 

making an appointment on-line with a practitioner, requesting a prescription on-line from 

a practitioner or seeking medical advice on-line from a practitioner. 

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Before the 2006 survey, Eurostat’s model questionnaire included three other items relating to 
e-health,  which  have  been  withdrawn  from  the  2006  model  for  practical  reasons  (difficult  to 
collect)  and  conceptual  reasons  (very  low  incidence  and  rather  a  measure  of  health  than  a 
measure of use of e-health) 
old)  Making  an  appointment  online  with  a  practitioner  covers  the  use  of  on-line  systems  to 
book a consultation with a doctor (general practitioner or specialist).  Such systems can 
be individual (for one specific doctor) but will rather be integrated systems depending on 
a hospital, a city administration or a group of doctors. 

old)  Requesting  a  prescription  online  from  a  practitioner  covers  the  use  of  on-line  systems 
where  patient  can  place  an  order  for  a  medication  prescription.  Again,  this  can  be  an 
individual  system  (organised  by  one  practitioner)  as  well  as  a  more  centralised  system 
where several practitioners are connected to. 

old)  Seeking  medical  advice  online  from  a  practitioner  concerns  getting  in  contact  with  a 
practitioner  via  electronic  way  (e-mail,  website  interface,  …)  in  order  to  get  medical 
advice. This can be a free as well as a commercial (paying) service. 

l) Other information search or on-line service 

This  item  is  supposed  to  close  the  block  on  Information  search  and  on-line  services  by 

ensuring that people who didn’t look for anything in particular (i.e. purposes covered by 

the above list of items), can nevertheless tick this item l) Other.  This can be relevant for 

Internet  users  who  only  do  general  browsing,  without  looking  for  a  particular  good, 

service or application (e.g. trying someone’s name in a search engine like Google). 

The  item  also  covers  goods/services/applications  that  are  relatively  new  (and  therefore 

not  yet  included  under  a  to  k),  sensitive  or  of  a  lower  relevance  (and  therefore  not 

mentioned as a separate entry). 

Selling of goods or services, banking 

m) Internet Banking 

This  includes  electronic  transactions  with  a  bank  for  payment,  transfers,  etc.  or  for 

looking up account information.  

Electronic  transactions  for  other  types  of  financial  services  are  not  covered  by  this 

category (purchase over the Internet of shares, financial services, insurances is covered 

by item i) of question E2, see Module E).  A simple information search on e.g. shares or 

financial  services  is  of  course  included  under  item  d)  Finding  information  on  goods  and 

services. 

n) Selling goods or services (e.g. via auctions) 

Selling goods or services on-line does not require an electronic payment transaction, i.e. 

the transaction or ‘deal’ is done on-line but the payment and/or delivery can  take place 

off-line.  

Putting  an  advertisement  on  a  website  to,  for  example,  sell  a  second-hand  bicycle  or  a 

spare ticket for an event, should not be included here as the transaction is in general not 

concluded  on-line  in  an  automatic  manner  (but  via  a  phone  call  or  informal  e-mail).  In 

this case, the individual could tick item l) Other information search or on-line service as 

he/she is making use of a website (e.g. a forum) to offer the product or service. 

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Training and education 

r) Formalised educational activities (school, university etc.) 

Includes  searching  for  information  relating  to  courses  being  taken  at  school,  college  or 

university whilst part of the education system. Post graduate courses at university should 

be included. 

s) Post educational courses 

Includes  leisure  courses  or  courses  taken  after  respondents  have  left  the  national 

education system.  

t) Other educational activities related specifically to employment opportunities 

This should include searching for information, applying for or attending distance-learning 

courses carried out on your own initiative or that of an employer that would contribute to 

employment opportunities, either at present or in the future.  

C8: In the last 3 months, did you receive unsolicited e-mails that you would 
regard as junk mail or spam and that you would prefer not to receive?  

[ Scope: individuals who used the Internet in the last 3 months (i.e. 1st option in C1) ] 

[ Type: one single answer needed, i.e. Tick only one ; binary (Yes/No) ] 

The  question  takes  into  consideration  the  respondent’s  subjective  perception.  In  other 

words,  one  respondent  can  see  a  certain  type  of  messages  as  spam  while  another 

respondents sees the same type of messages as an interesting offer or opportunity.  

Messages coming from mailing lists the individual has subscribed to, cannot be considered to 

be unsolicited, unless the individual has – vainly – tried to unsubscribe. 

old: Is the device you use to access the internet at home protected by: 

[ Scope: individuals who used the Internet in the last 3 months (i.e. 1st option in C1) and who 

used it at home (i.e. C3a = yes) ] 

If more than one device is used – any or all of them can be considered. 

a) a virus checking program? 

Software  that detects  a virus  on  the  computer.  The  software  will  alert  the  user  and  then  clean  the 
virus or move the infected files to the Quarantine section of the computer. 

b) a hardware or software firewall? 

Firewalls protect any server from damage by those who log onto it. It could be incorporated into the 
computer or could be a software-based protection. 

c) don’t know 

A specific “don’t know” category is included as the respondent may not be personally responsible for 
the security measures on the device(s) being used to access the Internet and so may not know what 
measures have been taken. 

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old: Has it been installed or updated in the last 3 months (incl. automatic updating?) 

[ Scope: individuals who used the Internet in the last 3 months (i.e. 1st option in C1) and who 

used it at home (i.e. C3a = yes) and who answered a and/or b to “Is the device you 
use to access the internet at home protected by a) virus checking program b) 
hardware or sofware firewall” ] 

Some security software are automatically updated on access to the Internet. Respondents may or may 

not know when this takes place but may be more aware that this takes place. 

old: In the last 3 months, have you used online authentication on the Internet for private use, 

such as password, PIN or digital signature? 

[ Scope: individuals who used the Internet in the last 3 months (i.e. 1st option in C1) ] 

A password needs to be typed in to gain access to the computer and/or Internet. 

A  password,  PIN  or  a  digital  signature  can  be  defined  as  a  word  or  a  combination  of  letters  and/or 

numbers to be typed when switching on a computer or opening an Internet software that would allow a 

person to proceed (pass). In this specific situation it would allow to use the computer/Internet. 

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II.1.6.4  MODULE D: E-GOVERNMENT 

(cid:4) Statistical unit: individuals 

This  Module  on  e-government  goes  beyond  the  more  general  indicators  on  Internet  usage  by 

households  and  individuals  and  tries  to  get  a  more  complete  picture  of  the  state  of  affairs  of 

e-government.  The  questions  ask  for  the  respondent’s  interest  in  using  e-government  (D1), 

followed  by  questions  on  barriers  to  using  this  facility  (D2)  or  e-government  applications  the 

respondent is interested in and whether he/she has already used them (D3). While question D3 

deals with different field of public services or administration, D4 tries to collect information on the 

level of interaction.  

As this is rather an ad-hoc module, Module D will not necessarily be included every year. 

As the competence of the government or the ‘public authorities’ differs strongly from one country 

to  another,  the  concept  has  been  kept  as  wide  as  possible:  public  services  and  administration. 

While ‘administration’ refers to obligation and rights one has as a citizen (the so-called red tape), 

public services can refer to non-administrative tasks or competences of government bodies, e.g. 

offering the public library’s catalogue on-line.  

The  service  providers  can  be  at  national  or  regional  level,  but  also  at  the  level  of  cities  or 

municipalities.  The  service  providers  can  even  be  ‘semi-governmental’,  e.g.  public  libraries, 

hospitals, universities, etc. 

D1: Would you be interested to use the Internet to replace some of your 

personal contacts with or visits to public services or administrations? 

[ Scope: individuals who used the Internet in the last 3 months, i.e. 1st option (Within the last 

3 months) in C1 ] 

[ Type: one single answer needed, i.e. Tick only one ; filter question ] 

This ‘opening’ question evaluates the individual’s interest in e-government applications and 

filters the respondent to D2 or D3.  

The answering options should be self-explanatory. 

D2: What are the reasons for not using the Internet for dealing with public 

services or administrations? 

[ Scope: individuals who used the Internet in the last 3 months, i.e. 1st option (Within the last 

3 months) in C1 and who have not yet used Internet to deal with public services or 
administrations, i.e. 2nd (Yes, I would be interested but I am currently not a user) or 
3rd option (No) in D1] 

[ Type: multiple answers allowed, i.e. Tick all that apply ; filter question for D3 ] 

This question is presented to respondents who have not yet used e-government, whether or 

not they are interested in using it. 

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a) The services I need are not available on-line or difficult to find 

This item covers cases where the needed application has not yet been developed by the 

competent  authority,  or  where  the  respondent  is  not  aware  of  its  existence  or  was  not 

able to browse to the needed application. 

b) Personal contact is missing 

Covers  cases  where  the  respondent  feels  safer  when  dealing  with  a  person  instead  of 

submitting  request  of  documents  ‘to  a  machine’  or  where  the  respondent  just  prefers 

some human touch when interacting with the government. 

c) Immediate response is missing 

When  dealing  with  administrative  matters  in  person,  one  usually  (?)  gets  an  immediate 

response.  The  respondent  may  prefer  this  method  to  e-government  where  a  request  is 

submitted  and  the  respondent  has  to  wait  a  few  hours  or  days  before  feedback  is 

received. 

d) Concerned about protection and security of my data 

The  respondent  can  be  concerned  abour  secure  storage  of  his  data  (although  the  same 

information  may  be  stored  in  the  same  way  after  having  dealt  with  a  matter  in  the 

‘traditional  way’)  or  the  respondent  may  fear  that,  for  instance,  a  hacker  will  intercept 

confidential data. 

e) Additional costs 

Although  less  relevant  with  the  growing  penetration  of  fixed  cost  connections  over 

broadband, the respondent may be concerned about the additional dial-up costs when an 

on-line declaration takes a long time.  

In  principle,  this  does  not  concern  additional  equipment  costs  as  this  Module  is  only 

directed to individuals who already use the  Internet, but it is possible that an individual 

who does not access the Internet at home prefers not to use e-government at e.g. his or 

her  place  of  work.    Specific  requirements  –  e.g.  a  card  reader  for  electronic  ID  cards  – 

could also involve additional equipment costs. 

f) Using the Internet for contacts with public administration is too complex 

For  some  issues,  one  only  has  to  deal  with  the  government  once  a  year.  Certain 

respondents may prefer to go on filling in the paper form (which takes e.g. 30 minutes) 

instead of investing time in learning how to use the electronic application. 

This item also covers a possible lack of skills to use advanced Internet applications.  

g) None of the above, but other 

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D3: With which of the following matters are you already dealing via Internet 

or would you like to deal via Internet? 

[ Scope: individuals who used the Internet in the last 3 months, i.e. 1st option (Within the last 
3 months) in C1 and who show interest in using Internet to deal with public services 
or administrations, i.e. 1st (Yes, I already use this possibility) or 2nd (Yes, I would be 
interested but I am currently not a user) option in D1 ] 

[ Type: one single answer needed for each of the 12 items, i.e. Tick only one box per line ] 

The  respondents  who  showed  interest  in  e-government  are  now  asked  for  the  types  of 

services they would like to deal with on-line. They are presented a list of public services. For 

each of the services, they are invited to say whether they already use this facility, whether 

they would be interested to use it, or whether they would not use it at all. 

The list is based on the list of 12 basic public services used for the e-government supply side 

indicator  of  Directorate  General  Information  Society  and  Media  (DG  INFSO).  Although,  the 

relevance of certain items may be different from one country to another (depending on the 

availability  of  the  on-line  service),  the  fact  that  respondents  can  express  their  interest  in 

having  an  Internet  application  can  give  an  indication  of  the  potential  or  the  desirability  of 

having the particular service on-line. In cases where one of the services is not relevant (e.g. 

car  registration  not  done  by  the  individual  but  by  third  parties  or  no  obligation  to  officially 

inform  the  authorities  of  a  change  of  address),  the  country  concerned  can  leave  out  this 

item for their national survey. 

Where  a  certain  service  is  currently  not  relevant  for  the  respondent  (e.g.  no  need  for  job 

searches  because  the  respondent  has  a  stable  job  or  is  retired,  or  no  need  for  enrolling  in 

higher education because the respondent already graduated from university), the option No 

I would not do this on-line can be ticked. However, the respondent may want to express his 

possible  future  interest  and  tick Yes,  I  would  like  to  do  this  on-line  (e.g.  the  respondent  is 

currently not concerned by job searches, if he/she would need to look for a new job, the job 

office’s on-line application would be a preferred channel).  

The  12  items  (basic  public  services)  should  be  self-explanatory,  but  country-specific 

examples  can  of  course  further  clarify  the  basic  public  services  for  the  respondent.  In  the 

questionnaire,  some  examples  have  been  added  between  brackets  to  clarify  the  ‘scope’  of 

the services listed.  

a) Income taxes (declaration, notification of assessment) 

b) Job search services by labour offices 

c) Social security contributions (unemployment benefits, family allowances, medical costs, 

student grants) 

d) Personal documents (passport and driver's licence) 

e) Car registration (new, used and imported cars) 

f) Application for building permission  

g) Declaration to the police (e.g. in case of theft) 

h) Public libraries (availability of catalogues, search tools) 

i) Certificates (birth, marriage): request and delivery 

j) Enrolment in higher education or university 

k) Announcement of moving (change of address)  

l) Health related services (e.g. interactive advice on the availability of services in different 

hospitals; appointments for hospitals) 

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D4: For which of the following activities relating to interaction with public 

services or administration did you use the Internet in the last 3 months 
for private purposes? 

[ Scope: individuals who used the Internet in the last 3 months, i.e. 1st option (Within the last 

3 months) in C1 ] 

[ Type: multiple answers allowed, i.e. Tick all that apply ] 

a) Obtaining information from public authorities’ websites 

Includes  searching  to  obtain  any  type  of  information  from  public  authority  web  sites. 

Public  authorities’  web  sites  include  local  or  central  government  offering  information  or 

services. It would be helpful to provide a list of local/central government web sites in the 

format  of  a  showcard  to  facilitate  respondents  to  recall  public  authority  web  sites  that 

they have used. For example respondents may not realise some public information sites 

are  run  by  public  authorities,  e.g.  a  meteorological  office  offering  weather  forecast 

services.  

b) Downloading official forms 

Includes  downloading  official  forms  for  any  purpose  of  use  (e.g.  for  information  or  for 

requesting a service). The downloaded files could be in formats such as PDF or Microsoft 

Word. 

c) Sending in filled forms 

Includes  filled  in  forms  sent  via  internet  only.  Forms  downloaded,  printed,  filled  in  and 

sent by post should not be included in this category. 

This question makes use  of the conceptual  framework for the levels of interaction between 

enterprises  or  citizens  and  public  authorities,  used  by  DG  INFSO.    The  framework  of  four 

levels  of  interaction  was  developed  to  measure  the  level  of  sophistication  offered  by 

websites  supplying  basic  public  services.  That  way,  one  can  distinguish  websites  that  only 

provide  information  on  a  public  service  (1st  level)  from  websites  that  allow  to  download 

forms (2nd level) or to submit information in an online form (3rd level) up to websites that  

allow to completely treat the public service or administrative obligation without the need for 

any  paperwork  whatsoever  (4th  level  of  sophistication).  For  the  time  being,  only  the  first 

three levels are considered in the household survey. 

It is expected or logical that a particular website that reaches a certain level of sophistication 

also  include  all  lower  levels,  for  instance  a  website  offering  the  possibility  to  download  a 

form  should  certainly  provide  information  on  the  particular  public  service  that  form  would 

refer to. The concept of the four levels of sophistication was adopted for the measurement of 

the usage of e-government by enterprises (and the 3 first levels for citizens). However, the 

interpretation  of  the  results  will  have  to  differ  slightly  from  the  interpretation  done  for  the 

sophistication  of  the  public  websites.  At  usage  level,  it  is  natural  to  assume  that  a  user 

(enterprise  or  citizen),  before  knowing  which  form  to  download  (2nd  level),  will  obtain 

information  on  the  public  service  he  is  interested  in  (1st  level),  but  he/she  will  only  do  it 

once  or  twice  and  not  every  time  it  downloads  the  form.  Therefore,  when  measuring  the 

usage  every  year,  it  is  perfectly  possible  that  there  are  users  who  have  downloaded  forms 

with  obtaining  information  in  those  cases  in  which  the  user  already  had  all  the  information 

he needed (although not very probable, as users may well constantly search for information 

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on several different issues). In this sense, it is possible that the respondents answers Yes to 

item  b  without  having  answered  Yes  to  a  (or  Yes  to  c  without  having  answered  Yes  to  a 

and/or b). 

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II.1.6.5  MODULE E: INTERNET COMMERCE DETAILS: ACTIVITIES AND BARRIERS 

(cid:4) Statistical unit: individuals 

E1: When did you most recently buy or order goods or services for private use 

over the Internet (excluding manually typed e-mails)? 

[ Scope: individuals who already used Internet, i.e. 1st, 2nd or 3rd option in C1 ] 

[ Type: one single answer needed, i.e. Tick only one ; filter question ] 

Purchases of financial investments, such as shares, should be included in this question. The 

ordering  of  goods  and  services  should  also 

include  confirmed  reservation 

for 

accommodation,  participation  in  lotteries  and  betting  and  obtaining  information  services 

from the Internet that are directly paid for.  

This question also applies to purchases that are made via Internet auctions, such as “eBay”.  

Only individuals that actually placed the order over the Internet should answer this question, 

even if the order was carried out on somebody else`s behalf. Therefore, individuals that had 

other people ordering for them should not be included. For the time of the transaction, the 

date  when  the  goods  or  services  were  ordered  is  relevant,  not  the  date  of  delivery  or 

payment.  

Orders  via  manually  written  e-mails  should  -  according  to  the  EUROSTAT  definition  of  e-

commerce in enterprises - not be included.  

Delivery  via  electronic  means  or  payment  via  electronic  means  is  not  a  requirement  for  an 

order via Internet.  

Goods  and  services  that  were  obtained  via  the  Internet  for  free  should  be  excluded.  Such 

goods  are  e.g.  free  software  (“freeware”),  reservations  in  restaurants  or  any  kind  of 

information obtained via Internet for free (such as downloading pdf-files). Software that can 

be  downloaded  from  the  Internet  and  used  for  free  for  a  certain  period  but  loses 

functionality after this time should only be counted as a purchase when the product is finally 

paid for.  

Orders that are placed for professional use should be excluded.  

E2: What types of goods and services did you order over the Internet for 

private use in the last 12 months? 

[ Scope: individuals who already used Internet (1, 2 or 3 in C1) and who bought/ordered 

over the Internet in the last 12 months, i.e. 1st (Within the last 3 months) or 2nd option 
(Between 3 months and a year ago) in E1 ] 

[ Type: multiple answers allowed, i.e. Tick all that apply ; filter question for E2b ] 

a) Foods / Groceries 

Groceries include necessities of "daily  use" such as  sanitary products, tobacco products, 

cosmetics,  pharmaceuticals  or  flowers.  This  category  also  includes  drinks.  Newspapers 

should be excluded from this category. 

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b) Household goods 

Includes  e.g.  furniture,  toys,  washing  machines,  micro-wave  ovens,  dish  washers, 

vehicles, gardening equipment, plants, antiques, art, tools, collectibles, etc. 

c) Films, music 

Includes DVDs, CDs, Video and music cassettes and similar devices that can store films, 

music or spoken word. Delivery of films and music on-line via files is also included. Only 

goods that are paid for should be mentioned here. 

d) Books / Magazines / Newspapers / E-Learning materials 

Subscription  to  newsletters  and  alike  –  if  not  free  of  charge  –  also  belong  to  this 

category. E-Learning materials are documents which are used for multi-media learning in 

digital form, but also comprise CD-Roms that are used for educational purposes.  

e) Clothes, sports goods 

Includes shoes, textiles, accessories.   

f) Computer software and upgrades (incl. computer and video games) 

Includes video games and other computer software on any media. 

g) Computer hardware 

Includes any accessories to computer hardware, such as modem and printer.  

h) Electronic equipment (incl. cameras) 

Includes  e.g.  mobile  phones,  cameras,  radios,  TVs,  stereos,  DVD  players,  video 

recorders. 

i) Share purchases / Financial Services / Insurance 

Includes  the  purchase  of  securities  of  all  kinds.  Transfers  from  account  to  account  and 

similar services via Internet where no purchase is carried out are not included.  

j) Travel and holiday accommodation 

Includes  e.g.  hotel  reservation,  travel  tickets  and  vehicle  hire.  Only  bookings  of 

accommodation and travel tickets should be included. The mere search for those services 

and booking inquiries without legal binding should be excluded.  

k) Tickets for events 

Includes tickets for concerts, cinema, sport events, theatre, and alike. 

l) Lotteries or betting 

m) Other  

Goods and services not mentioned above. Could include e.g. jewellery, fan articles, and a 

number of services ordered via Internet, e.g. information services (from databases). 

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E2b: Were any of the products that you ordered over the Internet downloaded 

or accessed from websites rather than delivered by post etc.? 

[ Scope: individuals who already used Internet (1, 2 or 3 in C1) and who bought/ordered 

over the Internet in the last 12 months (1 or 2 in E1) and who bought films/music, 
books/magazines/newspaper/e-learning material or computer software over the 
Internet (i.e. option c, d or f in E2) ] 

[ Type: multiple answers allowed, i.e. Tick all that apply ] 

Digitally delivered products include those products which can be delivered on physical media 

(such as CD or tape) but also over the Internet in digitised form as a computer file (and thus 

independently of those physical media).  

a) Films, music 

Delivery of films and music on-line via files (e.g. a video, an MP3 file or a CD). 

b) (Electronic) books , magazines, newspapers, e-learning materials 

c) Computer software (incl. computer and video games and software upgrades) 

E3: In the last 12 months, did you buy or order goods over the Internet from: 

[ Scope: individuals who already used Internet (1, 2 or 3 in C1) and who bought/ordered 

over the Internet in the last 12 months, i.e. 1st or 2nd option in E1 ] 

[ Type: multiple answers allowed, i.e. Tick all that apply ] 

a) Retailers known from outside the Internet (physical store, catalogues) 

b) Retailers known from the Internet or found on the Internet 

If the search on the Internet for a product leads to a web site of a company that was already 

known to the buyer from outside the Internet, then a) should be ticked. A typical case for a) 

might  be  if  a  customer  buys  now  via  Internet  from  a  direct  mail  company  from  which  he 

used to order via normal mail or phone before.  

Category b) applies to retailers from which the customer knows that they are selling only via 

Internet or to retailers which were found when surfing on the Internet and were not known 

to  the  customer  before.  These  retailers  can  also  sell  via  a  physical  store.  If  the  individual 

searches the Internet for a specific product and buys from a company that he has not known 

of, category b) should be chosen.  

Both categories can be ticked by the same individual.  

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133  

E4: In the last 12 months, did you encounter any problems when 

buying/ordering goods or services over the Internet? 

[ Scope: individuals who already used Internet (1, 2 or 3 in C1) and who bought/ordered 

over the Internet in the last 12 months, i.e. 1st or 2nd option in E1 ] 

[ Type: one single answer needed, i.e. Tick only one ; binary (Yes/No) ; filter question for E5 ] 

This question serves as a filter question for the following question, E5. 

E5: What problems have you encountered when buying/ordering goods or 

services over the Internet in the last 12 months?  

[ Scope: individuals who already used Internet (1, 2 or 3 in C1) and who bought/ordered 

over the Internet in the last 12 months, i.e. 1st or 2nd option in E1 and who 
encountered problems when buying/ordering over the Internet, i.e. E4 = Yes ] 

[ Type: multiple answers allowed, i.e. Tick all that apply ] 

a) Difficulties in finding information concerning guarantees 

This problem applies when the potential buyer cannot receive information on guarantees 

on  the  web  site  of  the  seller.  It  might  especially  affect  orders  from  abroad  when 

uncertainties about the legal framework in the other country arise. 

b) Speed of delivery longer than indicated 

c) Final costs higher than indicated (e.g. higher delivery costs, credit card transaction fee) 

E.g.  delivery  costs  that  accrue  to  the  buyer  might  not  be  mentioned  on  the  seller’s 

website. 

d) Wrong or damaged goods delivered or no goods received at all 

e) Lack of security of payments 

If  the  customer  doubts  that  a  certain  website  is  meeting  security  standards  concerning 

the disclosure of payment card details etc. and therefore is put off from ordering, he may 

have experienced “lack of trust in security of payments” without actually being a victim of 

fraud  etc.  It  is  not  necessarily  required  that  the  buyer  has  already  encountered  such 

problems. The concern about the security of the payments is enough.  

f) Complaints and redress were difficult or no satisfactory response received after complaint 

This  problem  arises  when  the  buyer  cannot  find  sufficient  information  on  the  website 

about contact channels with the selling enterprise. It also applies if a person that handles 

the complaint cannot be found or only with difficulties within the selling enterprise. 

g) Others 

Those  problems  might  include:  a  general  lack  of  information  about  the  good  or  the 

producer (no link to the web site of the producer, no information about the country where 

the good is bought) or different prices in different countries for the same product.   

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E6: What were the reasons for not buying/ordering any goods or services for 

your own private use in the last 12 months? 

[ Scope: individuals who already used Internet (1, 2 or 3 in C1) and who didn’t buy/order 
over the Internet in the last 12 months, i.e. 3rd (More than a year ago) or 4th option 
(Never bought or ordered) in E1 ] 

[ Type: multiple answers allowed, i.e. Tick all that apply ] 

a) Have no need 

This category applies to people that never thought of buying via Internet or did not that 

think  of  in  the  last  12  months  before  the  survey,  but  do  not  have  a  principle  objection 

towards this kind of purchasing.  

b) Prefer to shop in person, like to see product, loyalty to shops, force of habit 

c) Lack of skills 

This category applies if the knowledge of the user about Internet is not sufficient to order 

goods or services.  

d) Delivery of goods ordered over the Internet is a problem 

E.g.  takes  too  long  (too  long  delivery  times)  or  is  logistically  difficult  (problematic  to 

receive  ordered  goods  at  home  ;  products  might  be  delivered  via  carriers  that  do  not 

have good facilities to store the goods when the buyer is not at home).   

e) Security or privacy concerns  

The  first  refers  to  e.g.  worries  about  giving  credit  card  details  over  the  Internet.  The 

latter refers to e.g. worries about giving personal details over the Internet. 

f) Trust concerns about receiving or returning goods, complaint/redress concerns 

g) Don’t have a payment card allowing to pay over the Internet 

Very often a credit or debit card is required for Internet purchases.   

h) Speed of the Internet connection is too slow 

Due to sophisticated applications on the web site of the seller the process of ordering via 

Internet itself can be time-consuming. Technical restraints might therefore be an obstacle 

for purchasing.  

i) Others 

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135  

II.1.6.6  MODULE F: E-SKILLS 

(cid:4) Statistical unit: individuals 

F1:  When did you last take a training course (of at least 3 hours) on any 

aspect of computer use?   

[ Scope: individuals who already used a computer, i.e. 1st, 2nd or 3rd option in B1 ] 

[ Type: one single answer needed, i.e. Tick only one ] 

The  emphasis  is  on  formal  training  via  courses  (education)  and  excludes  informal  training 

such as help from colleagues or friends/relatives and learning-by-doing. All kinds of courses 

which can relate to computer use have to be included, e.g. word processing or spreadsheet 

courses, programming, web-design and so forth.    

F2:  Which of the following computer related activities have you already 

carried out? 

[ Scope: individuals who already used a computer, i.e. 1st, 2nd or 3rd option in B1 ] 

[ Type: multiple answers allowed, i.e. Tick all that apply ; indirect filter question for F4 ] 

The purpose of this question is to assess the skills level relating to general computer use of 

the  respondents.  Although  the  items  are  more  or  less  ordened  from  less  complex  to  more 

complex,  a  respondent  doesn’t  necessarily  need  to have  ticked  e.g.  item  a,  b  and  c  before 

item d can be ticked. In other words, there is no strict ordinality in the items presented. 

a) Copying or moving a file or folder 

b) Using copy and paste tools to duplicate or move information within a document  

E.g. in a Word document. 

c) Using basic arithmetic formulas in a spreadsheet  

E.g. in an Excel sheet. 

d) Compressing files 

This  activity  applies  when  the  respondent  has  compressed  a  file  by  using  Winzip  or 

related programs to limit the size of large files. 

e) Connecting and installing new devices, e.g. a printer or a modem 

This  activity  covers  both  the  hardware  and  the  software  side  of  the  operation,  even  if 

both  can  be  relatively  straightforward  nowadays  because  of  plug-and-play  USB 

connections. 

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136  

f) Writing a computer program using a specialised programming language 

Specialised  programming  language  refers  to  high-level  computer  languages  such  as 

BASIC,  Pascal  or  for  instance  SAS  programming,  which  might  only  be  familiar  to 

programmers, system analysts and so forth.   

old) Using a mouse (or other pointing device) to open programs 

(item from the 2005 survey, no longer included for the 2006 survey) 

It  applies  when  the  respondent  opens  an  Internet  browser,  a  word  processor  or  any  kind  of 

program.  Although  this  item  may  sound  obvious,  it  can  be  considered  as  a  ‘first  test’  of  the 

presence  of  any  e-skills.  Moreover,  quite  some  people  use  e.g.  Internet  Explorer  after  having 

asked  another  household  member  to  start  the  program  for  them  (the  item  is  not  restricted  to 

simply using the mouse to move the cursor). 

F3:  Which of the following Internet related activities have you already carried 

out? 

[ Scope: individuals who already used Internet, i.e. 1st, 2nd or 3rd option in C1 ] 

[ Type: multiple answers allowed, i.e. Tick all that apply ; indirect filter question for F4 ] 

The  purpose  of  this  question  is  to  assess  the  skills  level  of  the  respondents  relating  to 

Internet  use.  Although  the  items  are  more  or  less  ordened  from  less  complex  to  more 

complex,  a  respondent  doesn’t  necessarily  need  to have  ticked  e.g.  item  a,  b  and  c  before 

item d can be ticked. In other words, there is no strict ordinality in the items presented. 

a) Using a search engine to find information 

The question refers to search engines such as Yahoo, Google etc. 

b) Sending e-mail with attached files 

Attached files can be anything from a document, a video or pictures etc. 

c) Posting messages to chatrooms, newsgroups or any online discussion forum 

A  chatroom  can  be  defined  as  a  virtual  room,  where  participants  have  a  chat  session. 

Newsgroups are on-line discussion groups covering all kinds of interest. The member of a 

newsgroup view and post messages via a news server on the Internet. 

d) Using the Internet to make telephone calls 

e) Using peer-to-peer file sharing for exchanging movies, music etc. 

Peer-to-peer  (P2P)  refers  to  a  network  where  the  communication/information  is 

distributed to a wide variety of computers rather than residing on one central server. In 

this  network  each  computer  has  equal  capabilities  which  differ  from  a  traditional 

client/server network. P2P is more and more used for sharing of files, movies and music.   

f) Creating a web page 

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F4:  Where or how did you obtain the skills to carry out these activities? 

[ Scope: individuals who reported at least one activity under F2(a-f) or F3(a-f) ] 

[ Type: multiple answers allowed, i.e. Tick all that apply ] 

Items  a)  through  c)  refer  to  skills  obtained  via  formal  training  courses,  while  items  d) 

through f) refer to more informal ways of acquiring e-skills. 

a) Formalised educational institution (school, college, university) 

b) Training courses in adult education center 

Refers to courses taken by own initiative, not the employer. 

c) Vocational training courses 

Apart from b), this refers to skills obtained on demand from the employer. 

d) Self-study using books, cd-roms, etc. 

e) Self-study in the sense of learning-by-doing 

f) Informal assistance from colleagues, relatives, friends 

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II.1.6.7  MODULE G: SOCIO-DEMOGRAPHIC BACKGROUND VARIABLES 

[ Scope: all households / all individuals, excepting for G5 Occupation ] 

[ Type: G2, G3, G4, G6, G7: one single answer needed, i.e. Tick only one ; G1, G8, G9, G10: 

quantitative ; G5: open question, i.e. description needed (or coded by the interviewer) ] 

This  module  does  not  focus  on  ICT-related  study  variables,  but  on  background  variables  to  put 

the  results  on  the  study  variables  in  perspective.  These  background  variables  should  enable  to 

relate the outcome of the surveys to the sociologic, demographic and economical background of 

the observed statistical units.   

In  the  model  questionnaire,  this  module  is  inserted  at  the  end  of  the  survey.  This  was  an 

arbitrary  choice,  the  module  can  also  be  the  starting  point  for  the  survey  (in  most  cases,  the 

information will partly be available from other sources, e.g. registers or the survey the ICT usage 

questions are embedded in). 

The  questions  on  age  (G1),  gender  (G2),  educational  attainment  (G3),  employment  situation 

(G4) and occupation (G5) are to be answered by the individual(s) who is (are) selected within the 

household.  

The questions on geographical location (G6) and type of locality (G7) refer to the household, but 

the answer at household level should coincide with the individual level anyway as the individuals 

are  part  of  the  household.  Usually  these  two  variables  do  not  need  to  be  directed  to  the 

respondents as the NSI’s can derive the information on the basis of the household’s address. 

The  questions  on  the  household  composition  (G8,  G9)  and  household  income  (G10)  of  course 

refer to the household level. 

G1: Age 

The data transmitted to Eurostat is broken down by age group. Whether the year of birth or 

date  of  birth  or  the  age  is  collected,  is  relatively  unimportant.  In  a  postal  survey,  the  NSI 

could simply ask the respondent to tick the appropriate age group. However, in most cases, 

this information will be available from the sampling frame (e.g. the population register).  

Whether the reference point is the age during the interview or rather the age at the during 

the  reference  period,  is  not  expected  to  have  a  significant  impact  on  the  results  and 

comparability. 

G2: Gender 

Self-explanatory. 

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139  

 
G3:  Educational level 

In order to obtain comparable information for the different countries, the levels of education 

are linked to the UNESCO's International Standard Classification of Education (ISCED 1997).   

A  detailed  description  of  the  classification  is  available  from  the  UNESCO  Institute  for 

Statistics’ website (http://www.uis.unesco.org/ev.php?ID=3813_201&ID2=DO_TOPIC), but a short 

summary is presented below. 

Conversion tables matching the national educational levels to the ISCED codes are available 

from 

the  CIRCA  site 

(information 

relating 

to 

the  school  year  1999-2000): 

http://forum.europa.eu.int/Public/irc/dsis/edtcs/library?l=/public/unesco_collection/ 

programmes_isced97/school_1999_2000&vm=det 

For  the  purpose  of  this  survey,  information  on  the  educational  level  has  to  be  transmitted 

following a regrouping in three broad categories: 
▪  No formal education completed, primary or lower secondary education (corresponding to 

ISCED 0, 1 or 2); 

▪  Upper secondary education (corresponding to ISCED 3 or 4); 
▪  Tertiary education (corresponding to ISCED 5 or 6). 

Only the highest level reached is required (not all the levels frequented). Only a completed 

level may be considered; 'completed' in this context is taken to imply successful termination, 

normally accompanied by an appropriate qualification. 

Pre-primary education (ISCED level 0) 

Programmes  at  level  0,  (pre-primary)  defined  as  the  initial  stage  of  organised  instruction  are 
designed  primarily  to  introduce  very  young  children  to  a  school-type  environment,  i.e.  to 
provide a bridge between the home and a school-based atmosphere. Upon completion of these 
programmes, children continue their education at level 1 (primary education). 

Primary education or first stage of basic education (ISCED level 1) 

Programmes  at  level  1  are  normally  designed  on  a  unit  or  project  basis  to  give  students  a 
sound  basic  education  in  reading,  writing  and  mathematics  along  with  an  elementary 
understanding of other subjects such as history, geography, natural science, social science, art 
and music. The core at this level consists of education provided for children, the customary or 
legal  age  of entrance  being  not  younger  than five  years  or  older  than  seven years.  This  level 
covers in principle six years of full-time schooling. 

 Lower secondary or second stage of basic education (ISCED level 2) 

In many, if not most countries, the educational aim is to lay the foundation for lifelong learning 
and  human  development  on  which  countries  may  expand,  systematically,  further  educational 
opportunities.  The  programmes  at  this  level  are  usually  on  a  more  subject-oriented  pattern 
using  more  specialized  teachers  and  more  often  several  teachers  conducting  classes  in  their 
field of specialization. The full implementation of basic skills occurs at this level.  

Upper secondary education (ISCED level 3) 

The  educational  programmes included  at  this  level  typically  require  the  completion of  some  9 
years of full-time education (since the beginning of level 1) for admission or a combination of 
education and vocational or technical experience and with as minimum entrance requirements 
the  completion  of  level  2  or  demonstrable  ability  to  handle  programmes  at  this  level.  The 
entrance  age  to  this  level  is  typically  15  or  16  years.  More  specialization  may be  observed  at 
this  level  than  at  ISCED  level  2  and  often  teachers  need  to  be  more  qualified  or  specialized 
than for ISCED level 2.  The programmes can be general, technical or labour-market oriented. 

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140  

 
Post-secondary non-tertiary education (ISCED level 4) 

This  item  captures  programmes  that  straddle  the  boundary  between  upper-secondary  and 
post-secondary education  from  an  international point of  view, even  though  they  might clearly 
be considered as upper-secondary or post-secondary programmes in a national context. ISCED 
level  4  programmes  can,  considering  their  content,  not  be  regarded  as  tertiary  programmes. 
They  are  often  not  significantly  more  advanced  than  programmes  at  ISCED  level  3  but  they 
serve  to  broaden  the knowledge of  participants who  have  already  completed  a  programme  at 
level 3. Typical examples are programmes designed to prepare students for studies at level 5 
who, although having completed ISCED level 3, did not follow a curriculum which would allow 
entry to level 5. 

First stage of tertiary education (ISCED level 5) 

This level consists of tertiary programmes having an educational content more advanced than 
those  offered  at  levels  3  and  4.  Entry  to  these  programmes  normally  requires  the  successful 
completion of ISCED level 3 (esp. general or technical programmes) or a similar qualification at 
ISCED level 4 (esp. those preparing for entry to ISCED 5).  This level includes all the research 
programmes which are not part of a doctorate, such as any type of Master's degree. 

The  programmes  can  be of  a  general  nature  -  i.e.  largely theoretically  based  and  intended  to 
provide  sufficient  qualifications  for  gaining  entry  into  advanced  research  programmes  and 
professions  with  high  skills  requirements  -  or  more  technically  oriented  -  i.e.  practically 
oriented/occupationally  specific  and  mainly  designed  for  participants  to  acquire  the  practical 
skills  and  know-how  needed  for  employment  in  a  particular  occupation  or  trade  or  class  of 
occupations or trades (the successful completion of which usually provides the participants with 
a labour-market relevant qualification). 

Second stage of tertiary education (ISCED level 6) 

This level is reserved for tertiary programmes which lead to the award of an advanced research 
qualification,  such  as  a  doctorate.  The  programmes  are  therefore  devoted  to  advanced  study 
and  original  research  and  are  not  based  on  course-work  only.  They  typically  require  the 
submission  of  a  thesis  or  dissertation  of  publishable  quality  which  is  the  product  of  original 
research  and  represents  a  significant  contribution  to  knowledge.    It  prepares  graduates  for 
faculty posts in institutions offering ISCED 5 (general) programmes, as well as research posts 
in government, industry, etc. 

G4:  Employment situation 

Unlike the Labour Force Survey, this survey doesn’t contain a number of detailed questions 

to assess an individual’s employment situation or labour status. This variable is more related 

to the LFS question on the Main labour status where the respondent gives a self-perception 

regarding his/her activity status.  

The explanatory notes below should help the respondent and/or interviewer in indicating the 

appropriate  employment  situation.  The  concepts  and  definitions  used  are  based  on  those 

used  in  Eurostat’s  labour  market  statistics  and  recommended  by  the  International  Labour 

Organisation (ILO). 

Employee 

Employees  are  defined  as  persons  who  work,  by  agreement,  for  a  public  or  private  employer 
and  who  receive  compensation  in  the  form  of  wages,  salaries,  fees,  gratuities,  payment  by 
results or payment in kind; irrespective of the number or hours worked (full time or part time) 
and the duration of the contract (fixed or indefinite). 
This  category  includes  non-conscripted  members of  the  armed forces,  apprentices  or  trainees 
receiving remuneration, seasonal workers and persons on strike. 

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141  

This  category  does  not  include  voluntary  workers  and  family  workers  who  don’t  receive  a 
regular monetary wage. 

Persons who are simultaneously working in their own professional practice and for a public or 
private  employer  (e.g.  doctors  with  their  own  cabinet  and  working  in  an  hospital)  should  be 
classified according to the status where they work a more important number of hours. 

Self-employed 

Self-employed  persons,  with  or  without  employees,  are  defined  as  persons  who  work  in  their 
own or joinly-owned business, professional practice or farm for the purpose of earning a profit. 
This  category  includes  own-account  workers,  family  workers  who  don’t  receive  a  regular 
monetary  wage,  freelancers  (although  a  person  who  has  been  regularly  retained  by  a  single 
employer for some time may also be regarded as an employee) and persons who look after one 
or  more  children  that  are  not  their  own  on  a  private  basis  and  receiving  a  payment  for  this 
service. 

Persons who are simultaneously working in their own professional practice and for a public or 
private  employer  (e.g.  doctors  with  their  own  cabinet  and  working  in  an  hospital)  should  be 
classified according to the status where they work a more important number of hours. 

Unemployed 

In  accordance  with  the  ILO  standards  used  in  the  Labour  Force  Survey,  unemployed  persons 
comprise persons aged 15 to 74 who are (the three conditions must be fulfilled): 

(a)  without work during the reference week (the week of the interview), i.e. neither have a 
job nor are at work (for one hour or more) in paid employment or self-employment; 
(b)  currently available for work, i.e. are available for paid employment or self-employment 

before the end of the two weeks following the reference week; 

(c)  actively  seeking  work,  i.e.  have  taken  specific  steps  in  the  four  weeks  period  ending 
with the reference week to seek paid employment or self-employment or who found a 
job to start later, i.e. within a period of at most three months. 
The following are considered as specific steps in “actively seeking work”: 
-  having been in contact with a public employment office to find work, whoever took 
the initiative (renewing registration for administrative reasons only is not an active 
step), 

-  having  been  in  contact  with  a  private  agency  (temporary  work  agency,  firm 

specialising in recruitment, etc.) to find work, 

-  applying to employers directly, 
-  asking among friends, relatives, unions, etc., to find work, 
-  placing or answering job advertisements, 
-  studying job advertisements, 
-  taking a recruitment test or examination or being interviewed, 
-  looking for land, premises or equipment, 
-  applying for permits, licences or financial resources. 

Student 

This  category  refers  to  individuals  in  formal  education  (in  educational  institutions  such  as 
school,  university,  etc.)  and  not  belonging  to  any  of  the  other  categories  of  employment 
situation.  
When  strictly  applying  the  LFS  definitions,  students  with  small  jobs  have  to  be  classified  as 
employees.    However, due  to  the  absence  of  the  long  list of  questions  used  to determine  the 
employment status in the LFS, students who work only a few hours per week may be classified 
as students.  

Other not in the labour force 

This category refers to persons who are not employed or unemployed. Students are considered 
as a separate category (see above).  

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142  

“Other  not  in  the  labour  force  includes  persons  in  retirement  or  early  retirement,  persons  in 
compulsory  military  service,  persons  fulfilling  domestic  tasks  (without  being  an  employee  or 
self-employed, e.g. housewives) or other inactive persons. 

As some countries embed the ICT usage survey in the Labour Force Survey or other socio-

economic  surveys  using  LFS  definitions,  it  is  useful  to  briefly  discuss  the  correspondence 

between the five above categories and the 9 categories used in the LFS variable Main labour 

status (see column 101 in the LFS handbook or in the Annex to Regulation 1575/2000). 

ICT usage survey 

  Employment situation 

Labour Force Survey 

  Main Labour Status 

Employee 

(cid:4)  LFS col.101, code 1  

(carries out a job or profession, including unpaid work for a 
family  business  or  holding,  including  an  apprenticeship  or 
paid traineeship, etc.) 

Self-employed 

(cid:4)  LFS col.101, code 1 

(carries out a job or profession, including unpaid work for a 
family  business  or  holding,  including  an  apprenticeship  or 
paid traineeship, etc.) 

Unemployed 

(cid:4)  LFS col.101, code 2 
(unemployed) 

Student (not in the labour force)  (cid:4)  LFS col.101, code 3 

Other not in the labour force 

(cid:4)  LFS col.101, codes 4, 5, 6, 7 and 8 

(pupil, student, further training, unpaid work experience) 

(in retirement or early retirement or has given up business 
(=4);  permanently  disabled  (=5);  in  compulsory  military 
service  (=6);  fulfilling  domestic  tasks  (=7);  other  inactive 
person (=8). 

The  above  correspondence  table  shows  a  1-1  relation  between  the  breakdown  in  the  ICT 

usage survey and in the Labour Force Survey (with codes 4, 5, 6, 7 and 8 combined into one 

single category as the subcategories are less relevant for the ICT usage survey or could be 

problematic in terms of low cell frequencies).  

Only  the  additional  breakdown  in  employee  and  self-employed  cannot  be  distinguished 

directly from column 101 in the LFS as they are grouped in code 1.  A pragmatic approach - 

with an acceptable risk of coding error – would be to additionally use the Professional status 

from the LFS (column 26) and file all persons (in code 1 of column 101) who appear to be 

self-employed or family worker (codes 1, 2 or 4 in LFS column 26) under code self-employed 

for  the  ICT  usage  survey  and  all  others  under  employees.  In  other  words,  the  auxiliary 

information  from  LFS  column  26  is  only  used  to  redirect  some  persons  into  the  group  of 

self-employed  while  the  rest  remain  in  the  group  of  employees.  This  recoding  suggestion 

supposes  a  certain  correlation  between  the  professional  status  according  to  the  ILO 

definitions (= col.26) and ones self-assessment on the labour status (= col.101). 

Methodological manual for Information Society Statistics 

143  

 
 
 
 
G5:  Occupation (pilot question) 

[ Scope: individuals in employment, i.e. 1st (employee) or 2nd option (self-employed) in G4 ] 

The  individual’s  occupation  should  be  coded  according  to  the  ISCO-88  (COM)  classification 

which  is  used  in  most  of  Eurostat’s  social  statistics  and  which  is  based  upon  the  ILO’s 

International Standard Classification of Occupations, ISCO-88  

(see http://laborsta.ilo.org/applv8/data/isco88e.html).  

The basis for the classification is the job and the skills. A job is defined as the set of tasks 

and duties to be performed. Skills are the abilities to carry out the tasks and duties of a job. 

Skills  consist  of  two  dimensions:  skill  level  –  which  is  usually  related  to  the  level  of 

educational attainment - and domain specialisation.  

The classification is available in the RAMON-database: 

http://europa.eu.int/comm/eurostat/ramon  

An introductionary note can be found at: 

http://europa.eu.int/comm/eurostat/ramon/documents/isco_88_com/isco_88_com.zip) 

The  purpose  of  this  variable  as  a  background  characteristic  is  not  to  collect  data  on  ICT 

usage  broken  down  by  individual  occupations  (this  would  necessitate  very  large  samples), 

but  rather  by  groups  of  occupations.  E.g.  manual  versus  non-manual  or  ICT-jobs  versus 

non ICT-jobs.  To  be  able  to  make  such  regroupings,  it  is  necessary  to  code  and  store  the 

occupations  at  a  detailed  level,  at  least  at  3  digit  level  but  preferably  at  4  digit  level.  The 

major  groups  (1  digit)  or  submajor  groups  (2  digit)  don’t  allow  to  distinguish  ICT 

professionals from other workers. 

Manual workers 

This category corresponds to major groups 6 to 9 of ISCO:  
-  Major group 6: Skilled agricultural and fishery workers; 
-  Major group 7: Craft and related trades workers; 
-  Major group 8: Plant and machine operators and assemblers; 
-  Major group 9: Elementary occupations. 

Non-manual workers 

This category corresponds to major groups 0 to 5 of ISCO.  
-  Major group 1: Legislators, senior officials and managers; 
-  Major group 2: Professionals; 
-  Major group 3: Technicians and associate professionals; 
-  Major group 4: Clerks; 
-  Major group 5: Service workers and shop and market sales workers; 
-  Major group 0: Armed forces. 

ICT professionals 

The most appropriate recoding will be obtained where ISCO codes are collected at 4-digit level. 
However,  as  some  countries  collect  (or  enter)  the  information  relating  to  the  respondent’s 
occupation  only  at  3-digit  level,  the  discussion  below  also  includes  an  alternative  approach 
covering this case. 

ISCO available at 4-digit level  

The category ICT professionals consists of the individuals in one of the following eight 
ISCO Unit Groups (Unit Groups correspond to the 4-digit level): 

1236  Computing services managers 
2131  Computer systems designers, analysts and programmers 

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144  

 
Electronics and telecommunications engineers 
Electronics and telecommunications engineering technicians 

2139  Computing professionals not elsewhere classified 
2144 
3114 
3121  Computer assistants 
3122  Computer equipment operators 
3132  Broadcasting and telecommunications equipment operators 

ISCO available at 3-digit level 

The  category  ICT  professionals  consists  of  the  individuals  in  one  of  the following  two 
ISCO Minor Groups (Minor Groups correspond to the 3-digit level): 

213 
312 

Computing professionals 
Computer associate professionals 

Non ICT professionals 

The category Non ICT professionals consists of the individuals in all other ISCO Unit Groups (in 
the case of 4-digit coding) or all other ISCO Minor Groups (in the case of 3-digit coding). 

G6:  Geographical location 

“Objective  1”  promotes  the  development  and  structural  adjustment  of  regions  whose 

development  is  lagging  behind,  i.e.  whose  average  per  capita  GDP  is  below  75%  of  the 

European Union average.  

The  NUTS  regions  (statistical  demarcation)  eligible  for  support  from  the  Structural  Funds 

under  Objective  1  -  including  transitional  or  phasing-out  Objective  1  regions  until 

31/12/2006 which are marked in italic - are listed below.  

Please note that the list is different  for the one used in the 2005 survey as regions are no 

longer under transitional support as of 31/12/2005. 

Countries entirely covered by Objective 1: 

Estonia (the whole country counts as one single region at NUTS2-level) 

Greece 

Latvia (the whole country counts as one single region at NUTS2-level) 

Lithuania (the whole country counts as one single region at NUTS2-level) 

Hungary 

Malta (the whole country counts as one single region at NUTS2-level) 

Poland 

Slovenia (the whole country counts as one single region at NUTS2-level) 

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145  

 
 
 
Countries partially covered by Objective 1: 

Belgium: 

The following communes of the province of Hainaut: Bernissart, 
Chapelle-lez-Herlaimont, Charleroi (with the exception of former 
commune of Mont-sur-Marchienne), Châtelet, Courcelles, Farciennes, 
Fontaine-l'Evêque, Manage, Boussu, Dour, Frameries, Hensies, Mons 
(only the communes of Jemappes, Flenu et Cuesmes), Quaregnon, 
Quiévrain, Colfontaine, La Louvière (with the exception of the former 
commune of Boussoit), Anderlues, Morlanwelz 

(note: as of 31/12/2005, the rest of the province of Hainaut is no longer 
eligible for transitional support) 

Czech Republic: 

Střední Čechy, Jihozápad, Severozápad, Severovýchod, Jihovýchod, 
Střední Morava, Moravskoslezsko (i.e. the whole country except Praha) 

Germany: 

Spain: 

France: 

Brandenburg Nord-Ost, Brandenburg Süd-West, Mecklenburg-
Vorpommern, Chemnitz, Dresden, Leipzig, Dessau, Halle, Magdeburg, 
Thüringen 

(note: as of 31/12/2005, Berlin (part: former East Berlin, i.e. Kreis 
Berlin-Ost, Stadt) is no longer eligible for transitional support)  

Galicia, Principado de Asturias, Castilla y León, Castilla-La Mancha, 
Extremadura, Comunidad Valenciana, Andalucía, Región de Murcia, 
Ceuta, Melilla, Canarias, Comunidad Autonoma Cantabria 

Guadeloupe, Martinique, Guyana, Réunion, Corse, Nord - Pas-de-Calais 
(parts: arrondissements Avesnes, Douai, Valenciennes) 

Ireland: 

Border, Midlands, Western, South-East 

(note: as of 31/12/2005, Dublin, Mid-East, Mid-West, South-West are 
no longer eligible for transitional support) 

Italy: 

Campania, Puglia, Basilicata, Calabria, Sicilia, Sardegna, Molise 

Austria: 

Burgenland 

Portugal: 

Slovakia: 

Finland: 

Sweden: 

United Kingdom: 

Norte, Centro, Alentejo, Algarve, Açores, Madeira (i.e. the whole 
country except Lisboa) 

Západné Slovensko, Stredné Slovensko, Východné Slovensko (i.e. the 
whole country except Bratislavsky kraj) 

Itä-Suomi (all), Länsi-Suomi (part: northern part of Keski-Suomi), 
Pohjois-Suomi (parts: all of Lappi, part of Pohjois-Pohjanmaa, eastern 
part of Keski-Pohjanmaa) 

[see also: Annex I to Protocol 6 annexed to the Act of Accession of 
Austria, Finland and Sweden (http://europa.eu.int/eur-lex/en/ 
treaties/dat/AU_FI_SV_accession.html#0355010034)]  

Norra Mellansverige (parts: northwestern part of Gävleborgs län, 
northern and western parts of Dalarnas län, northern part of Värmlands 
län), Mellersta Norrland (all, but coastal part is under the "Special 
Programme") and Övre Norrland (all, but coastal part is under the 
"Special Programme") 

[see also: Annex I to Protocol 6 annexed to the Act of Accession of 
Austria, Finland and Sweden (http://europa.eu.int/eur-lex/en/ 
treaties/dat/AU_FI_SV_accession.html#0355010034)] 

South Yorkshire, West Wales and the Valleys, Cornwall and Isles of 
Scilly, Merseyside, Highlands and Islands (only Islands – 1995 NUTS III 
boundaries) 

(note: as of 31/12/2005, Northern Ireland and Highlands and Islands 
(except Islands) are no longer eligible for transitional support) 

Methodological manual for Information Society Statistics 

146  

 
 
 
 
 
 
 
 
 
 
 
 
 
Countries with no Objective 1 regions: 

Denmark (the whole country counts as one single region at NUTS2-level) 

Cyprus (the whole country counts as one single region at NUTS2-level) 

Luxembourg (the whole country counts as one single region at NUTS2-level) 

The Netherlands (note: as of 31/12/2005, Provincie Flevoland is no longer eligible for 

transitional support) 

The list of Objective 1 regions was published in O.J.  L194 p. 53 of 27/07/1999, Annexes I 

and II (http://europa.eu.int/eur-lex/pri/en/oj/dat/1999/l_194/l_19419990727en00530057.pdf). 

The  list  of  Objective  1  regions  in  the  Member  States  who  entered  the  EU  in  2004  can  be 

found in Annex  II to the Act concerning the conditions of accession of these countries. The 

list is valid from 01/05/2004 until 31/12/2006 

(http://www.europa.eu.int/eur-lex/en/treaties/dat/L_2003236EN/L2003236EN.065803.htm). 

The list of NUTS regions as of 2003 was published in O.J. L154 p. 1 of 21/06/2003; see also 

the RAMON-database on Eurostat’s website (http://europa.eu.int/comm/eurostat/ramon/nuts). 

G7:  Type of locality 

The  concept  of  "urbanisation"  has  been  introduced  to  indicate  the  character  of  the  area 

where  the  respondent  lives.  The  definition  of  the  type  of  locality  is  based  on  the 

classification of degrees of urbanisation which is also used in the Labour Force Survey (LFS, 

column 176).  

The following degrees of urbanisation have been identified: 

Densely-populated area 

This is a contiguous set of local areas, each of which has a density superior to 500 inhabitants 
per square kilometre, where the total population for the set is at least 50,000 inhabitants. 

Intermediate area 

This  is  a  contiguous  set  of  local  areas,  not  belonging  to  a  densely-populated  area,  each  of 
which  has  a  density  superior  to  100  inhabitants  per  square  kilometre,  and  either  with  a  total 
population for the set of at least 50,000 inhabitants or adjacent to a densely-populated area. 

Thinly-populated area 

This  is  a  contiguous  set  of  local  areas  belonging  neither  to  a  densely-populated  nor  to  an 
intermediate area. 

(a set of local areas totalling less than 100 km², not reaching the required density, but entirely enclosed 
within a densely-populated or intermediate area, is to be considered to form part of that area.  If it is 
enclosed within a densely-populated area and an intermediate area it is considered to form part of the 
intermediate area) 

In  this  definition  of  degree  of  urbanisation  there  is  a  criterion  of  geographical  contiguity 

together with a population threshold. Harmonised, comparable correspondence between the 

Methodological manual for Information Society Statistics 

147  

 
 
 
 
 
degree  of  urbanisation  and  NUTS  5  regions  are  being  (re-)defined  on  the  basis  of  2001 

census  data  (for  Member  States  and  Candidate  countries)  in  2005.  These  correspondence 

tables  enable  the  NSIs  to  easily  recode  the  addresses  or  postal  codes  into  the  three 

categories. In principle, this conversion table should cover all 25 EU countries at NUTS 5 (or 

LAU 2) level. However, for some countries there may be no results at all or the results will 

only be at NUTS 4 (or LAU 1) level. 

An "area" consists of a group of contiguous "local areas" where a "local area" corresponds to 

the following entities in the respective Member States : 

Belgium: Gemeente / Commune 

Czech Republic: Obce (6 251 in year 2000) 

Denmark: Kommuner 

Germany: Gemeinde 

Estonia: Vald+Alev+Linn (254) 

Greece: Demotiko diamerisma / Koinotiko diamerisma (after the kapodistria reform, ca. 6000 

units) 

Spain: Municipio 

France: Commune 

Ireland: DED / ward 

Italy: Commune 

Cyprus: Demos/Koinotites  

Latvia: Pagast+ Pilsetas (560) 

Lithuania: Seniunija  

Luxembourg: Commune 

Hungary: Telepules (3 135) 

Malta: Localities  

The Netherlands: Gemeente 

Austria: Gemeinde 

Poland: Gminy+Miasta (2 486) 

Portugal: Freguesias 

Slovenia: Obcinah (192 since 1 Jan 1999) 

Slovakia: Obce a Mesta (2 920 in year 1999) 

Finland: Kunnat 

Sweden: Kommune 

United Kingdom: Ward 

Iceland: Sveitarfélag (165 until 1997, 124 from 1998) 

Norway: Kommuner (435) 

Bulgaria: Naseleni miasti 

Croatia: not yet available 

Romania: Comuni, Municipii, Orasi  

Turkey: not yet available 

G8 and G9:  Household type 

“Household” refers either  to one person living alone or a group of people living together in 

the  same  dwelling  unit  with  at  least  one  person  of  the  age  of  16  –  74  years  (see  above: 

“General outline of the survey”, Scope - age limit).  

Methodological manual for Information Society Statistics 

148  

 
 
Excluded are permanent members of institutions such as hospitals, prisons, etc. 

The  household  composition  (as  used  in  the  tabulation  scheme)  is  determined  using  two 

indicators: the total number of persons in the household (including all age groups) and the 

number  of  children  under  16.  The  presence  (and  the  number)  of  children  is  collected 

separately as this is a driving force for adoption of ICT’s or Internet in a household. 

G10:  Household income (optional question) 

The  “income” concept used in this survey is the  net monthly income of the household (not 

the  individual!).  The  focus  is  on  the  household  income  as  one’s  access  to  and  use  of  ICT’s 

will rather be related to the total income of the household he/she is part of than by his/her 

personal income. 

For  persons  in  paid  employment,  this  refers  to  the  monthly  ‘take-home’  pay,  i.e.  the  pay 

after  deducting  income  taxes,  employee's  social  security  contributions  and  any  voluntary 

contributions.  

Bonuses  regularly  paid  at  the  time  of  each  payment  –  such  as  regular  overtime  hours, 

bonuses for team, night or weekend work, tips and commissions - are included. 

Bonuses  that  are  not  paid  at  each  pay  period  (f.i.  annual  profit  shares)  but  that  are  by 

accident  paid  in  the  considered  pay  period  are  excluded  as  they  will  lead  to  a  non-

representative estimate. 

Irregular  or  annual  bonuses  should  be  excluded.  No  “redistribution”  of  such  bonuses  –  i.e. 

dividing by 12 and adding to the monthly estimate – is required as this would unnecessarily 

increase  the  recall  burden  on  the  respondent.  This  may  however  make  international 

comparisons  less  relevant  as  the  impact  of  such  bonuses  tends  to  differ  heavily  from  one 

country to another. 

Where applicable and feasible, an estimate of the monetary value for the payments in kind 

should be added. 

Although  the  income  from  self-employment  may  be  difficult  to  measure,  the  respondents 

can be asked for an estimate of their disposable income. 

Income  from  allowances  such  as  unemployment  benefits,  pensions  and  sickness,  disability 

or  invalidity  allowances  should  refer  to  the  last  monthly  allowance  received  before  the 

interview  (or  the  monthly  average  for  a  recent  period  if  this  is  more  easy  to  collect  or 

estimate). 

Income  from  investments  (assets,  savings,  stocks,  shares,  etc)  is  to  be  excluded  as  this 

information is difficult to measure and/or collect. 

Although  undesirable,  derogations  from  the  above  definition  of  the  household  income  may 

be  justified  in  cases  where  the  data  can  be  obtained  from  slighly  different  income-related 

questions in the survey vehicle the survey on ICT usage is linked to. Especially when using 

such  already  available  data  is  the  only  way  of  providing  information  on  this  sensitive, 

optional variable. 

Methodological manual for Information Society Statistics 

149  

 
 
 
Ideally,  information  should  be  collected  by  asking  the  respondent  for  an  estimate  of  the 

actual  amount.  Where  it  is  not  desirable  or  feasible  to  collect  such  information,  the 

respondent  can  indicate  a  size  band.  These  size  bands  should  be  compatible  with  the 

breakdown  used  in  the  tabulation  scheme.  This  tabulation  scheme  foresees  the  use  of 

income  quartiles  rather  than  income  classes.  Such  approach  should  make  cross-country 

comparisons  more  meaningful.  Not  only  can  this  overcome  the  dispersion  of  income  levels 

across  countries  in  Europe,  the  use  of  quartiles  can  also  avoid  threats  to  comparability 

caused  by  the  use  of  different  concepts  by  different  countries  (e.g.  gross  versus  net 
earnings, whether or not including regular monthly bonuses, whether or not including 1/12th 
of  the  annual  bonuses,  whether  or  not  including  an  estimate  of  the  value  of 

payments-in-kind, etc.).  

For additional information, see Annex II.3.2 Transmission format. 

Methodological manual for Information Society Statistics 

150  

 
 
II.2.  PRODUCTION METHODOLOGY 

II.2.1. 

Timetable – Survey period 

According  to  the  measures  implementing  Regulation  808/2004,  “the  reference  period  for  the 

statistics  to  be  collected  is  the  first  quarter  of 2006”  (see  Annex  III.2).    As  the  majority  of  the 

questions in the model questionnaire and the variables in the above mentioned legal act refer to 

the  last  three  months  –  which  means  in  practice:  the  three  months  preceeding  the  interview  – 

the data collection should take place immediately after the first quarter.  Taking into account that 

the  fieldwork  can  take  several  weeks  or  even  months,  the  recommandation  is  to  interview  the 

respondents in April-May (or more general: in the second quarter). This way, a satisfying overlap 

with the theoretical reference period is guaranteed.  

The table and figure below present an overview of the survey periods in the 2005 survey. 

As  mentioned  in  the  previous  paragraph,  for  most  questions  the  reference  period  is  3  months. 

The  choice  for  this  3  months’  reference  period  is  a  trade-off  between  recall  bias  and  seasonal 

bias.  Using  a  reference  period  of  12  months  filters  out  seasonality,  but  a  recall  period  of  12 

months  may  be  too  demanding  for  the  respondents.  In  general,  priority  has  been  given  to 

limiting the intellectual burden for the respondents, only for the questions related to e-commerce 

(where  an  important  seasonal  effect  can  be  expected  in  consumption  patterns  throughout  the 

year,  e.g.  more  purchases  Christmas,  more  booking  of  holidays  during  Summer)  a  longer 

reference period is used.   

Looking at the results of previous surveys, the pattern for the last 3 months is not very difficult 

from the last 12 months’ pattern. In terms of e.g. Internet use, this means that only few people 

will state they have used the Internet in the past 12 months, but not in the past 3 months.  The 

harmonisation of the data collection periods across countries, should further reduce the possible 

risk of seasonal bias when comparing across countries or from one year to another. 

Table: Overview of the survey periods (2005 survey) 
Source: Interim reports for the Community survey on ICT usage in households and by individuals (2005) 

Belgium 

Second quarter 

Czech Republic 

January - March 

Denmark 

Germany 

Estonia 

Greece 

Ireland 

Italy 

Cyprus 

Latvia 

February, March and April (2004 survey) 

End of April - June 

11 April - 17 July 

1 April - 31 May 

6 June - … 

14 February - 28 February 

April - June 

23 April - 31 May 

Lithuania 

1 March - 30 April 

Luxembourg 

April - May 

Hungary 

1 April - 21 April 

Methodological manual for Information Society Statistics 

151  

 
Malta 

April - June 

Netherlands 

1 April - 31 May 

Austria 

Poland 

Portugal 

Slovenia 

February - May 

1 April - 20 April 

18 April - 27 May 

4 April - 22 April 

Slovak Republic 

June - July 

Finland 

Sweden 

29 March - 6 May 

11 April - 19 June 

United Kingdom 

21 February - 11 March and a 3 weeks' period in May 

Iceland 

Norway 

2 or 3 weeks end February - mid March 

4 April - 8 May 

Figure: Overview of the survey periods (2005 survey) 
Source: Interim reports for the Community survey on ICT usage in households and by individuals (2005) 

January

February

March

April

May

Belgium

June

July

Czech Republic

Denmark

Italy

Germany

Estonia

Greece

Ireland

Cyprus

Latvia

Lithuania

Luxembourg

Hungary

Malta

Netherlands

Austria

Poland

Slovenia

Finland

UK

Iceland

Norway

Portugal

Sweden

UK

Slovak Republic

January

February

March

April

May

June

July

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152  

 
 
 
 
II.2.2. 

Frame population 

This  issue  was  already  discussed  in  chapter  II.1.2  on  the  target  population.    The  frame 

population  (of  sampling  population)  is  the  frame  from  which  the  sample  will  be  drawn.  Ideally, 

this  list  of  units  should  be  equivalent  to  the  target  population  as  both  overcoverage  and 

undercoverage can induce bias and affect the reliability of the survey results.  

E.g. overcoverage due to inclusion of persons aged 75-79 in the sampling frame (making the simplistic 
assumption that the frame only has information on one’s age using age bands, not the actual age 
or year of birth): as this age group to score relatively low on ICT usage indicators, the population 
total may show a downwards bias due to inclusion of this group. 

E.g.  undercoverage  due  to  the  fact  that  some  remote  areas  are  not  covered  in  the  register:  as  such 
areas  usually  have  a  lower  penetration  of  ICTs,  the  overall  indicators  may  be  relatively 
overestimated for such country. 

To allow for an assessment, it is important to include the coverage and the sampling frame when 

reporting metadata (see Chapters 3 and 5 in the reporting template, Annex II.3.3). 

The  table  below  presents  the  sampling  frames  used  in  the  national  statistical  institutes  for  the 

2005 survey.  

The second table gives an overview of the target and non-target population. In most countries, 

the  target  population  of  individuals  aged  16  to  74  represents  approximately  75%  of  the  total 

population.  The  target  population  for  households  covers  the  population  relatively  more 

(approximately  90%)  as  only  households  where  all  members  are  over  74  are  excluded.    This 

information  has  to  be  kept  in  mind  when  disseminating  the  results:  the  results  are  not 

representative for the total population but only for the subpopulation of persons in the age group 

16  to  74.  This  difference  can  be  important  as  the  out-of-scope  groups  may  have  a  different 

profile  in  terms  of  ICT  use  (heavy  use  among  persons  younger  than  16  but  low  use  among 

persons over 74). 

Table: Overview of the sampling frames (2005 survey) 
Source: Quoted from the Interim reports for the Community survey on ICT usage in households and by 

individuals (2005) 

Belgium 

Population  register  (contains all  residents  of Belgium,  regardless of  nationality, 
together with information on household) 

Czech Republic 

Register of census areas 

Denmark 

Central  Population  Register  (contains  general  personal  data  on  individuals  with 
residence in Denmark; individuals without registered address in the CPR do not 
enter the survey) 

Germany 

No sampling frame (quota sampling) 

Estonia 

Greece 

Since 2005 the new sampling frame, the Population Register, is used. Therefore 
in  the  second  quarter  of  2005  50%  of  households  are  sampled  from  the  old 
frame,  which  is  2000  Population  and  Housing  Census  database,  and  50%  of 
households  from  the  Population  Register.  Population  Register  is  an  electronic 
database  containing  the  general  personal  data  about  all  Estonian  citizens  and 
foreigners  residing  in  Estonia.  Population  register  is  administered  by  the 
Estonian Ministry of the Interior. 

The  sampling  frame  containing  the  primary  units  (cluster  of  households  in  one 
or more unified blocks) for the ICT survey is the same as for the LFS of the year 
2004, which is an area frame constructed using the necessary information from 
the  recent  Greek  General  Population  Census  2001,  and  provides  complete 
coverage of the target population of this survey. In each selected primary unit, 
the  sampling frame  containing  the  households  is  updated on  month before  the 
data collection. 

Methodological manual for Information Society Statistics 

153  

Ireland 

Census of Population 

Cyprus 

Latvia 

Population Census 2001 register 

Two  sampling  frames  are  built  for  each  sampling  stage  due  to  two-stage 
sampling is used. At the first stage the list of Population census 2000 counting 
areas  is  used  as  sampling  frame.  All  territory  of  Latvia  was  divided  in  small 
territories  (smaller  than  NUTS4)  during  the  Population  census  2000.  The  list 
contains information about the number of households in each counting area. At 
the  second  stage  sampling  frame  is  built  from  The  Population  Register, 
statistical register of dwellings and statistical register of households. 

Lithuania 

Population Register 

Luxembourg 

Hungary 

Malta 

Netherlands 

Austria 

Poland 

Portugal 

Slovenia 

Slovak Republic 

It  will  be  worked  with  RDD  (random  digital  dialling)  by  using  computer 
generated  national  phone  numbers.  There  will  be  a  number  of  phone  numbers 
randomly chosen to be called. In order to reach representative results, a quota 
system for the individuals to be interviewed will be applied. 

The  stock  or  dataset  of  the  addresses  of  the  2001  population  and  housing 
census  was  used.  This  was  augmented  by  the  set  of  addresses  of  new 
constructions built between 1st of February 2001 and the middle of 2004. 

Database  maintained  by  the  NSO  containing  all  households  and  individuals  in 
Malta and Gozo. 

Municipal  Population  Register.  This  register  contains  all  the  persons  who  are 
registered  in  Dutch municipalities.  Advantage of  using  the Municipal  Population 
Register  is  the  actuality  of  information  from  the  registered  individuals.  Every 
day  information  about  birth,  death,  move  (house),  new  addresses  et  cetera  is 
coming  in.  Monthly  the  information  is  incorporated  in  the  mentioned  register.  
After the register is brought up to date in month t, individuals are selected for 
interviewing in month t+2 

The  “Zentrales  Melderegister  (ZMR)”  is  used  as  a  sampling  frame  for  the 
Continuous  Labour  Force  Survey.  A  sub-sample  of  this  sample  was  drawn  for 
the ICT survey. 

The  basis  for  selection  of  Primary  Sampling  Units  (PSU)  and  dwellings  is  the 
Domestic  Territorial  Division  Register.  The  Register  includes  (among  others) 
information about: 
- enumeration statistical district (ESD) 
- dwelling addresses 
The first stage sampling frame was a record of 29 thousand Area Survey Points 
(ASPs). They are enumeration statistical districts or sets of them which consist 
of  at  least  250  dwellings  for  urban  area  and  150  dwellings  for  rural  area.  The 
second stage sampling frame was based on the register of inhabited dwellings in 
the area survey points from the first stage. 

This  survey  uses  a  sample  selected  from  Master-sample  (Census  2001).  It 
constitutes the sampling basis to all households and individuals related surveys 
done by INE. 

Units of observation are persons aged between 10 and 74 years at the time of 
interviewing  and  their  households.  The  basis  for  the  sampling  frame  is  the 
Central  Population  Register  (CRP).  Target  persons  (persons  aged  between  10 
and  74  years)  are  randomly  selected  from  the  register.  For  the  allocation  of 
persons, in addition to the CRP also the frame of the enumeration units is used, 
which serves as a sampling frame for the selection of units at the first stage in 
two-stage sampling designs. 

Population and housing census is organised by So SR in 10year periodicity. The 
last one was realised in May 2001. On base of census results the information on 
whole  population  is  accessible  -  household  type,  age,  sex,  education  level, 
employment  situation,  location.  Meanwhile  SO  SR  organizes  surveys  on 
population increase and decrease by age and by sex. 
Census register from 2001 is used as sampling frame for survey on information 
and communication technologies (ICT) in households and individuals. 
Sampling  frame  for  individuals  is  created  on  the  state  of  population  as  of  31 
December 2003. 

Finland 

Updated Central Population Register. 
It  contains  the  official  information  of  Finnish  citizens  and  aliens  residing 
permanently in Finland, and on buildings and residences and their holders. 

Methodological manual for Information Society Statistics 

154  

Sweden 

The  sampling  frame  is  the  Total  Population  Register  (TPR)  kept  by  Statistics 
Sweden.  The  TPR  obtains  notifications  of  births,  deaths,  migrations  etc.  daily 
from the Tax Authorities. 

United Kingdom 

The  Omnibus  Survey  uses  the  Postcode  Address  File  of  ‘small  users’  as  its 
sampling  frame.  Private  household  addresses  in  Great  Britain  are  included  in 
this frame. 

Iceland 

The National Register of Persons is used as a sampling frame for the ICT survey. 
All Icelandic as well as foreign citizens domiciled in Iceland are registered in the 
National Register of Persons. Basic information such as gender, age and sample 
municipality  are  always  found  in  this  register.  To  be  able  to  monitor  every 
changes Statistics Iceland´s survey center has unlimited access to the National 
Register of persons during the data collection period. 

Norway 

BEBAS  -    the  central  demographic-/population  database  at  Statistics  Norway. 
The database is updated from The National Population Register several times a 
month. 

Table: Overview of the target and non-target population (2005 survey) 
Source: Interim reports for the Community survey on ICT usage in households and by individuals (2005) 

Individuals

Households

Target 
population

Non-target 
population

Target 
population as 
% of total 
population

Target 
population

Non-target 
population

Target 
population as 
% of total 
population

Belgium

Denmark (2004)

3 933 851

1 400 000

Germany

62 000 000

19 000 000

Estonia

Greece

Ireland

Italy

Cyprus

Latvia

Lithuania

Luxembourg

Hungary

Malta

1 026 000

330 000

8 160 045

2 440 939

3 002 900

1 040 900

44 000 000

13 500 000

524 151

1 778 195

2 575 400

333 866

206 216

541 008

870 500

117 734

7 720 917

2 218 474

296 400

103 400

Netherlands

12 700 000

3 300 000

Austria

Poland

Portugal

Slovenia

Finland

Sweden

6 050 000

2 000 000

28 503 984

9 726 096

7 873 696

2 511 810

1 551 637

429 676

3 941 000

1 295 000

6 500 000

2 500 000

United Kingdom

42 873 728

15 699 620

Iceland

Norway

207 000

86 000

3 273 926

1 330 818

74%

77%

76%

77%

74%

77%

72%

77%

75%

74%

78%

74%

79%

75%

75%

76%

78%

75%

72%

73%

71%

71%

4 000 000

2 307 329

400 000

350 000

35 000 000

3 000 000

3 726 806

1 301 000

415 801

104 900

20 000 000

2 300 000

220 695

18 105

1 232 700

156 451

113 300

15 484

91%

87%

92%

90%

93%

90%

92%

92%

91%

3 080 000

12 592 289

340 000

744 751

90%

94%

2 405 000

229 500

91%

21 491 569

3 211 384

103 000

8 300

87%

93%

Methodological manual for Information Society Statistics 

155  

 
 
 
 
II.2.3. 

Sampling design 

The  population  of  interest  of  this  survey,  i.e.  the  group  of  statistical  units  around  which  it  was 

intended to investigate is made up of households (with the exclusion of permanent members of 

cohabitation) and individuals living in Member States. 

As  the  country  details  in  the  table  below  show,  there  are  great  differences  among  national 

statistical  institutes  as  regards  sampling  design.  Some  countries  use  a  sample  based  on 

individuals  as  primary  sampling  units.  For  other  countries  the  primary  sampling  units  are 

represented  by  households  registered  in  the  public register  and  in  general  the  second  sampling 

units are all the actual components belonging to each household included in the sample. 

The  survey  should  be  based  on  a  probability  sample  from  which  results  representative  of  the 

population could be derived, considering the agreed breakdowns defined in the questionnaire. 

The final sample units should be the individuals but each participating country should design its 

sample selection according to what is most efficient to that country.  

The  sampling  design  and  the  resulting  sample  size  (see  below)  should  be  appropriate  for 

obtaining  accurate,  reliable  and  representative  results  on  the  survey  characteristics  and 

breakdowns  specified  in  the  Regulation  and  the  model  questionnaire.    Taking  into  account  the 

unbalanced distribution of e.g. Internet users over the different groups of society, this condition 

can be difficult to hold for all indicators and all breakdowns, but this requirement should at least 

be  followed  for  the  main  indicators  (e.g.  the  eEurope  Benchmarking  Indicators,  listed  in  the 

Council Resolution of 18 February 2003 on the implementation of the eEurope 2005 Action Plan, 

Official Journal of 28/02/2003, C48, p. 2-9).  

This  objective  should  be  achieved  for  the  overall  proportions  as  well  as  for  the  proportions 

relating  to  the  different  subgroups  of  the  population.  The  estimated  coefficient  of  variation  (or 

relative standard error) should not exceed 2% for the overall proportions and should not exceed 

4%  for  the  proportions  relating  to  the  different  subgroups  of  the  population  where  these 

subgroups constitute at least 5% of the total population in the scope of the survey. 

The aim of such requirement is to ensure the collection of a complete dataset – without empty, 

confidential or unreliable cells - for these indicators. 

Table: Overview of the sampling design and sampling methods (2005 survey) 
Source: Quoted from the Interim reports for the Community survey on ICT usage in households and by individuals 

(2005) 

Belgium 

Sample of households (through “Reference persons”) 
Stratification by NUTS2 (11 strata) 
Two-stage sampling:  
▪  598  (each  quarter)  Primary  Units  (=  parts  of  municipalities),  selected  with 

probability proportional to size, repetitions allowed 

▪  Secondary Units = households (23 for each PSU selection; exception: 26 in the 

Brussels stratum) 

Initial sample size 14027 households (some 35 000 individuals) 
Individual within household: Interviewer chooses person aged 16-74 with most recent 
birthday at the date of interview. 

Czech Republic 

Stratified random sampling 

Methodological manual for Information Society Statistics 

156  

 
 
All individuals aged 15+ in the household are interviewed.  
Post-stratification by gender, age and region was used. 

Denmark 

The sample is formed by a random selection from the CPR. As stated earlier the survey 
is  conducted  over  3  months  with  a  new  sample  being  drawn  every  month.  When  the 
sample has been drawn, the individuals taken part are contacted by mail, in which they 
are  asked  to  participate  in  the  survey.  If  it  is  impossible  to  find  a  telephone  number, 
the  respondent  is  asked  to  contact  Statistics  Denmark  with  a  number  by  which  he  or 
she  can  be  reached.  In  this  survey  round  a  qualified  sample  of  4.006  individuals  was 
formed  (February  through  April).  Total  interviews  for  analysis  (excluding  loses  etc.) 
ended up at 2.899.  
After the data has been collected, the data is grouped by gender, age (4 groups), civil 
status  (5 groups) and gross income (3 groups + unknown/don’t know). 

Germany 

The ICT survey is based on a representative quota sample. The representativeness was 
achieved 
by a stratification frame taken from German Microcensus 2003. 
Stratification variables are: 
▪  Federal State (16 Bundesländer); 
▪  Household  Type  (5  types):  1)  single  adult;  2)  couple  without  children;  3)  single 
parent  with  at  least  one  child  aged  less  than  18;  4)  couple  with  at  least  one  child 
aged less than 18; 5) other household; 

▪  Social status of head of the household (6 types): 1) self employed; 2) civil servant; 
3)  employee;  4)  worker; 5) retired  – only for  household  type 1  and 2  –  ; 6) other 
inactive; 

▪  Household net monthly income (4 classes): 1) < 1300 EUR; 2) 1300 to<2600 EUR; 

3) 2600 to < 3600 EUR; 4) > 3600 EUR; 

That is 108 strata for each federal state (Bundesland). 
Sampling  unit  is  the  private  household  at  main  residence.  Households  are  selected 
either  from  an  access  panel  or  from  other  address  databases  (i.e.  from  household 
budget survey) that give also information on the stratification variables. 
In  the  first  step,  households  are  contacted  by  mail  and  asked  to  send  back  their 
confirmation of 
participation. On that confirmation they are also asked to report the number of persons 
in  the  household  and  particularly  the  number  of  persons  10  years  and over.  Then  the 
household questionnaire  and the  correct  number of  personal  questionnaires  is  sent  to 
the  household.  All  persons  10  years  and  over  living  in  the  household  are  selected 
respondents.  There  is  no  second  step  of  sampling  within  the  households.  When  the 
participation  rate  in  a  certain  stratum  is  low,  other  households  with  the  same 
stratification characteristics can be recruited to fulfil the quota restrictions. 
To  achieve  results  broken  down  by  “Household  type”  or  “Social  status  of  head  of 
household”, 
taken 
disproportionally  into  the  sampling  frame.  In  case  of  “Household  type”  the  categories 
“couples  with  children”  and  “single  parents”  are  overrepresented.  In  case  of  “  Social 
status  of  head  of  household”  the  categories  “self  employed”,  “civil  servant”,  “worker” 
and  “other  inactive”  are  overrepresented.  This  disproportional  distribution  is  going  to 
be corrected in the grossing up procedure by adjusting the sample to the microcensus. 

two  stratification  variables  are 

the  categories  of 

these 

Estonia 

The sampling design is a stratified systematic two-phase sampling of individuals, whose 
households are included in the sample.  
In the first phase the sample is selected by systematic sampling inside strata and the 
information  on  the  size  of  sampled  households  is  collected.  In  the  second  phase  the 
sample is grouped by the number of persons aged 15-74 years in the household of the 
sampled individual. The final sample is then selected by systematic sampling from each 
household’s  size  group  with  inclusion  probability  inverse  to  the  household  size.  This 
yields  an  equal  probability  sample  of  households  (and  its  15-74  years  old  members) 
inside  strata.  All  persons  aged  15-74  years  in  the  households  of  the  final  sample  are 
interviewed. 

Methodological manual for Information Society Statistics 

157  

 
 
 
Greece 

A  stratified  systematic  sampling  is  used  on  the  first  step  of  sample  design.  The  15 
counties of Estonia and Tallinn are divided into four strata according to the population 
numbers  (I  –  Tallinn,  II  –  four  bigger  counties,  III  –  ten  smaller  counties,  IV  –  Hiiu 
county)  and  different  inclusion  probabilities  are  used  in  stratas,  the  highest  being  for 
Hiiu county. 

The two-stage stratified area sampling with self-weighting estimators is applied for the 
survey.  The  primary  units  are  the  areas  (one  or  more  unified  blocks)  and  the  final 
sampling  units  selected  in  each  sampling  area  are  the  households,  apart  from 
households not containing at least one member 16 to 74 years old.  

Stratification 
In  each  geographical  region  (NUTS  II),  the  urban  agglomerations,  the  Municipalities 
and  Communes  were  allocated  by  the  degree  of  urbanization  (urban,  semi-urban  and 
rural regions).  
The  Municipalities  of  the  Greater  Athens  (the  largest  urban  agglomeration)  were 
allocated  to 31  approximately  equally  sized  strata  (equal  number of  households),  and 
the  Municipalities  belonging  to  the  agglomeration  of  Thessalonica  (the  second  urban 
centre  of  Greece)  were  allocated  to  9  equally  sized  strata,  taking  into  account  social 
and  economic  criteria  for  this  further  stratification.  After  the  stratification,  79  strata 
were produced. 

Sampling fraction  

The overall sampling fraction is 

1 »
l

%144,0

 (5.500 households). 

Ireland 

Italy 

Cyprus 

For the QNHS, a two-stage sample design is used. This comprises a first stage sample 
of  2,600  blocks  (or  small  areas)  selected  at  county  level  to  proportionately  represent 
eight  strata  reflecting  population  density.  Each  block  was  selected  to  contain,  on 
average, 75 dwellings and the sample of blocks is fixed for a period of about five years. 
In  the  second stage of  sampling,  15  households  are surveyed  in  each block  to give  a 
total quarterly sample of 39,000 households. 
Households are asked to take part in the survey for five consecutive quarters and are 
then replaced by other households in the same block. Thus, one fifth of the households 
in  the  survey  are  replaced  each  quarter  and  the  QNHS  sample  involves  an  overlap  of 
80% between consecutive quarters and 20% between the same quarter in consecutive 
years.  The  ICT  household  survey  was  conducted  on  a  sub-sample  (20%)  of  the  main 
QNHS sample. 

The  survey  is  based  on  a  two  stage  stratified  sample.  At  first  stage,  about  800 
Municipalities  are  selected,  stratified  by  region  and  type  of  municipality  (metropolitan 
areas  and  other  municipalities  by  size).  Households  are  second  stage  sampling  units, 
randomly  (systematically)  selected 
lists  of  each  sampled 
municipality. All members of selected households are interviewed. […] 

from  administrative 

The sampling frame is stratified into urban and rural strata by district. 
The size of the sample is predetermined on the basis of the average size of households 
having  at  least  one  individual  in  age  group  16-74.  The  size  of  the  sample  should 
satisfactorily serve the desirable and acceptable confidence limits of the survey results, 
taking always into consideration time and cost constraints.   
The  households  are  then  allocated  in  each  stratum  according  to  the  number  of 
households in the population census register. 
The  selection  of  the  sample  in  the  urban  areas  is  done  by  using  simple  systematic 
random sample. A random start is selected and by using the sampling interval N/n for 
each district (urban areas) respectively. 
The  selection  in  rural  areas  is  done  two  stages.  The  villages  of  each  district  are  the 
Primary Sampling Units and the households the Ultimate Sampling Units. 
All  the  villages  of  each  district  are  listed  in  ascending  order  of  size.  The  sample  is 
drawn  with  Probability  proportional  to  size  (P.P.S.),  the  latter  being  determined  from 

Methodological manual for Information Society Statistics 

158  

 
 
 
Latvia 

the number of individuals. Once a PPS sampling is employed the number of households 
in each selected village is fixed at 20. In cases of very small villages with less than 20 
households,  these  villages  are  attached  to  other  neighbouring  ones  and  they  are 
considered as one village. 
For the selection of the households in each selected village, simple systematic random 
sampling is employed in each village separately. 

Stratified  two-stage  sampling  (systematic  sampling  with  inclusion  probabilities 
proportional  to  unit  size  at  the  first  stage,  simple  random  sampling  at  the  second 
stage) was used. 
The  stratification  was  made  depending  on  degree  of  urbanisation  of  area.  Riga  (the 
capital city), six other largest cities, other cities and rural areas forms four strata. The 
code of administrative territories was used to stratify. The population census counting 
areas were used as primary sampling units (PSU) at the first stage. PSUs were selected 
by  systematic  sampling  with  inclusion  probabilities  proportional  to  population  size 
(number of households) of PSUs. 
Households  were  used  as  secondary  sampling  units  (SSU).  Simple  random  sampling 
was used to select SSUs in each sampled PSU. 
All individuals aged 16-74 (15+) will be selected in each sampled household. 
The total sample size (number of households) was approximately defined depending on 
the  resources  available  and desirable  result  of  the  survey. The  initial  sample  size  was 
proportional  to  population  size  in  each  stratum.  The  initial  sample  size  was  adjusted 
according  to  response  rates  in  each  stratum  to  get  the  final  sample  size  in  each 
stratum. 

Lithuania 

Stratified two-stage sample design. The biggest towns of Lithuania counties, small and 
medium towns and rural area were divided into separate strata. Simple random sample 
of individuals of 16 and older from Population Register was drown in the biggest towns 
of  the  counties.  A  household,  which  lives  in  selected  persons  address,  was  surveyed. 
Two–stage  sample  design  was  used  in  small  and  medium  towns.  The  Pareto  sample 
with probability proportional to the clusters size was used in the first stage. Each town 
was  a  cluster.  Simple  random  sample  of  persons  of  16  and  older  was  drowning  from 
Population register in already selected cluster in second stage. In rural area the similar 
sample design like in medium and small towns was used. Cluster was a rural territorial 
unit in this case. 

Luxembourg 

The national sample was constructed in 2 stages:  
1rst level: selection of households by RDD.  
2nd  level:  selection  of  respondent  in  the  household.  1  individual  per  household  was 
selected.  
Quota sampling: age, sex, region, nationality and professional activity 
A weighting procedure for these quota variables will be applied (including sex by age). 
The reference figures will be taken from STATEC. 

Hungary 

The  ICT  sample  is  a  sub-sample  of  the  sample  of  the  micro-census  whose  reference 
period  is  1st  April  2005.    The  micro-census  sample  was  designed  to  provide  reliable 
estimates  of  the  main  demographic  indicators  for  the  176  General  Electoral  Districts 
(GEDs)  of  the  country.  The  GEDs  were  roughly  of  the  same  size,  the  average  being 
24,000 in terms of dwellings. Each GED has a     2 % sample of its own, resulting in a 
self-weighting 2 % overall sample of the country.  Some GEDs are towns or segments 
of  major  cities  (type  1),  other  GEDs  consist  of  a  number  of  small  localities  (type  2)  
GEDs  of  type  1  have  2  %  systematic  sample  of  dwellings,  those  of  type  2  have  two-
stage stratified samples of dwellings; the PSUs  (primary sampling units) are localities. 
When  selecting  the ICT sample  from  the  micro-census  sample,  an  effort  was  made  to 
keep is close to a self-weighting sample. 
When  selecting  the  sample  of  localities  within  the  GEDs,  we  were  able  to  compare 
population counts estimated from the sample with the corresponding actual values of 1 
January 2004. In the case of extremely large sampling errors, the selection procedure 

Methodological manual for Information Society Statistics 

159  

 
 
 
 
was repeated. 

Netherlands 

Austria 

Poland 

Sampling method: For the ICT survey a stratified two-stage sample is used. In the first 
stage municipalities are selected. Large municipalities being selected with a probability 
of  1.    All  the  other  municipalities  are  selected  at  random.  In  the  second  stage  the 
number  of  individuals,  as  determined  for  every  municipality,  are  selected.  Individuals 
aged  12  to  74  year  are  selected.  Variables  used  for  stratification  are  NUTS3  and 
regions used for the fieldwork 

For the Continuous Labour Force Survey (LFS) every quarter of the year appr. 22.500 
households  are  surveyed.  Every  household  remains  in  the  sample  for  five  quarters. 
(this means that 20% of the surveyed households are replaced every quarter).  
For the ICT survey a gross sub-sample of appr. 8.000 households has been drawn for 
which  the  “reference  week”  of  the  survey  are  the  calendar  weeks 6  to 13  in  the  year 
2005.  The  sample  is  stratified  by  region.  All  household  members  between  16  and  74 
years in the sampled households are surveyed. 

A two-stage sampling scheme was adopted with stratification on the first stage.  At the 
first stage of sampling design the same ASPs will be used as in a sample for Household 
Budget Survey (HBS). The sample already exists.  ASPs have been stratified within 
each of 16 voivodships in Poland by type of locality. Big cities usually constitute 
separate strata, whereas the strata in rural areas are composed of ASPs comprising 
neighbouring poviats. There are 96 strata (of which 31 covering rural areas). 
The  number  of  the  ASPs  selected  to  the  HBS  sample  from  a  given  stratum  was 
proportional  to  the  number  of  dwellings  in  that  stratum.  The  probability  of  ASP 
selection  was  proportional  to  the  estimated  number  of  dwellings  in  the  ASP.    The 
procedure of systematic sampling was applied after random ordering of the units (ASPs 
selected with PPS using Hartley-Rao method). 675 ASPs were selected and that is the 
first stage sample for HBS and ICT usage surveys. 
On  the  second  stage  12  dwellings  will  be  selected  in  each  ASP  by  means  of  simple 
random sampling method, but additional condition will be applied: dwellings selected to 
the  HBS  cannot be selected  to  the ICT  usage  survey.  Samples for  the  surveys  will  be 
separated. Gross sample size for ICT usage surveys: 12 * 675 ASP = 8100 dwellings. 

Portugal 

The sample used for the household survey on ICT usage is directly selected from 
Master-sample and for this specific subject, and inquires, in a first approach, 6 026 
dwellings by sampling method and around 10 500 individuals (estimate) who are 16-74 
years old.  
The sample is representative at NUTS I level: Portugal (Mainland), Azores and Madeira. 

Slovenia 

Two-stage,  stratified  sample  design  was  employed  in  the  survey.  The  sample  is 
implicitly  stratified  according  to  the  size  and  type  of  settlements  (6  classes)  and 
according to the statistical region (12 regions). 
At  the  first  stage  200  sampling  units  are  selected  with  the  probability  proportional  to 
size (PPS with replacement), and at the second stage 10 persons aged between 10 and 
74 years are selected. Thus 2000 persons were selected. The person who is supposed 
to be interviewed is defined by the selected person. 
The probability of selection of a person is calculated by the formula: 

N
∑

Slo

a
N

, 

10
N

a

a

where 

aN  is  the  number  of  persons  aged  between  10  and  74  years  in  the  sampling 

unit. 
The selected person in the household is interviewed. 

Slovak Republic 

The  sample  is  realised  on  the  base  of  the  same  methods,  which  are  used  in  other 

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(cid:215)
 
surveys organised by SO SR (census, inquiry methods face-to-face) 
Sample contains 4000 households including households with member’s aged 16 to 74. 
The  breakdown  of  households  is  following:  with  1  member,  with  2  members,  with  3 
members, with 4 members, with 5 and more members. 
Two –stage sampling is realised: 
▪ 
▪ 
The households are selected inside of each strata random sample. 

Number of persons in households 

Location 

Finland 

Systematic  random  sampling  is  used  to  extract  the  sample  from  the  updated  Central 
Population Register. The sorting system of the sampling frame is based on geographical 
population  density.  The  sampling  method  can  be  compared  to  the  use  of  simple 
random  sampling  with  the  addition  that  the  sample  is  geographically  self-weighting. 
The target area is the whole country, and the respondents represent the 10 to 74-year-
old population in Finland, according to age, gender, province, and native language. Two 
samples are drawn. The other sample consists of 15 to 74 year-old population and the 
other sample consists of 10 to 14-year-old population. 
Sample size is based on the knowledge of response rates in respective surveys earlier. 
After drawing the sample from the Central Population Register we search with different 
methods  the  telephone  number  for  the  target,  93  to  95  per  cent  of  them  are  within 
reach  of  the  telephone.  Fixed  telephone,  if  any,  will  be  used  as  the  primary  way  of 
communication. During the April 2004 interviews half of the interviews were given from 
fixed  telephone  numbers  and  another  half  from  mobile  numbers.  A  couple  of  weeks 
before the contact by phone, Statistics Finland sends out a target letter telling him or 
her briefly the contents and the meaning of the survey. The sample population without 
telephone number (5 to 7 per cent of the total sample) will receive their own letter by 
post, indicating that they are asked kindly to contact Statistics Finland. Around 10 per 
cent will normally make contact and give an interview. 

Sweden 

The LFS-sample is drawn at the end of the first quarter every year to cover the coming 
year’s  need of  sample persons.  When  the sample  is drawn  it  is  stratified  according  to 
county, sex, citizenship (Swedish, foreign), and employment (employed, not employed) 
as  appears  in  the  Register  of  Regional  Employment.  In  this  way  192  strata  are 
constructed. Within each stratum then population is ordered by age, and a systematic 
probability  sample  is  drawn.  The  sampling  differs  from  different  regions  according  to 
NUTS  III  and  between  Swedish  and  non-Swedish  citizens.  Within  regions  and  each  of 
the two citizen groups the sample size is directly proportional to stratum size.  
The LFS sample consists of three separate samples, one for each month in the quarter. 
Each  of  the  samples,  which  consists of  about  20 000  people,  is rotated  in  such  a way 
that  an  eighth  leaves  the  sample  between  two  survey  cycles.  For  every  sample  this 
occurs  every  three  months.  Persons  in  sample  are  interviewed  once  a  quarter  with  a 
total of eight interviews during a two-year period, after which they leave the sample.  
The sample for the Survey on ICT use is made by selecting all individuals in the third 
wave and a few individuals in the fourth to seventh wave. The ICT survey is conducted 
at the end of the interview, i.e. after the LFS questions. 

United Kingdom 

In February 2005, a sample of 100 postal sectors will be selected and stratified by: 
region, the proportion of households renting from local authorities; and the proportion 
in which the household reference person is in Socio-Economic Group 1-5 or 13 (i.e. a 
professional, employer or manager). The postal sectors will be selected with probability 
proportionate to size and, within each sector, 30 addresses (delivery points) will be 
selected randomly. If addresses contain more than one household, the interviewer will 
use a standard ONS procedure to randomly select just one household. Within 
households with more than one adult member, just one person aged 16 or over will be 
selected with the use of random number tables. The interviewers endeavour to 
interview that person – proxy interviews will not be taken.  
In  May  2005,  a  sample  of 67  postal  sectors  will  be  selected  and stratified  by:  region, 
the  proportion  of  households  with  no  car,  the  proportion  of  households  where  the 

Methodological manual for Information Society Statistics 

161  

 
 
 
household  reference  person  is  in  the  National  Statistics  Socio-economic  Classification 
(NS-SEC)  categories  1  to  3,  and  the  proportion  of  people  who  are  aged  over  65.  The 
postal  sectors  will  be  selected  with  probability  proportionate  to  size  and,  within  each 
sector,  30  addresses  (delivery  points)  will  be  selected  randomly.  If  addresses  contain 
more  than  one  household,  the  interviewer  will  use  a  standard  ONS  procedure  to 
randomly  select  just  one  household.  Within  households  with  more  than  one  adult 
member,  just  one  person  aged  16  or  over  will  be  selected  with  the  use  of  random 
number tables. The interviewers endeavour to interview that person – proxy interviews 
will not be taken. 

Iceland 

Stratified  random  sampling  without  replacement  is  used  to  select  individuals. 
Population  is  devided  into  two  strata  by  residence.  Within  households  with  more  than 
one  member  in  the  age  of  16-74  years,  one  person  is  randomly  selected,  i.e.  each 
individual represents one household. 

Norway 

The sampling follows the Statistics Norway's standard sample procedure. The country is 
first  divided  into  a  number  of  sampling  areas  and  these  again  are  divided  into  109 
strata.  The  sampling  areas  are  municipalities  or  a  group  of  municipalities.  The 
municipalities with few inhabitants are put together with other municipalities to ensure 
that  each  sampling  area consists  of  at  least seven  per  cent  of  the  total  inhabitants  in 
the  stratum  the  area  belongs  to.  In  some  cases  small  municipalities  close  to  highly 
populated  municipalities  are  put  together  with  the  large  one  in  that  region.  All 
municipalities  with  more  than  30  000  inhabitants  and  some  with  25 000  to  30 000 
inhabitants make separate strata. 

II.2.3.1  STRATIFICATION 

The recommendation is to use a stratified sample of individuals or households with the aim 

to form groups (or layers) of units characterised, in relation to the variables subject of the 

survey,  by  maximum  homogeneity  within  the  layers  and  maximum  heterogeneity  between 

the  layers.  Achieving  this  goal  in  statistical  terms  means  precision  of  estimates,  or  a 

reduction in sampling errors on a part with the sample quantity. 

Each  country  should  use  the  stratification  variables  according  to  what  is  most  efficient  to 

that country with particular attention to the demographic size of the localities. 

II.2.3.2  SAMPLE SIZE 

Calculation  of  sample  sizes  should  take  into  account  that  this  is  a  survey  with  multiple 

objectives.  It  has  to  ensure  representative  results  for  all  the  estimates  produced.  In 

particular calculation of sample size should take into account that each statistics have to be 

tabulated by age, sex, education level, employment situation, geographical location and type 

of locality.  

As  budgets  are  limited,  the  design  of  study  involves  making  trade-offs  along  various 

dimensions.  Larger  samples  make  it  possible  to  analyse  sub-groups  in  depth  but  every 

interview increases survey costs. 

Methodological manual for Information Society Statistics 

162  

 
 
 
 
 
 
On the basis of the previous considerations, it is suggested to adopt a mixed view, based on 

both cost and organisational criteria and on an evaluation of the sample errors of the main 

estimates  on  a  national  level  and  with  reference  to  each  of  the  territorial  domains  and  to 

each of the breakdown variables of interest. 

The calculation of sample sizes should be based on precision requirements (see above). On 

this basis countries should decide on sample design and calculate the sample sizes in order 

to receive estimates with sufficient quality and within possible budgetary constraints. 

The  table  below  gives  an  overview  of  the  sample  sizes  reported  by  the  national  statistical 

institutes  in  the  Final  Reports  for  the  2004  surveys.  Note  that,  due  to  national  programs 

(e.g. production of regional estimates) and different units (household versus individual), the 

countries  can’t  always  be  compared.  For  most  countries,  the  final  or  net  sample  size  was 

between 3000 and 6000 elements. The response and non-response as well as the quality (in 

terms of coefficient of variation) are discussed in more detail in the next chapters. 

Table: Overview of the sample sizes and response rates (2004 survey) 
Source: Final reports for the Community survey on ICT usage in households and by individuals (2004) 

Unit

IND

HH

IND

HH

HH

IND

HH

IND

IND

HH

IND

IND

IND

IND

IND

IND

Denmark

Germany

Greece

Spain

Ireland

Latvia

Lithuania

Luxembourg

Hungary

Austria

Poland

Portugal

Slovenia

Slovak Republic

Finland

Sweden

United Kingdom IND

Bulgaria

Romania

Iceland

Norway

HH

HH

IND

IND

Gross 
sample 
size

4 499

6 590

4 970

19 366

7 190

7 992

4 500

Number of 
eligible 
elements

Ineligible: 
out-of-
scope

Other 
ineligible

Non-
contact

Refusal Other non-
response

Net sample 
size

Unit 
response 
rate

336

445

326

2 899

72.4%

493

0

4 006

6 419

4 543

207

156

2 034

17 332

1 256

2 065

7 166

7 650

4 150

1 019

330

223

683

210

298

100

171

427

24

44

250

38 767

4 160

8 959

25 648

15 397

8 056

6 357

1 290

1 034

1 692

4 727

73.6%

0

81

726

129

39

660

173

4 180

92.0%

13 930

80.4%

5 421

75.6%

6 508

85.1%

3 678

88.6%

1 535

6.0%

3 860

60.7%

6 500

6 294

0

182

143

235

12 202

3 027

5 877

9 175

14 115

1 099

1 644

11 372

2 000

5 000

4 127

5 429

6 000

4 614

10 816

2 000

2 000

0

0

0

0

411

32

0

109

193

0

26

9

481

130

246

50

21

1 807

5 000

4 101

5 420

5 108

4 452

10 568

1 950

1 870

931

179

778

142

498

410

629

143

132

116

146

1 674

0

3 272

55.7%

36

251

184

259

302

589

1 427

60

167

152

458

121

8 839

96.3%

0

26

0

167

795

79

0

10 343

91.0%

1 455

80.5%

4 741

94.8%

3 134

76.4%

3 626

66.9%

2 973

58.2%

4 235

95.1%

222

10 047

95.1%

49

78

1 633

83.7%

1 188

63.5%

Methodological manual for Information Society Statistics 

163  

 
 
 
II.2.3.3  WEIGHTING – GROSSING UP METHODS 

The weighting factors are to be calculated taking into account in particular the probability of 

selection  and  external  data  relating  to  the  distribution  of  the  population  being  surveyed, 

where such external data are held to be sufficiently reliable.   

As the sampling design used differs strongly across countries, it is difficult to present ‘fit-all’ 

guidelines.  Moreover,  the  weighting  procedures  /  grossing  up  methods  are  usually 

determined by the sampling design used.  The discussion is more of a theoretical nature and 

goes beyond the scope of this manual.  

Where  more  advanced  methods  for  dealing  with  unit  non-response  are  not  feasible,  it  is 

advised  to  correct  for  unit  non-response  by  adjusting  the  grossing  up  weights.  Ideally, 

auxiliary information such as socio-economic differences should be taken into account. 

II.2.4. 

Survey type 

Data collection method 

Face-to-face interviews, telephone interviews and postal surveys are all possible techniques 

of  collecting  data.  The  socio-demographic  characteristics  which  can  be  found  in  registers 

need not be collected in the survey. 

Face-to-face  interviews  are  recommended  especially  where  telephone  penetration  is  low.  

Interviews face-to-face or by telephone are preferred to postal surveys because interaction 

between the respondent and the interviewer can be important for the  understanding of the 

questions and the answers but care should be taken to ensure a low rate of proxy response.  

When using telephone interviews it is important to include mobile and ex-directory users as 

well  as  fixed  link  users  in  the  population  sampled.  Postal  surveys  might  be  used  to  lower 

survey costs when budgets are limited. 

The  table  below  indicates  that  most  countries  collect  the  data  via  a  face-to-face  interview, 

although  telephone  interviewing  is  also  a  common  technique.  Postal  surveys  are  used  by 

only two countries. 

Table: Overview of the data collection methods (2005 survey) 
Source: Interim reports for the Community survey on ICT usage in households and by individuals (2005) 

Belgium 

Face-to-face (for persons aged 65+: face-to-face or telephone) 

Czech Republic 

Computer-assisted Personal interview 

Denmark 

CATI (2004 survey) 

Germany 

Self-administered mail questionnaire 

Estonia 

Greece 

Ireland 

Face-to-face 

Telephone interviews 

CAPI 

Methodological manual for Information Society Statistics 

164  

 
 
 
Italy 

Cyprus 

Latvia 

Lithuania 

The survey uses paper and pencil interview (PAPI) technique and it is based on 
a face-to-face interview questionnaire and a self administrate questionnaire. The 
ICT module is in the self administrate questionnaire. 

Face-to-face using CAPI 

Face-to-face 

Face-to-face  interview.  Household  members  not  at  home  during  the  visit  of 
interviewer  can  be  contacted  later  by  telephone.  Proxy  interviews  are  allowed 
only for persons who don't use computer or Internet. 

Luxembourg 

CATI (with computer generated phone-numbers (mobile phones not included)) 

Hungary 

Face-to-face 

Malta 

Face to Face interview with initial telephone call to fix appointment 

Netherlands 

CATI 

Austria 

Poland 

Portugal 

CATI 

The  main  survey  technique  will  be  face  to  face  interview.  Interviewers  are 
supposed  to  fill  in  the  household  questionnaires  together  with  heads  of 
households or other persons who will be able to give credible answers. Then all 
members  of  the  household  aged  12-74  will  be  interviewed  by  means  of 
individual  questionnaires. In case of  some members’  absence,  interviewers will 
visit  the  respondents  once  again 
in  order  to  complete  the  missing 
questionnaires.  If  more  convenient,  the  forms  may  be  left  to  the  respondents 
for  filling  in  by  themselves.  Interviewers  will  gather  these  questionnaires  on 
prearranged day. 

The survey method will be face-to-face interviews, with a portable computer, for 
the  household  representative  and  for  the  individuals  who  are  10-74  years  old. 
For  the  cases  where  the  interview  to  the  own  person  at  the  dwelling  is  not 
possible, we won’t admit the adoption of proxy interviews (information conceded 
by  another  individual  of  the household, which  is present at  the  moment of  the 
interview). In such cases we’ll use the telephone survey, in order to surpass the 
proxy interviews and ensure a high response rate. 

Slovenia 

Face-to-face 

Slovak Republic 

Face-to-face 

Finland 

CATI 

Sweden 

Telephone interviews 

United Kingdom  All interviews are carried out face-to-face by members of the general field force 
of  the  interviewers  trained  to  carry  out  National  Statistics  surveys.  Advance 
letters are sent to all addresses, prior to the interview, giving a brief account of 
the  survey.  The  interviewing  period  starts  during  the  last  two  weeks  of  the 
month  and  continues  into  the  first  week  of  the  following  month.  Interviewers 
call  at  the  selected  addresses  unless  a  refusal  has  been  made  beforehand  in 
response to the advanced letter. The interviewer makes at least three calls at an 
address at different times of the day and week before coding the household as a 
non-contact. 

Iceland 

Norway 

CATI 

CATI 

Independent versus embedded survey 

For practical reasons, an important number of countries has embedded the ICT usage survey 

into  an  existing  social  survey.  The  main  advantages  of  such  approach  are  a  cost-reduction 

(e.g.  travel  time  for  interviewers)  and  the  fact  that  certain  variables  need  to  be  collected 

only once (this is especially the case for background characteristics such as educational level 

or  employment  situation).  Further,  linking  the  survey  to  an  existing  survey  may  give 

Methodological manual for Information Society Statistics 

165  

 
additional  analytical  possibilities  (e.g.  when  embedded  in  the  EU-SILC,  the  ICT  usage 

pattern can be linked to the individual’s or the household’s living conditions).   

However, although the filtering and routing limits the length of the ICT usage survey, it can 

be very burdensome for the respondents to be expected to give 50 yes/no answers following 

an  already  long  interview  for  the  survey  vehicle,  e.g.  the  Labour  Force  Survey.  As  the  ICT 

usage  questions  will  usually  be  inserted  after  the  questions  of  the  main  survey,  this  can 

have unwanted negative effects on the response rates and the reliability of the answers. 

The  overview  table  indicates  that  a  majority  of  the  countries  has  a  separate  survey, 

although an important number of countries link the ICT usage survey to an existing survey. 

In this case, the ICT usage survey is usually embedded in another social survey such as the 

Labour Force Survey or general-purpose surveys (omnibus, micro-census, etc.). 

Table: Overview of the survey vehicles (2005 survey) 
Source: Interim reports for the Community survey on ICT usage in households and by individuals (2005) 

Belgium 

Labour Force Survey 

Czech Republic 

Labour Force Survey 

Denmark 

Annex to the monthly Danish consumer survey (2004 survey) 

Germany 

Stand-alone survey 

Estonia 

Greece 

Ireland 

Italy 

Labour Force Survey 

Stand-alone survey 

The ICT survey was attached to the Quarterly National Household Survey, which 
collects  information  continuously  throughout  the  year,  with  a  total  sample  of 
39,000 households in each quarter. The QNHS is the national title given to the 
continuous quarterly Labour Force Survey carried out in accordance with Council 
Regulation  577/98.  The  ICT  questionnaire  was  asked  of  direct  respondents  in 
wave 3 households in June of 2005, which constituted approximately one-fifth of 
the total sample of households. 

The module on ICT usage in households and by individuals is embedded in the 
annual  multipurpose  survey  "Aspects  of  Daily  Life"  that    is  the  main  survey  of 
Istat's integrated system of multi-purpose social surveys. This annual survey is 
the  supporting  and  normalising  element  of  the  whole  social  informative 
framework.  It  collects  a  set  of  data  concerning  individuals,  households  and 
events  which  affords  to  construct  and  analyse  the  citizen's  demand,  besides 
comparing it with services supply, already surveyed by Istat. 

Cyprus 

Latvia 

Stand-alone survey 

Stand-alone survey 

Lithuania 

Stand-alone survey 

Luxembourg 

The  EU-ICT-HH-survey  is  embedded  in  another  survey  called  "e-luxembourg", 
which  is  about  the  usage  of  ICT  in  the  Grand-Duchy  of  Luxembourg.  The 
questions of "e-luxembourg" follow the "e-Europe"-indicators. "e-luxembourg" is 
a regular project ordered by the Luxembourg's government since 2001. In order 
to  continue  the  existing  national  statistics,  it  is  necessary  to  conduct  those 
questions of "e-luxembourg" as well, that were originally not included in the EU-
ICT-HH-survey.  The  national  authorities  decided  to  merge  the  two  surveys  in 
order to catch synergies and to lower the response burden for the households. 

Hungary 

Supplementary  survey  to  the  micro-census  2005.  The  socio-demographic 
background characteristics of the households and the individuals of the sample 
will originate from the results of the micro-census. 

Malta 

Stand-alone survey 

Netherlands 

Stand-alone survey 

Methodological manual for Information Society Statistics 

166  

Austria 

Poland 

Labour Force Survey 

Stand-alone survey 

Portugal 

Stand-alone survey 

Slovenia 

Stand-alone survey 

Slovak Republic 

Stand-alone survey 

Finland 

Stand-alone survey 

Sweden 

Labour Force Survey 

United Kingdom 

‘Community  Survey  on  ICT  usage  in  households  and  by  individuals  2005’  is  a 
module  referred  as  ‘Internet  access’  within  the  National  Statistics  Omnibus 
Survey.    The  National  Statistics  Omnibus  Survey  is  a  multi-purpose  survey 
developed  by  the  Office  for  National  Statistics  for  use  by  government 
departments,  other  public  bodies,  charities  and  academics.  It  provides  a  fast, 
cost-effective  and  reliable  way  of  obtaining  information  on  topics  too  brief  to 
warrant a survey of their own, and for topics of immediate interest. Its flexibility 
allows this survey to be used for piloting questions for other surveys. 

Iceland 

Stand-alone survey 

Norway 

Statistics Norway's Omnibus surveys embrace questions on different themes, on 
behalf  of  various  customers.  The  surveys  consist  of  a  permanent  set  of 
background  variables,  in  addition  to  the  questions  of  the  customers.  In  the 
second Omnibus in 2005 questions on use and access to ICT is included. 

Mandatory versus voluntary survey 

Voluntary surveys are usually cheaper, quicker and easier to manage. A mandatory survey 

implies  to  make  several  attempts  to  contact  the  respondent  or  to  send  several  reminders. 

This proces usually makes the collection period longer as one needs to wait a long time for 

all  responses.  The  advantage  of  a  mandatory  survey  is  that  your  response  rate  is  much 

higher, reducing the risk of having serious non-response bias (see also below, 0). 

But a voluntary survey can settle this argument by increasing the sample size and sending 

reminder letters to the respondents. 

In practice, the ICT usage surveys will be mandatory as of 2006 in all EU countries following 

the legal acts (Regulation 808/2004 and Regulation 1099/2005). 

Table: Overview of the modes of survey participation (2005 survey) 
Source: Interim reports for the Community survey on ICT usage in households and by individuals (2005) 

Belgium 

Voluntary module in mandatory LFS 

Czech Republic 

Voluntary 

Denmark 

Voluntary (2004 survey) 

Germany 

Voluntary 

Estonia 

Greece 

Ireland 

Italy 

Voluntary 

Mandatory 

Voluntary 

Mandatory 

Methodological manual for Information Society Statistics 

167  

 
Cyprus 

Latvia 

Mandatory 

Mandatory 

Lithuania 

Voluntary 

Luxembourg 

Voluntary 

Hungary 

Voluntary 

Malta 

Mandatory 

Netherlands 

Voluntary 

Austria 

Poland 

Voluntary 

Voluntary 

Portugal 

Mandatory 

Slovenia 

Voluntary 

Slovak Republic  Mandatory 

Finland 

Voluntary 

Sweden 

Voluntary 

United Kingdom  Voluntary 

Iceland 

Voluntary 

Norway 

Voluntary 

II.2.5. 

Questionnaire – Data collection tool 

To  enhance  the  comparability  across  countries,  Eurostat  provides  a  model  questionnaire  to  the 

NSIs.  It is recommended to adopt the model questionnaire for the national survey. However, for 

practical reasons (for instance linked to the survey vehicle), this may not be appropriate. In this 

case,  the  statistical  institute  should  nevertheless  make  sure  that  the  routing  and  the  filtering is 

followed.  

Eurostat  designs  the  model  questionnaire  in  close  cooperation  with  the  national  statistical 

institutes,  the  main  users  and  in  coordination  with  other  organisations  such  as  the  OECD.  The 

results of previous surveys are taken into account, for instance to assess the relevance of certain 

questions or items, or to assess whether a variable needs to be collected on an annual basis. For 

reasons  linked  to  the  annually  renewed  implementing  measures  for  Regulation  808/2004,  the 

model  questionnaire  needs  to  be  finalised  9  months  before  the  survey  takes  place.  In  practice, 

this  means  that  the  questionnaire  reaches  its  final  status  in  March-April  of  the  year  preceeding 

(T-1) the reference year (T). The obvious disadvantage is that ‘last-minute’ policy needs can’t be 

included or that the results of the T-2 survey can’t be fully taken into account. The advantage is 

that  this  gives  the  NSIs  the  necessary  time  to  translate  the  questionnaire  and  implement  the 

survey. 

The  model  questionnaire  for  the  survey  on  ICT  usage  in  households  and  by  individuals  can  be 

found in Annex II.3.1. 

Methodological manual for Information Society Statistics 

168  

 
 
 
For  a  more  general  discussion  of  questionnaire  design,  the  reader  can  consult  the  Australian 

Bureau of Statistics Forms Design Standards Manual: 

http://www.sch.abs.gov.au/SCH/A1610103.NSF/Survey+Design?OpenView 

II.2.6. 

Quality control systems 

Quality control systems are of course country-specific as most statistical institutes have standard 

procedures and guidelines for plausibility checks or logic tests of datasets. 

Such controls can be executed on-line, at the moment of the data capture by the interviewer or 

the data entry in the statistical institute, or after the data entry process (a program checks the 

data  and  prints  the  errors  to  be  checked  or  corrected).    On-line  tests  have  the  advantage  that 

the  errors  can  be  corrected  immediately  (a  lot  of  errors  will  be  simple  data-entry  errors,  f.i. 

typing 17773 instead of 1773), a disadvantage is that one needs data-entry staff that is familiar 

with the concepts in the survey (in case they have to decide if a certain value will be accepted or 

not).  The  latter  case  of  course  doesn’t  apply  with  CATI  or  CAPI  where  the  interviewer 

immediately enters the data. 

Below, some of the most common errors or problems are briefly discussed. 

Measurement error 

There are a number of sources of measurement error: survey instruments (questionnaire), the 
respondent,  the  information  system,  the  mode  of  data  collection,  the  interviewer.  This 
paragraph  focuses  on  the  latter,  other  types  can  back  below.  The  first  and  probably  most 
important  step  in  the  statistical  process,  is  the  data  collection  or  field  work.  One  can  design 
excellent  questionnaires,  excellent  capture  tools,  excellent  imputation  methods  and  excellent 
data analyses, but as with any process the adagium ‘Garbage In Garbage Out’ also applies to 
statistics. If the interviewer is not well-trained, one can’t expect input data of a good quality. A 
more  important  problem  is  usually  the  reliability  of  the  interviewers.  The  interviewers  may 
have  an  interest  in  finishing  the  interviewers  in  the  shortest  possible  time.  This  can  lead  to 
interviews  where  certain  questions  are  skipped  (e.g.  the  person  looks  poor,  let’s  fill  in  he’s 
unemployed)  or  interviews  that  never  took  place  (e.g.  the  person  is  70  years  old,  let’s  put 
down  he  never  used  a  computer  nor  Internet).  Therefore  the  sensibilation  of  interviewers 
(which  can  include  threats  of  non-payment  or  exclusion  for  future  interview  rounds)  and  the 
follow-up is extremely important. The follow-up can be a check for coherence and consistency 
of  the  answers  or  follow-up  phone  calls  to  verify  with  the  respondents  whether  the  interview 
has  actually  taken  place  or  whether  the  interview  was  of  an  acceptable  quality  (e.g.  the 
respondent confirms that the interview only took 4 minutes, but on the questionnaire answers 
to 60 questions were recorded). 

Invalid response 

Relatively  unimportant  in  the  ICT  usage  survey  as  most  answers  are  limited  to  Yes  or  No. 
However,  it  is  possible  that  several  items  were  ticked  in  questions  where  only  one  answer  is 
expected. 

Relationship error 

Comparing the answers across the survey can reveal inconsistencies between the answers. The 
routing  and  filtering  should  normally  guarantee  that  respondents  are  not  presented  with 
questions  they  can’t  answer.  It  is  nevertheless  possible  that  e.g.  an  individual  aged  18 
indicates higher educational level or that an unemployed person indicates ‘place of work’ as a 
location  where  the  Internet  has  been  accessed.  In  the  first  case,  this  is  most  probably  an 

Methodological manual for Information Society Statistics 

169  

 
 
 
absolute error. In the latter case the combination is possible if the respondent lost his job only 
very recently (meaning he could have accessed the Internet at a place of work during the last 
3 months). 

Compulsory question left unanswered 

Again, the routing and filtering should avoid this type of errors. CATI or CAPI programs usually 
improve  the  quality  of  the  data  capture  in  this  respect.  With  traditional  interviews  or  self-
administered mail surveys, this error is more important. 

Suspicious values 

This  can  occur  when  the  individual  responses  are  compared  with  the  average  scores  within  a 
stratum and unexpected answers are found. In practice it will however be difficult to determine 
whether it concerns a mistake or an outlier. 

In terms of quality of the  survey as  such, the methodology and outcomes of  the survey can be 

benchmarked against other surveys: 

Representativeness 

It can be useful to do an ex-post check of the representativeness of the sample, e.g. does the 
sample have a representative age distribution, is there some variability in the occupational and 
educational codes? 

Year-to-year comparison at aggregate level 

Comparing  the  results  for  the  current  year  with  the  previous  survey  can  also  reveal  quality 
problems where the growth is outside the range of the expected growth (e.g. the proportion of 
individuals  using  the  Internet  decreases  …).  In  such  cases,  it  is  of  course  possible  that  the 
problem stems from the previous survey exercise … 
For this purpose, it can be interesting to produce some simple tabulations of the survey results.  

Coherence or consistency with other surveys 

The  results  can  be  compared  with  results  from  related  survey  or  studies.  However,  in  case 
inconsistent  results  are  observed,  it  is  not  always  easy  to  identify  which  survey  gave  the 
‘wrong’ results. 

Methodological manual for Information Society Statistics 

170  

 
 
 
II.2.7. 

Data processing 

This chapter mainly discusses the treatment of non-response. Although the grossing-up methods 

can  be  considered  as  a  part  of  the  data  processing,  this  topic  is  discussed  above  in  section 

II.2.3.3. 

II.2.7.1  MISCLASSIFICATION TREATMENT 

Not applicable to the household survey. 

II.2.7.2  NON-RESPONSE TREATMENT4 

Introduction 

An  important  source  of  non-sampling  error  in  surveys  is  the  effect  of  non-response  on  the 

survey  results.  Non-response  can  be  defined  as  the  failure  to  obtain  complete 

measurements  on  the  (eligible)  survey  sample.  The  extent  of  non-response  varies  from 

partial non-response (failure to answer just one or some questions) to total non-response.  

The latter case occurs when the interviewer was either unable to contact the respondent, no 

member  of  the  household  was  able  to  provide  the  information,  the  respondent  refused  to 

participate  in  the  survey  or  not  enough  information  was  collected  in  the  interview  (i.e.  the 

response  is  too  incomplete  to  be  useful).  This  type  of  non-response  is  called  unit  non-

response  (§2.7.2.1):  the  sample  unit  does  not  provide  any  of  the  data  required  by  the 

survey.  Unit  non-response  is  generally  handled  by  adjusting  the  weight  of  the  households 

and/or  individuals  that  responded  to  the  survey  to  compensate  for  those  that  did  not 

respond. 

Partial non-response or item non-response (§2.7.2.2) occurs when the respondents did not 

answer all questions because they did not understand or misinterpreted a question, refused 

to  answer  a  question  or  could  not  recall  the  requested  information.  Item  non-response  is 

generally dealt with by imputation. 

4 References for this chapter: 

•  Government Statistical Service (1997), Report of the Task Force on Imputation – June 1996. Government Statistical 

Service Methodology Series No. 3. London: Office for National Statistics. 

•  Statistics Canada (2003), Household Internet Use Survey, 2002 – Microdata User Guide. 
•  European Commission (2003), Household Budget Surveys in the EU: Methodology and recommendations for 

harmonisation 2003. Luxembourg: Office for Official Publications of the European Communities. 

•  National Centre for Social Research (1999), Item non-response (different contributions). Survey Methods Newsletter 

Volume 10 No.2 1999.  

•  Adjusting for Missing Data, Mohadjer, L., Choudhry, H., Studies of welfare populations: Data Collection and research 

Issues, 2001. 

•  Introduction to Survey Quality, Biemer, P., Lyberg, L., Wiley series in survey methodology, 2003. 
•  Weighting for non-response, Lynn, P., Survey and Statistical Computing, 1996. 
•  Non-response in the Norwegian Business Tendency Survey, Wang, J., Statistics Norway, 2004. 

Methodological manual for Information Society Statistics 

171  

 
                                                
Effect of non-response on the quality of the data 

Non-response  –  unit  as  well  as  item  non-response  – can  seriously  affect  the  quality  of  the 

data  collected  in  a  survey.  Firstly,  the  characteristics  (or  answering  pattern)  of  the  non-

respondents can be different from those collected among the sample units who did provide 

eligible  answers.  If  such  difference  is  systematic,  serious  bias  can  be  introduced  in  the 

survey results. Secondly, the reduction of the sample size (overall or for certain questions) 

will increase the variance of the estimates. Thirdly, non-response can have an impact on the 

total cost of a survey exercise. Not only because  a  larger initial sample may  be necessary, 

but  also  because  of  higher  unit  costs  of  the  last  few  percentages  of  respondents  (due  to 

multiple  visits).  Finally,  non-response  can  be  an  indicator  of  poor  overall  quality  of  the 

survey and thus create an image or confidence problem. 

Minimising non-response 

As prevention is always better than cure, attention should be given to avoiding non-response 

rather  than  treating  non-response.  The  number  (and  timing)  of  reminder  letters  or  call 

backs,  the  length  of  the  fieldwork  period,  the  survey  technique(s)  used,  the  length  of  the 

survey  (i.e.  the  response  burden),  the  use  and  structure  of  advance  letters,  the 

dissemination  of  previous  results  or    the  mandatory  nature  of  the  survey  can  all  have  an 

impact on the number of non-contacts or refusals. The length, design and complexity of the 

questionnaire, the interviewer’s training or the interviewer’s style can have an impact on the 

item non-response. 

As this issue is common to all surveys, it will not be discussed in detail in this manual. This 

chapter  is  mainly  focussed  on  the  treatment  of  non-response  in  the  specific  context  of  the 

ICT usage survey. 

UNIT NON-RESPONSE 

Introduction 

Unit non-response is defined as households/persons that are included in the sample but that 

have not participated to the survey and for which information consequently is missing for all 

the questionnaire variables.  

Types of non-respondents include: 

• 

• 

• 

• 

• 

• 

• 

Non-contact 

Refusals 

Inability to respond 

Rejected interviews 

Ineligible: out-of-scope 

Other ineligible 

Other non-response 

Methodological manual for Information Society Statistics 

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Unit  non-response  can  introduce  bias  in  the  survey  results  especially  in  situations  in  which 

the  non-responding  units  are  not  representative  of  those  that  responded.  Non-response 

increases both the sampling error, by decreasing the sample size, and non-sampling errors. 

An  overview  of  the  non-response  patterns  in  the  2004  survey  (based  on  the  2004  Final 

Reports)  can  be  found  above  (II.2.3.2,  Sample  size).  It  is  clear  that  in  most  countries  the 

unit non-response is important with rates of 25% and more, with non-contacts and refusals 

as the main types of non-response. 

Weighting adjustment for unit non-response 

The  principal  method  for  unit  non-response  adjustment  is  weighting.  Most  strategies  for 

weighting  for  non-response  involve  dividing  the  respondents  into  a  set  of  comprehensive 

and mutually exclusive groups, referred to as weighting classes. A weight is then applied to 

each class.  

Weighting classes 

In  order  to  implement  non-response  adjustments,  it  is  required  to  create  weighting 

classes. It is desirable to divide the sample in "response homogeneity groups/classes". 

Within these classes the respond rates should be as homogeneous as possible, and the 

response  rate  should  be  different  among  the  classes.  Data  used  to  form  these  classes 

must be available to both non-respondents and respondents. Usually it is possible to get 

information  about  demographical  (age,  gender,  ethnicity),  geographical  (urban/rural, 

zip code) or socioeconomical (employment, income) variables from administrative data.  

More  advanced  methods  for  creating  weighting  classes  is  methods  like  classification 

based  on  a  categorical  search  algorithm  or  a  logistic  regression  model  using  auxiliary 

variables to estimate the probability of response. 

Sample-Based Weighting Adjustment 

In sample-based weighting adjustment the weight  adjustment applied in each class, is 

equal to the reciprocal of the ratio of selected sample size to respondents within each of 

these  classes  (the  inverse  of  the  response  rate  within  each  class).  This  non-response 

adjustment factor should be multiplied with the initial base weight. 

A simple example: 

Population 
(I) 

Sample 
size  
(II) 

Respondents 
(III) 

Respondent 
with 
characteristic 
(IV)  

Non-response 
adjustment 
Factor 
(V = II / III) 

Initial 
Base 
Weight 
(I / II = VI) 

Adjusted 
Base 
Weight 
(V*VI=VII) 

Adjusted 
population 
estimate 
(=VIII) 

Male 

8 820 000 

2 100 

1 600 

Female  9 020 000 

2 200 

1 750 

Total 

17 840 000 

4 300 

3 350 

1 000 

1 200 

2 200 

1.31 

1.26 

4 200 

5 502 

5 502 000 

4 100 

5 166 

6 199 200 

11 701 200 

Alternative  forms  of  sample-based  weighting  are  that  the  weights  are  not  inverse 

response  rates,  but  estimated  coefficients  of  a  regression  model  (where  survey 

Methodological manual for Information Society Statistics 

173  

 
 
 
 
 
response is the left-side variable). In this case, the weights are reciprocals of estimated 

response rate by the regression model. 

Population-Based Weighting Adjustment 

Population-based  weighting  adjustment  requires  population  estimates  and  class 

membership  of  respondents.  If  there  is  no  data  available  about  the  non-respondents, 

population-based adjustment still is possible since this uses external control counts for 

the  population  and  not  data  from  the  sample.  The  method  is  used  to  correct 

simultaneously for both non-coverage and non-respondents. The method is used similar 

to the sample-based method. 

In population-based adjustment (poststratification adjustment) the classes are  created 

based  on  variables,  which  are    known  both  for  respondents  and  for  the  population. 

Weights are then applied in proportion to the ratio of population to achieved sample, so 

that the sums of the adjusted weights are equal to population totals for certain classes 

of the population.  

A two-step procedure of first adjusting for non-response (sample-based adjusting) and 

then adjusting to known population counts is a common method that is used. However, 

this procedure is the same as a population-based weighting adjustment if the weighting 

classes in the sample-based and the population-based weighting adjustment are equal.  

If the strata used in the stratification are used as classes in the weighting adjustment, 

there  is  no  need  for  the  weighting  adjustment.  The  adjusted  weighting  procedure  is 

then equal to the final grossing up/weighting procedure. 

ITEM NON-RESPONSE 

Introduction 

As  already  mentioned  above,  there  are  several  reasons  for  the  data  being  unavailable  . 

These  include  the  refusal  to  provide  an  answer,  the  inability  to  provide  an  answer, 

inadequate  quality  of  the  provided  answer  (e.g.  implausible,  incomplete,  inconsistent  with 

answers to other questions, etc.). It can be caused by either the respondent (e.g. refusal) or 

the interviewer (e.g. failure to record the answer adequately) but also by the survey design 

itself (e.g. ambiguous routing or filtering).  

In case a particular questionnaire shows too many errors, or if too many data are missing, it 

can be assumed that the household/individual in question has not co-operated satisfactorily 

in  the  survey.  Here,  the  best  solution  is  probably to  remove  the  household/individual  from 

the database and adjust the weighting coefficients for the other households accordingly. In 

other words, sampling units with a very high item non-response can better be classified as 

total  non-response  or  unit  non-response  (cf.  the  category  rejected  interviews  in  the 

reporting template in §2.8). It is however difficult to define a threshold as not all questions 

are  equally  important  (i.e.  having  missing  data  on  four  crucial  indicator  can  possibly  be 

worse than missing data on eight questions of secondary importance). 

Methodological manual for Information Society Statistics 

174  

 
 
In other cases where the household/individual has supplied high-quality information for most 

variables  but  for  which  data  on  other  variables  are  missing,  the  missing  data  can  be 

estimated  by  using  appropriate  imputation  techniques.  The  imputed  values  are  supplied  in 

such  a  way  as  to  preserve  the  underlying  structure  of  the  data  and  to  ensure  that  the 

resulting  records  will  pass  all  required  edits  or  plausibility  checks.  In  other  words,  the 

objective  is  not  to  reproduce  the  true  microdata  value,  but  rather  to  establish  internally 

consistent data records that yield good aggregate estimates. 

Where, for a specific variable, the proportion of missing data in relation to the total number 

of  households  exceeds  a  certain  threshold,  it  must  be  asked  whether  or  not  imputation  is 

still appropriate as this variable can probably not be used for analytical purposes. High item 

non-response  (e.g.  more  than  20%  non-response)  on  a  specific  question  across  several 

countries, can be a good reason to consider dropping or modifying the question or variable. 

It should be stressed that the detection and imputation of missing data is to be done by the 

national  statistical  offices  as  Eurostat  only  receives  aggregated  tables  which  do  not  allow 

imputations. 

Why  treating  non-response  in  the  survey  on  ICT  usage  by  households  and 

individuals? 

Most methods of compensating for missing items implicitly or explicitly make the assumption 

that data are missing at random . That is, the probability of an item being missing does not 

depend of the value of the missing item. 

In  our  survey  on  households’  usage  of  information  and  communication  technologies  there 

are without any doubt systematic patterns in the occurrence of non-response. It is obvious 

that non-response may be higher among older respondents or lower educated respondents 

as they are more at risk of not understanding the questions. We can take this into account 

by imputing within strata or classes. But the risk of wrongly imputing the data of ICT users 

(who  feel  concerned  and  “happily”  answer  the  questions)  to  non  ICT  users  (who  drop  out 

because  they  consider  themselves  not  concerned  by  the  survey)  remains  when  it  is  the 

research variable itself (e.g. internet use) which may be the critical factor for the willingness 

or ability to provide an answer. 

The  logical  solution  to  this  problem  would  be  not  to  impute  at  all.  However  not  imputing 

does not exist as there is always an implicit imputation.  

This is obviously the case where a respondent is dropped: the status moves from item non-

response to unit non-response, which will normally be solved by changing the extrapolation 

weight of the other respondents (and this basically comes down to a mean imputation …). 

Where  the  statistician  decides  to  preserve  the  collected  data  instead  of  imputing,  the  user 

will in most cases do make an implicit imputation of the  “non-stated” cases. Let’s take the 

following numerical example (“did you use internet during the past 3 months”): 

Methodological manual for Information Society Statistics 

175  

 
 
Answering category 

Number of respondents (grossed up) 

Percentage 

Yes 

No 

Non-stated (missing) 

Total 

924 000 

1 980 000 

1 496 000 

4 400 000 

21,0% 

45,0% 

34,0% 

100,0% 

The proportion of persons using the internet can be calculated in two ways: 
▪  Number of Yes answers compared to total population: 924 000 / 4 400 000 = 21,0% 
▪  Number of Yes answers compared to total respondents (Yes + No): 924 000 / 2 904 000 = 31,8% 

In  a  realistic  setting,  the end-user  will  only  be interested in  the  proportion  of  users,  not  in 

the  percentage  of  non-users  and  definitely  not  in  the  number  of  Non-stated.  If  these  Non-

stated  are  mentioned  separately,  they  will  most  probably  be  overlooked  by  the  user  or 

interpreted in different ways by different users – by accident or on purpose (which is not a 

good thing in terms of transparency and relevance of the official statistics). 

Both results above suffer from silent or implicit imputation. In the first case, the Non-stated 

cases are treated as ‘No’ answers. This bears the risk of overestimating the number of non-

users:   whether one  uses  the internet is in any case not the only  factor affecting response 

rates in household surveys.  

In  the  second  case,  there  is  a  risk  of  overestimating  the  number  of  users:  the  underlying 

distribution  of  ‘Yes’  and  ‘No'  answers  in  the  ‘Non-stated’  group  is  implicitly  supposed  to  be 

identical  to  the  distribution  in  the  group  of  respondents  while  the  incidence  of  non-use  is 

expected to be higher among the non-respondents. 

The true value (or better: most suitable estimate) is somewhere in between, but unknown. 

The  easy  to  implement  mean  imputation  (see  below)  will  normally  give  exactly  the  same 

proportion of internet users as the case where we only take into account the respondents , 

but  it  should  be  remembered  that  this  method  is  the  ‘worst  imputation  scenario’  where  no 

additional  information  is  taken  into  account.  More  intelligent  methods  would  give  more 

accurate  estimates.  E.g.  in  a  postal  survey  the  respective  response  pattern  of  the 

consecutive  reception  waves  can  help  fine-tuning  the  imputation:  if  response  to  our 

questionnaire  is  related  to  ICT  use,  the  questionnaires  received  after  a  first  or  second 

reminder  letter  will  show  lower  internet  use  figures.  Such  degressive  pattern  could  be 

introduced in the imputation process if we assume that non-response is the extreme case of 

a late reply. 

How  to  treat  non-response  in  the  survey  on  ICT  usage  by  households  and 

individuals? 

The choice of the imputation method is at the discretion of the national statistical institutes, 

but  a  number  of  options  are  briefly  discussed  in  this  section  .  As  experiences  with  the 

application  of  different  methods  are  still  missing,  putting  forward  one  particular  method  is 

not desirable at this stage. A more detailed discussion of these and other methods is beyond 

Methodological manual for Information Society Statistics 

176  

 
 
 
the scope of this manual, but can be found in the extensive literature on the issue of dealing 

with non-response.  

Deductive methods 

These methods are rather related to heuristics than to modelling. They try to deduct the 

most  logical  answer  using  the  available  information  for  the  household  or  individual.  In 

general,  such  procedures  will  be  part  of  the  validation  checks  and  not  of  the  non-

response treatment. 

Example:  the  respondent  did  not  state  whether  s/he  uses  internet  but  from  his  other 

answers,  we  know  s/he  doesn’t  use  a  computer.  In  this  case,  the  most 

obvious value to impute for internet use would be No. Wrong imputations will 

occur  if  this  specific  person  only  uses  internet  by  means  of  a  mobile  phone, 

TV, etc. 

Imputing the mean or mode 

This method consists of imputing missing values by the mean observed in the group of 

respondents in case of numerical variables or the mode in case of categorical or binary 

variables.  

Instead  of  imputing  the  overall  mean  or  mode,  usually,  the  imputation  will  be  done 

taking  into  account  some  background  characteristics  of  the  household  :  before 

imputing,  the  respondents  are  grouped  into  different  classes  according  to  background 

variables such as age group, gender and educational level; the breakdown variables can 

however  also  include  study  variables  (e.g.  computer  users  versus  non  users).  Within 

each group, the class mean or class mode is imputed to cases with missing values. The 

classes may be different for each variable to be imputed. 

The  big  advantage  of  this  method  is  that  it  is  very  easy  to  implement  and  to  explain. 

The main drawback is that it may compress the distribution of the survey variables (as 

the less popular items will probably never serve as a donor).  

Example: in the class ‘age group 45-54’ x ‘lower educational level’ x ‘male’, 20% of the 

respondents  appear  to  use  internet  (while  80%  don’t).  The  most  popular 

answer  –  in  other  words,  the  mode  –  is  No.  Therefore,  all  non-respondents 

will  be  imputed  with  a  No  value  (which  means  approximately  20%  of  those 

may be misclassified – to avoid this problem one can try the next technique). 

Hot deck imputation 

For  each  respondent  with  a  missing  value  for  a  specific  variable,  this  value  will  be 

imputed  with  the  corresponding  value  from  the  previous  respondent  in  the  database 

with a valid response on this variable. Usually, this method is applied within classes in 

order to improve the quality of the imputations. 

After  fixing  a  starting  value  for  each  item  and  each  class,  each  case  is  processed 

sequentially.  If  the  case  has  a  missing  item,  this  is  replaced  by  the  imputation  value 

from  the  relevant  class.  If  the  item  is  not  missing,  it  replaces  the  stored  initial 

Methodological manual for Information Society Statistics 

177  

imputation  value  for  its  class,  and  can  be  used  for  imputation  of  subsequent  missing 

items.  

Closely  related  to  this  sequential  hot  deck  imputation,  is  hierarchical  hot  deck 

imputation. Here, a lot more imputation classes can be considered as the boundaries of 

the  classes  are  not  fixed.  When  no  suitable  donor  is  found  at  the  finest  level  of  the 

classification,  classes  can  be  collapsed  into  broader  groups  until  a  donor  is  found. 

Taking  into  account  the  relatively  small  sample  sizes  used  in  our  ICT  survey,  the 

hierarchical  hot  deck  imputation  may  be  less  appropriate  than  the  sequential  variant 

(there are probably not enough cases available to fill the high number of classes). 

These  methods  are  relatively  simple  to  execute,  assign  real/existing  values  to  a  non-

respondent  and  better  respect  the  underlying  distribution  than  the  mean  or  mode 

imputation.  On  the  other  hand,  the  algorithms  may  be  more  difficult  to  program 

(especially in the case of hierarchical hot deck) and there is a risk that one donor value 

is used several times (in case successive cases all show a missing value). 

Nearest-neighbour imputation 

This method relies on being able to identify the distance between any two  units based 

on some suitable distance measure.  

Regression imputation 

Imputing  by  regression  methods  is  usually  carried  out  one  variable  at  the  time.  The 

methods require that the values of one or more auxiliary variables are known for both 

the  complete  cases  on  which  the  variable  of  interest  is  recorded  and  for  the  missing 

cases.  A  regression  model  is  fitted  that  relates  the  variable  of  interest  to  the  set  of 

auxiliary  variables.  For  categorical  variables,  particularly  binary  variables,  logistic 

regression is usually used. In this case, the imputed value will usually be the value with 

the  higher  predicted  probability.  For  categorical  variables  with  many  categories,  this 

method is less suited. For binary variables, more complex methods such as discriminant 

analysis could also be used. 

Indicating  an  optimal  imputation  method  is  difficult.  The  best  method  will  depend  on  the 

data  available,  the  nature  of  the  survey  and  of  course  the  nature  of  the  question  (binary, 

numerical, etc.).  

A general rule of thumb is however that the more simple methods such as mode imputation 

within classes or sequential hot deck do not necessary give poorer results than the advanced 

methods using modelling. This argument will even be stronger when making a cost/benefit 

analysis (in terms of processing and programming time). 

I.1.1.1 

COMPUTING ACCURACY MEASURES 

The  use  of  a  sample  survey  unavoidably  leads  to  sampling  error.  To  get  an  idea  of  the 

sampling error, it is advised to compute this error for certain indicators.  Such information is 

Methodological manual for Information Society Statistics 

178  

 
 
not  only  interesting  to  decide  whether  the  indicator  is  reliable  enough  to  be published,  but 

can also help to determine whether the sample size should be increased in a next edition of 

the survey for certain strata where a large sampling error was diagnosed. 

The sampling error reflects the fact that only a particular sample was surveyed rather than 

the entire population. The (estimated) relative standard error – or (estimated) coefficient of 

variation  (CV)  –  is  the  ratio  of  the  square  root  of  the  variance  of  the  estimator  for  the 

proportion to the expected value of the proportion. It is estimated by the ratio of the square 

root of the estimate of the sampling variance to the estimated value (see also Chapter 9 of 

the  Reporting  template,  Annex  II.3.3).  The  estimation  of  the  sampling  variance  should 

ideally take into account the sampling design (e.g. the stratification).  

Some  guidelines  for  interpretation  and  use  of  the  coefficients  of  variation  can  be  found  in 

section II.2.3 where the sampling design is discussed. 

The computated accuracy measures will also determine the reliability of the estimates. If the 

coefficient of variation for a certain proportion or absolute value is too high, the cell needs to 

be suppressed.   

To  avoid  that  the  level  of  the  estimate  has  an  extreme  impact  on  the  accuracy  measure 

(e.g.  a  proportion  of  1%  leads  to  a  denominator  of 0,01  when  calculating  the  CV,  in  other 

words, the standard deviation is multiplied by 100), the standard deviation (i.e. the square 

root of the sampling variance) could be used as a reference measure. 

In  case  the  computation  of  the  standard  deviation  or  coefficient  of  variation  for  all  cells  is 

not  feasible,  the  number  of  respondents  underlying  the  estimate  can  be  used  to  decide 

whether  a  proportion  can  be  published  (e.g.  if  based  on  less  than  10  respondents,  the 

estimate is not published). 

The  table  on  the  next  page  gives  an  overview  of  the  sampling  error  for  one  proportion, 

namely the proportion of individuals regularly using the Internet (i.e. at least once a week in 

the three months preceeding the interview).  The table clearly indicate the parameters that 

affect  the  sampling  error:  the  estimate  (i.e.  the  actual  proportion,  in  this  case  the  level  of 

Internet  use)  and  the  sample  size  (though  only  the  total  sample  size  for  the  survey  is 

presented in the table – between brackets next to the country name). 

Although  the  overall  proportions  (i.e.  for  all  individuals)  are  relatively  accurate  in  all 

countries,  the  situation  is  different  when  looking  at  the  accuracy  for  the  breakdowns.  The 

breakdown  between  men  and  women  doesn’t  really  affect  the  quality  of  the  estimates, 

because  of  the  absence  of  a  strong  relation  between  Internet  use  and  gender  and  hence 

relatively equal sample sizes for the two groups.  

For the breakdown by age group, the situation is more problematic. In the older age groups, 

the  sample  Internet  users  is  becoming  very  small  (because  of  the  filter  in  the 

questionnaire), which leads to unreliable estimates in most cases.  These conclusions can be 

taken into account when designing the sample, e.g. by including relatively more respondents 

in  the  sample  for  strata  where  poor  quality  in  terms  of  accuracy  can  be  expected  (such 

overrepresentation  should  of  course  be  compensated  for  in  the  weighting).  Unfortunately, 

cost restrictions may not always allow for larger samples and reducing the sample size (and 

accuracy?) in other strata may not be the optimal trade-off either. 

Table: Sampling error for the proportion of regular Internet users (2004 survey) 
Source: Final reports for the Community survey on ICT usage in households and by individuals (2004) 

(next page) 

Methodological manual for Information Society Statistics 

179  

Country
(survey net sample size)

Denmark (2899)

Estimated proportion
Coefficient of variation

Germany (8887)

Estimated proportion
Coefficient of variation

Greece (4180)

Estimated proportion
Coefficient of variation

Spain (n/a)

Estimated proportion
Coefficient of variation

Ireland (4638)

Estimated proportion
Coefficient of variation

Latvia (6508)

Estimated proportion
Coefficient of variation

Luxembourg (1535)

Estimated proportion
Coefficient of variation

Hungary (3860)

Estimated proportion
Coefficient of variation

Austria (5646)

Estimated proportion
Coefficient of variation

Poland (8839)

Estimated proportion
Coefficient of variation

Portugal (10343)

Estimated proportion
Coefficient of variation

Slovenia (1455)

Estimated proportion
Coefficient of variation

Slovakia (4741)

Estimated proportion
Coefficient of variation

Finland (3134)

Estimated proportion
Coefficient of variation

Sweden (3626)

Estimated proportion
Coefficient of variation
United Kingdom (2973)
Estimated proportion
Coefficient of variation

Bulgaria (9785)

Estimated proportion
Coefficient of variation

Romania (3317)

Estimated proportion
Coefficient of variation

Iceland (1633)

Estimated proportion
Coefficient of variation

Norway (1188)

Estimated proportion
Coefficient of variation

Proportion of individuals regularly using the Internet

All

Men

Women 16-24 yr

25-34 yr

35-44 yr

45-54 yr

55-64 yr

65-74 yr

70.0
1.2

50.0
1.3

17.3
3.5

40.4
1.3

37.0
3.4

27.3
4.8

59.0
1.6

28.6
2.5

46.1
0.9

22.4
2.6

25.1
1.4

33.4
4.5

39.8
1.6

72.4
1.1

75.0
1.0

77.0
2.0

13.5
3.8

9.9
3.6

77.0
1.2

77.7
1.3

73.0
1.6

55.0
2.5

59.5
2.9

44.9
1.7

37.0
4.4

27.6
5.0

34.0
1.4

31.1
3.5

52.9
1.2

23.6
3.1

27.1
1.8

35.6
6.1

21.6
2.3

72.3
1.6

78.0
1.2

82.0
2.0

7.1
5.5

52.7
1.9

79.0
1.6

80.8
1.8

66.0
1.9

44.0
2.6

40.5
4.2

35.9
1.7

37.0
3.4

27.0
5.4

25.0
2.0

26.6
3.6

39.4
1.1

21.4
3.4

23.2
1.4

31.3
6.3

18.2
2.7

72.5
1.5

73.0
1.4

72.0
2.0

6.4
5.8

47.3
2.1

75.0
1.8

74.5
1.9

82.0
2.8

78.0
5.0

33.4
5.1

75.5
1.9

49.0
4.7

53.9
3.2

11.0
3.9

71.6
3.0

69.3
2.0

49.5
2.9

54.0
5.9

66.4
5.5

12.3
4.1

97.5
0.7

92.0
1.2

78.0
4.0

5.4
6.4

40.8
3.2

91.0
1.6

98.4
0.9

79.0
2.4

72.0
7.3

30.4
5.3

57.6
2.1

48.0
4.3

41.2
5.5

13.0
3.4

45.1
4.5

65.3
2.1

30.7
4.6

36.9
3.9

53.9
7.5

9.8
3.3

95.6
1.0

87.0
1.4

80.0
3.0

3.8
7.7

25.2
5.0

87.0
1.9

92.1
2.0

80.0
1.9

60.0
4.4

23.9
5.8

43.4
2.5

43.0
3.4

28.9
6.3

16.0
3.0

33.4
5.9

53.0
1.7

18.0
6.5

25.2
2.6

31.2
10.5

8.4
3.2

86.8
1.6

82.0
1.7

82.0
3.0

2.2
10.1

17.9
5.6

82.0
2.3

88.6
2.2

73.0
2.6

49.0
6.2

9.7
10.8

29.7
4.0

32.0
4.9

19.2
11.7

12.0
4.3

24.0
6.5

42.1
2.0

14.6
6.4

17.5
2.2

26.3
10.8

7.5
4.0

71.3
2.6

76.0
2.1

72.0
4.0

1.6
12.0

13.3
7.1

75.0
3.0

80.7
3.4

59.0
3.6

27.0
11.8

2.0
24.4

13.7
7.1

17.0
9.5

8.0
15.4

6.0
8.3

11.1
11.1

23.6
1.6

7.3
12.5

7.0
1.2

8.2
21.3

1.5
7.6

55.3
3.7

64.0
2.8

75.0
4.0

0.5
22.1

2.5
17.1

59.0
5.3

57.9
6.0

26.0
9.0

13.0
35.7

0.7
41.1

2.9
15.6

6.0
11.9

1.3
61.2

2.0
23.2

2.9
26.3

6.6
1.1

1.5
31.2

1.1
0.6

1.0
71.8

0.4
21.5

13.5
1.3

41.0
19.5

67.0
9.0

0.1
53.3

0.3
45.8

29.0
12.0

22.2
17.4

Methodological manual for Information Society Statistics 

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II.2.8. 

Survey execution reports 

Drawing up reports after the execution of the survey is  not only a tool for a  self-assessment of 

the  work  carried  out  by  the  statistical  office  and  a  detection  of  possible  points  where  there  is 

space of improvement.  Survey execution reports are also a tool for assessing the comparability 

from one year to another or from one country to another. 

The methodological reports for the  ICT usage surveys coordinated by Eurostat should cover the 

following subjects: 

l.  General methodological information: reference period(s); survey period; survey vehicle, 

where  applicable;  survey  type;  pre-tests;  methodological  differences  compared  to 

previous data collection exercises. 

m. Statistical  unit(s),  scope  and  target  population:  statistical  unit;  age  groups  covered; 

territorial  coverage;  target  population  for  households  and  for  individuals;  non-target 

population for households and for individuals. 

n.  Information on the national questionnaire. 

o.  Sampling frame : name and description of the sampling frame or register used ; known 

shortcomings of the sampling frame, if any. 

p.  Sampling design: sampling method; additional measures taken at the time of sampling 

design to improve representativeness. 

q.  Unit non-response at household and at individual level, by giving information on: gross 

sample size; number of out-of-scope cases, number of other ineligible cases; number of 

eligible elements; number of non-contacts; number of refusals; number of cases unable 

to  respond;  number  of  rejected  interviews;  other  non-response;  net  sample  size;  unit 

response  rate.    Additionally,  the  report  shall  discuss  the  methods  used  for  minimizing 

non-response as well as the methods used for dealing with unit non-response. 

r.  Item  non-response:  variables  or  items  with  item  response  rates  below  90%;  methods 

used for dealing with item non-response. 

s.  Grossing-up procedures for households. 

t.  Grossing-up procedures for individuals. 

u.  Sampling  error:  the  report  shall  indicate  the  coefficient  of  variation  (relative  standard 

error)  for  a  selected  group  of  indicators  or  subindicators  listed  in  the  template  to  be 

provided by the Commission. 

v.  Problems encountered and lessons to be learnt. 

w.  The  report  should  include  the  questionnaire  in  national  language  and,  if  available,  in 

English.The  statistical  unit  is  the  base  type  of  the  elements  of  a  group  (also  called 

population)  that  we  want  to  observe  or  analyse.  The  basic  statistical  operations  of 

classification, aggregation and ordering are done on the statistical unit. 

The  Reporting  template  used  for  the  European  ICT  usage  surveys,  including  some  instructions, 

can be found in Annex II.3.3  

(see document MM2006_AnnexII.3.3_ReportingTemplateHH2005rev1.doc (14 pages)) 

This  template  covers  both  the  Metadata  report  (formerly  known  as  Interim  Report)  and  the 

Quality report (formerly known as Final Report) referred to in Article 7(4) of Regulation 808/2004 

(see Annex III.1) and in Annex II, chapter 6 of Regulation 1099/2005 (see Annex III.2). 

Methodological manual for Information Society Statistics 

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II.3.  ANNEXES 

II.3.1. 

Model questionnaire 

Version 2.2, 31 August 2005. 

EUROSTAT MODEL FOR A COMMUNITY SURVEY ON ICT USAGE IN HOUSEHOLDS AND BY INDIVIDUALS 

2006 

EUROSTAT MODEL QUESTIONNAIRE (V2.2) 

[Questions relating to the eEurope 2005 Benchmarking Indicators are marked with an asterisk *] 

Module A

Access to Information and Communication Technologies

Note : this module is directed to the household

 A1 Do you or anyone in your household have access to any of the following devices at home? 

(tick all that apply)

a) TV …………………………………………………………………………………………...……….

if yes to c) ,  a1) satellite dish ……………………………….……………………………………………...…

a2) cable TV ………………………………………………………...………………………...…

a3) digital TV ……………………………………………………….……………………………...……………

b) Fixed telephone line ……………………………………………..………………………………………………………

c) Mobile phone ……………………………………………………………………………...…………………………….

d) if yes to c) , Internet enabled mobile phone (WAP, GPRS, UMTS, etc.)………………….……………..………………………………………….

e) Games console ……………………………………………….……………………………………...…….

f) Desktop computer ……………………………………………………………………………………………

g) Portable computer (laptop) …………………………………………………………………………………..

h) Handheld computer (palmtop) …………………………………………………………………..…………………………

i) None of the above ………………………………………………………………………………………….

[ -> go to A2 ]

A2* Do you or anyone in your household have access to the Internet at home, 

regardless of whether it is used?

Yes

No

[ -> go to A3 ]

[ -> go to A5 ]

Don't know

[ -> go to B1 ]

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A3* On which of these devices is the Internet accessed at home?

(tick all that apply)

a) Desktop computer ………………………………………………………………….……….

b) Portable computer (laptop) ……………………………………………………………...……..

c) TV set with specific Internet device (e.g. digital TV or set top box) ……………….………….

d) Games console ……………………………………………………………………………………

e) Other means (i.e. none of the above) …………………………………………………………………..

of which:  (optional) e1) via Internet enabled mobile phone (WAP, GPRS, UMTS, etc.)……………………………………………………………..

e2) via handheld computer (palmtop, PDA) ………………………………  

f) Don't know ………………………………………………………………………………………...……..

[ -> go to A4 ]

A4* What types of Internet connection are used?

(tick all that apply)

a) Modem (dial-up access over normal telephone line) or ISDN …………………………….…………

b) DSL (e.g. ADSL, SHDSL, etc.) …………………………………………………………….…………………

c) Other broadband connection (e.g. cable, UMTS, etc) ………………………………..…………………….

d) Mobile phone over narrowband (WAP, GPRS, etc.) ………………………………………….…………………………………

[ -> go to B1 ]

A5 What are the reasons for not having access to the Internet at home?

(tick all that apply)

a) Have access to Internet elsewhere ………………………………...………………………..

b) Don’t want Internet (because content harmful, etc.) …………………..…………………

c) Don't need Internet (because not useful, not interesting, etc.) ………………………...………..

d) Equipment costs too high ……………………………………………………………………..…..

e) Access costs too high (telephone, etc.) …………………………………………………….…

f) Lack of skills ………………………………………………………………………………………...…..

g) Physical disability ………………………………………………………………………………..……..

h) Privacy or security concerns …………………………………………………………………………..…..

i) None of the above, but other ………………………..…………………………….…………………..

[ -> go to B1 ]

Methodological manual for Information Society Statistics 

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Module B:

Use of mobile phone and computers, location and frequency of use

Note : this and the following modules are directed to the individual selected within the household

B1 When did you most recently use a computer? (filter question)

Within the last 3 months ……………………………………………..

[ -> go to B2 ]

Between 3 months and a year ago ……………………………………………..

[ -> go to B4 ]

More than 1 year ago ……………………………………………..

[ -> go to B4 ]

Never used one …………………………………………….. 

[ -> go to B4 ]

B2 How often on average have you used a computer in the last 3 months?

(tick one)

Every day or almost every day ……………………………………………..

At least once a week (but not every day) …………………… 

At least once a month (but not every week) ………………… 

Less than once a month ……………………………………………..

[ -> go to B3 ]

B3

 Where have you used a computer in the last 3 months?
(tick all that apply)

a) At home …………………………………………………………….

b) At place of work (other than home) …………………………………………………………….

c) At place of education …………………………………………………………….

d) At another person's home …………………………………………………………….

e) Other (e.g. hotel, airport, internet café, etc.) …………………………………………………………….

[ -> go to B4 ]

B4 Do you use a mobile phone?

(tick only one)

Yes ……………………….

[ -> go to B5 ]

No ……………………….

[ -> go to C1 ]

B5

To what extent have you substituted private traditional postal mail (e.g. birthday 
wishes, season's greetings, contacts with companies or administration) 
by mobile messages (text or picture) ?

No substitution  ……………………………………………..

Minor substitution …………...……………………………………………..

Significant substitution  ………………... ……………………………………………..

Most or all substituted ………………... ……………………………………………..

Not applicable 

(didn't use traditional postal mail before
before I started using a mobile phone) …………………

[ -> go to C1 ]

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Module C:

Use of the Internet

C1 When did you most recently use the Internet?  (filter question)     

Within the last 3 months ……………………………………………..

[ -> go to C2 ]

Between 3 months and a year ago ……………………………………………..

[ -> go to E1 ]

More than 1 year ago ……………………………………………..

[ -> go to E1 ]

Never used it ……………………………………………..

[ -> go to F1 ]

C2* On average how often did you use the Internet in the last 3 months?

(tick one)

Every day or almost every day ……………………………………………..

At least once a week (but not every day) ……………………

At least once a month (but not every week) …………………

Less than once a month ……………………………………………..

[ -> go to C3 ]

C3* Where have you used the Internet in the last 3 months (using a computer or any other means)?

(tick all that apply)

a) At home ……………………………………………………

b) At place of work (other than home) ……………………………………………………

c) At place of education ……………………………………………………

d) At another person's home ……………………………………………………

e) At other places ……………………………………………………

of which:  (optional) e1)  Public Library ……………………………………………………  

e2)  Post office ……………………………………………………

e3)  Public Office, town hall, government agency ……………………………………………………

e4)  Community or voluntary organisation ……………………………………………………

e5)  Internet Café ……………………………………………………  

[ -> go to C4 ]

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C4 Do you use any of the following mobile devices to access the Internet?

(tick all that apply)

a) Mobile phone via WAP or GPRS ……………………………………………………………

b) Mobile phone via UMTS (3G) ……………...…………………………………………

c) Handheld computer (palmtop, PDA) ……………………………………………………

d) None of the above ………... …………………………………………………… 

[ -> go to C5 ]

C5

To what extent have you substituted private traditional postal mail (e.g. birthday 
wishes, season's greetings, contacts with companies or administration) 
by Internet or e-mail messages ?

No substitution  ……………………………………………..

Minor substitution …………...……………………………………………..

Significant substitution  ………………... ……………………………………………..

Most or all substituted ………………... ……………………………………………..

Not applicable 

(didn't use traditional postal mail before
before I started using the Internet) …………………

[ -> go to C6 ]

C6 Do you use a personal e-mail address (private or office)?

(tick only one)

Yes ……………………….

No ……………………….

[ -> go to C7 ]

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187  

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
C7* For which of the following activities did you use the Internet in the last 3 months 

for private purpose?
(tick all that apply)

Communication

a) Sending / receiving e-mails …………………………………………...…………………………………………………

b) Telephoning over the Internet / videoconferencing ………………………………………...…………………………………………………

c) Other (use of chat sites, etc.) ………………………………………...…………………………………………………

Information search and on-line services

d) Finding information about goods or services ………………………………………...…………………………………………………

e) Using services related to travel and accommodation ………………………………………...………………………………………………… 

f) Listening to web radios / watching web television ………………………………………...…………………………………………………

g) Playing or downloading games, images or music ………………………………………...…………………………………………………

h) Downloading software …………...………………………………………...…………………………………………………

i) Reading or downloading online newspapers / news magazines ………………………………………...…………………………………………………

j) Looking for a job or sending a job application ………………………………………...…………………………………………………

k) Seeking health-related information (e.g. injury, disease, nutrition, improving health, etc) …………. 

l) Other information search or on-line service …………………………………………………………………

Selling of goods or services, banking

m) Internet Banking ………………………………………...………………………………………………… 

n) Selling goods or services (e.g. via auctions) ………………………………………...…………………………………………………

Training and education

o) Formalised educational activities (school, university etc.) ………………………………………...…………………………………………………

p) Post educational courses ………………………………………...…………………………………………………

q) Other educational activities related specifically to employment opportunities ………………………………………...…………………………………………………

[ -> go to C8 ]

C8

In the last 3 months, did you receive unsolicited e-mails that you would regard 
as junk mail or spam and that you would prefer not to receive?
(tick only one)

Yes ……………………….

No ……………………….

[ -> go to D1 ]

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Module D:

e-Government

The questions in this module are to be answered by all regular Internet users (used Internet in the last 3 months: [C1a = Yes])

D1 Would you be interested to use the Internet to replace some of your personal contacts with

or visits to public services or administrations?
(tick only one)

Yes, I already use this possibility  ……………………………………………..

[ -> go to D3 ]

Yes, I would be interested (but I am currently not a user)  ……………………………………………..

[ -> go to D2 ]

No  ……………………………………………....……………………....

[ -> go to D2 ]

D2 What are the reasons for not using the Internet for dealing with public services 

or administrations?
(tick all that apply)

a) The services I need are not available on-line or difficult to find …………………………..

b) Personal contact is missing ………………………………………………………………………………

c) Immediate response is missing …………………………………………………………………………

d) Concerned about protection and security of my data ………………………………………………

e) Additional costs (e.g. connection costs) …………………………………………………………..……………

f) Using the Internet for contacts with public administration is too complex ………………………………………………………………………….

g) None of the above, but other ……………………………………………………………………………….…………………….

[ Respondents having answered "Yes, I would be interested (…)" in D1 -> go to D3 ]

[ Respondents having answered "No" in D1 -> go to D4 ]

D3 With which of the following matters are you already dealing via Internet or

would you like to deal via Internet?
(tick one box per line)

Yes, I have 
already done 
this on-line

Yes, I would 
like to do this 
on-line

No, I would 
not do this on-
line

a) Income taxes (declaration, notification of assessment)……………………………………………………………………………………………

b) Job search services by labour offices ……………………………………………………………………………………………

c) Social security benefits (unemployment benefits, 

child allowance, medical costs, student grants) ……………………………………………………………………………………………

d) Personal documents (passport and driver's licence) ……………………………………………………………………………………………

e) Car registration (new, used and imported cars) ……………………………………………………………………………………………

f) Application for building permission ……………………………………………………………………………………………

g) Declaration to the police (e.g. in case of theft) ……………………………………………………………………………………………

h) Public libraries (availability of catalogues, search tools) ……………………………………………………………………………………………

i) Certificates (birth, marriage): request and delivery ……………………………………………………………………………………………

j) Enrolment in higher education or university ……………………………………………………………………………………………

k) Announcement of moving (change of address) ……………………………………………………………………………………………

l) Health-related services (e.g. interactive advice on availability

of services in different hospitals; appointments for hospitals) ……………………………………………………………………………………………

[ -> go to D4 ]

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189  

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
D4* For which of the following activities relating to interaction with public services 

or administrations did you use the Internet in the last 3 months for private purpose?
(tick all that apply)

a) Obtaining information from public authorities' web sites ………………………………………...…………………………………………………

b) Downloading official forms ………………………………………...…………………………………………………

c) Sending filled in forms ………………………………………...…………………………………………………

[ -> go to E1 ]

Module E:

Internet commerce details: activities and barriers

E1* When did you most recently buy or order goods or services for private use over the Internet

(excluding manually typed e-mails) ?

Within the last 3 months ……………………………………………..

[ -> go to E2 ]

Between 3 months and a year ago ……………………………………………..

[ -> go to E2 ]

More than 1 year ago ……………………………………………..

[ -> go to E6 ]

Never bought or ordered ……………………………………………..

[ -> go to E6 ]

E2 What types of goods or services did you order over the Internet for private use 

in the last 12 months?
(tick all that apply)

a) Food / Groceries ………………………………………………………………………………………….…

b) Household goods (e.g. furniture, toys, etc) ………………………………………………………………………………………….…

c) Films, music ………………………………………………………………………………………….… 

d) Books / Magazines/ Newspapers/ E-learning material ………………………………………………………………………………………….…

e) Clothes, sports goods ………………………………………………………………………………………….…

f) Computer software and upgrades (incl. computer and video games) …………………………………

g) Computer hardware ………………………………………………………………………………………….…

h) Electronic equipment (incl. cameras) ………………………………………………………………………………………….…

i) Share purchases / Financial services / Insurance ………………………………………………………………………………………….…

j) Travel or holiday accommodation ………………………………………………

k) Tickets for events ………………………………………………………………………………………….…

l) Lotteries or betting ………………………………………………………………………………………….…

m) Other ………………………………………………………………………………………….…  

[ If 'yes' to categories  c) ,  d)  or  f) , go to question  E2b ; otherwise go to question  E3  ]

E2b Were any of the following products that you ordered over the Internet downloaded or 

accessed from websites rather than delivered by post etc.?
(if 'yes' to c, d or f in question E2)
(tick all that apply)

Films, music ………………………………………………………………………………………….… 

(Electronic) books, magazines, newspapers, e -learning material ………………………………………………………………………………………….…

Computer software (incl. computer and video games and software upgrades) ………………… 

[ -> go to E3 ]

Methodological manual for Information Society Statistics 

190  

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
E3

In the last 12 months, did you buy or order goods over the Internet from :
(tick all that apply)

a) Retailers known from outside the Internet (physical store, catalogues) ………………………..

b) Retailers known from the Internet or found on the Internet …………………………………………………………

[ -> go to E4 ]

E4

In the last 12 months, did you encounter any problems when buying / ordering goods or 
services over the Internet?
(tick only one)

Yes ……………………….

[ -> go to E5 ]

No ……………………….

[ -> go to F1 ]

E5 What problems have you encountered when buying / ordering goods or services 

over the Internet in the last 12 months?
(tick all that apply)

a) Difficulties in finding information concerning guarantees …………………………………………………………………….

b) Speed of delivery longer than indicated …………………………………………………………………….

c) Final costs higher than indicated (e.g. higher delivery costs, credit card transaction fee)………..

d) Wrong or damaged goods delivered or no goods received at all ………………………………….

e) Lack of security of payments ……………………………………………………………………. 

f) Complaints and redress were difficult or no satisfactory response after complaint …………………………….

g) Others …………...…………………………………………………………...………………………………….

[ -> go to F1 ]

E6 What were the reasons for not buying / ordering any goods or services 

for your own private use in the last 12 months?
(tick all that apply)

a) Have no need ………………………………………………………………………………………………………….

b) Prefer to shop in person, like to see product, loyalty to shops, force of habit ……………………………………

c) Lack of skills ……………………………………………………………………………………………………

d) Delivery of goods ordered over the Internet is a problem 

(e.g. takes too long or is logistically difficult) ……………………………………………….…………………….

e) Security or privacy concerns 

(e.g. giving credit card details or personal details over the Internet)……………………………… 

f) Trust concerns about receiving or returning goods, complaint / redress concerns ……………………………………

g) Don't have a payment card allowing to pay over the Internet …………………………………………

h) Speed of the Internet connection is too slow …………………………………………

i) Others ……………………………………………………………………………………………………………..

[ -> go to F1 ]

Methodological manual for Information Society Statistics 

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Module F:

E-skills

F1 When did you last take a training course (of at least 3 hours) on any aspect of computer use?

(for respondents who didn't answer "Never used one" in question B1)

Within the last 3 months ……………………………………………..

Between 3 months and a year ago ……………………………………………..

Between 1 and 3 years ago ……………………………………………..

More than 3 years ago ……………………………………………..

Never taken one …………………………………………..

[ -> go to F2 ]

F2 Which of the following computer related activities have you already carried out?

(tick all that apply)
(for respondents who didn't answer "Never used one" in question B1)

a) Copying or moving a file or folder ………………………………………………….…………………………….

b) Using copy and paste tools to duplicate or move information within a document ………………… 

c) Using basic arithmetic formulas in a spreadsheet …………………………………………………………….

d) Compressing files …………………………………………………………………………………………… 

e) Connecting and installing new devices, e.g. a printer or a modem …………………………………………………………

f) Writing a computer program using a specialised programming language ……………………………………

g) None of the above ……………………………………………………………………………

F3 Which of the following Internet related activities have you already carried out?

(tick all that apply)
(for respondents who didn't answer "Never used it" in question C1)

a) Using a search engine to find information ……………………………………………………………….

b) Sending e-mails with attached files (documents, pictures, etc.) ……………………………………………………..

c) Posting messages to chatrooms, newsgroups or an online discussion forum ……………………………………….

d) Using the Internet to make telephone calls ……………………………………………………………………

e) Using peer-to-peer file sharing for exchanging movies, music, etc. …………………………………………..;

f) Creating a web page ………………………………………………………………………………………………….

g) None of the above …………………………………………………………………………………………..;

F4 Where or how did you obtain the skills to carry out these activities?

(tick all that apply)
(for respondents who ticked at least one option (a to f) in questions F2 or F3)

a) Formalised educational institution (school, college, university) …………………………………………………………….

b) Training courses in adult education center (but not on the initiative of your employer) ……….  

c) Vocational training courses (on the demand of the employer) …………………………………………………………….

d) Self-study using books, cd-roms, etc. …………………………………………………………………………….

e) Self-study in the sense of learning-by-doing …………………………………………………………….

f)

Informal assistance from colleagues, relatives, friends …………………………………………………………….

g) Some other way ……………………………………………………………………………………………………

Methodological manual for Information Society Statistics 

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Socio-demographic background characteristics

G1 Age:

G2 Sex:

Man

Woman

G3 Educational level:

Primary or lower secondary education, no formal educat.

[ISCED 0, 1 or 2]

(tick only one)

Upper secondary education

Tertiary education

[ISCED 3 or 4]

[ISCED 5 or 6]

G4 Employment situation:

Employee

(tick only one)

Self-employed (incl. family workers)

Unemployed

Student (not in the labour force)

Other not in the labour force 
(retired, inactive, in compulsory military service, etc.)

G5 Occupation:

< description > 

< to be recoded into at least 3-digit ISCO categories >

G6 Geographical location:

"Objective 1" region

Non-"Objective 1" region

G7

Type of locality:

Densely-populated area

Intermediate area

Thinly-populated area

G8 Number of members in the household:

G9

of which,  number of children under 16:

G10 Household income:

(average net monthly income)

<currency>

OPTIONAL QUESTION 

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II.3.2. 

Transmission format 

Version 1, 31 March 2006. 

Note: this transmission format refers to the 2006 survey. 

(cid:3)(cid:3)(cid:3)(cid:3) See document MM2006_AnnexII.3.2_TransmissionFormatHH2006.doc (41 pages) 

Methodological manual for Information Society Statistics 

194  

 
 
II.3.3. 

Reporting template 

Note: the reporting template for interim & final methodological report refers to the 2005 surveys. 

(cid:3)(cid:3)(cid:3)(cid:3) See document MM2006_AnnexII.3.3_ReportingTemplateHH2005rev1.doc (14 pages) 

Methodological manual for Information Society Statistics 

195  

 
Part III  

EU Legislation 

Methodological manual for Information Society Statistics 

197  

III.1.  REGULATION  (EC)  NO  808/2004  OF  THE 
EUROPEAN  PARLIAMENT  AND  OF  THE  COUNCIL  OF 
21  APRIL  2004  CONCERNING  COMMUNITY 
STATISTICS ON THE INFORMATION SOCIETY 

Official Journal of the European Union, 30.04.2004, L143. 

(cid:3)(cid:3)(cid:3)(cid:3) See document MM2006_AnnexIII.1_Reg808-2004.pdf (7 pages) 

Versions in other languages can be found on the EU’s legislation server europa.eu.int/eur-lex/en  

1.  click ‘Official Journal’  

2.  select ‘Year’ (=2004) and ‘OJ Number’ (=143) 

3.  select language (upper right, only the 11 official languages before 01/05/2004) 

4.  scroll down in the table of contents to the link to page 49. 

Methodological manual for Information Society Statistics 

199  

 
 
 
III.2.  COMMISSION  REGULATION  (EC)  NO  1099/2005 
OF  13  JULY  2005  IMPLEMENTING  REGULATION 
(EC)  NO  808/2004  OF 
THE  EUROPEAN 
PARLIAMENT  AND  OF  THE  COUNCIL  CONCERNING 
COMMUNITY  STATISTICS  ON  THE  INFORMATION 
SOCIETY 

Official Journal of the European Union, 14.07.2005, L183. 

(cid:3)(cid:3)(cid:3)(cid:3) See document MM2006_AnnexIII.2_Reg1099-2005.pdf (16 pages) 

Versions in other languages can be found on the EU’s legislation server europa.eu.int/eur-lex/en  

1.  click ‘Official Journal’  

2.  select ‘Year’ (=2005) and ‘OJ Number’ (=183) 

3.  select language (upper right, all official languages excepting Maltese) 

4.  scroll down in the table of contents to the link to page 47. 

Methodological manual for Information Society Statistics 

200