Crime against business premises: findings from the Commercial Victimisation Survey
Source: data.gov.uk (2016-04-28)

Examines the extent of crime against businesses in England and Wales. The CVS was previously run in 1994 and 2002, and is planned to be repeated in 2013 and 2014.

1 
 
 
Crime against businesses: 
Detailed findings from the 
2012 Commercial 
Victimisation Survey 
June 2013 
 
 
 
 
 
 
 
 
 
 
 
This release has been prepared 
by staff in Home Office Statistics 
and can be downloaded from both 
the UK Statistics Authority 
website and the Home Office 
website:  
http://www.statistics.gov.uk  
https://www.gov.uk/government/organisa
tions/home-office/series/crime-against-
businesses 
© Crown Copyright 2013 
You may re-use this information (not 
including logos) free of charge in 
any format or medium, under the 
terms of the Open Government 
Licence. To view this licence, visit  
http://www.nationalarchives.gov.uk/doc/o
pen-government-licence/  
or write to the Information Policy 
Team, The National Archives, Kew, 
London, TW9 4DU or e-mail:  
xxx@xxx.xx 

2 
 
 
Contents 
Page 
Introduction 
 ....................................................................................................................................... 3 
Conventions used in figures and tables  ............................................................................................ 5 
Section 1 
Nature of crime against businesses .......................................................................... 6 
Section 2 
Experience of crime by business and location characteristics ............................ 23 
Section 3 
Crime prevention ....................................................................................................... 50 
Section 4 
Costs of crime against businesses.......................................................................... 58 
Section 5 
Crime in the wholesale and retail sector: 2002 and 2012 compared .................... 62 
Technical Annex .................................................................................................................................. 75 
The effect of using different measures for outliers and missing data .......................... 75 
Characteristics of the 2012 CVS sample ..................................................................... 76 
Details of logistic regression modelling........................................................................ 77 
Details of the calculations of costs of crime ................................................................. 78 
Methodology for the comparison of crimes against the wholesale and retail sector in 
2002 and 2012 ............................................................................................................. 81 
 

 
3 
 
Introduction 
This is the second release of data from the 2012 Commercial Victimisation Survey (CVS), which 
further examines the extent of crime against businesses in England and Wales. The CVS was a 
recommendation from the National Statistician‟s review of crime statistics to address the significant 
gap in crime statistics that existed for crimes against businesses, not covered by either of the two 
main sources of data on crime: the Crime Survey for England and Wales (CSEW) and crimes 
recorded by the police. While police recorded crime does include crimes against businesses, it does 
not separate these out from other crimes (other than for offences such as shoplifting which, by its 
nature, is against businesses). The police recorded crime also only includes those crimes that are 
reported to, and recorded by, the police. The CSEW is a survey of crime against households and 
individuals living in those households and so does not cover crime against businesses at all. The CVS 
was previously run in 1994 and 2002, and is planned to be repeated in 2013 and 2014.  
The 2012 CVS was a premises-based survey focused on four industry sectors: manufacturing, 
wholesale and retail, transportation and storage, and accommodation and food. The results of the 
survey should not be considered to be representative of crime against businesses as a whole, only of 
crime against these four sectors.  
This release covers the following topics: 
 Nature of crimes against businesses 
 Experience of crime against business premises, by business and location characteristics, for the 
core CVS crime types 
 Crime prevention  
 Costs of crime against businesses 
 Crime trends in the wholesale and retail sector between 2002 and 2012 
 A technical annex containing: 
 
Sensitivity analysis regarding treatment of outliers 
 
Characteristics of the 2012 CVS sample 
 
Details of logistic regression modelling 
 
Details of the calculations of costs of crime  
 
Methodology for comparison of 2002 and 2012 wholesale and retail subset  
 
The dates of forthcoming publications are pre-announced and can be found via the UK National 
Statistics Publication Hub: http://www.statistics.gov.uk/hub/index.html 
As this is the first detailed publication of findings from the CVS we would welcome any feedback on 
the publication, including suggestions for further analysis and comments on structure and content.  
To provide feedback, or for further information about the Commercial Victimisation Survey, please 
email xxx@xxx.xx 
Home Office Responsible Statistician 
David Blunt, Chief Statistician and Head of Profession for Statistics 

 
4 
 
Contact via xxx@xxx.xx 
 
 
This statistical bulletin is produced to the highest professional standards and is free from political 
interference. It has been produced by statisticians working in the Home Office Statistics Unit in 
accordance with the Home Office‟s Statement of Compliance with the Code of Practice for Official 
Statistics, which covers our policy on revisions and other matters. The Home Office Statistics Unit 
works under the direct line management of the Home Office Chief Statistician, who reports to the 
National Statistician with respect to all professional statistical matters.  
 

 
5 
 
Conventions used in figures and tables 
Table abbreviations 
‘0’ 
indicates no response in that particular category or less than 0.5. 
‘n/a’ indicates that the question was not applicable. 
‘-’ 
indicates that data are not reported because the unweighted base is fewer than 50 respondents. 
Unweighted base 
All percentages and rates presented in the tables are based on data weighted to compensate for 
differential non-response and stratification of the sample design. Where tables are not based on the 
full number of respondents in the sample, unweighted bases are shown which represent the number 
of people interviewed in the specified group. 
Percentages 
Row or column percentages may not add to 100% due to rounding. 
Where tables present cell percentages, the figures refer to the percentage of business premises 
having the attribute discussed and the complementary percentage, to add to 100%, is not shown. 
A percentage may be quoted in the text for a single category that is identifiable in the tables only by 
summing two or more component percentages. In order to avoid rounding errors, the percentage has 
been recalculated for the single category and therefore may differ by one percentage point from the 
sum of the percentages derived from the tables. 
‘No answers’ (missing values) 
All analysis excludes don‟t know/refusals unless otherwise specified.  
 
 
 

 
6 
 
1. Nature of crimes against businesses 
INTRODUCTION 
Respondents to the 2012 CVS were asked if the business at their current premises had experienced 
any of a range of crime types in the 12 months prior to interview (fieldwork was conducted between 
July and September 2012). Almost half (46%) of premises covered by the survey had experienced at 
least one of the main crime types covered by the survey. Where they had, respondents were asked for 
more detailed information about the most recent incident of each crime type, for example the time of 
day the incident occurred and whether the incident occurred during the week or at the weekend 
(assumed for analysis to be Monday to Friday or Saturday/Sunday). This includes some additional 
information specific to the crime type, for example type of items stolen in burglaries. Asking about the 
most recent event is a standard way of collecting representative data. If the question is posed in other 
ways that allow the respondent to choose the incident described or to say what they believe to be 
typical, distortions tend to arise. 
KEY FACTS 
 In incidents of burglary with entry, the most commonly reported way that the building was accessed 
was through a wooden or glass door (36% of incidents), or a metal door, roller door or shutter (17% 
of incidents). Goods or stock were the items most commonly reported stolen in burglary incidents 
(stolen in 37% of incidents). 
 The most common form of vandalism experienced was damage to any part of the premises‟ 
buildings, experienced by almost two-thirds (64%) of vandalism victims.  
 Of those premises that had experienced robbery (including attempts), almost all (91%) said that the 
most recent incident took place at their premises. The most common items stolen were goods and 
stock (stolen in 38% of cases); however, in 35% of cases, the robbery was not successful so 
nothing was stolen.  
 Amongst those premises whose employees had been victims of assaults or threats, the most 
common type were threats by a customer (80% of incidents). Employees were physically injured in 
12% of cases of assault or threat. 
 Goods or stock were stolen in 88% of most recent incidents of theft by customers, largely driven by 
the wholesale and retail sector where almost all (94%) incidents involved the theft of goods or 
stock.  
 The type of fraud experienced varied depending on who the perpetrator was. Credit, debit or store 
card fraud was made up half (50%) of fraud by persons unknown and one-third (33%) of fraud by 
others. However, withheld or „skimmed‟ takings and fraudulent accounting each made up around a 
third of incidents of fraud by employees (34% and 30% respectively). 
DATA TABLES 
Figures on the nature of each crime type, by sector, can be found in the 2012 Commercial 
Victimisation Survey Nature of crimes against businesses tables. 
NATURE OF BURGLARY (INCLUDING ATTEMPTS) 
This section covers both burglary with entry and attempted burglary. Burglary with entry is defined as 
entering any building on the premises without permission with intent to steal. This also applies to entry 

 
7 
 
into secure or non-public areas of buildings such as staff-only areas or stockrooms. Attempted 
burglary refers to incidents where the offender attempted, but failed, to gain access to a building on 
the premises. In this case there must be clear evidence that the offender made an actual, physical 
attempt to gain entry, for example damage to locks or broken doors. 
As shown in the headline findings report, there were around 214,000 incidents of burglary (including 
attempts) against the four sectors covered by the survey in the previous 12 months, and around 12% 
of all premises had been victims of some form of burglary.  
Respondents whose premises had experienced burglary (including attempts) during the previous 12 
months were asked a series of more detailed questions about the most recent incident of each type. 
The analysis below refers to the most recent incident of burglary with entry and the most recent 
incident of attempted burglary experienced, meaning if one premise has experienced both types of 
burglary then the most recent incident of each is included. 
Of the 9% of premises that had been a victim of burglary with entry, the most recent incident took 
place at the weekend in 40% of cases and on a weekday in 60% of cases. This is equivalent to 20% 
per weekend day compared with 12% per weekday assuming an equal split across the days (although 
this is a very broad assumption as it might be, for example, that Friday night has a higher incidence 
than other weekday nights). This means the likelihood of being a victim on any one day was higher at 
weekends than during the week. 
 
In all four of the sectors individually, the likelihood of victimisation on any one day was higher 
at weekends. 
 
In the manufacturing sector in particular, just over half (51%) of burglaries took place at the 
weekend.  
Across all businesses in the four sectors, over three-quarters of burglaries with entry (76%) took place 
during the evening or night (between 6pm and 6am), perhaps when the premises are more likely to be 
vacant. This pattern was similar for each of the sectors separately.   
Similarly to burglary with entry, the proportion of attempted burglaries taking place during the week 
was 61% (with 39% at the weekend), and 79% of all attempted burglaries took place during the 
evening or at night. This is as expected, as there is no reason to think that successful and 
unsuccessful burglaries would have different patterns. 
Offenders accessed the premises using a variety of entry points, and it was possible for more than 
one method of entry to be given for each incident as some burglaries involved more than one 
perpetrator. The most commonly reported way that the building was accessed by the perpetrators was 
through a door (53% of incidents), either a wooden or glass door (36% of incidents), or a metal door, 
roller door or shutter (17% of incidents).  In 16% of incidents a window was used for access. The most 
common entry method varied by sector, which is likely to reflect the different types of premises.  
Respondents were asked about the types of item that had been stolen from the premises during the 
most recent incident of burglary. Goods or stock were the items most commonly reported stolen from 
premises (37% of incidents), followed by other company property, which may include any other items 
owned by the business such as tools or electronic goods (stolen in 30% of incidents), and money 
(stolen in 28% of incidents). Other items, such as personal possessions or metal, were stolen in 21% 
of incidents and in 9% of incidents nothing was taken despite the offender gaining entry. As might be 
expected, the proportion of incidents where each type of item was stolen varied by sector (Figure 1.1).  
 
In the wholesale and retail sector, the most commonly reported items stolen were goods or 
stock (46% of incidents). 
 
In the transportation and storage and manufacturing sectors, „other company property‟ 
was most commonly reported as stolen (48% and 35% respectively). 

 
8 
 
 
In the accommodation and food sector, money was stolen most often (40% of incidents).  
Figure 1.1: Proportion of certain items stolen in burglary with entry incidents, by sector 
 
Chart notes:  
Note: Figures for each sector add to more than 100 as more than one response possible. 
Base: Businesses that had experienced burglary with entry. 
Source: Home Office, 2012 Commercial Victimisation Survey Nature of crimes against businesses tables: Table 1.1. 
 
NATURE OF VANDALISM 
In the CVS, vandalism is defined as deliberate damage to the premises. Unlike burglary, this is not 
limited to the building itself, and also includes damage to any of the following: walls and fences; fittings 
and fixtures (for example lighting, CCTV or signs); equipment or goods stored outside the building 
belonging to the business (for example shopping trolleys or bins); vehicles owned or leased by the 
business. Overall, 15% of premises in the four sectors covered by the survey had been victims of 
vandalism in the previous 12 months. The most common form of vandalism experienced was damage 
to any part of the premises‟ buildings, experienced by almost two-thirds (64%) of vandalism victims 
(Figure 1.2).  
 
Damage to buildings was also the most common form of vandalism experienced by the 
manufacturing, wholesale and retail, and accommodation and food sectors.  
 
However, reflecting the difference in the nature of the sectors, in the transportation and 
storage sector damage to vehicles was the most common form of vandalism (experienced by 
47% of vandalism victims in this sector); a smaller proportion (38%) experienced damage to 
buildings. 
 
 
28 
46 
25 
28 
37 
35 
33 
48 
15 
30 
11 
30 
14 
40 
28 
23 
19 
11 
26 
21 
17 
5 
13 
12 
9 
0 
10 
20 
30 
40 
50 
60 
Manufacturing 
Wholesale & 
Retail 
Transportation  
& Storage 
Accommodation 
& Food 
All four sectors 
PERCENTAGE OF INCIDENTS 
INDUSTRY SECTOR 
Goods or stock 
Other company property 
Money 
Other item 
Nothing taken 

 
9 
 
Figure 1.2: Proportion of incidents of vandalism where each type of damage was experienced, 
by sector  
 
Chart notes:  
Note: Figures for each sector may sum to more than 100% as some incidents involved more than one type of vandalism. 
Base: Businesses that had experienced vandalism. 
Source: Home Office, 2012 Commercial Victimisation Survey Nature of crimes against businesses tables: Table 1.3. 
 
Respondents whose premises had experienced vandalism were asked a series of more detailed 
questions about the most recent incident, and figures below refer to the most recent incident only. As 
with burglary, vandalism was more likely to take place at times when the premises were more likely to 
be empty. Overall, slightly more incidents of vandalism occurred at the weekend (54%) than during the 
week (46%). This means a relatively high rate of incidents took place over the weekend (equivalent to 
27% per weekend day) compared with during the week (9% per weekday); hence the likelihood of 
being a victim on a particular day was on average about three times higher at weekends.  
 
In the wholesale and retail and transportation and storage sectors, around half of the 
incidents of vandalism occurred at the weekend (48% and 51% respectively). 
 
The proportion of incidents taking place at the weekend was higher in the accommodation 
and food and manufacturing sectors (68% and 62% respectively).  
As might be expected, the vast majority of vandalism incidents took place in the evening or at night, 
with 83% of incidents across all four sectors reported as occurring between 6pm and 6am. This was 
also the case for each sector individually, although the proportion was slightly lower in the 
transportation and storage sector (75%).  
60 
68 
38 
64 
64 
48 
36 
45 
48 
40 
14 
15 
47 
6 
15 
10 
12 
20 
13 
12 
0 
10 
20 
30 
40 
50 
60 
70 
80 
Manufacturing 
Wholesale & 
Retail 
Transportation 
& Storage 
Accommodation 
& Food 
All four sectors 
PERCENTAGE OF VICTIMS THAT HAD EXPERIENCED TYPE 
INDUSTRY SECTOR EXPERIENCING DAMAGE 
Damage to buildings 
Damage to other part of premises 
Damage to vehicles 
Damage to equipment or stock 

 
10 
 
Respondents whose premises had experienced vandalism were asked whether they thought there 
was a racial or religious motivation for the incident; however, fewer than 2% of victims thought this 
was the case. 
NATURE OF VEHICLE-RELATED THEFT 
Vehicle-related theft includes both theft of vehicles and theft from vehicles. This covers all types of 
vehicle so may include cars, vans, lorries, motorbikes and industrial vehicles such as forklifts, 
essentially all vehicles that are owned or leased by the premises. This includes vehicles mainly based 
at the premises (and used by employees). However, incidents of vehicle-related theft taking place 
away from the premises are also included since the crime is still against the business at the sampled 
premises.  
As shown in the headline findings report, premises in the four sectors surveyed experienced around 
66,000 incidents of vehicle-related theft in the 12 months prior to interview, 90% of which were 
incidents of theft from vehicles (59,000 incidents). One per cent of premises had experienced theft of a 
vehicle and 4% had experienced theft from vehicles. 
The overall number of vehicle-related thefts (66,000) made up just 1% of the total number of crimes 
experienced overall. This was the only type of crime for which the transportation and storage sector 
experienced a notably higher rate than other sectors, which is not surprising given that premises in 
this sector are more likely to make more use of vehicles than other sectors. However, vehicle-related 
thefts still made up a relatively low proportion of the total crime against this sector (9%).  
Theft of a vehicle 
As the number of incidents of this crime type is very small, the estimates of theft of a vehicle should be 
treated with caution. For this reason, it has not been possible to do any sector level analysis, ie all 
figures presented in this section are for all four sectors combined.  
Around half (52%) of all theft of a vehicle incidents in the previous 12 months involved theft of 
passenger cars, around a quarter (26%) involved the theft of larger vans/lorries (ie those requiring an 
HGV licence to drive) and around a fifth (21%) involved the theft of smaller vans/lorries (ie those not 
requiring an HGV licence).  Respondents whose premises had experienced theft of a vehicle in the 12 
months prior to interview were also asked a series of detailed questions about the most recent incident 
and figures below refer to the most recent incident only.  
The majority of vehicle thefts (77%) took place during the week (23% took place at the weekend), 
meaning that proportionately, slightly more took place on a weekday assuming an equal split across 
each day. Around two-thirds (67%) of incidents took place during the evening or at night. Only 7% of 
vehicle thefts occurred during a delivery from the respondent‟s premises to their customers. 
In most cases of vehicle theft, the vehicle was not recovered (62% of the most recent incidents), but in 
a quarter of incidents (25%) the vehicle was recovered with its contents and in 15% of incidents the 
vehicle was recovered but without its contents. These sum to more than 100% as a small number of 
incidents involved the theft of more than one vehicle. 
These proportions are similar to theft of vehicle incidents experienced by households. The 2011/12 
Crime Survey for England and Wales estimated that in household incidents 62% of stolen vehicles 
were not returned to the owner.  
Theft from a vehicle 
Although the numbers of thefts from vehicles are too small to analyse at a sector level for most of the 
sectors, it was possible to look at the transportation and storage sector separately (since this sector 

 
11 
 
experienced the most incidents of this crime type, ie enough to carry out robust analysis). The other 
three sectors were combined for this analysis. 
Almost three-quarters (74%) of thefts from vehicles took place during the evening or at night (between 
6pm and 6am). This proportion was higher for the transportation and storage sector, with 81% of 
incidents occurring during the evening or at night.  
Around a fifth (19%) of thefts from a vehicle took place during a delivery from the respondent‟s 
premises to their customers. The proportion was also similar for the transportation and storage 
sector. 
NATURE OF ROBBERY (INCLUDING ATTEMPTS) 
Robbery is an offence in which force or the threat of force is used either during or immediately prior to 
a theft or attempted theft, which can include use of a weapon. As only a small proportion of premises 
(2%) experienced robbery (including attempts), analysis by sector is not possible. Therefore results 
are presented for all four sectors combined. 
Of those premises that had experienced robbery (including attempts) in the previous 12 months, 
almost all (91%) said that the most recent incident took place at their premises. Around 8% said the 
employees experienced the incident away from the premises (either in a vehicle, on the street or in 
any another situation). 
As shown in Table 1.1, the most commonly stolen items in the most recent incidents of robbery were 
goods or stock (stolen in 38% of cases). However, in 35% of cases, the robbery was not successful so 
nothing was stolen. 
Table 1.1: Proportion of most recent incidents of robbery where certain items were stolen 
Robbery: what was stolen? 
Percentage of incidents 
Goods or stock 
38% 
Money 
15% 
Other (including company 
property or personal possessions) 
15% 
Nothing – attempted robbery  
35% 
Unweighted base 
113 
 
Table notes:  
Figures for each sector sum to more than 100% as in some incidents more than one type of item was stolen. 
 
The majority of robberies took place during the week (82%), meaning the likelihood of being a victim 
on any day was greater during the week (equivalent to 16% on a weekday compared with 9% on each 
weekend day). Around half of incidents took place in the afternoon (12pm to 6pm, 53%), with around a 
quarter (26%) taking place in the morning (6am to 12pm) and a fifth (18%) during the evening/night.  
Thirty per cent of the most recent incidents of robbery (including attempts) against business premises 
in the four sectors involved the use of a weapon. In 18% of incidents the offender had a knife, while 
6% of incidents involved a firearm (a gun or imitation gun) and 10% involved some other weapon 
(such as a baseball bat or piece of piping). Employees were physically injured in 14% of incidents 
(although not necessarily with one of the aforementioned weapons). 

 
12 
 
In 60% of incidents there was only one offender involved, with a further 26% involving two offenders 
and 14% involving three or more. Most offenders were reported to be male (89% of incidents), with the 
remainder of offences involving either females or people of both sexes.  
Perhaps reflecting the size of the premises targeted, in over half (53%) of the most recent incidents of 
robbery (including attempts), five or more people were on the premises at the time. In 25% of incidents 
two to four people were on the premises and in 20% of incidents just one person was on the premises. 
In around 6% of robbery incidents (including attempts) the respondent whose premises were targeted 
thought there was a racial or religious motivation. 
NATURE OF ASSAULTS AND THREATS 
Assaults and threats are incidents where employees are assaulted, threatened or intimidated, 
including as a result of disagreements with customers or other employees. Assaults do not include 
incidents of force against employees that were motivated by theft (which would be classified as 
robbery), rather the motivation is to cause harm or to intimidate and may include the use of a weapon. 
As shown in the headline findings report, 10% of premises across all four sectors reported that their 
employees had been a victim of assaults or threats in the previous 12 months. This proportion was 
highest in the accommodation and food sector where 15% of premises had experienced at least one 
incident of assault or threats and lowest in the manufacturing sector (4%). This is possibly due to 
employees in accommodation and food premises having more contact with customers and members 
of the public than in other sectors and may also be related to the consumption of alcohol in many of 
these premises.  
Threats were far more common than assaults; almost all (93%) premises whose employees had been 
victims of assaults or threats had experienced a threat, whereas a much lower proportion (25%) had 
experienced an assault.  
By far the most commonly reported type of incident amongst those premises whose employees had 
been victims of assaults or threats was a threat by a customer (80% of incidents were of this nature). 
This was also the most common type in each of the wholesale and retail, transportation and 
storage, and accommodation and food sectors (Figure 1.3, sample sizes for assaults and threats in 
the manufacturing sector are too small to report on the sector separately for this crime type).  
Across all four sectors, 19% of incidents involved an assault by a customer, but this proportion was 
particularly high in the transportation and storage sector, with assaults by customers making up just 
under half (47%) of incidents of assaults and threats. This appears to be largely due to taxi operations 
in this sector, which accounted for almost half of assaults by customers in the transportation and 
storage sector. 
 
 

 
13 
 
Figure 1.3: Proportion of incidents of assaults and threats where each type was experienced, 
by sector 
 
Chart notes:  
Note: Figures for each sector may sum to more than 100% as incidents may involve more than one type of assault or threat. 
Base: Businesses that had experienced assaults or threats. 
Source: Home Office, 2012 Commercial Victimisation Survey Nature of crimes against businesses tables: Table 1.7. 
 
Respondents whose employees had experienced assaults or threats were asked a series of more 
detailed questions about the most recent incident, and figures below refer to the most recent incident 
only. 
Estimates from the CVS show that, overall, 72% of the most recent incidents of assaults and threats 
took place on weekdays and the remainder (28%) took place at the weekend, meaning that 
proportionately 14% of assaults and threats took place each day (ie there does not appear to be a 
difference between weekdays and the weekend). However, this varied by sector.  
 
In the wholesale and retail sector, 83% of assaults and threats took place during the week 
(equivalent to 17% per weekday compared with 9% per weekend day).  
 
In the accommodation and food sector around half (52%) of all incidents took place at the 
weekend (equivalent to 10% per weekend day compared with 26% per weekday). 
 
 
82 
69 
84 
80 
20 
28 
14 
21 
13 
47 
27 
19 
5 
12 
10 
8 
0 
10 
20 
30 
40 
50 
60 
70 
80 
90 
Wholesale & 
Retail 
Transportation & 
Storage 
Accommodation 
& Food 
All four sectors 
(inc. 
Manufacturing) 
PERCENTAGE OF VICTIMS THAT HAD EXPERIENCED 
TYPE 
INDUSTRY SECTOR 
Threat by customer 
Threat by employee/other 
Assault by customer 
Assault by employee/other 

 
14 
 
Table 1.2: Proportion of assaults and threats taking place by day and sector 
  
Wholesale 
& Retail 
Transportation 
& Storage 
Accommodation 
& Food 
All four 
sectors 
During the week 
83% 
61% 
48% 
72% 
At the weekend 
17% 
39% 
52% 
28%  
Unweighted base 
134 
94 
194 
464 
Table notes:  
Base: Businesses that had experienced assaults and threats.  
 
Across all four sectors, 55% of incidents took place in the morning or afternoon (6am to 6pm), 
although again this varied by sector (Figure 1.4).  
 
Seventy-seven per cent of assaults and threats against the wholesale and retail sector 
occurred during the evening and night (between 6pm and 6am).  
 
In the accommodation and food sector the proportion was 32% during the evening and 
night. 
These results are likely to reflect the differing hours and days of the week in which businesses in each 
sector tend to be open to the public and the differing natures of these businesses. 
Figure 1.4: Proportion of all assaults and threats taking place by time of day and sector 
 
Chart notes:  
Note: Morning is from 6am to noon; afternoon is from noon to 6pm; evening is from 6pm to midnight; night is from midnight to 
6am. 
Base: Businesses that had experienced assaults or threats. 
Source: Home Office, 2012 Commercial Victimisation Survey Nature of crimes against businesses tables: Table 1.7. 
 
77 
57 
32 
55 
23 
43 
68 
45 
0 
10 
20 
30 
40 
50 
60 
70 
80 
90 
100 
Wholesale & 
Retail 
Transportation & 
Storage 
Accommodation 
& Food 
All four sectors 
(inc. 
Manufacturing) 
PERCENTAGE OF VICTIMS THAT HAD 
EXPERIENCED TYPE 
INDUSTRY SECTOR 
During morning/afternoon 
During evening/night 

 
15 
 
No incidents of assaults or threats were reported as involving a firearm; however, 1% involved a knife 
and around 3% involved another type of weapon (such as a baseball bat or piece of piping). Overall, 
an employee was physically injured in 12% of cases of assault or threat. This proportion was higher in 
the transportation and storage and accommodation and food sectors (26% and 19% respectively) 
and lower in the wholesale and retail sector. In around 5% of incidents of assaults and threats the 
respondent perceived a racial or religious motivation for the incident.  
NATURE OF THEFT 
As shown in the headline findings report, thefts were by far the most common type of crime 
experienced, making up around three-quarters (74%) of all incidents of crime against the four sectors 
covered by the survey and were experienced by around a quarter of premises (24%).  
Theft is an offence where money, goods, company property or services are stolen from the business 
at that premises. The four types of theft covered by the survey are:  
 
theft by customers, most obviously including shoplifting but can include theft of any business-
owned property or non-payment of services 
 
theft by employees, covering thefts of money, services or property owned by the business 
which are committed by employees 
 
theft by others, which can include thefts by other known parties, for example a supplier or an 
employee from another company who is based at the same site 
 
theft by persons unknown, where something has been taken without permission but it is not 
possible to work out who the offender was. A proportion of this may include undetected theft 
by customers 
Respondents whose premises had experienced theft in the previous 12 months were asked a series of 
detailed questions about the most recent incident of each type experienced, which the analysis below 
is based upon. For analysis of thefts by customers and thefts by employees, it is possible to look at 
the wholesale and retail sector separately (since this sector experienced the most incidents of this 
crime type). The other three sectors have been combined for analysis as the numbers are too small to 
analyse robustly at a sector level. As numbers experiencing theft by others were small overall, 
experienced by just 2% of businesses, analysis had not been presented for this crime type. 
As the wholesale and retail sector is by far the largest of the four sectors covered by the survey in 
terms of numbers of premises, the overall distribution of crime is heavily influenced by patterns of 
crime against this sector. The vast majority of all crimes against the wholesale and retail sector 
(80%) were incidents of theft, and particularly thefts by customers (53%) (ie shoplifting).  
Theft by customers 
Overall, thefts by customers made up almost half of all incidents of crime across the four sectors 
(47%), and were experienced by 14% of all businesses. The vast majority (94%) of these incidents of 
theft by customers occurred in the wholesale and retail sector. 
Across all four sectors, 81% of incidents of theft by customers took place on weekdays.  This means 
the likelihood of being a victim was higher on a weekday (equivalent to 16% per weekday compared 
with 10% per weekend day). This was largely driven by incidents in the wholesale and retail sector 
(where 82% of incidents of theft by customers took place on weekdays) whereas in the other three 
sectors combined, the equivalent proportion was 14% on both weekdays and at the weekend. The 
daily pattern may reflect times where the business premises were open to the public, in particular 
some shut on Sundays. This contrasts with burglaries, where a lower proportion (60%) took place 
during the week, and reflects the different nature of the two offences, ie less likely to burgle a shop 

 
16 
 
when it is open and it is not possible for a customer to steal from it when it is shut and locked up (as 
otherwise it would be classed as a burglary). 
Around 60% of thefts by customers took place during the afternoon (noon to 6pm), and again this was 
driven by the wholesale and retail sector where 64% of incidents took place during this period. This 
is perhaps unsurprising as a greater proportion of the hours that shops are typically open for (usually 
in the region of 9am to 5pm) occur during the afternoon (defined by the CVS as noon to 6pm). As 
shown in Figure 1.5, in the other three sectors combined thefts by customers were more evenly 
spread between morning (26%), afternoon (31%) and night (27%).  
Figure 1.5: Proportion of thefts by customers by time of day most recent incident occurred, by 
sector 
 
Chart notes:  
Base: Businesses that had experienced thefts by customers. 
Source: Home Office, 2012 Commercial Victimisation Survey Nature of crimes against businesses tables: Table 1.8. 
 
Goods or stock were stolen in 88% of incidents of theft by customers. Again, this was largely driven by 
the wholesale and retail sector where almost all (94%) incidents involved the theft of goods or stock. 
„Other‟ items, which may include unpaid services or personal possessions, made up around 8% of 
thefts by customers across all four sectors, but this proportion was much higher in the three non-retail 
sectors combined (36% of thefts by customers, Figure 1.6). 
 
 
17 
26 
64 
31 
5 
8 
14 
27 
0 
6 
0 
1 
0 
10 
20 
30 
40 
50 
60 
70 
80 
90 
100 
Wholesale and Retail 
Other three sectors 
PERCENTAGE OF VICTIMS THAT HAD 
EXPERIENCED TYPE 
INDUSTRY SECTOR 
Morning 
Afternoon 
Morning/afternoon (unsure) 
Evening 
Night 
Evening/night (unsure) 

 
17 
 
Figure 1.6: Proportion of thefts of certain items by customers, by sector 
 
Chart notes:  
Note: Figures for each sector sum to more than 100% as it was possible for more than one item to be reported stolen in each 
incident. 
Base: Businesses that had experienced thefts by customers. 
Source: Home Office, 2012 Commercial Victimisation Survey Nature of crimes against businesses tables: Table 1.8. 
 
Thefts by employees 
Thefts by employees were less common than thefts by customers, experienced by 4% of business 
premises across all four sectors. In around half (49%) of incidents of thefts by employees the items 
stolen were goods or stock; similarly around half (47%) of incidents involved theft of money. These 
were by far the most commonly stolen items in both the wholesale and retail and other three sectors 
combined. However, the other three sectors combined had a higher proportion of incidents where 
money was stolen (51%) than the wholesale and retail sector (45%), Figure 1.7. 
 
 
94 
48 
3 
36 
1 
20 
2 
9 
0 
10 
20 
30 
40 
50 
60 
70 
80 
90 
100 
Wholesale and Retail 
Other three sectors 
PERCENTAGE OF VICTIMS THAT HAD 
EXPERIENCED TYPE 
INDUSTRY SECTOR 
Goods or stock 
Other Item 
Other company property 
Money 

 
18 
 
Figure 1.7: Proportion of thefts of certain items by employees, by sector 
 
Chart notes:  
Note: Figures for each sector may sum to more than 100% as it was possible for more than one item to be reported stolen in 
each incident. 
Base: Businesses that had experienced thefts by employees. 
Source: Home Office, 2012 Commercial Victimisation Survey Nature of crimes against businesses tables: Table 1.8. 
 
In 70% of all incidents of thefts by employees disciplinary action was taken against the employee 
responsible. 
Thefts by unknown persons 
Thefts by unknown persons, which may include a large proportion of theft by customers where 
incidents were not observed or detected, made up around a fifth (21%) of all incidents of crime 
experienced by businesses. Ten per cent of business premises across all four sectors had 
experienced this crime type. 
As shown in Figure 1.8, goods or stock were stolen in around two-thirds (66%) of incidents of theft by 
unknown persons. These were the most commonly stolen items in each of the four sectors, but made 
up a particularly large proportion of incidents in the wholesale and retail sector (76%).  
Other company property was stolen in 18% of incidents overall, but this proportion was higher in the 
transportation and storage (38%) and manufacturing (29%) sectors. While money was stolen in 
12% of incidents overall, this proportion rose to 32% of incidents in the accommodation and food 
sector. 
 
 
53 
43 
49 
45 
51 
47 
4 
16 
9 
6 
7 
6 
0 
10 
20 
30 
40 
50 
60 
Wholesale and Retail 
Other three sectors 
All four sectors 
PERCENTAGE OF VICTIMS THAT HAD 
EXPERIENCED TYPE 
INDUSTRY SECTOR 
Goods or stock 
Money 
Other company property 
Other Item 

 
19 
 
Figure 1.8: Proportion of thefts of certain items by unknown persons, by sector 
 
Chart notes:  
Note: Figures for each sector sum to more than 100% as it was possible for more than one item to be reported stolen in each 
incident. 
Base: Businesses that had experienced thefts by unknown persons. 
Source: Home Office, 2012 Commercial Victimisation Survey Nature of crimes against businesses tables: Table 1.8. 
 
NATURE OF FRAUD 
Incidents of fraud occur where someone “cheats” the business (at the sampled premises) in terms of 
diverting funds, goods or services for their own purposes. Frauds are different to thefts as there must 
be an element of deception involved. As shown in the headline findings report, premises across all 
four sectors experienced around 644,000 incidents of fraud during the previous 12 months, and 10% 
of business premises had been a victim of any type of fraud. 
Fraud is divided in to three types: 
 
fraud by employees, which can include fraud by employees who are not based at the sample 
premises 
 
fraud by others, covering fraud by another known person, for example customers, distributors 
or suppliers 
 
fraud by persons unknown, where a fraud has been detected but it is not possible to ascertain 
who carried it out 
The survey is likely to underestimate fraud as premises may not have been aware of all the offences 
that had taken place – this is not likely to be the case for other crime types, for example vandalism or  
robbery.  As only a small proportion of premises in each sector were reported to have experienced 
42 
76 
47 
38 
66 
29 
15 
38 
18 
18 
23 
7 
5 
32 
12 
13 
8 
14 
18 
10 
0 
10 
20 
30 
40 
50 
60 
70 
80 
Manufacturing 
Wholesale & 
Retail 
Transportation 
& Storage 
Accommodation 
& Food 
All four sectors 
PERCENTAGE OF VICTIMS THAT HAD 
EXPERIENCED TYPE 
INDUSTRY SECTOR 
Goods or stock 
Other company property 
Money 
Other Item 

 
20 
 
each type of fraud, analysis by sector is not possible and therefore results are presented for all four 
sectors combined. As for other incidents of crime, the analysis refers to the most recent incident of 
each type fraud. 
Fraud by employees 
Fraud by employees was experienced by 2% of business premises across the four sectors covered by 
the survey. The most commonly reported type was withholding or „skimming‟ takings (for example by 
taking money from customers that was intended for the business). This made up around a third of 
fraud by employees (34%), with fraudulent accounting (including fiddling expenses, fraudulent claims 
for work not done or creating fake payroll records) making up a further 30% of fraud by employees. 
The remaining proportion was made up of a range of less common types of fraud. These included 
creating non-existent customers or suppliers with the intention of defrauding the business (10% of 
incidents) and selling goods or services fraudulently (7% of incidents). Other types of fraud (which 
made up the remaining 19% of incidents) included receiving inferior or no goods and services at all for 
personal gain and using a business credit card fraudulently (Figure 1.9).  
Figure 1.9: Fraud by employees: type experienced in most recent incident 
 
Chart notes:  
Base: Businesses that had experienced fraud by employees. 
Source: Home Office, 2012 Commercial Victimisation Survey Nature of crimes against businesses tables: Table 1.9. 
 
In around three-quarters (73%) of cases disciplinary action was taken against the employee 
responsible. 
Action Fraud is the UK‟s national fraud reporting centre that records incidents of fraud directly from 
organisations and the public. Just 7% of respondents whose premises had experienced fraud by 
employees said that the most recent incident was reported to Action Fraud, with a further 85% saying 
that they had not reported the incident to them as they were not aware of Action Fraud. The remaining 
9% said that they had not reported the incident to Action Fraud despite being aware of the 
organisation. However, 37% of victims said that the incident was reported to the police. 
 
 
34 
30 
10 
7 
19 
Withheld/‘skimmed’ 
takings 
Fraudulent accounting 
Created non-existent 
customers/suppliers 
Sold goods or services 
fraudulently 
Other type 

 
21 
 
Fraud by others 
As shown in the headline findings report, fraud by others was experienced by 6% of business 
premises in the fours sectors surveyed in the previous 12 months.  
Around a third (33%) of incidents of fraud by others (ie non-employees) were credit, debit or store card 
fraud (for example paying with stolen, cloned or invalid cards). Cheque fraud (including forged 
cheques and cheque overpayment fraud) made up 10% of fraud by others and fraudulent payment 
claims for goods or services that were not delivered (or not delivered as specified) made up 7%. A 
large proportion (45%) of fraud by others was made up of a variety of less common fraud types 
(Figure 1.10).   
Figure 1.10: Fraud by others: type experienced in most recent incident 
 
Chart notes:  
Base: Businesses that had experienced fraud by others. 
Source: Home Office, 2012 Commercial Victimisation Survey Nature of crimes against businesses tables: Table 1.9. 
 
Incidents of credit, debit or cheque card fraud by others were most frequently conducted over the 
phone (42% of most recent incidents) or in person (40%). The remainder were conducted over the 
internet (18% of incidents). 
Similarly to incidents of fraud by employees, just 3% of respondents whose premises had been a 
victim of fraud by others said that the most recent incident was reported to Action Fraud, with the 
majority of all victims (91%) saying that they were not aware of Action Fraud and the remaining 6% 
saying that they had not reported the incident despite being aware of Action Fraud. However, 39% had 
reported the incident to the police. 
Fraud by persons unknown 
As shown in the headline findings report, 4% of business premises across the four sectors had 
experienced fraud by persons unknown in the 12 months prior to the survey. Credit, debit or store card 
fraud was by far the most common type of fraud by persons unknown, making up half (50%) of this 
crime type. Ten per cent of incidents involved forged bank notes and 9% were cheque fraud (Figure 
1.11). Other types of fraud by persons unknown (which altogether made up 23% of incidents) included 
33 
10 
7 
4 
45 
Credit/debit/store card 
fraud 
Cheque fraud 
Fraudulent payment 
claims for goods/services 
not delivered 
Refunds/receipt fraud 
Other type 

 
22 
 
online banking fraud, diverting payments to a fraudulent account or fraudulent payment claims for 
goods or services that were not delivered (or not delivered as specified). 
Figure 1.11: Fraud by persons unknown: type experienced in most recent incident 
 
Chart notes:  
Base: Businesses that had experienced fraud by persons unknown. 
Source: Home Office, 2012 Commercial Victimisation Survey Nature of crimes against businesses tables: Table 1.9. 
 
Of incidents of credit, debit or cheque card fraud by persons unknown, 64% were conducted over the 
phone, 27% over the internet, and just 9% in person. 
Similarly to the other fraud types, just 4% of fraud by persons unknown was reported to Action Fraud, 
with 89% of all victims saying that they were not aware of Action Fraud and the remaining 7% saying 
that they had not reported the incident despite being aware of Action Fraud. Some 37% of incidents of 
fraud by persons unknown had been reported to the police. 
 
 
 
50 
10 
9 
8 
23 
Credit/debit/store card 
fraud 
Forged bank notes 
Cheque fraud 
Refunds/receipt fraud 
Other type 

 
23 
 
2. Experience of crime by business and 
location characteristics  
INTRODUCTION 
Respondents to the 2012 CVS were asked if the business at their current premises had experienced 
any of a range of crime types in the 12 months prior to interview and, if so, how many incidents of 
crime had been experienced. Although these statistics were published in the headline findings report, 
this section looks to analyse this information further with reference to the characteristics of the 
business, the premises and the local area. Examples include distance from nearest housing, length of 
time at premises, location in terms of urban or rural, and region1.  
Incidence and prevalence rate figures are available by sector in the relevant data tables. 
Key facts 
 Across the four sectors covered by the survey, business premises in urban areas experience a 
greater rate of crime than premises in rural areas. There were 15,500 incidents of crime per 1,000 
premises in urban areas compared with 5,600 in rural areas, ie the incidence rate was almost three 
times higher in urban areas than in rural areas.  
 For certain crime types, including vandalism, assaults and threats, theft and fraud, the incidence 
rates are generally higher in more deprived areas than in less deprived areas. 
 Premises open to the public, in all sectors, experienced a greater incidence rate (17,600 incidents 
of crime per 1,000 premises) compared with premises not open to the public (2,100 incidents of 
crime per 1,000 premises). Over half (52%) of premises open to the public had experienced crime 
in the last 12 months, driven by high rates in the wholesale and retail sector. 
 The incidence rates of crime in the last 12 months are nearly always higher for those with security 
measures on their premises than those without. However, it is possible that premises could have 
installed these measures as a result of being victimised or that these premises are at most risk and 
the presence of security measures has not fully offset the risks of victimisation. 
 The North East of England had the highest number of incidents of crime (against the four sectors) 
per 1,000 premises of all regions in England and Wales, driven by the high rate of thefts. However, 
the incidence rates for certain other crime types were higher in other regions. For example, London 
experienced the highest rate of fraud and the North West, London and the West Midlands had the 
highest robbery rates (likely to reflect the large metropolitan cities in these regions). In fact, if thefts 
are excluded, London had the highest overall crime incident rate. 
DATA TABLES 
Incidence rates, number of victims and prevalence rates by sector, business characteristics and 
location, can be found in the 2012 Commercial Victimisation Survey Experience of crime by 
characteristics Tables 2.1a to 2.17a and Tables 2.1b to 2.17b.  
 
 
                                                 
1 The areas covered by the former Government Office Regions are referred to as 'regions' for statistical purposes. 

 
24 
 
ALL CVS CRIME TYPES 
This first section gives incidence and prevalence rates for all crime types captured in the CVS. Figures 
for each individual crime type are shown in later sections. 
The headline findings report showed there were 13,305 incidents of crime per 1,000 premises across 
all four CVS sectors in the last 12 months. Premises in the wholesale and retail sector experienced 
the highest rate of crime (19,701 incidents per 1,000 premises) of the four sectors covered in the 
survey, mostly driven by shoplifting offences. There were a total of 4.1 million incidents of shoplifting 
estimated from the survey, almost half the total number of crimes across all four sectors. 
The North East of England and London had the highest number of incidents of crime (against the four 
sectors) per 1,000 premises of all regions in England and Wales. The North East experienced 23,051 
incidents of crime per 1,000 business premises, while London experienced 22,168 incidents per 1,000 
business premises in the last 12 months. The South West region had the lowest incidence rate with 
7,096 crimes per 1,000 premises. 
The high rate of crime in the North East is driven by the high rate of thefts (as shown in Figure 2.1), 
which may, in part, be the result of the North East having the highest proportion of shops and retail 
units of all regions in the survey. This reflects the findings in the headline report which showed that 
thefts were by far the most common type of crime experienced, and the majority of crimes against the 
four sectors covered by the 2012 CVS were experienced by premises in the wholesale and retail 
sector. In fact, London had a higher rate of crimes per 1,000 premises than the North East if theft 
incidents are excluded. 
Figure 2.1: Number of incidents of crime per 1,000 premises, by crime type and region 
 
Chart notes:  
Source: Home Office, 2012 Commercial Victimisation Survey Experience of crime by characteristics – incidence tables: Table 
2.17b.  
 
0 
5,000 
10,000 
15,000 
20,000 
25,000 
North 
East 
London 
South 
East 
Wales 
North 
West 
East 
Midlands 
East of 
England 
West 
Midlands 
Yorkshire 
and the 
Humber 
South 
West 
NUMBER OF INCIDENTS PER 1,000 PREMISES 
All vehicle-
related theft 
All burglary 
All robbery 
Vandalism 
All fraud 
Assaults and 
threats 
All theft 

 
25 
 
Premises open to the public, in all sectors, experienced 17,600 incidents of crime per 1,000 premises 
compared with premises not open to the public which experienced 2,100 incidents of crime per 1,000 
premises. Over half (52%) of premises open to the public had experienced at least one incident of 
crime in the last 12 months, driven by the wholesale and retail sector where 59% of premises open 
to the public experienced crime in the last 12 months. By comparison, across all four CVS sectors, 
31% of premises not open to the public experienced crime in the last 12 months.  
As reflected in the results from other crime surveys2, the incidence rate was higher in urban areas 
than in rural areas, with 15,500 incidents of crime per 1,000 premises in urban areas compared with 
5,600 in rural areas3, ie around 3 times higher in urban areas. Around half (49%) of all business 
premises (in the four CVS sectors) in urban areas experienced at least one incident of crime in the last 
12 months, compared with just over a third (37%) of business premises in rural areas. Together with 
the incidence rate, this suggests that urban premises experience more repeat victimisation than 
premises in rural areas. 
Premises in town or shopping centres had the highest proportion (58%) of premises experiencing at 
least one incident of crime in the last year, compared with premises in other locations. In part at least, 
this is due to town and shopping centres having a higher concentration of wholesale and retail 
premises (which experience the highest crime rates) than other locations and also that the majority of 
town and shopping centres are found in urban areas. 
Premises that were more than a 15-minute walk from the nearest pub, club, bar or hotel experienced 
the lowest rates of crime per 1,000 premises (3,700 per 1,000) compared with those next to a pub, 
club, bar or hotel (20,400 per 1,000). Again, the high incidence rates here are largely driven by thefts. 
There could be a number of reasons for this pattern, for example those premises near pubs and other 
similar establishments may be more likely to be in urban areas or in town centres where crime rates 
are shown to be higher. It is also possible that the effects of alcohol from these establishments may 
have an impact on these figures, for example the rate of assaults and threats decreases the further 
away the premises are from a pub, club, bar or hotel (Figure 2.2).  
Figure 2.2: Number of incidents per 1,000 premises of all CVS crime, by crime type and 
distance from nearest pub/club/bar/hotel 
 
                                                 
2 For example, the ONS publication „Crime Statistics, Focus on Property Crime, 2011/12‟ presented findings showing that 
households in urban areas were more likely to be victims of crime than those in rural areas. 
http://www.ons.gov.uk/ons/rel/crime-stats/crime-statistics/focus-on-property-crime--2011-12/index.html 
3 For the purposes of this analysis, urban areas are defined as settlements with a population greater than 10,000. All other 
settlements are defined as rural.  
0 
5,000 
10,000 
15,000 
20,000 
25,000 
Next to your premises Within a 5-minute 
walk 
Within a 15-minute 
walk 
Further away 
NUMBER OF INCIDENTS PER 1,000 
PREMISES 
All vehicle-
related theft 
All burglary 
All robbery 
Vandalism 
All fraud 
Assaults and 
threats 
All theft 

 
26 
 
Chart notes:  
Source: Home Office, 2012 Commercial Victimisation Survey Experience of crime by characteristics – incidence tables Table 
2.17b. 
 
Premises that were a branch of a business with headquarters elsewhere (for example, a local branch 
of a supermarket chain) experienced 38,000 incidents of crime per 1,000 premises in the last 12 
months, the highest rate when compared with other business types. Independent businesses 
occupying a single premise experienced the lowest rate with 4,500 incidents of crime per 1,000 
premises (Figure 2.3).  
Figure 2.3: Number of incidents per 1,000 premises of all CVS crime, by business type 
 
Chart notes:  
Source: Home Office, 2012 Commercial Victimisation Survey Experience of crime by characteristics – incidence tables Table 
2.17b. 
 
Looking at various security measures present as reported by CVS respondents, the incidence rates of 
crime in the last 12 months are nearly always higher for those with security measures on their 
premises than those without. For example, there were 13,000 incidents of crime per 1,000 premises 
with a burglar alarm installed compared with 10,000 incidents of crime per 1,000 premises with no 
burglar alarm installed. This is reflected for all security measures, including incidence rates for 
premises with protective window and door measures, stock protection measures, vehicle protection 
measures, entry control and outer security.  
In addition, around two-thirds (65%) of those businesses that were members of a local partnership that 
works together to help reduce crime against businesses experienced at least one crime in the last 12 
months, compared with 43% of those businesses that were not member of such a partnership.  
Although this seems to imply that those premises with security measures in place are more likely to be 
victims of crime, it is not possible to determine whether or not this is the case as respondents were not 
asked if measures were installed before or after victimisation. In other words, it is possible that 
premises could have installed these measures as a result of being victimised, hence inflating the 
incidence rate for this group. Another factor may be that these premises are at most risk (either due to 
 4,482  
 12,212  
 38,350  
 23,651  
 -    
 5,000  
 10,000  
 15,000  
 20,000  
 25,000  
 30,000  
 35,000  
 40,000  
 45,000  
An independent 
business occupying 
these premises only 
The headquarters of a 
business occupying 
more than one 
premises 
A branch or division of 
a business with 
headquarters 
elsewhere 
A branch of a 
franchised chain 
NUMEBR OF  INCIDENTS PER 1,000 
PREMISES 

 
27 
 
their location or the service/goods provided) of crime and the presence of security measures cannot 
fully offset the other risks of victimisation. 
Analysis of likelihood of victimisation using logistic regression 
Logistic regression can be used to estimate how much the likelihood of victimisation is increased or 
reduced according to different characteristics or behaviours, taking into account the fact that some 
variables may be interrelated (for example, urban or rural location and IMD score4). Although logistic 
regression can be used to explore associations between variables, it does not necessarily imply 
causation and results should be treated as indicative rather than conclusive. Methodological details 
are available in the Technical Annex. 
Logistic regression shows that those characteristics that contributed most to explaining the likelihood 
of victimisation were business type (independent, HQ, etc.), whether the premises were open to public 
and business location (retail park, industrial estate, etc.). 
The model shows that, assuming all other characteristics are constant: 
 
premises open to the public were twice as likely to be a victim of crime than premises never 
open to the public  
 
premises in a town, city or shopping centre were more likely to be a victim of crime than those 
in a retail park 
 
branches of a franchised chain were almost twice as likely as independent businesses to have 
been victims of crime in the last year 
Other important factors were sector, number of employees and distance from nearest housing. 
According to the model: 
 
wholesale and retail premises and transportation and storage premises were more likely 
to be victims of crime than manufacturing premises 
 
premises with more than 50 employees were more likely to be victims of crime than those with 
fewer than 10 employees 
 
premises next to the nearest housing were more likely to be victimised than those with the 
nearest housing further away 
BURGLARY (INCLUDING ATTEMPTS) 
Across the four CVS sectors combined, the rate of burglaries was higher in urban areas (340 incidents 
of burglary per 1,000 premises) than in rural areas (206 per 1,000 premises). The wholesale and 
retail sector has the highest proportion of premises (82%) in urban areas than any of the other three 
sectors5 and, as shown in the headline findings report, this sector experienced the highest rate of 
burglaries (337 per 1,000 premises). 
Premises in Yorkshire and the Humber had the highest proportion (16%) of premises across the four 
CVS sectors experiencing burglary in the last 12 months, while the North East and East of England 
had the lowest (9%). Although the West Midlands had the same proportion of premises burgled in the 
last year as the England and Wales total (12%), they had the highest number of incidents per 1,000 
                                                 
4 The Index of Multiple Deprivation (IMD) combines all seven separate domains into one index to give a single score. A low score means 
high deprivation, and vice versa. 
5 Please see the technical annex for details of the characteristics of the sample, including proportions of urban 
and rural premises surveyed in each sector. 

 
28 
 
premises (Figure 2.4). This suggests that premises in the West Midlands experienced higher levels of 
repeat victimisation than other areas of England and Wales. 
Figure 2.4: Proportion of premises experiencing burglary in the last 12 months, by region 
 
Chart notes:  
Source: Home Office, 2012 Commercial Victimisation Survey Experience of crime by characteristics – prevalence tables: Table 
2.3a. 
 
Burglary rates are higher where premises are within a 5-minute walk of housing, than for those further 
than a 15-minute walk away (Figure 2.5). Again this may reflect that those businesses closest to 
housing are likely to be in urban areas where there are higher rates of crime. 
Figure 2.5: Number of incidents of burglary per 1,000 premises, by distance from housing  
 
16 
14 
13 
13 
12 
12 
12 
11 
9 
9 
0 
2 
4 
6 
8 
10 
12 
14 
16 
18 
Yorkshire 
and the 
Humber 
London 
South 
East 
Wales 
West 
Midlands 
East 
Midlands 
South 
West 
North 
West 
East of 
England 
North 
East 
PROPORTION OF PREMISES EXPERIENCING 
BURGLARY (INCLUDING ATTEMPTS) 
350 
303 
194 
219 
0 
50 
100 
150 
200 
250 
300 
350 
400 
Next to your premises Within a 5-minute 
walk 
Within a 15-minute 
walk 
Further away 
NUMBER OF INCIDENTS PER 1,000 
PREMISES 

 
29 
 
Chart notes:  
Source: Home Office, 2012 Commercial Victimisation Survey Experience of crime by characteristics – incidence tables: Table 
2.3b. 
 
In terms of proportion of premises experiencing burglary, 12% of premises less than 15 minutes from 
the nearest housing experienced burglary in the last year, compared with up to 10% further away. 
Thirteen per cent of premises less than 15 minutes from the nearest pub/hotel/club/bar experienced at 
least one incident of burglary in the last year, compared with up to 10% further away. 
Premises that had operated from the same location for 20 years or more had at least twice the number 
of incidents of burglary per 1,000 premises in the last 12 months than other premises. For example, 
businesses operating from the same premises for 10 to 20 years experienced 224 burglaries per 
1,000 premises, compared with 507 per 1,000 at premises established for 20 years or more (Figure 
2.6). It is possible that those businesses that have been at the same premises for more than a decade 
will have less sophisticated security measures in place, or be located in older, less secure buildings 
and therefore experience more crime.  
Figure 2.6: Number of incidents of all burglary per 1,000 premises, by length of time at premise 
 
Chart notes:  
The number of incidents of burglary in premises at the same location for less than one year has been inflated to reflect the 
average length of time at premises for this group (6.3 months on average; therefore rate multiplied by 1.9 to give 249).   
Source: Home Office, 2012 Commercial Victimisation Survey Experience of crime by characteristics – incidence tables: Table 
2.3b. 
 
The rate of burglaries at premises that had window and door security measures was lowest for those 
with shutters on windows or doors (172 incidents per 1,000) compared with those that had bars, gates, 
grilles or shatterproof glass (308 incidents per 1,000) or security locks (289 per 1,000). Thirteen per 
cent of premises with protective window or door measures had been victims of burglary, compared 
with 7% without such measures.  
131 (multiplied by 
1.9) 
155 
183 
194 
248 
224 
507 
0 
100 
200 
300 
400 
500 
600 
Less than 12 
months 
12 months 
but less than 
2 years 
2 years but 
less than 3 
years 
3 years but 
less than 5 
years 
5 years but 
less than 10 
years 
10 years but 
less than 20 
years 
20 years or 
longer 
NUMBER OF INCIDENTS PER 1,000 PREMISES 

 
30 
 
Premises with a burglar alarm experienced 304 burglaries per 1,000 premises whereas those without 
a burglar alarm experienced 196 per 1,000 premises. Conversely, 11% of premises with burglar 
alarms were victims of burglary, compared to 13% without. However, the higher number of burglaries 
per 1,000 premises for those with burglar alarms installed is likely to be explained by repeat 
victimisation.  
As previously mentioned, it is not possible to tell from the CVS data whether security measures were 
installed as a result of victimisation. Therefore, it is possible that measures were installed in response 
to a burglary taking place. Also, those premises most at risk of crime are the most likely to install 
security measures. 
Analysis of likelihood of burglary victimisation using logistic regression 
Logistic regression (explained in earlier in the section) shows that the characteristics that contributed 
most to explaining burglary victimisation were size (as approximated by number of employees), type of 
premises (shop, restaurant, etc.) and whether the business was a member of a local crime 
partnership. 
Assuming all other characteristics are constant, the model shows that: 
 
larger premises (those with more than 50 employees) were almost twice as likely to have 
been victims of burglary than smaller premises (those with 1 to 9 employees) 
 
premises that were members of a crime reduction partnership were more likely to have been a 
victim of burglary in the last year than non-members, however, membership could be as a 
result of being victimised or being located in an area at greater risk of victimisation 
 
serviced offices were the premises type least likely to have been victims of burglary in the last 
year, compared to all other premises types (eg shops, restaurants, etc.) 
Other important factors were business type (independent, HQ, etc.), whether the business is open to 
the public, region and length of time at premises. According to the model: 
 
premises open to the public are more likely to be victims of burglary than those not open to 
the public 
 
headquarters and branches of businesses were more likely to be burgled than independent, 
single premise businesses 
 
premises in the North East of England were less likely to be burgled than those in other 
regions of England and Wales 
 
VANDALISM 
Across all four sectors, premises in a town, city or shopping centre had the highest vandalism rate with 
762 incidents per 1,000 premises. The lowest rate was found in villages, rural areas, airports, on the 
coast or on a farm where 175 incidents of vandalism occurred per 1,000 premises in the last year.  
Perhaps unsurprisingly, urban areas were more than twice as likely to have experienced vandalism in 
the last year, compared with rural areas (556 incidents per 1,000 premises in urban areas compared 
with 230 incidents per 1,000 premises in rural areas). This is also reflected in the vandalism 
prevalence rates with around a fifth (18%) of all premises in urban areas experiencing at least one 
incident of vandalism in the last 12 months compared with 7% of business premises in rural areas. 

 
31 
 
The difference between urban and rural areas is mirrored in the vandalism rates by Output Area 
Classification6, which show that premises in areas categorised as „City Living‟ had the highest number 
of incidents per 1,000 premises and premises in the areas categorised as „Countryside‟ had the lowest 
(Figure 2.7). 
Figure 2.7: Number of incidents of vandalism per 1,000 premises, by Output Area Classification 
(OAC) 
 
Chart notes:  
Source: Home Office, 2012 Commercial Victimisation Survey Experience of crime by characteristics – incidence tables: Table 
2.4b. 
 
The vandalism incidence rate decreased the further a premises was from the nearest pub, club, bar or 
hotel. There were 640 incidents per 1,000 premises where such an establishment was next door but 
only 278 incidents per 1,000 premises where a pub, club, bar or hotel was more than a 15-minute walk 
away. Again, this may reflect the urban/rural differences between vandalism victimisation rates. 
Premises in more deprived areas (according to the IMD) experienced a higher rate of vandalism, 
compared with premises in the least deprived areas (Figure 2.8). A similar pattern occurs when 
looking at the proportion of premises experiencing vandalism. 
 
 
                                                 
6 This classification groups areas into clusters based on similar socio-economic and demographic characteristics. 
763 
701 
569 
491 
425 
272 
232 
0 
100 
200 
300 
400 
500 
600 
700 
800 
900 
City Living 
Blue Collar 
Communities 
Constrained by 
Circumstances 
Multicultural Typical Traits 
Prospering 
Suburbs 
Countryside 
NUMBER OF INCIDENTS PER 1,000 PREMISES 
OAC group 

 
32 
 
Figure 2.8: Number of incidents of vandalism per 1,000 premises in England, by IMD quintile 
 
Chart notes:  
Premises in England only. 
Source: Home Office, 2012 Commercial Victimisation Survey Experience of crime by characteristics – incidence tables: Table 
2.4b. 
 
Premises open for more than 12 hours on a weekday experienced a higher rate of vandalism than 
those open for less hours. There were 1,286 incidents of vandalism per 1,000 premises amongst 
those open for more than 12 hours on a weekday, almost four times as many as those open for 1 to 8 
hours a day during the week (328 incidents per 1,000 premises). In part this may be because the 
longer that premises are open, the more people are likely to be in the area. 
Analysis of likelihood of vandalism victimisation using logistic regression 
Logistic regression shows that those characteristics that contributed most to explaining the likelihood 
of vandalism were the urban/rural location, whether the business was a member of a crime 
partnership and business location (retail park, industrial estate, etc). 
The model shows that, assuming all other characteristics are constant: 
 
premises in urban areas were almost twice as likely to have been a victim of vandalism than 
those in rural areas 
 
premises in towns, cities or shopping centres were more likely to be victims of vandalism than 
premises in other business locations (eg retail parks, industrial estates) 
Other important factors were size of business (determined by number of employees), whether open to 
public, ACORN classification, region and distance from nearest housing or pub/club/bar/hotel. 
According to the model: 
0 
100 
200 
300 
400 
500 
600 
700 
800 
900 
1,000 
1 
2 
3 
4 
5 
NUMBER OF INCIDENTS PER 1,000 PREMISES 
IMD quintile 
Most deprived 
Least deprived 

 
33 
 
 
premises with more than 50 employees were more likely to be vandalised than those with 
fewer than 10 employees 
 
premises open to the public were more likely to be vandalised than those not open to the 
public 
 
premises located in neighbourhoods where residents are classed as „Moderate Means‟ were 
more likely to be vandalised than those where residents were „Wealthy Achievers‟ 
 
Premises in the North East of England were less likely to be vandalised than other regions of 
England and Wales 
 
Premises further from nearest housing, pubs, clubs, bars or hotels were less likely to be 
vandalised than those next to such places 
 
VEHICLE-RELATED THEFT 
The findings presented in this section cover theft from a vehicle and theft of a vehicle. Vehicle theft 
attempts are not covered.  
Findings from the headline findings report showed that transportation and storage premises had the 
highest rate of vehicle-related theft (506 incidents per 1,000 premises over the year compared to 70 or 
less per 1,000 premises in the other three sectors) and also the highest proportion of premises 
experiencing vehicle-related thefts (14% in the last 12 months). The report also showed that premises 
with more than 50 employees (and therefore those perhaps likely to have more vehicles) were 
consistently more likely to be victims of vehicle-related theft in each of the four CVS sectors. 
For all four sectors combined, retail parks had the highest rate of vehicle thefts with 156 incidents per 
1,000 premises (driven by vehicle crimes against the wholesale and retail sector), followed by 
industrial estates with 136 incidents per 1,000 premises. However, for the transportation and 
storage sector only, the highest rate of incidents occurred where premises were located on main or 
side streets near a town centre (1,038 per 1,000 premises) as shown in Figure 2.9.  
Figure 2.9: Number of incidents of vehicle-related theft per 1,000 premises in the transportation 
and storage sector, by premises location 
 
1,038 
382 
344 
8 
0 
200 
400 
600 
800 
1,000 
1,200 
Main/side street 
outside town centre 
Industrial estate 
Other 
Town/city/shopping 
centre 
NUMBER OF INCIDENTS PER 1,000 
PREMISES 

 
34 
 
Chart notes:  
Due to a small base size, incidents of vehicle-related thefts on retail parks in the transportation and storage sector are excluded 
from this figure. 
Source: Home Office, 2012 Commercial Victimisation Survey Experience of crime by characteristics – incidence tables: Table 
2.5b. 
 
Overall, of business premises that reported owning or leasing vehicles, those with crime prevention 
measures protecting vehicles experienced 310 incidents of vehicle-related theft per 1,000 premises 
compared with 95 incidents per 1,000 where no security protection measures were used. This relates 
to 16% of premises with vehicle security measures experiencing vehicle-related theft in the last 12 
months, compared with 7% where no security protection measures were used. It is possible that those 
businesses with measures in place are more likely to be victims because they are larger and have 
more vehicles on the premises. Again, it is possible that crime prevention measures on vehicles are 
used where there is greater risk of crime or as a result of victimisation. 
Analysis of likelihood of vehicle theft victimisation using logistic regression 
Logistic regression shows that those characteristics that contributed most to explaining the likelihood 
of vehicle theft victimisation were sector, size (number of employees) and business location (retail 
park, industrial estate, etc). 
The model shows that, assuming all other characteristics are constant: 
 
premises in the transportation and storage sector were three times more likely to be victims 
of vehicle theft than those in the manufacturing and wholesale and retail sectors 
 
larger premises (ie those with more than 50 employees) were twice as likely to have been 
victims of vehicle theft than smaller premises (ie those with fewer than 10 employees). Larger 
businesses may have more vehicles on the premises, and therefore have more exposure to 
vehicle-related theft 
 
premises on industrial estates were at least twice as likely to have been victims of vehicle-
related theft in the last 12 months than those in retail parks or in towns, cities or shopping 
centres 
 
ROBBERY 
The headline findings report showed that just 2% of premises had experienced robbery in the last 12 
months, the lowest prevalence rate of all crime types. 
The headline findings report also showed that wholesale and retail premises experienced the highest 
rate of robbery (633 per 1,000 premises over the year) of all four sectors and one of the highest 
prevalence rates (3% of wholesale and retail premises experienced at least one incident of robbery). 
Compared to other types of premises (eg factory, restaurant, etc.), shops experienced the highest 
proportion of robbery in the last year (5%). Similarly, in terms of business location, retail parks had the 
highest proportion of premises experiencing robbery (4%). 
Premises in the North West of England had the highest rate of robberies in England and Wales, with 
940 incidents of robbery per 1,000 premises, followed by London with 907 incidents per 1,000 
premises. The North East and Wales had the lowest rates with 59 and 54 incidents of robbery per 
1,000 premises respectively (Figure 2.10). This reflects the geographical concentration of robberies 
shown in police recorded crime figures, which show that London and the North West regions, along 

 
35 
 
with the West Midlands, had the highest number of robberies in the year to December 2012, while the 
North East and Wales had the lowest.7 
Figure 2.10: Number of incidents or robbery per 1,000 premises, by region 
 
Chart notes:  
Source: Home Office, 2012 Commercial Victimisation Survey Experience of crime by characteristics – incidence tables: Table 
2.6b. 
 
Urban areas had higher robbery rates than rural areas with 495 incidents of robbery per 1,000 
business premises in urban areas compared with just 60 incidents per 1,000 in rural areas. This ties in 
with the above as large metropolitan areas in England and Wales (London, Manchester, Birmingham) 
are in the regions with the highest robbery rates. The proportion of premises experiencing robberies in 
the last year was the same in urban and rural areas (2%), suggesting there is a higher rate of repeat 
victimisation in urban areas. 
Those premises closest to housing or pubs, clubs, bars or hotels had higher rates of robbery than 
those more than a 5-minute walk away, as shown in Figure 2.11. Again this may reflect the urban/rural 
split with those premises closest to housing or pub, club, bar or hotel perhaps more likely to be in 
urban areas. 
 
 
                                                 
7 Recorded Crime Data at Police Force Area Level is available at: http://www.ons.gov.uk/ons/publications/re-reference-
tables.html?edition=tcm%3A77-300972 
940 
907 
481 
403 
158 
123 
105 
89 
59 
54 
0 
100 
200 
300 
400 
500 
600 
700 
800 
900 
1,000 
North 
West 
London 
West 
Midlands 
South 
West 
South 
East 
Yorkshire 
and the 
Humber 
East 
Midlands 
East of 
England 
North 
East 
Wales 
NUMBER OF INCIDENTS PER 1,000 PREMISES 

 
36 
 
Figure 2.11: Number of robberies per 1,000 premises, by distance from housing, pub, club, bar 
or hotel 
 
Chart notes:  
Source: Home Office, 2012 Commercial Victimisation Survey Experience of crime by characteristics – incidence tables: Table 
2.6b. 
 
The number of robberies per 1,000 premises was considerably lower where premises did not employ 
someone to control entry. Premises where someone was employed to control entry experienced 1,084 
robberies per 1,000 premises compared with 292 per 1,000 premises where no one was employed to 
control entry. However, this may be because those premises that employ somebody to control entry 
are generally more susceptible to robbery (ie due to the goods they stock or the property they may 
hold). Again, it is also possible that someone is employed to control entry as a result of experiencing 
robbery in the last year.  
Robbery rates at premises open to the public were higher (540 per 1,000 premises) than where 
premises were not open to the public (32 per 1,000 premises). In addition, the rate of robberies per 
1,000 premises increased with the length of time open during the week or at the weekend as shown in 
Figure 2.12. These findings are likely to be driven by premises open to the public being in the 
wholesale and retail sector, which has a relatively high proportion of premises experiencing robbery. 
 
 
563 
330 
81 
0 
446 
592 
65 
12 
0 
100 
200 
300 
400 
500 
600 
700 
Next to your 
premises 
Within a 5 minute 
walk 
Within a 15 minute 
walk 
Further away 
Number of incidents per 1,000 premises 
Distance from 
nearest housing 
Distance from 
nearest 
pub/club/ 
hotel/bar 

 
37 
 
Figure 2.12: Number of robberies per 1,000 premises, by length of time open during the week 
and at weekends 
 
Chart notes:  
Source: Home Office, 2012 Commercial Victimisation Survey Experience of crime by characteristics – incidence tables: Table 
2.6b. 
 
Premises with a burglar alarm were less likely to have been victims of robbery (391 per 1,000 
premises) than those without an alarm (420 per 1,000 premises). While only marginally different, this 
opposes findings for other crime types, where presence of such security measures is associated with 
an increased victimisation rate.    
Analysis of likelihood of robbery victimisation using logistic regression 
Logistic regression shows that those characteristics that contributed most to explaining the likelihood 
of robbery were size (determined by number of employees), distance from nearest pub/club/bar/hotel 
and premises type (shop, office, factory, etc.). 
The model shows that, assuming all other characteristics are constant: 
 
premises with more than 50 employees were almost 8 times more likely to have been a victim 
of robbery than premises with fewer than 10 employees 
 
premises next to a pub/club/bar/hotel were around twice as likely to have experienced robbery 
in the last year than those further away 
Other important factors were presence of burglar alarm, region and membership of crime reduction 
partnership. According to the model: 
 
those without a burglar alarm were more likely to have been a victim of robbery in the last year 
than those with a burglar alarm installed 
31 
104 
534 
752 
1,999 
1,828 
376 
994 
0 
500 
1,000 
1,500 
2,000 
2,500 
Hours open during the week 
Hours open at the weekend 
NUMBER OF INCIDENTS PER 1,000 PREMISES 
1 - 8 hours 
9 - 12 hours 
More than 12 
hours 
24 hours a day 

 
38 
 
 
premises in the West Midlands and London were at least 3 times more likely than those in the 
North East to have been robbed in the last year. Premises in the North West, South West and 
Wales were at least twice as likely to have been robbed in the last year, compared with those 
in the North East 
 
premises that were members of a crime reduction partnership were more likely to have 
experienced robbery in the last year. It should be noted that it is not possible to tell from the 
CVS data whether premises became members of such partnerships before or after becoming 
a victim of crime 
 
ASSAULTS AND THREATS 
There were 1,182 incidents of assaults or threats per 1,000 premises across all four CVS sectors, as 
shown in the headline findings report. Accommodation and food premises experienced the highest 
incidence rate of assaults and threats (2,073 incidents per 1,000 premises) and the highest 
prevalence (15% of premises in this sector experienced at least one incident of this crime type). 
Manufacturing premises experienced the lowest prevalence with just 4% of premises experiencing at 
least one incident. 
Premises in the North East and in London had the highest rates of assaults and threats in England 
and Wales with 2,415 and 2,174 per 1,000 premises respectively. However, London and the North 
West had the highest proportion of premises experiencing assaults or threats in the last 12 months. As 
the North East had the highest incidence rate for assaults and threats, but a prevalence rate similar to 
the rate for England and Wales as a whole (10% of premises experienced at least one incident), this 
suggests that premises in the North East had higher levels of repeat victimisation. 
Figure 2.13: Proportion of premises experiencing assaults or threats in the last 12 months, by 
region 
 
Chart notes:  
Source: Home Office, 2012 Commercial Victimisation Survey Experience of crime by characteristics – prevalence tables: Table 
2.7a. 
 
14 
11 
11 
11 
10 
10 
9 
8 
7 
7 
0 
2 
4 
6 
8 
10 
12 
14 
16 
London 
North 
West 
Yorkshire 
and the 
Humber 
South East East of 
England 
North East Wales 
South 
West 
West 
Midlands 
East 
Midlands 
PROPORTION OF PREMISES EXPERIENCING 
ASSAULTS OR THREATS 

 
39 
 
Across all four sectors, premises in urban areas experienced a higher rate of assaults and threats 
(1,310 incidents per 1,000 premises) compared to premises in rural areas (737 per 1,000 premises). 
In particular, accommodation and food premises in urban areas experienced almost 4 times as 
many (2,628 per 1,000) assaults and threats than those in rural areas (710 per 1,000 premises). 
Eleven per cent of premises in urban areas experienced at least one incident of assaults or threats 
compared to 7% in rural areas. 
Retail parks had the highest rates of assaults and threats per 1,000 premises (4,028 incidents per 
1,000 premises). This is driven by the wholesale and retail sector where there were 5,629 incidents 
of assaults or threats per 1,000 wholesale and retail premises in retail parks. Town/city/shopping 
centres had the next highest rate (1,676 incidents per 1,000 premises), driven by incidents in premises 
in the accommodation and food sector and the transportation and storage sector (the latter 
perhaps being taxis). 
Figure 2.14: Number of incidents of assaults or threats per 1,000 premises, by premises 
location 
 
Chart notes:  
Due to small numbers, figures for some sectors are not shown in this chart. 
Source: Home Office, 2012 Commercial Victimisation Survey Experience of crime by characteristics – incidence tables: Table 
2.7b. 
 
Across all four sectors, businesses open to the public experienced 1,505 assaults and threats per 
1,000 premises, compared with 296 per 1,000 premises not open to the public. The rate was 
particularly high for premises open to the public in the accommodation and food and transportation 
and storage sectors (1,977 and 1,911 incidents per 1,000 premises, respectively). Around 13% of 
premises open to the public experienced at least one incident of assaults and threats in the last year, 
compared with just 3% of premises not open to the public.  
Where premises are open for longer hours the rate of assaults and threats increases. For those open 
for more than 12 hours a day during the week, accommodation and food premises have the highest 
rates of assaults or threats (5,826 per 1,000 premises) compared with other sectors. For premises 
0 
1,000 
2,000 
3,000 
4,000 
5,000 
6,000 
Retail park 
Town/city/ 
shopping centre 
Main/side 
street outside 
town centre 
Industrial estate 
Other 
NUMBER OF INCIDENTS PER 1,000 PREMISES 
Wholesale and retail 
Accommodation 
and food 
Transportation and 
storage 
Manufacturing 
All four sectors 

 
40 
 
open for more than 12 hours a day at the weekend, wholesale and retail premises have the highest 
rates of assaults or threats (6,408 per 1,000 premises) compared with other sectors. 
As shown in Figure 2.15, there is a difference in incidence rate of assaults and threats according to 
the level of deprivation in the areas in which premises are located. In general, premises located in the 
lowest 5 deciles of the Index of Multiple Deprivation (the most deprived areas) had higher rates of 
assaults and threats per 1,000 premises than those in highest 5 deciles (the least deprived areas). 
Figure 2.15: Number of incidents of assaults or threats per 1,000 premises, by IMD decile 
 
Chart notes:  
Figures for England only. 
Source: Home Office, 2012 Commercial Victimisation Survey Experience of crime by characteristics – incidence tables: Table 
2.7b. 
 
Thirteen per cent of premises with someone employed to control entry were victims of assaults or 
threats in the last 12 months, compared with 9% of premises without someone controlling entry. A fifth 
(20%) of premises with security guards experienced assaults or threats, compared to 10% of premises 
with a receptionist. Pubs, clubs and bars are more likely to have security guards rather than a 
receptionist, so we would expect these premises to have a high proportion experiencing assaults and 
threats. Hotels are likely to have a receptionist, and therefore we would expect a lower rate of assaults 
and threats than pubs, clubs and bars. 
This is reflected in the proportion of premises experiencing at least one incident of assaults and 
threats by type of premises: 
 
21% of pubs, clubs or bars 
 
15% of shops or retail units 
 
13% of hotels 
1,067 
1,322 
2,336 
1,811 
1,466 
622 
611 
1,086 
914 
476 
0 
500 
1000 
1500 
2000 
2500 
1 
2 
3 
4 
5 
6 
7 
8 
9 
10 
NUMBER OF INCIDENTS PER 1,000 PREMISES 
IMD decile 
Most deprived 
Least deprived 
Average for  5 most 
deprived deciles: 1,600 
Average for  
5 least 
deprived 
deciles: 742 

 
41 
 
Similarly, the proportion of licensed premises experiencing assaults or threats was disproportionately 
high. Around a fifth (18%) with licences to consume alcohol on the premises (eg pubs, clubs, bars, 
retaurants, hotels) and a quarter (26%) licensed for consumption off premises (eg shops), had 
experienced assaults or threats in the last year compared with 13% of unlicensed premises. This 
corresponds to other findings given in this section, as shops, pubs or restaurants are open to the 
public and likely to be in retail parks or in town and shopping centres. 
Analysis of likelihood of assaults and threats victimisation using logistic 
regression 
Logistic regression shows that those characteristics that contributed most to explaining the likelihood 
of assaults/threats were business type (independent, HQ, etc.), membership of a crime reduction 
partnership, and whether the premises is open to the public, again likely to be reflective of the type of 
premise. 
The model shows that, assuming all other characteristics are constant: 
 
premises that are open to the public were around 5 times more likely to have experienced 
assaults or threats than those not open to the public 
 
compared to independent businesses occupying one premises only, premises for other 
business types (headquarters, branches) were at least twice as likely to have experienced 
assaults or threats; this could be reflective of the size of the business 
 
premises that were members of a crime reduction partnership were more likely to have 
experienced assaults or threats in the last year; it should be noted that it is not possible to tell 
from the CVS data whether premises became members of such partnerships as a result of 
becoming a victim of crime 
Other important factors were number of employees, sector and premises type (shop, hotel, restaurant, 
etc.). According to the model: 
 
transportation and storage and accommodation and food premises were more likely to 
have experienced assaults or threats in the last year than manufacturing premises 
 
premises with more than 50 employees were 3 times as likely to be victims of assaults or 
threats as those with fewer than 10 employees. This is supported by findings from the 
headline report, which showed that for each sector, premises with more than 50 employees 
had a higher proportion of assaults and threats than those with less than ten employees 
 
shops, retail units and warehouses were most likely to have been victims of assaults or 
threats than any other premises type (includes factory, offices, hotels) 
THEFT 
Thefts were the most common type of crime experienced by business premises across the four 
sectors covered by the survey (6.8 million incidents). Theft incidents made up almost three-quarters 
(74%) of all incidents of crime covered by the survey and were experienced by around a quarter of 
premises (24%), as shown in the headline findings report. Of all four sectors, wholesale and retail 
premises experienced the highest rate of theft (15,835 per 1,000 premises). In fact, thefts by 
customers against wholesale and retail premises (ie shoplifting) made up almost half (45%) of all 
incidents of crime covered by the survey. The findings presented in this section cover all types of theft 
(by customers, employees, others and unknown persons) combined. 
Urban areas had higher rates of theft (11,619 per 1,000 premises) than rural areas (3,938 per 1,000 
premises). A quarter of premises (26%) in urban areas experienced at least one incident of theft in the 

 
42 
 
last year, compared with 18% in rural areas. Perhaps related to this is experience of theft according to 
premises‟ distance from housing and pubs, bars or hotels. In general, the proportion of premises 
experiencing theft decreased the further away from housing or pubs, clubs, bars or hotels, 
corresponding with the findings on incidence rates by rural/urban location (Figure 2.16). 
Figure 2.16: Proportion of premises experiencing theft in the last 12 months, by distance from 
housing and pubs, clubs, bars or hotels 
 
Chart notes:  
Source: Home Office, 2012 Commercial Victimisation Survey Experience of crime by characteristics – prevalence tables: Table 
2.12a. 
 
As shown in Figure 2.17, there are differences in theft incidence rates according to the deprivation of 
the area in which premises are located. According to the Index of Multiple Deprivation (IMD), those 
premises in the most deprived areas of England experienced higher rates of theft than those in the 
least deprived areas. 
 
 
26 
22 
22 
15 
32 
26 
19 
13 
0 
5 
10 
15 
20 
25 
30 
35 
Next to your 
premises 
Within a 5-minute 
walk 
Within a 15-
minute walk 
Further away 
PROPORTION OF PREMISES 
Distance from 
nearest housing 
Distance from 
nearest pub, club, 
bar or hotel 

 
43 
 
Figure 2.17: Number of thefts per 1,000 premises in last 12 months, by IMD quintile 
 
Chart notes:  
England premises only. 
Source: Home Office, 2012 Commercial Victimisation Survey Experience of crime by characteristics – incidence tables: Table 
2.12b. 
 
The higher rates of theft in urban and deprived areas is also reflected by the Output Area 
Classification variable, which shows that those premises in areas categorised as „Constrained by 
Circumstances‟ and „City Living‟ had the highest rate of theft, especially when compared to 
„Prospering Suburbs‟ and „Countryside‟, as shown in Figure 2.18.  
 
 
11,412 
13,485 
6,872 
9,071 
7,847 
0 
2,000 
4,000 
6,000 
8,000 
10,000 
12,000 
14,000 
16,000 
1 
2 
3 
4 
5 
NUMBER OF INCIDENTS PER 1,000 
PREMISES 
IMD quintile 
Most deprived 
Least deprived 

 
44 
 
Figure 2.18: Number of thefts per 1,000 premises in last 12 months, by Output Area 
Classification 
 
Chart notes:  
Source: Home Office, 2012 Commercial Victimisation Survey Experience of crime by characteristics – incidence tables: Table 
2.12b. 
 
As perhaps expected, given the high incidence rate for the wholesale and retail sector as a whole, 
theft rates were highest for shops and retail units (24,300 incidents of theft per 1,000 premises 
compared to the next highest of 3,637 incidents per 1,000 pub, bar or club premises). Around 44% of 
shops and retail units experienced thefts in the last 12 months, compared with 27% of hotels and 20% 
of restaurants. Town/city/shopping centres and retail parks had the highest proportions of premises 
experiencing thefts in the last 12 months (38% and 36%, respectively). These findings reflect those 
presented in the headline report which shows that 32% of wholesale and retail premises and 17% of 
accommodation and food premises experienced thefts in the last year. The rates were lowest for 
transportation and storage (15%) and manufacturing premises (9%). 
Two-thirds of premises that were licensed to sell alcohol for consumption off premises experienced 
theft in the last 12 months. This is perhaps unsurprising given that the majority of premises licensed to 
sell alcohol for consumption off premises only are shops. The proportion of premises licensed for 
alcohol consumption on and off premises experiencing theft is much lower (23%). High theft rates are 
driven by thefts by customers and it is likely that premises licensed to sell alcohol for consumption on 
the premises are bars, hotels and restaurants, where the products on sale are less easy to steal (ie 
behind a bar or in a kitchen). 
Independent businesses had the lowest proportion of premises experiencing theft of all business types 
(17%), compared with branches of businesses with headquarters elsewhere (42%) and branches of a 
franchised chain (45%). Again, this could be a reflection of the size of business. Findings in the 
headline report show that the proportion of premises experiencing thefts in the last 12 months 
increases with business size (as measured by number of employees). 
 
 
16,226 
12,752 
10,638 
10,475 
10,261 
9,571 
2,206 
0 
2,000 
4,000 
6,000 
8,000 
10,000 
12,000 
14,000 
16,000 
18,000 
Constrained 
by 
Circumstances 
City Living 
Multicultural 
Blue Collar 
Communities 
Typical Traits 
Prospering 
Suburbs 
Countryside 
NUMBER OF INCIDENTS PER 1,000 PREMISES 

 
45 
 
Analysis of likelihood of theft victimisation using logistic regression 
Logistic regression shows that those characteristics that contributed most to explaining the likelihood 
of theft were business type (independent, HQ, etc.), premises type (shop, restaurant, hotel, etc.) and 
membership of a crime reduction partnership. 
The model shows that, assuming all other characteristics are constant: 
 premises in shops or retail units were the most likely of all premises types to have 
experienced theft 
 independent businesses were the least likely to be victims of theft, compared to headquarters 
or branches 
 members of crime reduction partnerships were twice as likely to have been a victim of theft in 
the last 12 months than non-members; however, it is not possible to tell from the CVS data 
whether victims of crime became members of such a partnership before or after victimisation 
occurred. 
Other important factors were sector, size (number of employees), distance from nearest housing, and 
distance from nearest pub/club/bar/hotel. According to the model: 
 premises next to the nearest housing are 3 times more likely to be victims of theft than those 
more than 15 minutes away 
 premises with more than 50 employees were 3 times more likely to be victims of theft than 
those with fewer than 10 employees 
 premises in the wholesale and retail and transportation and storage sectors were more 
likely to have been victims of theft than those in the manufacturing sector 
 
FRAUD  
Fraud is defined in the CVS as “an incident where someone cheated the business in terms of diverting 
funds or goods”. The findings in this section cover all types of fraud captured in the CVS (i.e. fraud by 
employees, others and persons unknown). 
Types of fraud covered in the CVS include: 
 refund fraud (eg fraudulently claiming a refund for goods or services) 
 credit, debit or store card fraud (eg paying with stolen, cloned or invalid cards) 
 online banking fraud 
 false claims to be working for a business to obtain credit, goods or services  
The headline findings report showed there were 933 incidents of fraud per 1,000 premises in the last 
year across all four sectors together. Wholesale and retail premises experienced the highest rate 
(1,167 per 1,000 premises) and manufacturing the lowest (264 per 1,000 premises).  

 
46 
 
Urban areas experienced higher rates of fraud than rural areas (1,113 incidents per 1,000 premises 
compared with 306 per 1,000 premises in rural areas). Eleven per cent of premises in urban areas 
experienced at least one incident of fraud in the last 12 months, higher than 7% of premises in rural 
areas.  
Of all of the regions, London had the highest incidence rate (2,321 incidents per 1,000 premises, 
Figure 2.19) and the highest proportion of premises experiencing at least one incident of fraud (17%). 
This is likely to be driving the higher rates in urban areas. 
Figure 2.19: Number of incidents of fraud in the last 12 months per 1,000 premises, by region 
 
Chart notes:  
Source: Home Office, 2012 Commercial Victimisation Survey Experience of crime by characteristics – incidence tables: Table 
2.16b. 
 
Premises located in areas categorised as „Multicultural‟ or „City Living‟ by the Output Area 
Classification had the highest rate of fraud (1,566 and 1,340 per 1,000 premises, respectively) 
compared with all other premises. Areas classed as „Countryside‟ had the lowest fraud rate (391 per 
1,000 premises), reflecting the higher rate of fraud in urban areas, compared with rural areas (Figure 
2.20). 
 
 
2,321 
1,038 
986 
975 
894 
783 
629 
593 
409 
254 
0 
500 
1,000 
1,500 
2,000 
2,500 
London 
Wales 
South 
East 
North 
East 
East of 
England 
East 
Midlands 
Yorkshire 
and the 
Humber 
West 
Midlands 
South 
West 
North 
West 
NUMBER OF INCIDENTS PER 1,000 PREMISES 

 
47 
 
Figure 2.20: Number of incidents of fraud per 1,000 premises, by Output Area Classification 
 
Chart notes:  
Source: Home Office, 2012 Commercial Victimisation Survey Experience of crime by characteristics – incidence tables: Table 
2.16b. 
 
Rates of fraud incidents were also highest in those premises located in the more deprived areas of 
England (as shown in Figure 2.21).  
Figure 2.21: Number of incidents of fraud in last 12 months per 1,000 premises, by IMD quintile 
 
 
 
1,566 
1,340 
1,098 
886 
632 
466 
391 
0 
200 
400 
600 
800 
1,000 
1,200 
1,400 
1,600 
1,800 
Multicultural 
City Living 
Constrained 
by 
Circumstances 
Typical Traits 
Blue Collar 
Communities 
Prospering 
Suburbs 
Countryside 
NUMBER OF INCIDENTS PER 1,000  PREMISES 
1,176 
1,505 
577 
553 
715 
0 
200 
400 
600 
800 
1,000 
1,200 
1,400 
1,600 
1 
2 
3 
4 
5 
NUMEBR OF INCIDENTS PER 1,000 
PREMISES 
IMD quintile 
Least deprived 
Most deprived 

 
48 
 
Chart notes:  
Source: Home Office, 2012 Commercial Victimisation Survey Experience of crime by characteristics – incidence tables: Table 
2.16b. 
 
In terms of premises type (eg factory, restaurant, etc.), shops and retail units had the highest rate of 
fraud with 1,564 incidents of fraud per 1,000 premises. This is perhaps unsurprising given that the 
wholesale and retail sector experienced the highest rate of fraud of all four sectors covered by the 
survey. 
Reflecting these findings, premises in towns, cities and shopping centres had higher rates (5,787 per 
1,000 premises) than those in other locations, eg industrial estates (452 per 1,000). The proportion of 
premises experiencing fraud was highest in town/city/shopping centres (13%) or just outside the town 
centre (11%). These rates are driven by high fraud rates for premises in the wholesale and retail and 
accommodation and food sectors. 
Rates of fraud increased with the length of time premises were open to the public in a day, as shown 
in Figure 2.22. This is likely to be due to the fact that fraud is defined in the CVS as “an incident where 
someone cheated the business in terms of diverting funds or goods”. This means that the business 
was likely to have been open when the fraud occurred. Therefore, the longer premises were open, the 
more likely they were to be a victim of fraud. 
Figure 2.22: Number of incidents of fraud per 1,000 premises by number of hours premises 
open to the public, weekdays and weekends 
 
Chart notes:  
Due to small numbers the number of incidents of fraud per 1,000 premises open for 24 hours are not included in this chart. 
Source: Home Office, 2012 Commercial Victimisation Survey Experience of crime by characteristics – incidence tables: Table 
2.16b. 
 
Branches of a business with headquarters elsewhere had a higher proportion of premises that 
experienced fraud (14%) than independent businesses (9%). As seen previously, it is likely that this is 
related to the size of the business. Findings in the headline report show that, in general, the proportion 
of premises experiencing fraud increased with the number of employees. 
0 
500 
1,000 
1,500 
2,000 
2,500 
3,000 
During the week 
At the weekend 
NUMBER OF INCIDENTS PER 1,000 
PREMISES 
NUMBER OF HOURS OPEN TO THE PUBLIC 
1 - 8 hours 
9 - 12 hours 
more than 12 
hours 

 
49 
 
Analysis of likelihood of fraud victimisation using logistic regression 
Logistic regression shows that those characteristics that contributed most to explaining the likelihood 
of fraud were sector, size (number of employees) and region. 
The model shows that, assuming all other characteristics are constant: 
 
premises in the wholesale and retail and accommodation and food sectors were twice as 
likely to have been a victim of fraud than those in the manufacturing sector 
 
premises with more than 50 employees were almost three times more likely than those with 
less than 10 employees to have been a victim of fraud 
 
premises in London were almost seven times more likely than those in the North East to have 
been a victim of fraud 
Other important factors were whether the premises is in an urban or rural area, whether open to the 
public and membership of a crime partnership. According to the model: 
 
premises in urban areas were more likely to have been victims of fraud than those in rural 
areas 
 
premises open to the public were more likely to have been victims of fraud than those not 
open to the public 
 
premises that were members of a crime reduction partnership were more likely to have been a 
victim of fraud than those who were not members of such a scheme. Again, it should be noted 
that it is not possible to tell from the CVS data whether premises became members of such 
partnerships before or after becoming a victim of crime 
 
 
 

 
50 
 
3. Crime prevention 
INTRODUCTION 
In the 2012 CVS, half of the respondents were selected to answer additional questions about crime 
prevention measures at their current premises. This included questions on a range of security 
measures, including burglar alarms and security guards. As the half sample was randomly selected, 
the respondents are still a representative sample of business premises in England and Wales.  
In addition, all respondents were asked about membership of any local crime partnerships. Some 
analysis of these measures have also been carried out at a sector level and a business-size (in terms 
of number of employees) level.  
KEY FACTS 
 Around three-quarters (76%) of premises had burglar alarms installed. This proportion was higher 
for larger premises. 
 The wholesale and retail sector had the highest proportion of burglar alarms, with 79% of 
premises having a burglar alarm at their premises. 
 Around three-quarters (73%) of premises had protective window and door measures in place, the 
most common measures of this kind being bars, gates, grilles or shatterproof glass. 
 A third of premises (34%) reported having crime prevention measures on stock or equipment. 
 The transportation and storage sector had the highest proportion of premises with someone 
controlling entry (27%), while the wholesale and retail premises had the lowest proportion (9%). 
DATA TABLES 
Figures on the proportion of businesses with different security measures by sector and business size, 
can be found in the 2012 Commercial Victimisation Survey Crime prevention tables. 
SECURITY MEASURES 
Around three-quarters (76%) of premises had burglar alarms installed and, of these, around two-thirds 
(65%) had a notice explaining that an alarm system was used on the premises. The proportion of 
business premises with a burglar alarm is more than double the proportion of households having a 
burglar alarm, with figures published by the ONS showing that 29% of households had a burglar alarm 
in 2011/12.8 
The proportion of business premises with burglar alarms increased as the size of the premises 
increased. Almost three-quarters (73%) of premises with fewer than 10 employees have a burglar 
alarm, compared with 88% of premises with more than 50 employees (Figure 3.1). 
 
 
                                                 
8 Figures can be found in „Crime in England and Wales – Quarterly First Release, March 2012‟ 
http://www.ons.gov.uk/ons/rel/crime-stats/crime-statistics/period-ending-march-2012/index.html 

 
51 
 
Figure 3.1: Proportion of premises with a burglar alarm, by business size 
 
Chart notes:  
Source: Home Office, 2012 Commercial Victimisation Survey Crime prevention tables: Table 3.2. 
 
The wholesale and retail sector had the highest proportion of burglar alarms, with 79% of premises 
having a burglar alarm at their premises. The accommodation and food sector had the lowest 
proportion (70%). 
Around three-quarters (73%) of premises had protective window and door measures in place, with the 
wholesale and retail sector having the highest proportion (77%). These measures included bars, 
shutters and security locks on doors or windows. There was no difference between the proportion of 
large and small businesses having window and door security measures (Table 3.1). 
Table 3.1: Proportion of premises with window and door measures in place, by business size 
and sector 
2012 CVS, England and Wales 
  
Business size 
  
Industry Sector 
  
  
  
1-9 
Employees 
10-49 
Employees 
50+ 
Employees 
  
Manufacturing 
Wholesale 
& Retail 
Transportation 
& Storage 
Accommodation 
& Food 
  
All four 
sectors 
Window and 
door measures 
in place at 
premises 
73% 
73% 
73% 
74% 
77% 
71% 
61% 
73% 
Unweighted 
base 
1,002 
521 
473 
  
499 
516 
434 
547 
  
1,996  
 
The most common window and door security measures in place were bars, gates, grilles or 
shatterproof glass with almost half of premises (45%) reporting this kind of protection. Over half (52%) 
of manufacturing premises who reported having window and door measures had this type of 
measure. Of those with window or door security measures, the wholesale and retail sector had the 
highest proportion of premises with shutters (45%).  
73% 
87% 
88% 
76% 
0% 
10% 
20% 
30% 
40% 
50% 
60% 
70% 
80% 
90% 
100% 
1-9 Employees 
10-49 
Employees 
50+ Employees 
All business 
sizes 
PROPORTION OF PREMISES 

 
52 
 
Around a third of premises (34%) in all four sectors reported having crime prevention measures on 
stock or equipment. The manufacturing sector reported the lowest proportion of premises (24%) with 
this type of security measure in place. Again, the proportion of businesses with stock or equipment 
measures increased as the size of the premises increased. Just under a third (30%) of premises with 
fewer than 10 employees have crime prevention measures on stock or equipment, compared with two-
thirds (64%) of premises with more than 50 employees (Figure 3.2). 
Figure 3.2: Proportion of businesses with crime prevention measures on stock or equipment, 
by business size 
  
Chart notes:  
Source: Home Office, 2012 Commercial Victimisation Survey Crime prevention tables: Table 3.2. 
 
Across all four sectors combined, of those premises that reported having stock or equipment 
protection measures, almost two-thirds (65%) had security cameras, lighting or mirrors inside the 
premises. This proportion was similar regardless of business size. Around a quarter (24%) of those 
premises stating they employed stock or equipment protection measures said they used property 
marking or tagging. Just 6% of accommodation and food premises using these measures reported 
using property marking or tagging of equipment or stock, compared to 20% or more in the other three 
sectors (Table 3.2).  
There was also variation by size of business with around a fifth (20%) of those premises with fewer 
than 10 employees employing these measures having this particular security measure, compared with 
over a third (37%) of premises with 50 or more employees.  
 
 
30% 
47% 
64% 
34% 
0% 
10% 
20% 
30% 
40% 
50% 
60% 
70% 
1-9 Employees 
10-49 
Employees 
50+ 
Employees 
All business 
sizes 
PROPORTION OF PREMISES 

 
53 
 
Table 3.2: Proportion of premises with stock or equipment protection measures in place, by 
type of security and sector 
2012 CVS, England and Wales 
  
Manufacturing 
Wholesale & 
Retail 
Transportation 
& Storage 
Accommodation 
& Food 
  
All four 
sectors 
Property marking or 
tagging of your 
equipment or stock 
30% 
30% 
20% 
6% 
 
24% 
 
Security cameras, 
lighting or mirrors 
inside your premises 
53% 
68% 
65% 
65% 
 
65% 
 
Merchandise alarms 
6% 
11% 
8% 
4% 
 
9% 
 
A safe 
4% 
8% 
10% 
16% 
 
9% 
 
Security cage/ locked 
areas for stock or 
equipment 
9% 
7% 
4% 
10% 
 
7% 
 
Other 
19% 
20% 
20% 
29% 
  
22% 
 
Of those premises that owned or leased vehicles for business use from their premises, around half 
(47%) reported having crime prevention measures in place to protect their vehicles. As perhaps 
expected, two-thirds (66%) of these types of premises in the transportation and storage sector used 
crime prevention measures to protect their vehicles. Of these, 64% had an alarm and 42% had a 
vehicle tracking system. One-third of transportation and storage premises with vehicle protection 
measures had an immobiliser (Figure 3.3). 
Figure 3.3: Crime prevention measures on vehicles, transportation and storage premises that 
own or lease vehicles for business use 
 
 
 
64 
42 
33 
9 
28 
0 
10 
20 
30 
40 
50 
60 
70 
Alarm 
Vehicle tracking 
system 
Immobiliser 
Securely locked 
area 
Other 
PROPORTION OF PREMISES 

 
54 
 
Chart notes:  
Source: Home Office, 2012 Commercial Victimisation Survey Crime prevention tables: Table 3.1. 
 
Of premises in all sectors that reported having measures to protect their vehicles, 68% made use of 
alarms, 27% used immobilisers and 20% used vehicle tracking systems.  
Around 3 out of 4 (78%) premises have protective measures on the outside of their premises. Such 
measures included security lighting (80% of those premises with outer security measures had this), 
CCTV (60%) and barbed wire or anti climb walls (24%). Larger business premises (those with more 
than 50 employees) were more likely (96%) to have outer security measures installed than premises 
with fewer than 10 employees (75%).  
Thirteen per cent of premises in the four CVS sectors employed someone to control entry to their 
premises (for example, a security guard or receptionist). Of those that employed someone to control 
entry, 41% employed a security guard and a third (33%) employed a receptionist. The transportation 
and storage sector had the highest proportion of premises with someone controlling entry (27%), 
while wholesale and retail premises had the lowest proportion (9%, Figure 3.4).  
Figure 3.4: Proportion of premises employing someone to control entry, by sector 
 
Chart notes:  
Source: Home Office, 2012 Commercial Victimisation Survey Crime prevention tables: Table 3.1. 
 
Around half (52%) of larger premises (ie those with 50 or more employees) employed someone to 
control entry, compared with just 10% of premises with fewer than 10 employees.  
Overall, 14% of business premises in the four sectors are members of a partnership that works to 
reduce crime against businesses. The accommodation and food sector had the highest proportion of 
premises that were members of such a partnership (26%), while the manufacturing sector had the 
lowest proportion (6%). The proportion of premises that are members of a partnership increases with 
business size. Twelve per cent of premises with fewer than 10 employees were members, compared 
with a quarter (25%) of premises with 50 employees or more (Figure 3.5). 
 
 
27 
18 
15 
9 
13 
0 
5 
10 
15 
20 
25 
30 
Transportation 
and Storage 
Manufacturing Accommodation 
and Food 
Wholesale and 
Retail 
All four sectors 
PROPORTION OF PREMISES 

 
55 
 
Figure 3.5: Membership of crime reduction partnerships, by business size 
 
Chart notes:  
Source: Home Office, 2012 Commercial Victimisation Survey Crime prevention tables: Table 3.2. 
 
Of those reporting membership of a crime reduction partnership, almost half (48%) were members of a 
local neighbourhood watch or business watch group, while over a quarter (28%) had attended 
meetings between local businesses and police in the last 12 months. Findings from the 2002 
Commercial Victimisation Survey showed that participation in „co-operative activities‟ (such as a ring-
round scheme or meeting between police and local businesses) was often spurred by victimisation, 
with 35% of retailers and 23% of manufacturers saying that they became involved after an offence.9  
Details of the total amount spent on security in the last 12 months are available in Section 4 – Costs of 
crime against businesses.  
SECURITY AND VICTIMISATION 
This section has covered incidence and prevalence rates for each crime type by a range of 
characteristics, including security measures in place at the premises. The findings imply that those 
premises with security measures in place are more likely to be victims of crime. However, it is not 
possible to determine whether or not this is the case as respondents were not asked if measures were 
installed before or after victimisation. In other words, it is possible that premises could have installed 
these measures as a result of being victimised.  
There were only a handful of places where the number of incidents per 1,000 premises was lower 
where a particular security measure was present compared with where absent. These include: 
 
premises that had a burglar alarm present AND a notice up explaining that an alarm system 
was in use had a lower rate of burglaries (274 per 1,000 premises) than those without a notice 
(371 per 1,000 premises) 
                                                 
9 Due to differences in question wording, figures from the 2002 CVS on membership of crime reduction partnerships are not 
directly comparable to the 2012 survey. 
12% 
20% 
25% 
14% 
0% 
5% 
10% 
15% 
20% 
25% 
30% 
1-9 Employees 
10-49 
Employees 
50+ 
Employees 
All business 
sizes 
PROPORTION OF PREMISES 

 
56 
 
 
presence of a burglar alarm or protective window and door measures (e.g. bars, shutter, 
security locks on windows) led to lower vandalism rates than those without these types of 
security 
 
protective window and door measures at premises were associated with lower levels of 
assaults or threats (727 incidents per 1,000 premises) than those with no window or door 
measures (967 per 1,000) 
 
protective window and door measures at premises were also associated with lower levels of 
robbery (282 incidents per 1,000 premises) than those with no window or door measures (706 
per 1,000) 
Comparing prevalence rates for burglary with entry and attempted burglaries by security measures 
gives an idea of how preventative certain measures are (see Figure 3.3). For the most part there is 
little difference between the rates for those with or without security measures in place. However, for 
those premises with security measures outside, the rate of attempted burglaries is much higher (18%) 
than the rate of burglaries with entry (8%). This perhaps suggests that outer security measures are 
important in helping to reduce burglary with entry.   
Table 3.3: Proportion of premises experiencing burglary, by security measures in place  
Percentages 
2012 CVS, England and Wales 
Type of security measure 
Proportion of premises 
experiencing burglary with entry 
Proportion of premises 
experiencing attempted burglary 
Burglar alarm 
7 
6 
Outside premises 
8 
18 
Protective window and door 
measures  
8 
7 
Crime prevention measures 
to protect stock or 
equipment  
10 
9 
 
Another factor that may help to explain why victimisation rates are higher where security measures are 
present may be due to these premises being most at risk of crime (either due to their location or the 
service/goods provided), so the presence of security measures cannot fully offset the other risks of 
victimisation.  
Findings presented in the „Experience of crime by business and location characteristics‟ section 
showed that crime rates are higher in urban areas. Figure 3.6 shows how the proportion of premises 
with burglar alarms, window and door security measures or someone employed to control entry is 
higher in urban areas than rural areas. For example, 78% of premises in urban areas had burglar 
alarms, compared with 69% in rural areas.  
This supports the conclusion that crime rates are higher where security measures are present as 
these premises are most at risk of crime, and therefore experience more victimisation, regardless of 
the security prevention measures in place. 
 
 

 
57 
 
Figure 3.6: Proportion of premises with security measures, in urban and rural areas 
 
Chart notes:  
Source: Home Office, 2012 Commercial Victimisation Survey Crime prevention tables: Table 3.3. 
 
 
 
 
78 
75 
14 
69 
68 
11 
0 
10 
20 
30 
40 
50 
60 
70 
80 
90 
Burglar alarm 
Window/door measures 
Someone employed to 
control entry 
PROPORTION OF PREMISES (%) 
Urban 
Rural 

 
58 
 
4. Costs of crime against businesses 
INTRODUCTION 
This section covers the costs of crime to businesses, both as a result of victimisation and through 
preventative measures.  
KEY FACTS 
 The most expensive individual incidents of crime were theft of vehicles, which cost £5,000 on 
average (defined using the median value). Burglary with entry also incurred high average costs 
(£1,000 per incident), with the other crime types each having lower median costs ranging from £35 
to £350 per incident. 
 The total amount spent by businesses per year on security at the premises was £376 on average 
(median). This tended to be higher than the amount spent on IT security. Of those businesses that 
had computers, the average (median) amount spent on IT security over the previous 12 months 
was £200. 
DATA TABLES 
Figures on the cost of each crime type by sector and the cost of crime prevention measures can be 
found in the 2012 Commercial Victimisation Survey Costs of crime against businesses tables. 
COSTS OF CRIME PER INCIDENT 
Respondents who had been victims of crime within the previous 12 months were asked for the direct 
financial cost resulting from the most recent incident of that crime type. Respondents were asked for 
the total value regardless of whether the items were returned or whether they received any insurance 
payment. A minority of respondents were unable to provide absolute figures for these costs and were 
therefore asked to estimate them within a range. For these cases, the midpoint of that range was then 
taken as the cost of the particular crime to that respondent. The figures in this section have been 
derived by combining the absolute figures and midpoint answers, although a few cases which 
indicated an extremely high range of cost were excluded from the analysis. For more details please 
see the Technical Annex. The costs of each crime type are shown in Table 4.1 below. 
Table 4.1: Cost of incidents of crime types 
All four industry sectors 
  
Mean 
25th 
percentile 
Median 
75th 
percentile 
Maximum 
Unweighted 
base 
Burglary 
  
  
  
  
  
  
  Burglary with entry 
£3,986 
£250 
£1,000 
£3,751 
£502,000 
417 
  Attempted burglary 
£445 
£0 
£80 
£300 
£6,000 
281 
  
  
  
  
  
  
  
Vandalism 
£548 
£50 
£150 
£400 
£65,000 
630 
  
  
  
  
  
  
  
Vehicle-related theft 
  
  
  
  
  
  
  Theft of vehicles 
£19,526 
£4,000 
£5,000 
£30,001 
£61,000 
38 
  Theft from vehicles 
£1,117 
£150 
£350 
£1,000 
£100,000 
231 
  
  
  
  
  
  
  
All robbery (inc. 
attempts) 
£1,650 
£12 
£80 
£500 
£100,000 
68 

 
59 
 
  
  
  
  
  
  
  
Theft 
  
  
  
  
  
  
 Theft by customers 
£380 
£10 
£35 
£100 
£75,000 
290 
 Theft by employees 
£1,048 
£20 
£107 
£500 
£150,000 
244 
 Theft by others 
£1,583 
£35 
£200 
£600 
£26,000 
97 
Theft by persons 
unknown 
£889 
£35 
£110 
£350 
£100,000 
407 
  
  
  
  
  
  
  
Fraud 
  
  
  
  
  
  
  Fraud by employees 
£5,494 
£50 
£200 
£1,500 
£1,000,000 
85 
  Fraud by others 
£5,690 
£50 
£250 
£1,200 
£1,000,000 
216 
  Fraud by unknown 
persons 
£1,859 
£20 
£280 
£1,300 
£50,000 
113 
 
Table notes:  
Note: Mean costs will be heavily skewed by a small number of incidents incurring large costs. 
Theft of vehicles includes both incidents where the vehicle was not recovered and cost of damage to recovered vehicles. 
 
In terms of individual incidents, the most expensive on average (defined using the median value) was 
theft of vehicles (£5,000), which is perhaps to be expected given the high value of vehicles. In 
particular, for those incidents where the vehicle was not recovered the median cost was much higher 
(£14,000, based on an unweighted base of 30). In contrast, the average cost of theft from vehicles, 
was much lower at a median cost of £350, and this crime type made up 90% of all vehicle-related 
thefts. 
The average cost of burglary with entry, which includes both the cost of goods stolen and of damage, 
was also relatively high (£1,000). On average the total cost of burglary with entry was highest in the 
wholesale and retail sector (£1,800) and lowest for transportation and storage (£630) and 
accommodation and food (£400) sectors (Figure 4.1).  
Figure 4.1: Average (median) cost of selected crime types, by sector 
 
£0 
£200 
£400 
£600 
£800 
£1,000 
£1,200 
£1,400 
£1,600 
£1,800 
£2,000 
Manufacturing 
Wholesale 
& Retail 
Transportation 
& Storage 
Accommodation 
& Food 
All four sectors 
MEDIAN COST OF INCIDENT 
INDUSTRY SECTOR 
Burglary with entry 
Vandalism 
Theft by persons unknown 
Theft by employees 
Attempted burglary 

 
60 
 
Chart notes:  
Base: Businesses that had experienced each crime type. 
Note: Cost for theft by employees in the manufacturing sector not presented as sample size for the sector is too small. 
Source: Home Office, 2012 Commercial Victimisation Survey Costs of crime against businesses tables. 
 
For most other types of crime the average cost of any one incident was much lower than for theft of 
vehicles or burglary with entry. For example, the median cost of theft by customers across all four 
sectors was £35. It should be noted that the total financial cost of crime depends not just the cost of 
individual incidents but also on their frequency. Thefts by customers make up almost half (47%) of all 
crimes against businesses in the four sectors, so although the average cost of each individual incident 
may be low, the total cost to businesses of all thefts by customers is likely to be high.  Although 
theoretically possible to calculate the total cost per year for a particular crime type by multiplying the 
cost of the most recent incident by the estimated number of crimes over the last year, due to high cost 
outliers and respondents estimating the extent of multiple victimisations, the resulting estimates are 
unlikely to accurately reflect the true figure and therefore have not been calculated. 
COSTS OF CRIME PREVENTION 
In order to reduce the average length of the questionnaire, during the survey respondents were 
assigned at random to one of two sets of questions on crime prevention. Half of all respondents were 
asked questions on electronic crime, including the total amount of money spent per year on IT 
security. The other half of respondents were asked about crime prevention, including the total amount 
spent on security for the premises during the previous 12 months. These costs include maintenance 
and running costs, charges for new security equipment and security personnel costs, but do not 
include the costs of insurance or IT security. Similarly to the cost of incidents of crime, those 
respondents who were unable to give an absolute figure have been included as the midpoint of the 
range they indicated. 
Across all four sectors, of those business premises that had computers, the average (median) amount 
spent on IT security over the previous 12 months was £200. While this did vary by sector, with the 
transportation and storage sector spending on average £400 and the accommodation and food 
sector spending less (£120), the average cost of IT security was much more dependent on the size of 
the business premises (as represented by number of employees). Perhaps unsurprisingly, the 
average (median) amount spent on IT security tended to increase with size, as shown in Figure 4.2 
below.  
 
 

 
61 
 
Figure 4.2: Median total amount spent per year on IT and non-IT security by number of 
employees 
 
Chart notes:  
Note: Small businesses have 1-9 employees, medium businesses have 10-49 employees and large businesses have 50 or 
more employees. 
Source: Home Office, 2012 Commercial Victimisation Survey Costs of crime against businesses tables. 
 
These average costs may appear at first to be relatively low; however, this reflects the nature of the 
local premises sampled in that they probably do not have high IT security costs compared with head 
offices. This will particularly be the case for local branches of national chains. 
 
On average, the total amount spent per year by business premises on non-IT security, with a median 
cost of £376, was higher than the average amount spent on IT security. Again, these costs tended to 
increase with business size (number of employees), as shown in Figure 4.2. In particular, the median 
cost for the largest business premises (those with 100 or more employees) was £25,000, much higher 
than the average spend by smaller business premises. This is likely to be due to the types of security 
used by larger business premises which would be more likely to employ a security guard and use 
CCTV.  
Similarly to IT security costs, the median cost of all non-IT security tended to be higher in the 
transportation and storage sector (£1,000) and lower in the accommodation and food sector 
(£250). This variation in spend on security is likely to be due to the proportion of businesses in each 
sector with any security measures in place (as a higher proportion of premises with no measures 
would lower the average) and the type of security measures in place in each sector (see Section 3). 
 
 
 
 
 
£0 
£5,000 
£10,000 
£15,000 
£20,000 
£25,000 
£30,000 
1-4 
5-9 
10-19 
20-49 
50-99 
100+ 
MEDIAN SECURITY COST PER YEAR 
NUMBER OF EMPLOYEES AT PREMISES 
IT security 
non-IT security 

 
62 
 
5. Crime in the wholesale and retail sector: 
2002 and 2012 compared 
INTRODUCTION 
This section provides a comparison of crime in the wholesale and retail sector recorded by the 2002 
and 2012 Commercial Victimisation Surveys (CVS). The section focuses on changes in the likelihood 
of victimisation for each crime type and on levels of repeat victimisation; on the likelihood of reporting 
crimes to the police and levels of contact and satisfaction with the police. The final section focuses on 
the crime of theft by customers, and specifically on changes in the factors which are associated with 
the risk of victimisation for this crime.  Due to differences in the definition of the wholesale and retail 
sector between 2002 and 2012, this analysis is based on a subset of the 2012 data. Therefore results 
in this section will be different to those in the rest of this publication and the headline findings report. 
KEY FACTS 
 There were around 14.5 million fewer crimes against wholesale and retail business premises in 
2012 than in 2002 (down from a total of around 21.5 million to around 7 million). 
 The incidence rates for all main crime types declined between the two surveys (with the exception 
of vandalism and robbery, for which changes were not statistically significant). 
 The largest decrease between 2002 and 2012 was for theft (down from 51,799 incidents per 1,000 
premises to 20,265 per 1,000 premises). 
 Although the volume of crime has changed notably between the two surveys in the wholesale and 
retail sector, theft accounts for a similar proportion of total crime in 2012 as it did in 2002; around 4 
out of 5 incidents reported in both surveys were incidents of theft.  
 The number of wholesale and retail premises which were victimised has fallen from 242,000 to 
162,000, meaning there were around 80,000 fewer premises that were victims of crime in 2012 
than in 2002. 
 The largest decreases in victimisation rates were for theft (down from 52% to 38% of premises) 
and burglary (down from 25% to 12%). 
DATA TABLES 
Figures on the comparison of crime in the wholesale and retail sector recorded by the 2002 and 2012 
Commercial Victimisation Surveys can be found in the 2012 Commercial Victimisation Survey, 
Wholesale and retail sector – 2002 and 2012 comparison tables. 
A NOTE ON METHODOLOGY 
Both the manufacturing and wholesale and retail sectors were included in the 2002 and 2012 CVS. 
However, due to wide-ranging changes in the manufacturing sector, reflected in changes to the 
Standard Industrial Classification (SIC) codes manufacturing data from the two years are not 
comparable.  
As there have been only limited changes to the SIC classifications in the wholesale and retail sector, a 
subset of the 2012 data is comparable with the full wholesale and retail sample from 2002. It should 
be noted, however, that as this analysis uses only a subset of the 2012 data, results in this section will 

 
63 
 
be different to those in the rest of this publication. The 2012 subset includes only those businesses 
that would have been classed as wholesale and retail in 2002, as well as in 2012, plus a small 
additional sample of businesses which would have been classed as wholesale and retail in 2002, but 
not in 2012 due to changes in the SIC codes. In 2012 this additional sample of business premises 
belonged to sectors outside of those surveyed and so would otherwise not have been eligible for 
inclusion in the CVS. There are 3,955 business premises in the 2002 wholesale and retail sample and 
777 business premises in the 2012 wholesale and retail subsample.  
For information on crime in the wholesale and retail sector in 2012, readers should refer to the other 
sections of this report and to the Crime against businesses: Headline findings from the 2012 
Commercial Victimisation Survey publication.   
Table 5.1: Proportion of types of business premises within the wholesale and retail sector 
Percentages 
CVS, England and Wales 
  
2002 
2012 
Independent business occupying these premises only 
62 
63 
HQ of business occupying more than 1 premises 
4 
4 
Branch or division of business with HQ elsewhere 
31 
29 
Branch of a franchised chain 
3 
3 
Unweighted Base  
3,953 
773 
 
As Table 5.1 shows, the coverage of business types, in terms of independent businesses, multi-site 
businesses and franchises is very similar between the two surveys.   
Both surveys used stratified random sampling techniques to identify their respondents and telephone 
interviews with businesses to collect their data. The 2002 CVS had a slightly higher response rate 
than the 2012 CVS, with 61% of potential premises taking part, compared to 54% of premises in 2012.  
Although many of the same questions were asked of respondents there are some differences between 
the questionnaires and recoding was necessary to make variables comparable across the two 
surveys. This was not possible for all crime types or questions, however, and consequently cyber 
crime and anti-social behaviour have not been included in this analysis.  
In order to determine if the differences between the surveys were statistically significant, estimated 
confidence intervals were used. For further information see the Technical Annex.     
LIKELIHOOD OF VICTIMISATION   
Incidence rates 
The number of crimes experienced by the wholesale and retail population has dropped markedly 
between the two surveys. In 2002 it was estimated that there were around 21.5 million crimes. In 2012 
the estimated total number of crimes was 7 million10, around one-third of those in 2002. 
 
 
                                                 
10 This figure is for the 2012 comparative subsample only. For the full wholesale and retail sample in 2012 the total number of 
crimes was 7.7 million. 

 
64 
 
Table 5.2 Rate and number of incidents of crime in the wholesale and retail sector 
Percentages 
CVS, England and Wales 
  
2002 
2012 
% change 
and 
statistical 
significance 
of change 
  
Incidents 
per 1,000 
premises 
Number of 
incidents 
(000s) 
Incidents 
per 1,000 
premises 
Number of incidents (000s) 
All burglary (inc. 
attempts) 
746 
243 
274 
79 
-63 
* 
Vandalism 
1,360 
444 
590 
170 
-57 
Theft of vehicles 
45 
15 
6 
2 
-87 
* 
Theft from vehicles 
228 
74 
59 
17 
-74 
* 
All vehicle-related theft 
273 
89 
65 
19 
-76 
* 
All robbery (inc. 
attempts) 
400 
131 
858 
248 
114 
Assaults and threats 
5,325 
1,738 
1,481 
428 
-72 
* 
Thefts by customers 
37,264 
12,163 
13,327 
3,849 
-64 
* 
Thefts by employees 
2,081 
679 
786 
227 
-62 
Thefts by others 
2,402 
784 
174 
50 
-93 
* 
Thefts by unknown 
persons 
10,053 
3,281 
5,979 
1,727 
-41 
All theft 
51,799 
16,907 
20,265 
5,852 
-61 
* 
Fraud by employees 
684 
223 
295 
85 
-57 
Fraud by others 
5,244 
1,712 
397 
115 
-92 
* 
All fraud 
5,949 
1,942 
691 
200 
-88 
* 
ALL CVS CRIME 
65,973 
21,533 
24,224 
6,996 
-63 
* 
 
Table notes:  
* Indicates a statistically significant difference between incidence rates.  
As Table 5.2 shows, the number of crimes experienced by the wholesale and retail sector in 2012 has 
decreased across most of the major crime types, compared to 2002. In particular, theft has fallen 
considerably from a rate of 51,799 incidents per 1,000 premises in 2002, to 20,265 per 1,000 
premises in 2012. Much of the reduction in volume of theft comes from the lower rate of thefts by 
customers in 2012; although theft by others also shows a decrease in incidence rate in 2012.  
In contrast, levels of police recorded shoplifting offences11 remain quite similar between 2002/3 and 
2011/12, although there had been some fluctuation in the intervening years. Police recorded 
shoplifting fell from 310,881 offences in 2002/3 to 308,322 offences in 2011/12. The CVS records a 
much higher volume of this crime in both years of the survey, with the number of incidents falling from 
12.2 million in 2002 to 3.8 million in 2012. This may indicate that police recorded crime figures have 
underestimated the extent of the decline in this crime type. However, it should be noted that police 
recorded crime figures are highly dependent on whether the shops themselves apprehend suspects 
and/or subsequently involve the police, whereas the CVS data are not.  
 
In 2012, incidence rates for assaults and threats and all vehicle theft were around a quarter of those 
reported in 2002. Assaults and threats fell from 5,325 per 1,000 premises to 1,481 per 1,000 premises 
and all vehicle theft fell from a rate of 273 per 1,000 premises in 2002 to 65 per 1,000 premises in 
                                                 
11 The terms theft by customers and shoplifting are used interchangeably within this report. In the tables the term theft by 
customers will be used.  

 
65 
 
2012. The incidence rates for both of the subcategories of vehicle theft – theft of a vehicle and theft 
from a vehicle – have also decreased.  
Burglary rates also decreased between 2002 and 2012. Although not strictly limited to commercial 
retail properties, the CVS trend for burglary is similar to the decline seen in police recorded crime for 
burglary in a building other than a dwelling, which fell from 451,904 offences in 2002/3 to 255,626 
offences in 2011/12.  
In the CVS, fraud offences have fallen from a rate of 5,949 incidents per 1,000 premises in 2002 to 
691 per 1,000 premises in 2012. A reduction in fraud by others (ie non-employees) seems to be 
driving this decline.  
There was a non-statistically significant decrease in the rate of vandalism against wholesale and retail 
premises between the two surveys. Conversely, there has been a non-statistically significant increase 
in the rate of robberies (including attempts) amongst wholesale and retail premises. However, police 
recorded crime figures show a decline in robbery from a business property, falling from 11,066 
offences in 2002/3 to 6,770 offences in 2011/12. It should be noted that police recorded crime figures 
cover all industry sectors, whilst the CVS data cover only the wholesale and retail sector.  
Figure 5.1: Incidents of crime per 1,000 premises experienced in the last 12 months 
 
Chart notes: 
Source: Home Office, 2012 Commercial Victimisation Survey Wholesale and retail sector – 2002 and 2012 comparison tables 
Table 5.2. 
 
 
0 
10,000 
20,000 
30,000 
40,000 
50,000 
60,000 
All burglary 
(inc. attempts) 
Vandalism 
All vehicle-
related theft 
All robbery 
(inc. attempts) 
Assaults and 
threats 
All theft 
All fraud 
NUMBER OF INCIDENTS PER 1,000 
PREMISES 
2002 
2012 

 
66 
 
Table 5.3: Number of incidents by crime type as a proportion of total incidents of crime 
Percentages 
CVS, England and Wales 
  
2002 
2012 
All burglary (inc. attempts) 
1 
1 
Vandalism 
2 
2 
All vehicle-related theft 
0 
0 
All robbery (inc. attempts) 
1 
4 
Assaults and threats 
8 
6 
All theft 
79 
84 
All fraud 
9 
3 
 
Table Notes:    
For number of incidents by crime type and total number of incidents of crime see Table 5.1.  
Although the overall volume of crime experienced has declined between the surveys the proportion 
that crime types account for within the total remains quite similar. Theft offences accounted for 79% of 
total crime against wholesale and retail premises in 2002 and 84% of total offences in 2012. Similarly, 
within this crime type, it is estimated that thefts by customers made up 56% of total crime in 2002 
compared with 54% in 2012. Although at a much lower volume than theft offences, burglary, 
vandalism, and vehicle crime also follow this pattern and account for the same fraction of crime in 
2012 as they did in 2002 (Table 5.3). 
Prevalence rates 
As shown in Table 5.4, around 242,000 wholesale and retail premises were victims of at least one 
incident of crime in the 12 months prior to interview in 2002, which fell to 162,000 in 2012. This 
represents 56% of the current comparable retail population, a lower proportion than the 74% of 
wholesale and retail premises experiencing crime in 2002. As with incidence rates, this pattern holds 
for most of the major crime types, with the exception of robbery and vandalism (where apparent falls in 
rate of victimisation were not statistically significant). 
Table 5.4: Prevalence of crime and number of victims in the wholesale and retail sector 
Percentages 
  
CVS, England and Wales 
  
2002 
2012 
% change and 
statistical significance 
of change 
  
% of 
premises  
Number of 
victims 
(000s of 
premises) 
% of 
premises  
Number 
of victims 
(000s of 
premises) 
All burglary (inc. 
attempts) 
25 
83 
12 
35 
-53 
* 
Vandalism 
23 
75 
18 
52 
-21 
Theft of vehicles 
3 
10 
1 
2 
-81 
Theft from vehicles 
8 
27 
3 
8 
-64 
* 
All vehicle-related theft 
10 
32 
4 
10 
-65 
* 
All robbery (inc. 
attempts) 
6 
18 
4 
10 
-37 
Assaults and threats 
20 
66 
12 
35 
-41 
* 
Thefts by customers 
43 
139 
27 
77 
-38 
* 
Thefts by employees 
10 
33 
5 
16 
-46 

 
67 
 
 
Table notes:  
*Indicates a statistically significant difference between prevalence rates. 
Burglary of wholesale and retail premises has fallen notably. A quarter of premises (25%) reported at 
least one incident of this crime in 2002, compared with 12% in 2012.  This is also the case for overall 
theft; the proportion of premises experiencing any type of theft has dropped from 52% in 2002 to 38% 
in 2012. This reduction is driven by falls in the victimisation rate of theft by customers and is supported 
by a fall in theft by others.  
A similar trend is observed for fraud: 1 in 5 (20%) wholesale and retail premises experienced fraud in 
2002, falling to 8% in 2012. Fraud by others seems to be driving this reduction. 
Vehicle crime also fell within the wholesale and retail sector between 2002 and 2012, dropping from 
10% to 4%. This decrease is largely caused by reductions in thefts from a vehicle. 
Decreases in victimisation are not limited to acquisitive crime. The proportion of premises which had 
experienced assaults and threats also fell. A fifth (20%) of wholesale and retail premises stated that 
they had been the victim of this crime once or more in 2002, compared with 12% premises in 2012.  
Figure 5.2: Proportion of premises that experienced each crime in the last 12 months 
 
Chart notes: 
Source: Home Office, 2012 Commercial Victimisation Survey Wholesale and retail sector – 2002 and 2012 comparison tables 
Table 5.4. 
 
25 
23 
10 
6 
20 
52 
20 
12 
18 
4 
4 
12 
38 
8 
0 
10 
20 
30 
40 
50 
60 
All burglary 
(inc. attempts) 
Vandalism 
All vehicle-
related theft 
All robbery 
(inc. attempts) 
Assaults and 
threats 
All theft 
All fraud 
PROPORTION OF PREMISES 
EXPERIENCING CRIME 
2002 
2012 
Thefts by others 
9 
29 
2 
6 
-78 
* 
Thefts by unknown  
    persons 
20 
66 
15 
43 
-26 
All theft 
52 
170 
38 
108 
-28 
* 
Fraud by employees 
4 
12 
2 
7 
-39 
Fraud by others 
18 
58 
7 
19 
-63 
* 
All fraud 
20 
65 
8 
24 
-58 
* 
ALL CVS CRIME 
74 
242 
56 
162 
-24 
* 

 
68 
 
In general, the risk of victimisation from any crime increases with business size, as measured by 
number of employees. This is apparent for both years of the survey with the level of risk appearing 
higher in 2002 than in 2012 for most crime types. The risk of victimisation for small businesses (1 to 9 
employees) decreased between 2002 and 2012 across all crime types, with the exception of robbery 
and vandalism. The greatest reductions in victimisation for this size of business are for theft (down 
from 44% to 31%) and burglary (down from 21% to 11%).   
REPEAT VICTIMISATION  
The CVS shows that the volume of crimes experienced by the wholesale and retail sector declined by 
about two-thirds between 2002 and 2012 (from around 21.5 million crimes to 7 million crimes). 
However, the number of victimised premises only decreased by around one-third between the surveys 
(from 242,000 to 162,000). This may indicate more incidents of repeat victimisation happened in 2002 
than in 2012, where more premises experienced multiple episodes of the same crime in the year prior 
to interview.  
On both surveys premises that had experienced victimisation were asked how many times they had 
experienced each crime in the last year. These responses were recoded into groups of premises that 
had experienced between 1 and 5, or 6 or more incidents of the same crime to replicate analysis 
published for the 2002 survey.  
As the „all crime‟ category in Figure 5.3 shows, more than half (55%) of the 2002 wholesale and retail 
premises experienced at least 6 incidents of the same crime, compared with 41% in 2012. This pattern 
recurs for most crime types although only overall theft and vandalism show statistically significant 
differences.12  
 
It is estimated that 55% of premises experienced 6 or more incidents of theft in 2002, 
compared with 41% in 2012. 
 
 
The proportion of premises that experienced vandalism 6 or more times fell from 20% in 2002 
to 7% in 2012.  
 
Conversely, a greater proportion of wholesale and retail premises reported experiencing 6 or more 
incidents of theft by employees in 2012 than in 2002; although this was not a statistically significant 
increase.  
                                                 
12 No comparable data for repeat victimisation are available for robbery, vehicle theft, theft by others and fraud by an employee 
due to the small number of business experiencing these crimes in 2012. 

 
69 
 
Figure 5.3: Proportion of premises which experienced 6 or more incidents of the same crime in 
the last 12 months 
 
 
Chart notes:  
The figures for robbery and vehicle crime cannot be reported due to the small numbers of businesses experiencing these crimes 
in 2012. 
Source: Home Office, 2012 Commercial Victimisation Survey Wholesale and retail sector – 2002 and 2012 comparison tables 
Table 5.6. 
 
REPORTING OF CRIME TO THE POLICE 
Of those respondents who had experienced a crime, both surveys asked if the most recent incident of 
this crime had been reported to the police. Figure 5.4 shows that there has been a general trend 
towards less reporting of crimes between 2002 and 2012, with rates decreasing for all crime types 
except burglary with entry, which has remained at the same high level (92%)13.  
The largest falls in reporting rates can be seen for theft offences, which have approximately halved 
between the two surveys.  
 
Reporting of theft by persons unknown is down from 44% to 21%. 
 
Reporting of theft by an employee is down from 42% to 24%.  
Reporting of violent crime has also decreased. 
 
Reporting of threats and assaults has fallen from 41% in 2002 to 28% of incidents in 2012.  
Only the reporting rates for the aforementioned crimes show statistically significant differences 
between years. 
Early investigations suggest that the largest businesses (premises with more than 50 employees) are 
the most likely to report crimes to the police (data not shown).  
                                                 
13 No comparable data for the reporting of theft of a vehicle are available as this question was not asked in 2002. Due to the 
small number of business premises experiencing robbery, theft by others and fraud by employees in 2012, no comparable data 
are available for these crimes.  
12 
20 
35 
55 
37 
55 
5 
7 
32 
47 
29 
41 
0 
10 
20 
30 
40 
50 
60 
All burglary (inc. 
attempts) 
Vandalism 
Assaults and 
threats 
All theft 
All fraud 
ALL CVS CRIME 
PROPORTION OF PREMISES  
2002 
2012 

 
70 
 
The downward trend in the proportion of wholesale and retail premises reporting crimes to the police is 
different to the trend for households reporting crimes as measured by the Crime Survey for England 
and Wales (CSEW). This survey finds that the overall reporting rate for all crime against households 
has been generally flat between 2002/3 and 2011/12.  
The reduction in reporting of crimes to the police – particularly theft offences, and especially in the 
case of theft by an employee – may reflect the increasing use of private security firms within the retail 
sector, and a move towards dealing with incidents themselves rather than involving the police (as was 
shown in the 2012 headline findings report – See Figure 2, page 23).  
Figure 5.4: Proportion of victimised premises which reported the last incident of each crime to 
the police 
 
Chart notes:  
The figures for robbery, vehicle crime, theft by others and fraud by employees cannot be reported due to the small numbers of 
business premises experiencing these crimes in 2012. 
Source: Home Office, 2012 Commercial Victimisation Survey Wholesale and retail sector – 2002 and 2012 comparison tables 
Table 5.7.  
 
CONTACT AND SATISFACTION WITH THE POLICE 
Respondents to both surveys were asked if they had had contact with the police regarding crime 
prevention or reduction issues, other than when reporting a crime. Between 2002 and 2012 estimates 
of the level of contact have remained very similar, with 23% of premises in 2002 and 24% of premises 
in 2012, reporting that they met with the police regarding crime prevention or reduction.  
Satisfaction with the police has increased from 2002. Respondents to both surveys were asked how 
satisfied they were with the way that the police had dealt with crime problems in the area. In 2002 63% 
of wholesale and retail premises gave a satisfied response, whereas 80% of wholesale and retail 
premises were satisfied with the police in 2012; an increase of 17 percentage points.  
A higher proportion of non-victims were more satisfied than victims in both years of the CVS.  
 
In 2002, 76% of non-victims were satisfied compared with 59% of victims. 
92 
72 
56 
46 
44 
42 
41 
41 
92 
69 
49 
40 
21 
24 
28 
39 
0 
10 
20 
30 
40 
50 
60 
70 
80 
90 
100 
Burglary 
with entry 
Attempted 
burglary 
Vandalism Thefts by 
customers 
Thefts by 
unknown 
persons 
Thefts by 
employees 
Assaults 
and threats 
Fraud by 
others 
PERCENTAGE OF CRIMES AGAINST 
BUSINESSES REPORTED TO THE POLICE 
2002 
2012 

 
71 
 
 
In 2012, 89% of non-victims were satisfied compared with 75% of victims. 
Between the surveys, satisfaction with the police has increased for both victims and non-victims by a 
similar proportion (13 percentage points and 16 percentage points, respectively) though the increase 
is slightly higher amongst those premises that experienced a crime.     
FACTORS THAT AFFECT THE RISK OF SHOPLIFTING VICTIMISATION  
Thefts were by far the most prevalent crime type experienced by wholesale and retail premises in both 
years of the CVS, a large proportion of which was thefts by customers (ie shoplifting).  
 
In 2002, of the 21.5 million crimes experienced over half (56%) of all crimes were incidents of 
shoplifting.  
 
In 2012, of the 7 million crimes, shoplifting again accounted for over half of all crimes 
experienced (55%).  
Within the wholesale and retail sector, of all the subtypes of crime, shoplifting had the highest 
prevalence in both 2002 (43%) and 2012 (27%).  
The following analysis looks at changes in the risk of victimisation from shoplifting. It focuses on the 
nature of the crime and the characteristics of the businesses which were most likely to experience 
shoplifting between the two surveys.  
The nature of shoplifting in 2002 and 2012 
More incidents of shoplifting took place during the week than at the weekend. 
 
In 2002, 75% of thefts by customers took place during the week and 25% at the weekend.  
 
In 2012, 81% took place during the week and 19% at the weekend.  
Although there has been an apparent increase in the number of incidents which happened during the 
week, between the two surveys, this is not a statistically significant difference.  
Wholesale and retail premises which were victims of shoplifting were also asked about the total cost of 
the last theft by a customer that they had experienced. The largest and only statistically significant 
difference between the surveys was a reduction of almost half in thefts valued at more than £300 
(Table 5.5).  
Table 5.5: Costs of the last incident of shoplifting experienced by wholesale and retail 
premises by experience of shoplifting 
Percentages 
CVS, England and Wales 
  
2002 
2012 
  
  
  
up to £10 
23 
30 
£11 to £25 
18 
18 
£26 to £50 
13 
17 
£51 to £100 
14 
15 
£101 to £300 
15 
12 
More than £300 
17 
9 
* 
 
 
 

 
72 
 
Table notes:   
*Indicates a statistically significant difference between years. 
2002 figures have been uprated in line with inflation to be comparable to 2012 figures. 
 
There has also been a general trend towards reduced rates of reporting thefts by customers to 
insurers between 2002 and 2012 (the rate declined from 6% to 3%, although this is not a statistically 
significant difference).  
Characteristics of wholesale and retail premises and the risk of shoplifting 
victimisation 
There was a decrease in risk of shoplifting victimisation between the two surveys according to 
business location.14 
 
Shoplifting victimisation among wholesale and retail premises on a main street fell from 57% 
in 2002 to 26% in 2012.   
 
Shoplifting victimisation among premises on a side street fell from 55% in 2002 to 33% in 
2012.   
Small businesses (1 to 9 employees) were the least likely to experience shoplifting and were less 
prone to victimisation in 2012 than they were in 2002, with the victimisation rate decreasing from 36% 
to 21%. Medium-size businesses (10 to 49 employees) also had a lower rate of victimisation in 2012 
than in 2002 (53% down from 56%). However, experience of shoplifting appears to have increased 
from 58% to 68% between the surveys for larger businesses (more than 50 employees) although this 
is not a statistically significant difference.  
A different measure of the size of a business is annual turnover.15 In 2002 businesses with turnover 
between £500,000 and £999,000 appeared most likely to experience shoplifting (51%). In 2012, 
however, businesses which turned over more than £5 million pounds – the highest selected value 
category on both surveys – appeared most at risk (53%). However, differences in risk of victimisation 
between businesses at each level of turnover are not statistically significant in either survey.  
Aside from the highest value category, risk of victimisation from shoplifting is lower for business 
premises in all other value brackets in 2012 than in 2002. Between the two surveys there is a general 
decline in victimisation, irrespective of business turnover, although the only statistically significant 
decreases in shoplifting victimisation risk are in the £200,000–£499,000 and £500,000–£999,000 
bands.  
There was a lower risk of shoplifting in 2012 than in 2002 for wholesale and retail premises which sold 
food, tobacco and beverages (from 55% to 39%) or cosmetics and pharmaceuticals16 (from 80% to 
48%). Although all businesses, no matter what the products sold, appear less likely to experience 
thefts by customers in 2012, these were the only statistically significant decreases.  
In both surveys vendors of cosmetics and pharmaceutical products were most likely and vendors of 
motor-vehicle-related goods or services were least likely, to be victims of shoplifting. However, for the 
2012 data, it is not possible to say if the observed differences in victimisation between types of vendor 
are statistically significant.  
Independent businesses which operate at single premises were less likely to experience shoplifting 
than divisions or franchises of larger, multi-site businesses. Both statuses of business were less likely 
to be a victim of shoplifting in 2012 than in 2002.  
                                                 
14 Comparable data are not available for town or city centre location due to the small number of cases in this category in 2002. 
15 Figures for 2002 have been uprated in line with inflation to be comparable with those in 2012. 
16 This category includes Opticians. 

 
73 
 
 
In 2002, 32% of independent businesses experienced thefts by customers, compared with 
17% in 2012.  
 
In 2002, 64% of branches or franchises experienced thefts by customers, compared with 47% 
in 2012.  
Independent businesses were half as likely as branches or franchises to be a victim of shoplifting in 
2002 and around a third as likely in 2012.  
Respondents in both 2002 and 2012 were asked how long their business had occupied their current 
premises. As has been consistently observed for other characteristics, across all time spans, 
victimisation rates for shoplifting declined from 2002. As shown in Table 5.6, both survey years show 
the same trend in that newer businesses which have occupied their premises for less than 3 years are 
less likely to experience shoplifting than well-established businesses (at their premises for more than 
20 years).17 
Table 5.6: Length of time that businesses had occupied their premises by experience of 
shoplifting  
Percentages 
CVS, England and Wales 
  
2002 
2012 
  
  
  
Less than 3 years 
33 
19 
* 
Between 3 and 20 years 
44 
26 
* 
More than 20 years 
41 
29 
* 
Table notes: 
*Indicates a statistically significant difference between years. 
The figures indicate that well-established businesses were more at risk than the least well established 
ones in both years. However, one should also take into account that those businesses which had 
occupied their premises for less than 12 months at the time of interview also had less exposure to 
potential thefts.  
In both years of the survey respondents were asked if they had any form of control on the entry to their 
premises; for example, a security guard or patrol. Premises that had a form of entry control were more 
likely to have experienced shoplifting in the last year on both surveys, than those that did not. It is not 
possible to tell from the survey whether the entry control was in place at the time of the theft or 
whether it was put in place afterwards. 
 
In 2002, 48% of premises with entry control were a victim of shoplifting, compared with 42% 
that did not have entry controls. 
 
In 2012, 37% of premises with entry control were a victim of shoplifting compared with 27% of 
those that had no controls in place. 
Although the same trend is evident across surveys, the proportions of victimised premises, both with 
and without entry control, decreased between 2002 and 2012.   
The fact that those premises which had a higher level of security experienced more thefts might seem 
counterintuitive; however, one might associate greater security with more expensive products, which, 
in turn, would provide greater incentives for thieves to steal them. If this were true it would account for 
                                                 
17 In order to make data from the two surveys comparable for this question it was necessary to recode data into the following 
categories (1) up to 3 years (2) from 3 to 20 years (3) more than 20 years. Due to the categories in the original variables, this 
was the only possible combination.  

 
74 
 
the increased level of victimisation amongst these premises despite having some form of protection 
against shoplifting. However, as we do not know when the security was initiated, it is also possible that 
crime prevention was heightened after shoplifting victimisation and as a direct consequence of it. 
 
 
 
 

 
75 
 
Technical Annex 
This technical annex contains the following: 
 
discussion of the effect of using different measures for outliers and missing data 
 
details of characteristics of the sample interviewed for the CVS 2012 
 
the methodology for the logistic regression analysis (Section 2) 
 
details of the calculation of costs of crime (Section 4) 
 
the methodology for comparing 2002 and 2012 data (Section 5) 
DATA TABLES 
Data tables for the Technical Annex can be found in the 2012 Commercial Victimisation Survey 
Technical Annex tables. 
THE EFFECT OF USING DIFFERENT MEASURES FOR OUTLIERS AND 
MISSING DATA 
As described in the headline findings publication, the 2012 CVS data were examined for outlier values 
in terms of the number of incidents reported by a respondent. The nature of crime against businesses 
means that it is possible that a small number of premises may have experienced a volume of crime 
that has a disproportionately large effect on figures for the sample as a whole, which would make 
comparison of trends over time problematic. In order to prevent a small number of sampled premises 
having an excessive influence on overall figures, the data were assessed to identify any outliers.  
A statistical measure known as Cook‟s distance was used as a measure of whether data points were 
outliers. For each crime type, any data points within a particular sector and size band that had a 
Cook‟s distance greater than 10 and that were substantially higher than the mean number of incidents 
experienced by respondents in the same sector and size band (ie more than 30 times the square root 
of the mean) were identified as outliers.  
Across the 4,017 interviews and the 14 crime types covered by the survey (a total of 56,238 figures 
supplied on numbers of crimes experienced), a total of 32 figures (0.06%) were identified as outliers. 
These were then set to the mean number of incidents experienced by victims within the same sector 
and size band. Of the 56,238 responses to the number of crimes experienced, a total of 271 (0.5%) 
missing values were imputed as the mean number of incidents experienced by the other business 
premises in the same industry sector and size band. 
Subsequently, some analysis was carried out to look at the effect of replacing the outliers and missing 
data with measures other than the mean. The analysis was carried out using the value of the median, 
75th and 95th percentiles within each size and sector band. The results are shown in below and in 
Appendix Table T1. 
 
 

 
76 
 
Table T1: Number of incidents of crime experienced in the last 12 months, by industry sector, 
using different replacements for outliers 
Number of incidents (000s) 
2012 CVS, England and Wales 
ALL CVS CRIME 
Manufacturing 
Wholesale 
and Retail 
Transportation 
and Storage 
Accommodation 
and Food 
All four sectors 
Raw data 
(includes 
outliers) 
530 
10,617 
480 
2,795 
14,423 
Original (mean) 
164 
7,708 
324 
985 
9,181 
Median 
131 
6,965 
265 
867 
8,229 
75th percentile 
213 
7,051 
318 
878 
8,461 
95th percentile 
273 
8,283 
502 
2,066 
11,123 
 
The first row of Table T1 shows the total number of crimes in each sector if no outliers were removed, 
and the second row shows the totals published as headline figures in January 2013 using the 
modelled arithmetic mean for the size and sector of business as a replacement value.  
The purpose of replacing outliers with an imputed value was to reduce the impact of a small number of 
very large (and likely unrealistic) estimates and it can be seen that by using the mean this has been 
achieved. In addition, by using the mean, larger estimates still have some effect, unlike if the median 
was used (which would likely result in an underestimate of the number of crimes).  
There is more detail in Appendix Table TA1. The first column shows the total number of crimes of 
each type if no imputation had taken place, and the second column shows the totals previously 
published using the modelled arithmetic mean for the size and sector of business as a replacement 
value. Columns 3, 4 and 5 show that, as expected, for crime types with no or very few outliers or 
missing data, replacing them with the median (or 75th or 95th percentile) instead of the mean made 
little difference to the estimates. For example, in the 962 cases in the manufacturing sector, there 
were no cases of thefts by customers identified as outliers and the 5 missing cases were replaced with 
a 018, and so there was no change to the total number of offences. In comparison, there were 2 
outliers identified among the values for thefts by employees, and 4 missing cases replaced by 0. This 
changed the total number of offences from 136,000 with no imputation to 31,000 using the mean as a 
replacement value and to 4,000 using the median, 87,000 using the 75th percentile and 137,000 using 
the 95th percentile. The effect of these changes was particularly large as the weight for one of the 
businesses with the outliers was larger than average. 
CHARACTERISTICS OF THE 2012 CVS SAMPLE 
The characteristics of those premises sampled in the 2012 CVS are described in this section. Further 
details can be found in Table TA2 in the 2012 Commercial Victimisation Survey Technical Annex 
tables. 
A number of different indicators have been used to measure geo-demographic factors, such as 
whether businesses are located in urban or rural areas. One such indicator is the Output Area 
Classification which groups areas into clusters based on similar socio-economic and demographic 
characteristics. 
Over three-quarters of interviews were conducted with business premises in urban areas, with 82% of 
the wholesale and retail premises sampled located in an urban area, compared with other sectors. 
This slight imbalance in urban representation of the wholesale and retail sector compared to other 
sectors is further confirmed through the Output Area Classification, as shown in Table T2 below (eg 
20% of wholesale and retail premises in the sample were in urban areas, as opposed to 8% of 
manufacturing).  
                                                 
18 See section on data cleaning for more explanation of replacing outliers and missing values. 

 
77 
 
Table T2: Location of premises according to Output Area Classification, by sector 
Percentages 
  
  
 2012 CVS, England and Wales 
Output Area 
Classification 
Manufacturing 
Wholesale 
and Retail 
Transportation 
and Storage 
Accommodation 
and Food 
All four 
sectors 
Blue Collar 
Communities 
11 
8 
9 
5 
8 
City Living 
8 
20 
10 
24 
18 
Countryside 
23 
13 
22 
22 
17 
Prospering 
Suburbs 
12 
10 
12 
6 
10 
Constrained by 
Circumstances 
8 
10 
10 
8 
9 
Typical Traits 
23 
25 
25 
24 
25 
Multicultural 
15 
13 
11 
12 
13 
Unweighted base  
962 
1,021 
879 
1,155 
4,017 
 
Over two-thirds (68%) of premises in the sample belonged to independent businesses operating only 
at those premises, whilst around a quarter were part of a business with branches or part of a 
franchised chain (26%). 
In terms of their local environment, the most common locations for sampled premises were:  
 in a main or side street near a town centre (36%) 
 on an industrial estate (26%) 
 in a town, city or shopping centre (21%) 
Most premises in the sample had housing next door (44%) or within a 5-minute walk (43%), whereas 
14% had a pub, club, bar or hotel next door or 55% within a 5-minute walk. 
Nearly three-quarters (72%) of sampled premises were open to the public, a proportion driven by the 
accommodation and food and wholesale and retail sectors where 93% and 80% of premises, 
respectively, were open to the public.   
DETAILS OF LOGISTIC REGRESSION MODELLING 
Logistic regression is a multivariate statistical technique that predicts the outcome of a dependent 
variable, from a set of independent variables (such as area or business characteristics associated with 
a CVS respondent). The dependent variable must have only 2 possible outcomes; for example, 
logistic regression can model the risk of a business premises becoming a victim of a crime or not. The 
technique allows the assessment of which of the independent variables are statistically related to the 
dependent variable when the influence of all other variables in the model is taken into account. 
The approach using CVS data is based on an iterative process, which relies on a theoretical rationale 
of how the independent variables might affect the outcome. This process enables evaluation of the 
impact of certain types of variables on the outcome, for example, if the risk of being a victim of crime is 
due to area-based factors rather than business characteristics. 
Each of the iterations is based on logistic regressions using the „Enter‟ method; the final model is also 
run using a „Forward stepwise‟ regression to evaluate the strength of the contribution that each 

 
78 
 
variable makes to that model. The „-2 log likelihood‟ statistic (minus 2 times the log of the likelihood, 
also known as the „scaled deviance‟) of each model is presented as a measure indicating how much of 
the outcome remains unexplained by the independent variables. The fit of each model is compared 
using a likelihood-ratio test to see if the subsequent iteration predicts the outcome significantly better 
(this is the case when the difference of the „-2 log likelihoods‟ of both models exceeds a critical value). 
The Nagelkerke R square statistic is presented as a measure indicating how much the independent 
variables predict the dependent variable. The model which has the highest value is the model that is 
considered to have the best fit. It can only be used to compare models predicting the same dependent 
variable in the same dataset. 
The odds of an event (eg victimisation) are calculated as the ratio of the probabilities of occurrence 
and non-occurrence of the event. Logistic regression describes the impact of independent variables by 
comparing the odds of a subgroup of interest with a fixed reference category set by the analyst; within 
a variable all other categories are compared with this reference category.  
Using the example of vehicle-related theft we can conclude that, assuming all other characteristics in 
the model remain constant, transportation and storage premises are 3 times as likely (3.32 vs. 1.00) to 
have been a victim of vehicle-related theft than manufacturing premises (see odds ratios circled in 
Table T3). 
Table T3: Results of analysis of likelihood of victimisation using logistic regression, for all 
vehicle-related theft 
β-
coefficient 
Standard 
error 
p-value2 
Odds 
ratio3 
Confidence interval 
Lower 
Upper 
-5.25 
Constant 
0.000 
Industrial sector 
1.00 
Manufacturing 
0.09 
0.28 
0.746 
1.09 
0.63 
1.89 Wholesale and retail 
1.20 
0.31 
0.000 
3.32 
1.82 
6.04 Transportation and storage 
-0.86 
0.65 
0.188 
0.42 
0.12 
1.52 Accommodation and food 
 
DETAILS OF THE CALCULATION OF COSTS OF CRIME  
As described in Section 4, respondents who had been victims of crime within the previous 12 months 
were asked for the direct financial cost resulting from the most recent incident of that crime type. 
Respondents were asked for the total value regardless of whether the items were returned or whether 
they received any insurance payment. 
A minority of respondents were unable to provide absolute figures for the cost of a particular crime and 
were therefore asked to estimate them within a range. The ranges defined in the questionnaire are as 
follows:  
Which of the following is closest to the total value? 
Nil, negligible 
Up to £250 
£251-£500 
£501-£750 
£751-£1000 
£1,001-£2,500 

 
79 
 
£2,501-£5,000 
£5,001-£10,000 
£10,001-£50,000 
£50,001-£100,000 
£100,001-£500,000 
£500,001-£1,000,000 
£1,000,001-£5,000,000 
£5,000,001-£9,000,000 
More than £9,000,000 
Don't know 
 
For cases where the respondent was able to specify a range, the midpoint of that range was taken as 
the cost of the particular crime to that respondent. The figures in „Costs of crime against businesses‟ 
have been derived by combining the absolute figures and midpoint answers. This is consistent with 
the methodology used in the 2002 Commercial Victimisation Survey. Where a respondent answered 
„don‟t know‟ or refused to answer, they were excluded from the analysis.  
As the costs for each individual incident of crime tended to be fairly low, the impact of this 
methodology on the average costs of each crime type was relatively minor.  This is despite some of 
the ranges being wide. Additionally, four cases which indicated an extremely high range of cost 
(higher than exact costs given by other respondents) were also excluded.  
To assess the impact on the mean and median, the analysis was carried out assigning first the 
minimum value within the range and then the maximum value to each case. The results of this 
sensitivity analysis are shown in Tables T4 and T5 below, along with the number of respondents 
answering each question. 
Table T4: Sensitivity analysis of cost of incidents of crime types, using mean 
2012 CVS, England and Wales 
All four industry sectors 
  
  
  
  
    
  
  
Mean 
  
  
  
  
  
Assigning value of... 
  
  
  
  
  
minimum 
of range 
midpoint 
of range 
maximum 
of range 
difference 
min to max 
  
Unweighted 
base (range) 
Unweighted 
base (total) 
Burglary 
  
  
  
  
  
  
  
  Burglary with entry 
£3,906 
£3,986 
£4,063 
£157 
  
47 
417 
  Attempted burglary 
£440 
£445 
£448 
£8 
  
17 
281 
  
  
  
  
  
    
  
Vandalism 
£535 
£548 
£556 
£21 
  
70 
630 
  
  
  
  
  
    
  
Vehicle related theft 
  
  
  
  
    
  
  Theft of vehicles 
£18,149 
£19,526 
£20,902 
£2,752 
  
2 
38 
  Theft from vehicles 
£1,077 
£1,117 
£1,156 
£78 
  
6 
231 
  
  
  
  
  
    
  
All robbery (inc. 
attempts) 
£1,644 
£1,650 
£1,656 
£11 
  
2 
68 
  
  
  
  
  
    
  
Theft 
  
  
  
  
    
  
 Theft by customers 
£377 
£380 
£381 
£4 
  
10 
290 
 Theft by employees 
£1,027 
£1,048 
£1,064 
£36 
  
17 
244 
 Theft by others 
£1,571 
£1,583 
£1,590 
£19 
  
6 
97 
 Theft by persons unknown 
£869 
£889 
£901 
£32 
  
30 
407 
  
  
  
  
  
    
  
Fraud 
  
  
  
  
    
  

 
80 
 
  Fraud by employees 
£5,462 
£5,494 
£5,524 
£62 
  
7 
85 
  Fraud by others 
£5,588 
£5,690 
£5,792 
£203 
  
6 
216 
  Fraud by unknown  
  persons 
£1,859 
£1,859 
£1,859 
£0 
  
2 
113 
Table T5: Sensitivity analysis of cost of incidents of crime types, using median 
  
2012 CVS, England and Wales 
All four industry sectors 
  
  
  
  
  
  
Median 
  
  
  
Assigning value of... 
  
  
  
minimum 
midpoint 
maximum 
Unweighted 
Unweighted  
of range 
of range 
of range 
base 
(range) 
base   
(total) 
Burglary 
  
  
  
  
  
  Burglary with entry 
£950 
£1,000 
£1,000 
47 
417 
  Attempted burglary 
£70 
£80 
£80 
17 
281 
Vandalism 
£150 
£150 
£150 
70 
630 
Vehicle related theft 
  
  
  
  
  
  Theft of vehicles 
£5,000 
£5,000 
£5,000 
2 
38 
  Theft from vehicles 
£350 
£350 
£350 
6 
231 
All robbery (inc. attempts) 
£80 
£80 
£80 
2 
68 
Theft 
  
  
  
  
  
 Theft by customers 
£30 
£35 
£35 
10 
290 
 Theft by employees 
£100 
£107 
£107 
17 
244 
 Theft by others 
£200 
£200 
£200 
6 
97 
 Theft by persons unknown 
£100 
£110 
£110 
30 
407 
Fraud 
  
  
  
  
  
  Fraud by employees 
£200 
£200 
£200 
7 
85 
  Fraud by others 
£250 
£250 
£250 
6 
216 
  Fraud by unknown  
  persons 
£280 
£280 
£280 
2 
113 
 
Similarly to the cost of incidents of crime, those respondents who were unable to give an absolute 
figure for costs of crime prevention have been included as the midpoint of the range that they 
indicated. In addition, one case which indicated a disproportionately high cost was excluded. The 
results of sensitivity analysis are shown in Table T6 below.  The effect on the mean costs of taking the 
midpoint values is greater for crime prevention than for incidents of crime, largely due to higher costs 
of security and more respondents indicating a range (as they didn‟t know or refused to give the exact 
cost). However, the median costs – a more accurate estimate of average costs than the mean – are 
less affected; in particular, there is no change in the median value of IT security costs.  
 
 

 
81 
 
Table T6: Sensitivity analysis of cost of crime prevention 
2012 CVS, England and Wales 
All four industry sectors 
  
  
  
  
  
  
  
Assigning value of... 
  
  
  
  
  
minimum 
of range 
midpoint 
of range 
maximum 
of range 
difference 
min to 
max 
  
Unweighted 
base (range) 
Unweighted 
base (total) 
Mean 
  
  
  
  
  
  
  
 IT security 
£3,774 
£5,362 
£6,940 
£3,165 
  
274 
971 
 Non-IT security 
£5,988 
£6,529 
£7,066 
£1,078 
  
205 
          2,019  
  
  
  
  
  
  
  
  
Median 
  
  
  
  
  
  
  
 IT security 
£200 
£200 
£200 
£0 
  
274 
971 
 Non-IT security 
£300 
£376 
£400 
£100 
  
205 
2,019 
 
METHODOLOGY FOR THE COMPARISON OF CRIMES AGAINST THE 
WHOLESALE AND RETAIL SECTOR IN 2002 AND 2012  
Introduction 
The 2012 Commercial Victimisation Survey (CVS) is the first of a new series of Home Office surveys 
focusing on crimes against businesses. It was previously run in 1994 and 2002. Section 5 of this 
publication focuses on change in business crime between the 2002 and 2012 CVS. This section 
provides the methodological detail behind that analysis. For full details on the survey methodology for 
the 2012 CVS see the Technical Report. 
Survey and sample coverage 
The 2002 CVS focused on businesses within two industry sectors: manufacturing and wholesale 
and retail. However, the 2012 CVS focused on four sectors: manufacturing, wholesale and retail, 
transportation and storage, and accommodation and food. In both surveys UK Standard Industrial 
Classifications (SIC) were used to define each sector. As the classifications had changed between 
2002 and 2012, manufacturing businesses were not comparable between the two surveys. However, 
as the SIC codes for wholesale and retail changed minimally between the two surveys a large 
proportion of the 2012 wholesale and retail sample of businesses could be compared with those in 
2002.  
In order to boost the 2012 comparable subsample, an additional 25 businesses were sampled which 
met the wholesale and retail criteria as they were in 2002, but were not classed as wholesale and 
retail businesses in 2012. These businesses were from sectors outside of those sampled for the main 
survey and so would not otherwise have been included in the 2012 CVS. Estimates for the 2012 
comparative subsample are based on interviews with 777 wholesale and retail premises (1,021 
interviews were conducted for the total wholesale and retail sector in 2012). Estimates for the 2002 
wholesale and retail sector are based on 3,955 interviews with wholesale and retail premises. 
In 2002, the selection of premises to interview was based on random sampling from the Yell Data 
business database, stratified by business sector, business size and whether the premises were 
located in a deprived area. In 2012, selection of premises was based on random sampling from the 
Interdepartmental Business Register (IDBR) and was stratified by business sector and size. There 
was no deliberate sampling based on deprivation in 2012, but there was deliberate over-sampling of 
large businesses which were believed to be underrepresented on the IDBR. In terms of business type, 
in the form of independent, multi-site or franchise businesses premises, sample coverage was very 
similar between the two surveys (Table T7). 

 
82 
 
Table T7: Proportion of types of business premises within the wholesale and retail sector 
Percentages 
CVS, England and Wales 
  
2002 
2012 
Independent business occupying these premises only 
62 
63 
HQ of business occupying more than one premises 
4 
4 
Branch or division of business with HQ elsewhere 
31 
29 
Branch of a franchised chain 
3 
3 
Unweighted Base  
3,953 
773 
 
In both surveys respondents were the most senior person responsible for security issues at each 
premises. In the case of larger businesses (more than 50 employees) this may have been a dedicated 
security manager, but for smaller businesses this could have been an owner or general manager if 
specialist security positions did not exist. For the 2002 survey interviews were carried out between 
November 2002 and January 2003 by IFF Research. In 2012, interviews took place between August 
and November of that year and were carried out by TNS-BMRB. The 2012 CVS had a lower response 
rate than the 2002 CVS; 54% of sampled premises took part in 2012 compared with 61% in 2002. In 
both years of the CVS respondents were sent an „Experience of Crime‟ sheet prior to the interview so 
that respondents could prepare for the interview.   
Questionnaire structure 
The structure of both surveys is very similar. Respondents were first asked about some general 
characteristics of their business; for example, location of premises and number of employees. They 
were then asked about their experience of crime over the past 12 months, in terms of what crimes, if 
any, they had experienced at their premises and how many times. Both surveys focused on the 7 core 
crimes of theft, burglary, robbery, vandalism, threats and assaults, fraud, vehicle-related theft and the 
subcategories of these crimes. In both 2002 and 2012, detail on the most recent incident of each 
crime type experienced was also sought, such as whether the incident took place at the week or 
weekend and whether it was reported to the police.  
As well as the core crimes, both surveys asked respondents about their experiences of cyber crime 
and of anti-social behaviour. However, due to differences between question wording and structure (ie 
use of filter questions which narrowed the possible scope of response) it was not possible to compare 
data from the cyber crime or anti-social behaviour modules, despite their presence on both the 2002 
and 2012 CVS. 
Both surveys asked respondents about their crime prevention activities and about their levels of 
contact and satisfaction with the police. In 2002 all respondents were asked questions in all modules 
of the survey. In 2012, for the cyber crime and crime prevention modules, respondents were randomly 
allocated to answer only one of these sections, resulting in half of the sample responding to each 
module. 
The 2002 CVS also contained sections about experiences of bribery and extortion, tobacco and 
alcohol smuggling and handling stolen goods. These modules were not present on the 2012 CVS, 
however.  
Although the overall structure of both surveys was very similar the content and format of questions did 
differ in some cases. In other modules, where possible, variables were recoded so as to be 
comparable across both surveys. Due to the relatively small comparative wholesale and retail 
sample in 2012, recoding was also necessary to ensure usable cell sizes (for more detail on the 
recodes, see the end of this section). Figures with unweighted bases of fewer than 50 have not been 

 
83 
 
reported; however, in order to present as much information as possible from this dataset, some figures 
with cell sizes of fewer than 30 have been reported.  
Access 
to 
the 
paper 
questionnaires 
is 
available 
for 
both 
surveys: 
2002 
(http://discover.ukdataservice.ac.uk/catalogue/?sn=7143&type=Data%20catalogue) 
and 
2012 
(http://discover.ukdataservice.ac.uk/catalogue/?sn=7268&type=Data%20catalogue)  
Weighting 
Both CVS datasets were weighted to account for non-response and stratification. Weighting ensures 
that the sample is representative of the businesses in the wholesale and retail sector and corrects for 
non-response in cases where sampled businesses could not be contacted or refused to take part. 
Accordingly, „weightf‟ in 2002 and „retailwgt03‟ in 2012 are the scaled weights for the surveys. Neither 
weight was grossed to the population, although „weightf‟ was multiplied by a factor of 10,000. Final 
estimates for the total number of victims within the wholesale and retail population were therefore 
derived using population multipliers (326,396 in 2002 and 288,788 in 2012).  
The 2002 CVS dataset is available here: 
http://discover.ukdataservice.ac.uk/catalogue/?sn=7143&type=Data%20catalogue 
The 2012 CVS dataset is available here: 
http://discover.ukdataservice.ac.uk/catalogue/?sn=7268&type=Data%20catalogue 
Data cleaning 
In 2012 the data were assessed for any outlying values in the numbers of incidents of each crime 
reported. This was to limit the impact of those premises that had experienced a disproportionately 
large amount of crime on overall figures, as the large, potentially erroneous numbers could have 
skewed trends. Data identified as outliers were then set to the mean for this variable. This process 
was not undertaken for the 2002 survey. For further information on this and other data cleaning 
processes see the „Methodology‟ section of the 2012 „Headline Findings Report‟.  
The Report can be accessed here:  
https://www.gov.uk/government/publications/crime-against-businesses-headline-findings-from-the-
2012-commercial-victimisation-survey--2  
Testing for statistical significance 
Formal significance testing of the differences between survey estimates was not carried out as 
information on design effects was not available for the 2002 data. This information was available for 
the 2012 data, however, and the Complex Samples module of SPSS was used to generate confidence 
intervals based on complex standard errors. For 2002, a simple random sample was assumed and 
estimated confidence intervals calculated. For each estimate, if the confidence intervals did not 
overlap, statistical significance was assumed. 
 
 

 
84 
 
RECODING OF 2002 AND 2012 CVS VARIABLES FOR COMPARABILITY AND 
USABLE CELL SIZES 
Location Characteristics 
Location of Premises 
 
 
 
 
 
 
 
 
 
 
 
 
 
2002 CVS: S10ret 
 
1. 
Indoor shopping centre 
2. 
Outdoor shopping centre 
or retail park 
3. 
Shopping precinct in a 
side street 
4. 
Industrial/commercial 
estate with retail element 
5. 
Main shopping street 
6. 
On own, not with other 
shops/businesses 
7. 
Main road 
8. 
Side street 
9. 
Residential area 
10. Town centre 
11. House/home 
12. Market 
13. Village 
14. Other 
Comparable Variable 
1. 
Retail park or industrial 
estate 
(2002: 2, 4)  
(2012:1, 2) 
2. 
Town or city centre 
(2002: 10) 
 (2012: 4) 
3. 
Main street  
(2002: 5, 7) 
 (2012: 5) 
4. 
Side street  
(2002: 3, 8) 
 (2012: 6) 
5. 
Other 
(2002: 13, 1, 6, 9, 11, 12, 
14) 
(2012: 3, 8, 9, 19, 12, 14, 
7, 11) 
 
2012 CVS: Q9b 
 
1. 
Retail park outside 
town or city centre 
2. 
Industrial estate with 
retail element 
3. 
Industrial estate with no 
retail element 
4. 
Town or city centre 
5. 
Main street outside 
town or city centre 
6. 
Side street outside 
town or city centre 
7. 
Village 
8. 
Rural/countryside area 
9. 
Airport 
10. Coast/river/port/ marina 
11. Shopping centre 
12. Farm 
13. Other 

 
85 
 
Business Characteristics 
Time occupied current premises 
 
 
 
 
 
 
 
 
 
 
 
Organisation of the business 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Annual turnover of business 
 
 
 
 
 
 
 
2002 CVS: S6 
 
1. 
This calendar year 
(2002) 
2. 
Last calendar year after 
Nov./Dec. 2001 
3. 
Last calendar year 
before Nov./Dec. 2001 
4. 
In 2000 
5. 
Between 1995 and 1999 
6. 
Between 1990 and 1994 
7. 
Between 1980 and 1989 
8. 
Between 1970 and 1979 
9. 
Between 1960 and 1969 
10. Before 1960 
. Comparable Variable 
.  
1. 
Up to 3 years 
(2002: 1,2,3,4) 
(2012: 1, 2, 3) 
2. 
From 3 to 20 years 
(2002: 5, 6, 7) 
(2012: 4, 5, 6) 
3. 
More than 20 years 
(2002: 8, 9, 10) 
(2012: 7) 
 
N.B. Interviews were 
carried out for the 2002 
survey between 
November 2002 and 
January 2003.  
2012 CVS: Q7 
 
1.  Less than 12 months 
2.  12 months but less 
than 2 years 
3.  2 years but less than 
3 years 
4.  3 years but less than 
5 years 
5.  5 years but less than 
10 years 
. 
6.  10 years but less than 
20 years 
. 
7.  20 years or longer 
 
. 2002 CVS: S7  
.  
. 
1.  Independent business 
occupying these 
premises only 
. 
2.  Headquarters of a 
business occupying 
more than one premises 
. 
3.  Branch or division of 
a business with 
headquarters elsewhere 
. 
4.  Branch of a 
franchised chain 
 
Comparable Variable 
 
. 
1.  Independent 
business occupying 
these premises only 
(Both surveys: 1) 
 
2. Division of 
business or franchise 
with HQ elsewhere 
(Both surveys: 3, 4) 
(Both surveys: 2 removed 
due to insufficient numbers 
for analysis) 
 
2012 CVS: Q9 
 
1.  Independent business 
occupying these 
premises only 
2.  Headquarters of a 
business occupying 
more than 1 premises 
3.  Branch or division of 
a business with 
headquarters elsewhere 
4.  Branch of a 
franchised chain 
 
. 2002 CVS: T40i (open 
scale) 
 
. Comparable Categorical 
Variable 
.  
. 
1.  £1 to £199,999 
. 
2.  £200,000 to £499,999 
. 
3.  £500,000 to £999,999 
. 
4.  £1,000,000 to 
£4,999,999 
. 
5. £5,000,000 or more 
. 2012 CVS: T40 (open scale) 
 

 
86 
 
What does the business mainly sell? 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
. 2002 CVS: S5ca – S5cr 
.  
. 
A. Motor vehicles 
. 
B. Motor vehicle 
accessories 
. 
C. Petrol 
. 
D. Food/groceries 
. 
E. Tobacco/alcohol 
. 
F. High value electrical 
goods 
. 
G. Furniture/clothing 
. 
H. Jewellery/precious 
metals 
. 
I. CDs/records/books 
. 
J. IT 
equipment/accessories 
. 
K. Electrical and 
hardware 
. 
L. Chemists/ 
pharmaceuticals/ 
opticians 
. 
M. Cosmetics/toiletries 
. 
N. 
Newspapers/stationery 
. 
O. Pets/pet accessories 
. 
P. Florists/garden 
centres 
. 
Q. Sports equipment 
. 
R. Other 
 
 
Comparable Variable 
 
. 
1.  Motor vehicles and 
accessories 
(2002: A, B, C)  
(2012: 1, 2, 3) 
. 
2.  Food, tobacco and 
beverages 
(2002: D, E) 
(2012: 4, 5) 
 
. 
3.  Electrical and 
hardware 
(2002: F, J, K) 
(2012: 6,11, 12) 
 
. 
4.  Cosmetic/ 
pharmaceutical/ 
opticians 
(2002: L, M) 
(2012: 13, 19, 31) 
 
. 
5.  Recreational 
(2002: I, P,Q) 
(2012: 10, 23,14) 
. 
6.  Homeware/clothing/ 
jewellery 
(2002: G, H) 
(2012: 7, 8, 9) 
 
. 
7. Other  
(2002: N, O, R) 
(2012: 15, 16, 17, 18, 20, 
21, 22, 24, 25, 26, 27, 
28, 29, 30, 32, 33, 34, 
35, 36, 37, 38, 40) 
 
2012 CVS: Q5c_1 to 
Q5c_40 
 
1. 
Motor vehicles 
2. 
Motor vehicle 
accessories 
3. 
Petrol   
4. 
Food/groceries 
5. 
Alcohol/tobacco 
6. 
High value electrical 
goods 
7. 
Furniture 
8. 
Clothing/footwear 
9. 
Jewellery/precious 
metals 
10. CDs/records/books 
11. IT 
equipment/accessories 
12. Electrical and hardware 
13. Drugs/pharmaceuticals 
14. Sporting goods 
15. Office 
supplies/stationery 
16. Mobile phones 
17. Homeware/DIY 
products 
18. Accommodation 
19. Glasses/contact lenses 
20. Giftware/souvenirs 
21. Newspaper/magazines 
22. Caravans/boats/trailers/ 
bikes 
23. Garden supplies/ 
furniture 
24. Agricultural machinery 
25. Toys 
26. Outdoor/camping 
27. Leather goods 
28. Printing products 
29. Packaging/storage 
products 
30. Machinery/ engineering 
products 
31. Health/beauty/hair 
32. Travel/holidays 
33. Metal/steel 
34. Service/repair of motor 
vehicles 
35. Coal/heating oil 
36. Tools 
37. Aviation 
38. Building goods 
39. Other 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
ISBN 978 1 78246 155 5