3rd European company survey : innovative changes in European companies.
Date: 2017-06-20
Institutions: Eurofound
Subjects: European company, competitiveness, innovation, organisation of work, productivity, research report, worker participation, working conditions, workplace

RESEARCH REPORT

Innovative changes in 
European companies

rdEuropean 

Company 
Survey

Innovative changes in 
European companies 

rdEuropean 

Company 

Survey3

When citing this report, please use the following wording: 
Eurofound (2017), Innovative changes in European companies: Evidence from the European Company Survey,  
Publications Office of the European Union, Luxembourg. 

Authors: Stavroula Demetriades, Franz Ferdinand Eiffe

Research managers: Stavroula Demetriades, Franz Ferdinand Eiffe 

Research project: Further analysis of the European Company Survey – Reported changes in European companies 

Acknowledgements
The authors of this report would like to thank Professor Dr Monique Ramioul (Research Institute for Work and 
Organisation HIVA-KU Leuven) for the concept paper she produced for Eurofound, Surveying innovation from an 
organisational perspective, which provided input to this report. Special thanks to Professor Edward Lorenz (Department 
of Economics, University of Nice-Sophia Antipolis), Professor Lilian M. de Menezes (Faculty of Management, Cass Business 
School, City University of London) and Dr Bernd Brandl (Business School, University of Durham) for their detailed 
comments on previous versions of this report. Also, thanks to Professor Lena Tsipouri (Department of Economic Sciences, 
University of Athens) for her useful commentary on an earlier version of this report.

Luxembourg, Publications Office of the European Union, 2017

Print 
PDF 

ISBN 978-92-897-1579-9 
ISBN 978-92-897-1578-2 

doi: 10.2806/743977 
doi: 10.2806/536983 

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© European Foundation for the Improvement of Living and Working Conditions, 2017
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List of abbreviations

AMO

CIS

ECS

EIS

EWCS

HCWS

HIWS

HPWP

HPWS

HR

HRM

OLS

ROC

SMEs

VIF

Ability, Motivation and Opportunities [model]

Community Innovation Survey

European Company Survey

European Innovation Scorecard

European Working Conditions Survey

high commitment work systems

high involvement work systems

high performance work practices

high performance work systems

human resources

human resource management

ordinary least squares

receiver operating characteristic

small and medium-sized enterprises

variance inflation factor

Contents

Executive summary 

Introduction 

1 –  Innovation at company level 

Innovation: Definition and measurement 

Challenges in measuring innovation processes  

Research framework of innovation 

Summary - Concepts of innovation 

2 –  Innovation, workplace practices and performance – insights from the literature 

HRM practices as factors contributing to innovation 

Innovation and aspects of work organisation 

Employee involvement and social dialogue 

Innovation, workplace practices and impact on performance and well-being 

3 –  Setting the scene: Innovation in EU establishments 

Innovation across the EU 

Characteristics of the workforce 

Workplace practices in changing environments 

Country differences 

Summary - Innovation in EU establishments 

4 –  Methodology 

Bundles of practices 

Model specification – measures  

5 – Results of the analysis 

Determinants of innovation in establishments 

Links between workplace practices, performance and well-being 

Summary - Links between the main dimensions 

6 –  Workplace practices in fostering innovation 

Role of work organisation in innovation 

HRM practices 

Employee participation and social dialogue 

Performance and workplace well-being 

Mediating role of social dialogue 

Interaction of practices 

Summary - HRM practices and innovation 

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Innovative changes in European companies: Evidence from the European Company Survey7 –  Conclusions: The changing workplace 

Participatory change 

Performance and well-being: mutual gains 

Policy pointers 

Future research on innovation 

References 

Annex 1: Methodology 

Annex 2: Regression tables 

Annex 3: Correlations between performance and well-being 

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5

Executive summary

Introduction
Innovation in its various forms is considered an important 
driver of improved competitiveness, productivity and 
the growth potential of companies. By innovating both in 
their products and in workplace practices and processes, 
European workplaces may have a better chance to 
compete internationally.

This report critically reflects on common concepts of 
innovation and explores the links between innovation, 
practices, performance and workplace well-being across 
the EU28. In particular, it examines associations between 
innovative company behaviour and the implementation 
of bundles of workplace practices. The report also studies 
the role of social dialogue in translating innovative 
workplace practices into higher levels of performance and 
well-being.

The report contributes to research and policy debates 
by examining innovation from a different perspective. It 
acknowledges that companies need to invest in research 
and development (R&D), increase the number of patents 
granted and improve technology. However, it highlights 
other important factors that contribute to innovation 
such as the organisation of work, human resource 
practices and employee participation.

Policy context
In the European context and the Europe 2020 strategy, 
innovation is seen as a way to achieve smart, sustainable 
and inclusive growth. A sustainable recovery from the 
economic and social crisis calls for structural changes 
driven by innovation. Innovation is considered essential 
to preserve and improve Europe’s competitiveness and its 
ability to create jobs and to tackle societal challenges. The 
Innovation Union, a Europe 2020 flagship initiative, aims 
to improve Europe’s capacity to innovate. Efficient use of 
skills and tacit knowledge, informal and lifelong learning, 
and the adaptation of work organisation to meet new 
challenges are among key EU priorities. In a future-proof 
European workplace, innovation is a central feature, as 
are workplace practices that drive innovative behaviour 
to the benefit of the company, employees and society.

The findings of this research are relevant for the Skills 
Agenda for Europe, in particular the Digital Skills and Jobs 
Coalition and the Blueprint for Sectoral Cooperation on 
Skills, as innovation depends on relevant skills.

Key findings
This research investigates innovation in the form of the 
introduction of new or significantly changed products 

or processes, new or significantly improved marketing 
methods and organisational change. It examines 
innovations reported as being new to the company (but 
not necessarily new to the market).

Across the EU28, more than half of the establishments 
(55%) reported the introduction of new or significantly 
changed products and services, marketing strategies or 
processes over the period 2010–2013. Looking at the EU 
average, the most frequent type of innovation related to 
products (40%), followed by processes (35%). Changes in 
marketing (32%) were the least frequent.

The research also examined how innovation is associated 
with work practices, including work organisation, human 
resource management (HRM) and employee involvement. 
Such practices provide the context within which skills 
development, participation, collaboration and innovation 
can thrive. Innovative company behaviour requires joint 
efforts and an organisational setting that facilitates and 
supports innovation. Additionally, certain combinations 
(bundles) of workplace practices were found to have 
stronger links with performance and workplace well-
being.

Various sets of work organisation practices were 
examined through statistical analysis. The use of 
monitoring instruments for internal quality and external 
developments turned out to be among the strongest 
determinants of overall innovation. Collaboration 
on – and/or outsourcing of – production, marketing or 
development also showed positive links with innovation; 
the degree of workers’ autonomy was another important 
factor. However, the accumulation of positive individual 
practices will not necessarily positively boost innovation 
in isolation. The probability of innovation is boosted 
when strong work organisation structures are combined 
with direct employee participation (for example, 
involvement in solving problems or improving the quality 
of production).

HRM practices play a major role in enhancing employees’ 
knowledge and skills, and can influence behaviour. 
They can also reward initiative and develop innovative 
capacity. Analysis of HRM-related variables found that 
access for employees to training was linked positively 
to innovation. Training to ensure appropriate skills 
helps a company ensure a competitive edge (as other 
research has shown). Motivation, in the form of financial 
incentives such as variable pay, was also positively linked 
to innovation. Bundles of HRM practices that encouraged 
employee participation were very strongly associated 
with innovation, indicating that such practices have 
a better chance of creating a pro-innovation environment.

7

  National programmes should continue to support 

training to develop skills.

  Planning for the future workplace should support 

companies to assess and adopt workplace practices 
that contain the important elements presented in this 
research.

Learning networks can bring together researchers 
with businesses and workers’ organisations. Taking 
a bottom-up approach and exploring the needs of 
companies and employees could create benefits for 
all.

  Governments and the business community could 

assist small businesses and start-ups to embrace pro-
innovation workplace practices.

  Participative change nourishes an environment of 
trust between management, employees and their 
representatives. Social dialogue can help inform 
employees about adaptation needs, promote 
employee involvement in operations, and engage 
the workforce in debates about the future of their 
company.

  European-level social partners could work with 

national-level social partners to address the issue 
of different forms of participation and the linking of 
workplace practices with innovation.

Overall, a strong link was found between innovation and 
direct employee involvement. In particular, the number of 
direct participation instruments in place was found to be 
important, as was the participation of employees in the 
decision-making process.

Taken together, all three bundles of workplace practices 
(work organisation, HRM and employee involvement) 
were significantly associated with innovation. The 
strongest effects were found for the bundle of employee 
involvement practices.

It was also found that the more innovative organisations 
experienced better company performance and greater 
workplace well-being. These innovative companies 
tended to have strong employee participation practices 
in place.

Trusting social dialogue is also important for performance 
and well-being. Levels of performance and workplace 
well-being were well below average in establishments 
where disputes and industrial action had taken place. 
A trusting relationship between employee representation 
and management, in combination with direct employee 
participation, was associated with higher levels of 
performance and well-being and created a positive 
environment for innovative action.

Policy pointers
  European initiatives associated with innovation 

and the future of work should encourage Member 
States to adopt pro-innovation workplace practices. 
National policies and regional programmes need to 
be aware of the importance of specific workplace 
practices, in particular the work organisation 
and HRM practices that encourage employee 
involvement.

  National and regional programmes should also 
provide opportunities for companies to tap into 
external ideas and research, and to collaborate with 
other companies and research institutes to help 
them improve their products or services. Relevant 
European networks can facilitate such an exchange.

8

Innovative changes in European companies: Evidence from the European Company Survey 
Introduction

Introduction

Change is a constant feature of the lives of companies 
and their employees. Employers and employees 
alike are facing unprecedented challenges, including 
volatility in the global business environment; responding 
constructively requires constant vigilance, versatility and 
innovation. There is a shift away from mass production 
to an emphasis on customised products and services. 
There is also a shift from centralised to decentralised 
production, made possible by advances in technology. 
As a result, traditional production modes and processes 
are changing. The advent of Industry 4.0 is becoming 
possible through cyber-physical systems, which enable 
networks of virtual and physical systems in different 
locations and times to interact1. These developments are 
leading to the emergence of new business models, such 
as the smart factory; e-business; on-demand models such 
as Netflix; and market-place models such as eBay and 
Airbnb. These new models require different approaches to 
managing resources, people and processes.

In such work environments, workers’ jobs and 
competency profiles will be transformed. Work needs 
to be organised in a way that fosters participative 
work design, embraces lifelong learning, gives greater 
responsibility to employees and provides opportunities 
for self-development. Additionally, investment is required 
in research and development (R&D), as is innovation in 
production, processes and organisation. Firms need to 
be ready to deal with complex, networked systems and to 
use their resources intelligently. Some of the challenges 
managers are faced with require greater flexibility in 
the use of systems and networks, optimal resource 
productivity and decision-making based on big data 
in real time. It is becoming clear that previously valid 
styles of managing and organising work cannot deliver 
the adaptability required in this new landscape of fierce 
competition and rapid, pervasive technological change.

Policy context
In the Europe 2020 strategy, innovation is seen as a way 
to achieve smart, sustainable and inclusive growth 
(European Commission, 2010). A sustainable recovery 
from the economic and social crisis calls for structural 
changes driven by innovation (European Commission, 
2013). However, developing the capacity for companies 
to innovate, grow and be flexible enough to respond 
to changing markets is not a one-dimensional task. It 
requires nurturing, enhancing and making optimal use 
of human capital, implementing more effective methods 

of work organisation and dealing with issues of work–life 
balance (Oeij et al, 2012).

Innovation is considered essential for improving Europe’s 
competitiveness and its ability to create jobs and tackle 
societal challenges (European Commission, 2014). For 
that reason, the Innovation Union strategy, a Europe 2020 
flagship initiative, aims to improve Europe’s capacity to 
innovate. Supporting companies in translating ideas to 
marketable products has been given priority through 
various investment schemes (including financial support, 
R&D, training and partnerships). Recent data from the 
European Innovation Scoreboard show that, since 
2008, the EU has significantly narrowed the innovation 
performance gap with the USA and Japan. However, the 
position of other competitive regions such as South Korea 
and China poses a major challenge.

The new Skills Agenda for Europe emphasises the 
development of workforce skills. EU policies consider 
the following areas as priorities: using employees’ skills 
and tacit knowledge at work; informal learning; lifelong 
learning; and adapting work organisation practices to 
new challenges.

Organising work in teams and with broad employee 
participation can help develop human capital. Good 
company outcomes and employee well-being are features 
of ‘happy companies’, which produce efficiently, compete 
successfully and avail of their employees’ skills and 
experience.

Research suggests that the survival of companies is 
dependent upon their ability to innovate in terms of their 
products, processes and systems. One way companies 
can achieve this is to develop the talents of the workforce. 
By being innovative in their products, services and their 
processes, European workplaces may have a better 
chance to compete in international markets.

It is therefore important to understand how firms 
innovate in terms of their products, processes, marketing 
and organisation; also important are the particular 
bundles of practices that innovative firms use to produce 
positive outcomes for the organisation and the workforce. 
This type of understanding can inform policymaking so 
as to achieve sustainable, inclusive economic growth and 
build resilient, inclusive societies.

This report explores innovation-enhancing practices in 
establishments and companies across EU Member States; 
it is based on quantitative analysis of Eurofound’s third 
European Company Survey (ECS 2013). The overview 

1 

The term ‘Industry 4.0’ originated in Germany. The Plattform Industrie 4.0 website describes it as people, machines, equipment, logistics systems and 
products communicating and cooperating with each other directly. This results in production and logistics processes being integrated intelligently across 
company boundaries to make manufacturing more efficient and flexible. Industry 4.0 was originally one of the projects that the German federal government 
adopted in 2010 for its action plan for a high-tech strategy for 2020. The concept exists in different countries using alternative terms such as ‘smart factories’, 
‘the industrial Internet of things’, ‘smart industry’, and ‘advanced manufacturing’.

10

report on the results of the ECS 2013 examines the 
incidence of work organisation practices, human resource 
(HR) policies and social dialogue (Eurofound, 2015).

Structure of the report
The report is organised in seven chapters.

Introduction

Research objectives
The impact of management practices and organisational 
behaviour has been reported in management and human 
resource management (HRM) literature for many years. 
Furthermore, a growing body of economics literature has 
drawn attention to management practices in terms of 
employee motivation and involvement, and their impact 
on performance. The link between different forms of 
innovation and performance has long been identified in 
economics literature. It has thus been recognised that 
workplace practices can be a driver of performance and 
innovation.

Innovation is an extremely complex concept, developing 
on multiple levels and being influenced by a huge 
variety of external and internal factors. The ECS 2013 
was not originally designed to capture the conditions 
and determinants of innovation; rather, it provides 
information on workplace practices which can be linked 
to innovation. The ECS is the only EU-wide establishment 
survey that encompasses a wide range of questions 
about work organisation, HRM practices, direct employee 
involvement and social dialogue. This report seeks to 
make use of this rich dataset and to investigate the links 
between different forms of innovation and establishment 
practices across the EU28 as a whole. A particular focus 
of this research is to explore the associations between 
innovative company behaviour and outcomes on the one 
hand and the organisational settings and practices on 
the other. The report also aims to use quantitative data 
to contribute to the debate about the triggers of, and 
barriers to, innovation at the establishment level.

On this basis, the main research questions of this report 
can be formulated as follows.

  What are the main components of innovation and 
to what extent are these captured by the changes 
reported in the establishments surveyed in the ECS 
2013?

  Can specific structural, organisational and employee-
related characteristics of innovative establishments 
be identified? How do they differ from those of non-
innovative establishments?

  What are the main internal factors associated 
with innovation in establishments in terms of 
combinations of workplace practices in place?

  To what extent do innovative practices in the 
workplace affect workplace well-being and 
performance? What is the role of social dialogue in 
this regard?

The findings of this work will contribute to information 
provided to policymakers to inform decisions regarding 
possible measures at national and/or European level.

Chapter 1 discusses the concept of innovation and how 
it is measured in international surveys. The chapter 
also critically reflects on the main challenges in the 
measurement and argues for a broader and extended 
conceptualisation of innovation in future surveys and 
research.

Chapter 2 goes through the literature and presents 
empirical findings about determinants of innovative 
establishment behaviour. How are different workplace 
practices, HRM strategies and instruments of employee 
participation linked to change at the company level? How 
is overall performance affected?

Chapter 3 analyses the prevalence of innovative 
activities across the EU in terms of three areas: products 
and services; processes; and marketing. The chapter 
looks at the structural characteristics of innovative 
establishments such as size, type, sector and the 
composition of the workforce and compares them with 
those establishments that did not report changes in any 
of the three areas.

Chapter 4 explains the methodology used to analyse the 
main determinants of innovation on the basis of data 
from the ECS 2013. It then outlines the approach taken 
to explore the impact of workplace practices associated 
with innovation and of social dialogue on the overall 
performance of the establishment and well-being at 
the workplace. For this purpose, multivariate logistic 
regressions are used to show which practices, company 
characteristics and structures are most important in 
analysing the different relationships.

Chapter 5 presents the results of the quantitative 
analysis. The first part explores which of the identified 
practices are significantly associated with change in 
establishments, using a range of variables. The second 
part of this chapter shows how far the identified practices 
and bundles of practices impact on overall performance 
of the establishment and on well-being at the workplace. 
In addition, the mediating role of social dialogue in 
translating these workplace practices into higher levels of 
performance is investigated.

Chapter 6 discusses the findings and embeds them in 
a broader picture.

Finally Chapter 7 summarises and highlights the findings 
and presents policy pointers.

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1  Innovation at company level

1  Innovation at company level

Innovation: Definition and 
measurement
Innovation and change in this research is considered 
within the context of the Europe 2020 strategy, which 
aims to achieve smart, sustainable and inclusive growth. 
The concept of ‘creative destruction’ – coined by Joseph 
Schumpeter in the 1940s – refers to those phenomena 
today called ‘innovations’. In innovation, new combinations 
and further developments of existing production 
processes are replacing old products, detached processes 
and production systems. This section explains how the 
phenomenon of innovation is captured by organisations 
such as the OECD, the European Commission and in the 
present report. It also discusses some issues related to 
measurement.

OECD Oslo Manual
The OECD sees innovation as a factor underpinning the 
growth and dynamism of the economy and thus important 
for all countries. It lists the main features of innovation:

a wide scope beyond traditional R&D

encompassing social and organisational innovation

involvement of various actors

a strong basis in the digital economy

a wide geographical scope.

While growth and job creation are closely linked with 
innovation, a broader set of activities rely on innovation: 
these include public services, green growth, health, food 
security and the fight against poverty.

The OECD defines innovation as wider than R&D, going 
‘beyond the confines of research labs to users, suppliers 
and consumers everywhere – in government, business and 
non-profit organisations, across borders, across sectors, 
and across institutions’2.

While no overall innovation index has been developed 
the country reviews focus on innovation systems and 
other issues such as policy developments with regard 
to university research, linking research and innovation, 
and dealing with societal challenges and priorities, and 
governance.

The Oslo Manual (OECD and Eurostat, 2005) is the foremost 
international source of guidelines for the collection and 
use of data on innovation activities in industry. The third 
edition of the Oslo Manual is still the valid reference work 
on definitions and methodology. (Another relevant OECD 
document for the collection of R&D statistics is the Frascati 

Manual, which provides a broader definition of R&D and is 
regularly updated.)

With the publication of the Oslo Manual for the first time in 
1992, recommendations for the statistical monitoring of 
innovation were launched, offering a framework for OECD 
Member States. While the first edition of the Oslo Manual 
focused on technological product and process innovations, 
the second edition specified the concept of innovations 
in the service sector. With the third edition in 2005, the 
definition of innovation was expanded to non-technological 
innovations. Also for the first time, marketing and 
organisational innovations were conceptualised and moved 
into the focus of interest. The document distinguishes 
between product, process and marketing innovation – 
which are clearly outputs of the innovation process – and 
organisational change, which can be thought of as an 
intermediate step in reaching innovation goals. Innovation 
is defined as ‘new to the firm’ – rather than ‘new to the 
market’ or completely new. This definition also implies that 
innovation need not be developed by the establishment 
itself but that it can be acquired by the process of diffusion 
from other companies or institutions. In the latest edition of 
the Manual, innovation activities in the service sector and in 
‘low technological’ industries have received more attention. 

Community Innovation Survey
The Community Innovation Survey (CIS) innovation 
statistics are integrated in the EU science and technology 
statistics. EU Member States and other partner countries 
are responsible for the data collection, which takes place 
every two years.

The  CIS  investigates  innovation  activities  in  companies. 
As Eurostat (2016) states:

The harmonised survey is designed to provide information 
on the innovativeness of sectors by type of enterprises, on 
the different types of innovation and on various aspects of 
the development of an innovation, such as the objectives, the 
sources of information, the public funding, the innovation 
expenditures etc.

Statistics  based  on  CIS  data  can  be  analysed  by  country, 
type of innovators, economic activities and size classes.

With reference to the Oslo Manual, the CIS captures 
information on the four types of innovation: products/
services, processes, marketing and organisation. 
Furthermore, the survey includes data on innovation 
expenditure, public funding of innovation, information 
sources for innovation, cooperation in innovation, and 
public procurement and innovation.

2  OECD Innovation Strategy: http://www.oecd.org/site/innovationstrategy/defininginnovation.htm

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 1 – Innovation at company level

European Innovation Scoreboard
The European Innovation Scoreboard (EIS), previously 
known as the Innovation Union Scoreboard, provides 
a comparative analysis of the research and innovation 
performance in EU Member States as well as other 
European countries and neighbouring countries3. 
 The EIS uses three main types of indicators: enablers, firm 
activities and outputs. It also includes eight innovation 
dimensions, capturing in total 25 indicators. The ‘enablers’ 
indicator captures the main drivers of innovation 
performance external to the firm (such as human resources, 
research systems, finance and support). ‘Firm activities’ 
captures the innovation efforts at company level, such 
as investments by the firm, other innovation activities 
specific to small and medium-sized enterprises (SMEs), 
and intellectual assets. Lastly, the ‘outputs’ indicator 
captures the effects of firms’ innovative activities, including 
indicators such as product, process, marketing and 
organisational innovation (for SMEs) and economic effects.

The EIS has been produced on an annual basis (apart 
from 2012) since 2007 and uses Eurostat data and other 

Figure 1: Innovation performance by country

sources from international organisations such as OECD 
and the United Nations. The methodology has been 
revised and data sources and definitions have developed 
over the years. To assess the performance of national 
innovation systems, a composite indicator known as the 
Summary Innovation Index has been produced, using 
an unweighted average of the 25 indicators. The EIS 
measurement framework does not include measures of 
management or organisational practices.

Data from the EIS 2015 show the ranking of Member 
States; Figure 1 shows significant differences between 
countries with regard to innovation performance. 
The Nordic countries and Germany are classified as 
innovation leaders, while most countries fall into one 
of two categories: innovation followers and moderate 
innovators. The fourth group, modest innovators, 
consists of a small number of countries with scores of 
less than 50% of the EU average. This group includes 
Bulgaria, Latvia and Romania. Compared with the 
previous year, 13 Member States saw a decline in their 
innovation performance while 15 countries experienced 
improvement in their innovation performance.

0.800

0.700

0.600

0.500

0.400

0.300

0.200

0.100

0.000

BG     LV   RO    PL   LT    HR    MT   SK    HU    EL   PT     ES     CZ     IT   CY     EE   SI     EU    FR    AT  

IE     UK    BE   NL    LU   FI     DE    DK    SE 

Modest innovators  

Moderate innovators  

Innovation followers  

Innovation leaders  

Source: EIS 2015

ECS 2013 and definition of innovation
The quantitative analysis of this report is based on data 
from the third wave of the ECS carried out by Eurofound in 
2013 (Eurofound, 2015 – see Chapter 1 for details). The ECS 
2013 included a set of questions that capture innovation 
by asking whether or not establishments had recently 
introduced the following changes:

introduction  of  new  or  significantly  changed  products 
or services

introduction of new or significantly changed processes;

introduction of new or significantly improved marketing 
methods

introduction of any organisational change.

3 

The full report, national rankings and methodology are available from: http://ec.europa.eu/growth/industry/innovation/facts-figures/scoreboards_en

15

 
 
 
 
 
 
 
 
 
 
  
 
 
 
 
 
More specifically these are defined as follows.

Product innovation – any new or significantly changed 
product or service with respect to its characteristics or 
intended uses. This includes significant improvements 
in technical specifications, components and materials, 
software incorporated, user-friendliness or other functional 
characteristics.

Process innovation – any new or significantly changed 
process either for producing goods or supplying services. 
This includes significant changes in techniques, equipment 
and/or software. These can also be delivery methods, 
storage, inventory handling, management information 
software or an innovation to improve internal production or 
support processes.

Marketing innovation – any new or significantly improved 
marketing method. This can be in product packaging, 
product placement, product promotion or pricing.

Organisational innovation – any organisational change. 
This could be any of the following: new business practices 
for organising procedure; new methods of organising work 
responsibilities and decision-making; and new methods 
of organising external relations with other companies or 
public institutions. These particular innovations may come 
from a larger organisation that the establishment is part of, 
but they must be introduced at the local establishment.

It should be emphasised that, unlike the CIS, the definition 
used in the ECS 2013 did not distinguish between ‘new 
to the firm’ and ‘new to the market, EU or the world’; it 
captured only ‘new to the firm’ innovations. 

Challenges in measuring innovation 
processes 

Conceptual issues
The concept of innovation, and how it is commonly 
measured in surveys as a result, is challenged by recent 
trends and by insights on how innovation processes 
actually occur in organisations. Several of these challenges 
are not new and are reflected in revisions of the innovation 
concept and its measurement by leading institutes. It has 
proved difficult to measure the organisational complexity 
of innovation processes in quantitative studies and, in 
particular, to achieve a quantitative understanding of how 
innovation is embedded in organisational structures and 
work practices and how it affects jobs and workers.

Questionnaires addressing the topic of innovation, 
including the CIS and the ECS, typically identify at least four 
major types of innovation as mentioned above: product/
service innovation, process innovation, organisational 
innovation and marketing innovation. These relate to the 
OECD definitions and the Oslo Manual. The OECD itself has 
adopted a broad concept of innovation and says that it is 
a key economic strategy in enabling economic growth and 

4 

http://www.oecd.org/site/innovationstrategy/defininginnovation.htm

16

job creation, and in supporting sustainability and social 
inclusion4.

However, it appears that the different types of innovations 
(process, product, organisation and marketing) are in 
fact approached in an analytical way, even if surveys 
include questions on the combinations of the four types. 
Today, innovations may imply profoundly new business 
models where the distinction between product, process, 
organisation and marketing strategy is very difficult to 
make. Examples include innovations in the form of credit 
derivatives (for example, mortgage-backed securities and 
credit default swaps) in financial services. The current 
Industry 4.0 innovations, which are represented as 
fundamentally new paradigms in manufacturing goods, 
present another example. While this is not a core issue 
of this chapter, the question is whether the distinction 
between the four types and their isolated measurement will 
eventually have to be revised.

Other researchers have acknowledged the distinction 
between radical and incremental innovation and gone on 
to identify five types of innovation: incremental product, 
incremental process, radical product, radical process and 
administrative innovation (Vermeulen, 2005; Herrmann 
et al, 2007; Di Benedetto et al, 2008; Kim et al, 2012). 
The term ‘radical innovation’ refers to the adoption of 
new technology that would create new demand (‘not 
recognisable by markets’, according to Kim et al, 2012), 
while incremental innovation entails smaller changes to 
current technologies.

The inclusion of organisational innovation as part of the 
paradigm of innovation is of key importance. It reflects the 
fact that organisational innovation contributes to economic 
growth. As explained below, the inclusion of organisational 
innovation does not entirely solve the problem of 
measuring innovation as undertaken by Eurofound and 
the ECS. For one thing, definitions of organisational 
innovation (in particular, work organisation innovation) 
seem much less straightforward than definitions of product 
innovation. It is often not easy to clearly distinguish 
whether (work) organisational innovation is a condition 
for innovation, an objective of its own, or a consequence 
of the other types of innovation. Also, harmonised or 
standardised measurements are not available due to 
the multidimensional character of innovation in (work) 
organisation. While significant improvements have been 
made in measuring product and process innovation in 
surveys, challenges remain with regard to measuring 
organisational innovation. Issues that need to be addressed 
include the actual definition of organisational innovation 
and a shared understanding regarding its contribution 
to innovation processes, as explained above. For these 
reasons, the concept of innovation in this report includes 
only changes in products/services, processes or marketing 
strategies, while organisational change will be analysed as 
an impact factor and not as part of the concept itself.

Innovative changes in European companies: Evidence from the European Company SurveyDespite a generally broadened conceptualisation 
and measurements, the approach to innovation (and 
the distinction of the four types) remains primarily 
business-oriented, rooted in a science–technological 
perspective and, more importantly, the principal interest 
is economic when it comes to assessing benefits and 
outcomes. In innovation surveys, some questions remain 
underrepresented and underdeveloped: precisely how 
innovation is embedded in organisational structures and 
work practices; what the extent and contribution is of 
direct and indirect employee participation in innovation; 
and what the effects are on workers’ jobs and well-
being. The ECS aims not to investigate the technological, 
commercial or purely economic aspects of innovation, 
but rather to link innovation with work organisation, 
HRM practices,  performance, and well-being. In order to 
achieve this, it is important to address innovation from 
the perspective of how innovation processes are actually 
set up and embedded in organisations, rather than to 
focus only on the types of innovation initiated, as will be 
further explained. More than in the innovation literature, 
this perspective is covered in the broad literature and 
empirical studies on work organisation innovation. The 
conceptualisation and measurement of work organisation 
innovation (including its distinction from social 
innovation) is for instance clarified in the Eurofound study 
Work organisation and innovation (Eurofound, 2013a). It 
was also the core theme in the ECS 2013, which included a 
qualitative follow-up study. Aspects of work organisation 
are also a key theme in the European Working Conditions 
Survey (EWCS) reports insofar as work organisation is 
linked with job quality and well-being at work.

In short, while both the human factor and work 
organisation innovation are now commonly accepted in 
the conceptualisation and measurement of innovation, 
they are still part of separate theoretical and empirical 
approaches. On the one hand, innovation studies have 
a key interest in the technological and economic drivers 
and outcomes. On the other hand, work organisation 
literature and studies have a key interest in work 
organisation practices, HRM and well-being at work.

Lastly, innovation is often presented as a linear process, 
from research effort to invention to commercial 
application, development and marketing (Cooper and 
Merrill, 1997) or variations on these phases (for example, 
idea generation, development and implementation). In 
reality, innovation in companies occurs as a complex, 
continuous and non-linear interaction between idea, 
development, implementation, experiences and iterative 
adaptations. In order to understand this complexity and 
to take account of the interactive and circular character of 
innovation processes, it is essential to address innovation 
from an organisational and a process perspective. More 
knowledge is therefore needed about the way innovation 
projects are set up, who is involved, and how innovation 
and change are embedded in the organisation and in the 
daily work practices of workers.

 1 – Innovation at company level

Role of employees in innovation
The difference in perspectives and emphasis – 
technological, business and economic versus 
organisational and employee-oriented – is reflected in 
the definitions of innovation. In the innovation literature, 
research generally focuses on the aim of creating or 
sustaining economic added value. While such economic 
added value and company performance in general is 
not absent from the work organisation and innovation 
literature, the latter places emphasis on work practices 
and the role of employees in innovation processes. It 
also investigates the knowledge-sharing dimension of 
innovation, producing mutual benefits and win-win 
outcomes (Dobbins and Gunnigle, 2009; Geary and 
Trif, 2011; Eurofound, 2015). Other scholars approach 
innovation as a result of the exchange of knowledge 
between different actors within an organisation and in 
different organisations (Powell, 1998; Hargadon, 2003; 
Caloghirou et al, 2004).

This focus on the utilisation, sharing and generation of 
knowledge implies the inclusion of innovations that are 
achieved in daily work by individual workers, or by the 
joint effort of more employees or regular teams, and 
that may be implemented without the prior approval 
of higher management. This type of innovation is the 
‘doing–understanding–interacting’ mode of innovation 
(Jensen et al, 2007); it involves the use of workers’ tacit 
knowledge. Taking a broad view of the role of tacit 
knowledge, one might argue that even informal work 
practices might be considered as ‘innovations’ to the 
extent that they contribute to improvements in the 
labour process that potentially add economic value to the 
company.

The academic debate on tacit knowledge has certainly 
had implications for the economics of science and 
technology and innovation. As a consequence, it is 
accepted that innovation cannot solely rely on R&D 
infrastructures or patents, and that the diffusion of 
innovations is in reality quite complex due to the 
impossibility of codifying this type of knowledge. This 
insight has led to the development of Gibbons’ ‘mode 2’ 
form of innovation, in which knowledge is produced in 
interdisciplinary teams, brought together to solve specific 
real-world problems in a particular context (Gibbons et al, 
1994).

The importance of uncodified knowledge as a key asset 
for innovation at the company level, and hence for the 
competitive position of companies, is also emphasised 
by resource-based views of the company (Johnson et al, 
2002; Gertler, 2003) and in a broad strand of academic 
theories on organisational learning. It is also prominent 
in the literature on participative job design and high-
involvement workplaces (HIWs).

This focus on tacit knowledge, and on employee 
behaviour and involvement, is important: it acknowledges 
that workers are not simple ‘executives’ but have an 
expertise and role that should be included in the analysis 
of innovations.

17

Research framework of innovation

of workplace practices may have an impact on the 
company’s performance and on workplace well-being.

Data
This report uses data from the ECS 2013. The ECS is a 
telephone survey of establishments in Europe. Interviews 
are carried out with a management representative (the 
most senior person in charge of personnel) and, where 
available, an employee representative responsible for the 
establishment5. 
The respondent for the employee representative 
interview is identified through a series of questions 
in the management questionnaire. These questions 
were adapted to match the institutional structure of 
each country. The questionnaire was translated into 
31 languages and tested to verify that the terminology 
used in the source questionnaire was suitable for 
a cross-national survey. The unit of enquiry for the 
survey, as in previous waves, is the establishment. 
The target population is all establishments with 10 or 
more employees in all economic sectors except those 
in the Statistical Classification of Economic Activities 
in the European Community (NACE) Rev. 2 categories 
A (agriculture, forestry and fishing), T (activities of 
the household) and U (activities of extraterritorial 
organisations and bodies). The survey covers all 28 EU 
Member States, as well as Iceland, the former Yugoslav 
Republic of Macedonia, Montenegro and Turkey.

This analysis considers only the 28 EU Member States 
and covers establishments engaged in what are termed 
here ‘market activities’ (NACE Rev. 2 categories B, C, D, 
E, F, G, H, I, J, K, L, M, N, R and S). The report is based 
on 24,471 management interviews (ranging from 280 in 
Malta to 1,514 in Italy) and 6,919 employee representative 
interviews (ranging from 41 in Malta to 563 in Finland).

Main framework
This research uses the definitions of innovation in the Oslo 
Manual and CIS, as adapted in the ECS 2013. ‘Innovation’ 
is thus captured as new or significant changes in 
products, processes and marketing. For the reasons 
mentioned above, organisational change is not part of the 
innovation concept used in this report but it is treated as 
a factor contributing to change.

The particular emphasis of this research is to explore the 
links between innovation and work organisation, HRM 
practices, and performance and workplace well-being. 
It recognises that the role of the ‘human factor’ is crucial 
in the innovation process and assumes that HRM, work 
organisation and employee-involvement practices have 
a central role in, and are associated with, a company’s 
disposition to innovate.

Research suggests that particular bundles of practices, as 
well as their various configurations, may have a different 
impact on innovation than individual measures – an 
issue investigated in this report. It is also assumed that 
the implementation of certain bundles or configurations 

5 

See Annex 1 for a full description of the methodology used for the ECS 2013.

18

The innovation pursued within an organisation is 
affected by a number of internal factors (for example, 
company strategy or competitive advantage of company 
resources) and external factors (such as the national 
innovation system, institutions and legislation) which 
are not accounted for in this research. The analysis in 
this report focuses on organisational structures and 
practices as drivers of innovation. Innovation requires 
the creativity, commitment and full involvement of 
employees to solve problems and provide new insights 
or ideas. To enable individual employees and the entire 
organisation to participate in the innovation process, 
organisational practices should be in place to encourage 
such behaviours, provide resources, incentivise, foster 
collaboration, share information and develop skills.

Figure 2 illustrates the framework of this research: 
innovation is reflected in changes to processes, products, 
services or marketing strategies taking place within the 
organisation. It is affected by a combination of individual 
practices, bundles of practices and their interactions 
(as well as other unobserved factors not covered by the 
ECS), as illustrated by arrow 1. The combinations of these 
practices and their interaction also have an impact on 
performance and workplace well-being (shown by arrows 
2 and 3). Social dialogue can be a mediator, influencing 
workplace practices and translating them into higher 
levels of well-being and overall performance.

Figure 2: Research framework

1

Workplace 
practices 
(HRM-WO)

Products

Innovation

Process

Marketing

2

3

Social 
dialogue

Performance 
and workplace 
well-being

Note: WO = work organisation.

Source: Authors’ illustration.

Innovative changes in European companies: Evidence from the European Company Survey 1 – Innovation at company level

Concepts of innovation

This chapter discusses current issues regarding concepts of innovation and measuring the phenomenon. 
Innovations are considered an important driver of improved competitiveness, productivity and the general growth 
potential of companies. More broadly, innovation is seen as a factor underpinning the growth and dynamism of 
the economy. The main features of innovation as defined by the OECD go beyond R&D, encompassing social and 
organisational innovation, involving various actors, and with a strong basis in the digital economy and a wide 
geographical scope.

The Oslo Manual is the foremost international source of guidelines for the collection and use of data on innovation 
activities in industry. These guidelines are implemented in the CIS and in the ECS 2013, which delivers the 
quantitative basis for the following analysis.

However, the concept of innovation and how it is commonly measured in surveys needs to be critically reflected 
upon. While the different types of innovations already capture a broad picture of innovation, the concept is still 
more complex. Innovations may imply new business models where the distinction between product, process, 
organisation and marketing strategy is very difficult to make and probably is becoming less relevant. Often it is 
more complex and not a linear process.

In innovation surveys, some key questions are underrepresented and underdeveloped: how precisely innovation 
is embedded in organisational structures and work practices, what the extent and contribution is of direct and 
indirect employee participation in innovation, and what the effects of innovation are on workplace well-being. It 
is thus important to address innovation from the perspective of how innovation processes are actually set up and 
embedded in organisations, rather than to focus solely on the types of innovation initiated. In order to understand 
this complex issue, it is essential to address innovation from an organisational perspective.

Moreover, the employee component in innovation processes needs to be taken into account. The analysis of 
innovation needs to include the way employees generate, use and share (tacit) knowledge, the way they initiate 
changes in tasks, products, processes and procedures and the way they are involved in and deal with innovations 
initiated by management in their daily work.

The concept of innovation used in this report puts work organisation, HRM and employee involvement centre 
stage and explores their links with innovation. Furthermore, it explores links with performance and workplace 
well-being. This report thus highlights the role of the ‘human factor’ in the innovation process.

19

2 Innovation, workplace 

practices and performance – 
insights from the literature

Introduction2  Innovation, workplace practices 
and performance – insights from 
the literature

The link between innovation and company practices, 
performance and, to a lesser extent, well-being is the 
subject of a growing body of literature. Innovation has 
been explored by different disciplines, with contributions 
from HRM, economic, organisational and psychological 
literature. Impacts on performance have been particularly 
explored in the HRM literature. Associations between 
innovation and workers’ well-being are often interlinked 
with organisation performance measures, with a focus on 
job satisfaction and organisational commitment.

This chapter reviews selected literature and empirical 
findings on the main determinants of innovation (in terms 
of workplace practices) and their impact on economic 
performance and workplace well-being. This review, 
together with insights from the ECS overview report 
(Eurofound, 2015), provides the basis for the quantitative 
analyses that follow. Literature and empirical findings on 
HRM and work organisation practices are of particular 
interest insofar as such practices have been identified as 
‘push factors’ of innovation processes. (More often than 
not, HRM and work organisation practices are intertwined 
in both theory and practice.) Additionally, relevant research 
regarding the role of direct employee involvement and 
social dialogue in triggering change is explored. Lastly, 
empirical evidence on the overall impact of innovation on 
economic performance and well-being is presented.

HRM practices as factors 
contributing to innovation
The association of innovation with HRM strategies – both as 
bundles of combined practices and also single HR measures 
– has been the subject of a large body of literature 
addressing the question: why is HR policy relevant to 
innovation? (Lawler, 1986; Wood, 1999; Wood et al, 2015).

On a general level, human resources are crucial to a firm’s 
competitive advantage, for becoming more creative and 
for contributing to growth. The focus of research in this 
area is diverse in terms of the countries, sectors and 
specialisms covered. However, recent academic research 
generally agrees that well-designed HRM strategies directly 
or indirectly enhance the likelihood of innovation in a 
company (Laursen and Foss, 2003; Shipton et al, 2006; 
Jiménez-Jiménez and Sanz-Valle, 2005; Jiang et al, 2012; 
Eriksson et al, 2014; Lin et al, 2015; Donate et al, 2016). The 
literature about high-performance work systems (HPWS) 
and its two variations – high-involvement work systems 

22

(HIWS) and high-commitment work systems – HCWS (Boxall 
and Macky, 2009), as discussed below, influences the body 
of research on HRM and innovation practices.

A large body of literature on HPWS examines the impacts 
of HRM and work organisation practices on companies 
and employees (Huselid, 1995). High-performance 
work practices (HPWP) have been explored in depth 
in management science since the 1970s (Becker and 
Gerhart, 1996; Ashton and Sung, 2002; Appelbaum, 2015). 
Researchers in the field recognise that there is no one 
best way to organise production and work organisation 
practices, and they emphasise the importance of combining 
practices. They argue that the existence of a practice 
should not be taken as a proof of good performance; 
the researcher should seek for proof of the contribution 
the work practice makes to performance (Becker and 
Gerhart, 1996).  Another term and approach would be 
high-involvement workplace practices or high-commitment 
workplace practices (Pil and MacDuffie, 1996). High-
involvement practices are of particular relevance as they 
emphasise employee involvement and highlight some of 
the practices that can be included in this analysis.

Although it makes no specific reference to innovation, this 
literature is useful for this discussion as it deals with HRM 
impacts on performance and the combination of practices 
into bundles rather than being implemented as individual 
practices.

In an extensive review of empirical literature on the impact 
of HRM on innovation published between 1990 and 2015, 
Seeck and Diehl (2016) found the role of high-commitment 
practice bundles to be particularly important. They 
concluded that ‘studies on the various individual practices 
indicate that practices that foster employee commitment, 
loyalty, learning and intrinsic motivation are conducive to 
innovation’. The authors provided some evidence of the 
role factors such as creativity and knowledge-management 
play as explanatory mechanisms for the HRM–innovation 
link (while also acknowledging that the industry companies 
are operating in and company strategy may also have an 
influence).

Approaching innovation as a socio-psychological process, 
Searle and Ball (2003) found that an integrated HRM policy 
creates understanding, support and trust at all levels and 
fosters the emergence of creative ideas, which in turn lead 
to incremental and radical changes. Laursen and Foss 
(2000) found positive links between innovation and HRM 
bundles – including interdisciplinary groups, quality circles, 

 2 – Innovation, workplace practices and performance – insights from the literature

systems for collecting employees’ views, job rotation, 
performance-related pay and training.

Many publications explore specific HR practices and 
their associations with innovative activities. Jiménez-
Jiménez et al (2008), for instance, identified positive links 
with flexibility in job definition, autonomy, employee 
participation, communication, teamwork, training, 
employment security, broad career paths, systematic 
performance appraisals and variable pay rewards. In 
line with this, Beugelsdijk (2008) found evidence that 
certain combinations of practices such as task autonomy, 
training and performance-based pay are more associated 
with incremental innovations, while radical innovations 
are more linked to task autonomy and flexible working 
hours. Chowhan (2016) identified that skill, motivation 
and opportunity practices (HRM) had a causal role in 
enhancing organisational, operational (innovation) and 
financial performance outcomes. Similarly, Lundvall 
(2002) concluded – using the example of Danish firms 
– that certain characteristics associated with learning 
organisations (such as autonomy in work, training, cross-
unit teams or job rotation) had a positive link to innovation. 
Another interesting conclusion of Lundvall’s paper is that 
the interaction between technical innovations and HRM 
organisational cooperation between firms (‘networking’) 
is crucial for transforming innovation into economic 
performance.

Other research mainly focuses on the positive impact of 
HRM bundles on innovation. In a study of UK manufacturing 
companies, Shipton et al (2006) emphasised the role of 
skills development and training combined with exploratory 
learning (generating new ideas through actively searching 
for alternative viewpoints and perspectives) in supporting 
innovation performance. Jiménez-Jiménez and Sanz-Valle 
(2005) concluded, on the basis of a sample of 180 Spanish 
companies, that the use of internal labour markets and 
practices promoting participation and commitment are 
more likely to boost every kind of innovation. Similar results 
are demonstrated by Verburg et al (2007) who concluded 
that HRM practices that promote commitment are more 
likely to be associated with higher levels of innovative 
activities. Wang (2005) concluded that the effect of strategic 
HRM, as compared to functional practices, on innovation 
remains particularly strong.

The literature on the links between HRM and innovation is 
growing and only a few selected results are presented here6.

Innovation and aspects of work 
organisation
Work organisation is more directly concerned with the ways 
in which work processes are organised; HRM practices, in 
contrast, are concerned with job design and the motivation 
and/or control of workers. Work organisation builds the 

context for a fertile innovative environment, though it is 
not necessarily the result of conscious and systematic 
effort. Typical models of work organisation described in the 
literature include:

  discretionary learning models

lean production models

  Taylorist models

traditional models.

Discretionary learning organisations are characterised 
by an emphasis on problem-solving and innovation 
processes. High levels of autonomy, autonomous teams 
or the prevalence of project teams are some of the key 
characteristics of this type.

Lean production models, while using autonomous 
teams, also promote highly formal structures with 
limited employee discretion, often constrained by various 
hierarchical levels.

The Taylorist approach is characterised by limited 
autonomy, few possibilities for learning and teamwork that 
does not include task autonomy.

Lastly, the simple or traditional forms of work organisation 
are known for their informal modes of work and are often 
non-codified (Mintzberg, 1979; Greenan and Lorenz, 2009).

Often work processes develop over time rather than 
being explicitly designed. It was pointed out by Lundvall 
(2013) that, in the past, researchers into innovation paid 
little attention to the link with work organisation. Also 
Lorenz (2013) concluded in the same volume that the 
analysis of work organisation and organisation design ‘has 
been relatively marginal to development of the field of 
innovation studies’.

HIWS is a useful concept for explaining management 
approaches towards work organisation, as mentioned 
earlier. It covers practices such as employee involvement 
in task definition, high levels of autonomy in task 
implementation and enhanced learning opportunities. 
Higher involvement implies a greater level of skills.

However, some authors have focused on specific aspects of 
work organisation. A relatively large number of researchers 
have studied particular work organisation practices – for 
instance, practices of quality management – and the links 
with innovation. Many researchers, including Prajogo and 
Sohal (2001) have argued that firms that implement quality 
management practices will create a beneficial environment 
for innovation and will enable knowledge-sharing. Kim 
et al (2012) stated that a set of quality management 
practices that relate to process management has a positive 
relationship with all types of innovation. They found that 
process management directly and positively relates to 
incremental, radical and administrative innovation. Based 
on the analysis of data from 283 plants in eight countries, 

6 

For an extensive literature review on this topic, see Seeck and Diehl (2016), who differentiate between HRM bundles and practices and the main mediators 
(contextual promoters linking HRM practices to innovation) and moderators (contextual barriers) identified as influencing the impact on innovation. For an 
integrated model of HRM and innovation, see also De Leede and Looise (2005).

23

 
 
Zhang et al (2014) indicated that ‘hard’ quality management 
affects innovation performance directly and indirectly 
through its effect on quality performance7. They advised 
managers to emphasise quality control techniques and use 
teamwork, training, employee empowerment and problem-
solving approaches. Based on data from 383 firms in nine 
Chinese provinces, Zhang et al (2016) found evidence that 
both quality management infrastructure practices and core 
quality management practices have a positive effect on 
innovation performance. Others (for example, Slater and 
Narver, 1994) noted that quality management practices 
hinder creativity by enforcing standards or formalisation.

In terms of the more general division of labour, some 
country studies have explored the link between innovation 
and collaboration/outsourcing. Beke (2009), for example, 
found a positive relationship between outsourcing/off-
shoring and product innovation performance in the Dutch 
production industry. Mazzanti et al (2007) studied the 
link between outsourcing practices and innovation in the 
Italian province of Emilia-Romagna and concluded that ‘in 
the district-like context investigated, where networking 
intertwines with market mediated mechanisms, the firm’s 
innovativeness correlates positively with the complexity of 
the outsourcing strategies’. Görg and Hanley (2011) found 
that international outsourcing of services had a positive 
effect on innovative activity at the plant level.

Other, more employee-related aspects of work organisation 
such as degree of autonomy, work design in terms of 
teamwork and the links to innovation are often dealt with in 
HRM-related literature, as discussed partly above, or in the 
debate on employee-driven innovation, as considered in 
the next section.

Employee involvement and social 
dialogue
Managers make strategic choices as to the approaches and 
practices they use to achieve desirable outcomes. A better 
unit of analysis is the bundle of practices employed to meet 
these objectives. The main thrust of HIWS is the different 
approaches that management uses to engage employees 
in achieving desirable outcomes. Lawler (1986) argued that 
in HIWS, all elements of employee involvement should be 
present – that is, participation of employees in decision-
making, information-sharing, training and rewards. 
Lawler maintains that decision-making power without 
information and rewards is likely to lead to poor decisions; 
information without the ability to influence decisions 
may lead to frustration; information and decision-making 
power without rewards for performance do not guarantee 
that people will exercise their power towards desirable 
organisational effectiveness. HIWS is a sensible notion, 
which is used in this research when selecting variables 

for analysis such as the incidence of teamwork, employee 
involvement in decision-making, and instruments and 
opportunities for direct employee participation.

Some authors have suggested that participation enhances 
innovation by enabling the integration of different ideas, 
suggestions and solutions (Sawyer, 2006). Wang et al (2015, 
p. 1162) stated that ‘employees’ intimate knowledge and 
experience about their firms’ businesses and operations 
enable them to generate innovative ideas to improve and/
or develop new products and processes’. In their study, they 
provided evidence for their hypothesis that the percentage 
of participatory employees has a strongly positive effect 
on innovation. Other studies explore the link between 
employee participation and innovation in specific types 
of establishments, sectors or countries. Andries and 
Czarnitzki (2014), for example, provided evidence that 
for process innovation performance, small firms benefit 
greatly from involving non-managerial employees. They 
also identified that employee participation has a positive 
effect on product innovation performance. Kesting et al 
(2016) found that employee participation had a positive 
impact during the generation phase of the innovation 
process in Chinese high-tech companies. Overall, it can be 
concluded from these findings that employee participation 
is particularly relevant for innovations in skilled labour 
contexts.

Research on the precise role and effects of representative 
participation in innovation is still relatively scarce. Issues 
focusing on the direct participation of workers in innovation 
are addressed in the literature on employee-driven 
innovation and employees’ innovative behaviour. Employee 
innovative behaviour is defined as employee behaviour that 
implies the generation, introduction and/or application of 
new ideas, processes, products and procedures that are 
potentially beneficial for the unit the workers belong to. 
Using this definition, the type of innovation initiated by 
workers is more comprehensive and far-reaching than is 
suggested by the term ‘incremental innovation’.

Studies on indirect or representative participation in 
innovation are covered by other strands of the literature, 
first and foremost the industrial relations literature, 
including the recent Eurofound project about win–win 
arrangements (Eurofound, 2016a). In another recent 
piece of research, Brandl (2016) stated that trust between 
employers and employees improves the efficacy of social 
dialogue.

The main findings about the factors that affect innovation 
are summarised in Table 1. Workplace practices that were 
also covered in the ECS 2013 are shown in red. Together 
with insights from the ECS overview report, this literature 
review builds the basis for the quantitative analyses 
carried out in the following chapters.

7 

‘Hard’ quality management is the use of technical tools and techniques in quality management.

24

Innovative changes in European companies: Evidence from the European Company Survey 2 – Innovation, workplace practices and performance – insights from the literature

Table 1: Overview of main predictors of innovation

Reference

HRM practices

Work design/ work 
organisation

Direct employee 
participation

Research focus

Ganter and Hecker 
(2014)

Access to external 
knowledge, ideas

Configurational paths to 
organisational innovation: qualitative 
comparative analyses

Beke (2009)

Outsourcing/off-shoring 

Beugelsdijk (2008) Training

Task autonomy

Product innovation

Product innovation

Teamwork

Performance-
based pay

Flexible working 
hours

Bogliacino and 
Pianta, (2016)

Chowhan (2016)

Skills

Investment in R&D, 
knowledge accumulation

Innovation

Innovation

Motivation

HR strategies

Lundvall (2002)

Training

Work autonomy

Skills orientation

Cross-unit teams

Job rotation

Cooperation

Görg and Hanley 
(2011)

Jiménez-Jiménez 
and Sanz-Valle 
(2005), Jiménez-
Jiménez et al 
(2008)

International outsourcing

Innovative activity at the plant level

Training

Autonomy

Performance 
appraisal

Variable pay 
rewards

Teamwork

Flexibility in job definition

Use of internal labour 
markets and practices 
promoting participation 
and commitment

Employee 
participation

Employment 
security

Could HRM support organisational 
innovation? 

Innovation

Laursen and Foss 
(2000)

Training

Autonomy

Collection of 
employee views

Innovation performance

Performance pay

Interdisciplinary groups

Mazzanti et al 
(2007)

Mazzola and 
Perrone (2013)

Prajogo and Sohal 
(2001), Kim et al 
(2012), Zhang et 
al, 2014, 2016

Job rotation

Quality circles

Teamwork

Delegation

Outsourcing practices

Knowledge/learning/
develop new products/
process

Inter-company 
cooperation

Quality management 
practices

Quality management 
through process 
management

Hard quality management

General innovativeness in the district-
like context

Innovation

Innovation/technological innovation/
product innovation

25

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Reference

HRM practices

Work design/ work 
organisation

Direct employee 
participation

Research focus

Training

Integrated HRM 
policies

Searle and Ball 
(2003)

Shipton et al 
(2006)

Slater and Narver 
(1994)

Verburg et al 
(2007)

Wang et al (2015), 
Andries and 
Czarnitzki (2014), 
Kesting et al. 
(2016)

Skills development and  
training combined with 
exploratory training

Negative impact of 
Quality management 
by standardisation and 
formalisation 

HRM practices promoting 
commitment

% of participative 
employees

Employee 
participation

Involvement of 
non-managerial 
employees

Innovation

Innovation performance

Market orientation performance 

Levels of innovative activities

Note: Items shown in blue are also covered in the ECS 2013.

Innovation, workplace practices 
and impact on performance and 
well-being
Why do companies innovate? The main reason is probably 
to maintain competitive advantage and performance 
(Becker and Gerhart, 1996).

The link between innovation and performance is being 
explored in a growing body of literature. Researchers have 
examined the relationship between performance and 
specific types of innovation such as strategic knowledge 
management (López-Nicolás and Meroño-Cerdán, 2011), 
organisational innovation (Yamin and Mavondo, 2015), 
strategic innovation (Talke et al, 2011) or the influence of 
organisational culture on innovation and performance 
(Hogan and Coote, 2014).

Research has provided evidence that certain 
organisational practices, which are linked to innovation, 
influence a company’s performance (Damanpour et al, 
1989; Caroli and Van Reenen, 2001; Piva and Vivarelli, 
2002; Greenan, 2003). The topic of organisational 
innovation has been included in innovation surveys 

(including the CIS, as described earlier) and some 
research based on national data provides evidence of the 
links between organisational characteristics (such as size 
and ownership), work practices and performance.

Other empirical work has examined more specifically the 
effects of innovation on productivity (Crepon et al, 1998; 
Lööf and Heshmati, 2003; Griffith et al, 2006). The well-
known Crepon–Duguet–Mairesse (CDM) model (Crepon et 
al, 1998) investigated the interplay between innovation 
performance and productivity. R&D has been used as an 
input and output factor in many of these studies, which 
measure the rate of return on R&D. Additionally, the effect 
of different types of innovation (for example, product or 
process innovation) on productivity has been investigated 
(Mairesse and Mohnen, 2005). Innovation and profitability 
has been the subject of several studies (Teece, 1986; 
Cefis and Ciccarelli, 2005). Using survey data, Bartoloni 
(2012) and Antonelli et al (2012) found some effects of 
innovation on profitability. A great number of studies 
have found a link between innovation and productivity/
labour productivity (Bigliardi, 2013; Cusí et al, 2013; 
Klingenberg et al, 2013; Preenen et al, 2015; Friesenbichler 
and Peneder, 2016; Inigo et al, 2016).

26

Innovative changes in European companies: Evidence from the European Company Survey 
 
 
 
 
 
 
 
 
 
 
 
 2 – Innovation, workplace practices and performance – insights from the literature

The HPWS literature focuses on a system of work 
practices that lead to superior organisational 
performance. Work by Appelbaum et al (2000) maintained 
that technological advances are not enough and that a 
reform of work systems is also needed. Several studies 
conducted at the establishment level with a group of 
production workers, using specific performance metrics, 
proved the associations of certain groups of HRM 
practices with performance (MacDuffie, 1995; Ichniowski 
et al, 1997; Ichniowski and Shaw, 1999; Appelbaum et 
al, 2000). Two variations of the HPWS model – HCWS 
and HIWS – have attempted to explain performance 
with regard to management attitude towards work 
organisation and employee-involvement practices. 
Wood and de Menezes (2008) found that management’s 
orientation towards the involvement and development 
of employees can be more significant than any specific 
practice. Variable pay and high-involvement management 
in conjunction with total quality management (TQM) were 
found to contribute to productivity.

Motivation-enhancing bundles were found to be 
significantly linked with performance in a study involving 
150 manufacturing companies (Bello-Pintado, 2015).

Through a meta-analysis of 92 recent studies, Combs 
et al (2006) found associations between HRM practices 
and performance in terms of an increase in return on 
assets and decrease in turnover. Recent publications 
have focused on the role of organisational learning and 
leadership style in achieving high performance and 
innovation (Vargas, 2015), the relationship of performance 
and innovation in non-profit firms (Chen et al, 2016) and 
the impact of innovation and performance on the capital 
structure (Nosheen et al, 2016)8.

The literature above used a variety of variables to 
analyse the relationship between innovation and HRM 
practices, work organisation practices and performance. 

With regard to HRM and work organisation, a great 
emphasis has been placed on practices that lead to 
superior organisation performance. The literature 
revealed that combinations of work organisation and 
HRM practices can contribute to better organisational 
performance. Research also indicates that certain HRM 
or work organisation practices are better able to boost 
innovation. 

Very little research has been undertaken to establish a 
link between innovation and well-being. One example is 
the National Endowment for Science Technology and the 
Arts (NESTA) project to create an innovation index for the 
UK (see Dolan et al, 2008, for a review). Miller et al (2008) 
state that ‘the idea of well-being as both an input to and 
outcome from innovation is both naturally appealing and 
supported by a great deal of indirect evidence’.

A study (Vandenberg et al, 1999) of North American 
insurance companies found a connection between high-
involvement practices and good well-being outcomes. 
The authors found that organisational practices linked 
with high involvement of employees and organisational 
effectiveness can follow two paths: 

the motivational path, which increases employee 
satisfaction through involvement 

the cognitive path, through which employee high-
involvement practices make use of their skills and 
abilities. 

High-involvement practices act positively through 
motivational and cognitive paths. Furthermore, Mackie et 
al (2001) found benefits of high-involvement practices in 
US healthcare sites for employee mental health. Similarly, 
Macky and Boxall’s research (2008) found that workers in 
companies using-high involvement practices were more 
satisfied with autonomy and communication.

8 

‘Capital structure’ is how a company finances its assets.

27

 
 
3  Setting the scene: 
Innovation in EU 
establishments

Introduction3  Setting the scene: Innovation in 

EU establishments

This chapter provides an overview of reported 
innovations across EU Member States and investigates 
(bivariate) links between innovation, establishment 
characteristics, sectors, characteristics of the workforce 
and selected workplace practices. Chapter 4 analyses 
whether these links remain significant after controlling for 
other impact factors.

Innovation across the EU
Across the EU28, more than half of the establishments 
(55%) reported changes in marketing, products/services 
or processes during the period 2010–2013. According to 
Eurostat (2016), the proportion of innovative enterprises 
over this time frame decreased compared with the period 
2008–2010.

Table 2 provides an illustration of innovation across EU 
Member States between 2010 and 2013. The highest 
prevalence of change overall was reported in Denmark 
(75% of establishments reported change), followed by 
Malta and Greece (both 67%). The lowest percentages 
were in the Czech Republic (41%) and Hungary (43%).

On average in the EU, product innovation was the 
most frequent type of innovation (reported by 40% 
of establishments), followed by process innovation 
(35%). The least frequently reported was innovation in 

marketing (32%) (Figure 3). Establishments in Lithuania 
(43%) and Finland (45%) most often reported innovations 
in processes (Table 2).

The analysis of innovation intensity at the workplace 
level in the EU Member States indicates that change in 
products and processes is reported mostly in Portugal 
(51% of establishments report product innovation and 
47% report process innovation), Greece (54% and 50% 
respectively) and Denmark (55% and 52%). The highest 
proportion of establishments reporting innovations 
in marketing is found in Luxembourg (47%), Malta and 
Romania (both 48%).

Certain countries, including Austria, Denmark, 
Luxembourg and Sweden, feature both among the 
‘innovation leaders’ of the EIS 2015 and at the top of the 
ECS innovation rankings. However, some countries that 
rank as ‘moderate’ innovators in the EIS 2015 innovators 
also rank quite high in the ECS 2013 dataset. This is 
largely due to the fact that the ECS 2013 captured the 
introduction of new or significantly changed products and 
processes, as well as marketing and any organisational 
changes that were new to the firm and not necessarily 
new to the market or the world. The effect of this inclusion 
appears to be quite significant and thus results in a 
different ranking of countries.

Table 2: Changes within the three years preceding the survey, by country (%)

Marketing

Products

Processes

Any change

21

16

24

26

21

36

28

21

33

30

31

35

32

35

33

31

33

31

34

37

32

33

42

41

42

39

38

40

39

45

21

27

29

28

32

23

31

43

32

35

31

31

35

30

33

41

43

46

47

50

51

51

54

54

54

55

55

55

57

58

Czech Republic

Hungary

Slovakia

Latvia

Estonia

Croatia

Germany

Lithuania

France

Poland

Belgium

UK

EU28

Ireland

Slovenia

30

 
 3 – Setting the scene: Innovation in EU establishments

Marketing

Products

Processes

Any change

Spain

Netherlands

Italy

Bulgaria

Finland

Sweden

Romania

Austria

Cyprus

Luxembourg

Portugal

Greece

Malta

Denmark

36

35

32

35

31

33

48

33

37

47

40

36

48

47

45

43

45

45

36

42

48

46

44

45

51

54

46

54

Source: ECS 2013 – Management questionnaire

Figure 3: Innovations in EU establishments (%)

Any 

Products or 
services 

Processes 

Marketing 

55 

40 

35 

32 

0 

10 

20 

30 

40 

50 

60 

Source: ECS 2013 – Management questionnaire

Nearly 2 in 10 EU establishments (17%) reported 
innovations in all three dimensions, while 21% 
implemented innovation in only one of the dimensions. 
However, 45% of the establishments did not introduce 
any significant renewals or innovation at all (Figure 4).

Figure 4: Innovations in multiple dimensions (%)

17% 

17% 

45% 

21% 

0 dimensions 

1 dimension 

2 dimensions 

3 dimensions 

Source: ECS 2013 – Management questionnaire

43

35

41

37

45

35

37

42

43

38

47

50

41

52

59

60

60

60

61

62

63

64

65

65

66

67

67

75

Further analysis focuses on companies in which 
innovation was reported. The following chapters examine 
the key characteristics of these companies and assess 
whether they differ from those that did not report 
innovation at all. What are the main drivers of innovation 
and how do they relate to particular work practices? What 
are the associations of performance and well-being with 
innovation?

Establishment characteristics
In most sectors, small establishments are less likely 
to implement innovations than larger firms due to 
limited resources and information (Murphy, 2002). Small 
establishments are, however, likely to be more informal 
and flexible, and may constantly change practices 
according to context. Still, it can also be observed in the 
ECS data that innovation generally is more probable the 
larger the establishment is. Around 7 in 10 companies 
with 250 or more employees implemented some kind of 
innovation in the three years preceding the survey. The 
same holds for only 54% of small establishments with 
10–49 employees. The most prevalent innovation type in 
small, and in medium-sized, establishments was product 
innovation (39% and 47% respectively), while the most 
common type of innovation in large establishments was 
process-oriented innovation. Marketing innovations were 
the least prevalent in all three sizes of establishment 
(Figure 5).

31

 
 
Figure 5: Innovations by establishment size (number of employees)

70 

64 

52 

54 

42 

37 

39 

31 

51 

47 

44 

33 

80 

70 

60 

50 

40 

30 

20 

10 

0 

Marketing 

Products 

Processes 

Any change  

10–49 

50–249 

250+ 

Source: ECS 2013 – Management questionnaire

Sectors
In line with the ECS overview report (Eurofound, 2015), 
sectors of economic activity have been summarised into 
six broad categories. These categories are: construction, 
industry, commerce and hospitality, transport, financial 
services and other (business- and administration-related) 
services. The biggest sectors EU-wide are commerce 
and hospitality (30% of establishments belong to these 
sectors), followed by industry (27%) and other services 
(23%), while the remaining sectors count for less than 
10% each. There is a considerable difference in the 
prevalence of different sectors across the EU Member 
States (Eurofound 2015, p. 20).

Table 3 shows the proportion of establishments in each 
sector that had implemented innovations in the three 
dimensions as well as overall. Innovations in general took 
place in around 40% of establishments in the construction 
and the transport sector (with changes across the single 
dimensions of less than 30% of establishments in the 
sector). A majority of establishments in all other sectors 
reported innovations in at least one dimension. The 
most common innovations reported in the financial 
services sectors were in processes. In contrast, product 
or services innovations were the most frequent type in 
the commerce and hospitality sector (reported in 45% of 
establishments), the industry sector (43%) and the other 
services sector (42%). 

Table 3: Innovations in the three years preceding the survey, by sector (%)

Sector

Construction

Transport

Financial services

Other services

Industry

Commerce and hospitality

Average

Source: ECS 2013 – Management questionnaire

Marketing

Products

Processes

Any

22

22

30

34

29

40

32

25

27

35

42

43

45

40

25

29

38

36

41

33

35

40

42

53

57

59

60

56

32

Innovative changes in European companies: Evidence from the European Company Survey 
 
 
 
 
 
 
 
 
 
  
 
 3 – Setting the scene: Innovation in EU establishments

Characteristics of the workforce
The ECS 2013 captured three key structural 
characteristics of the workforce in each of the 
establishments: gender, age and education. More 
specifically, it asked about the proportion of workers in 
the following groups: women; those aged over 50 years 
of age; and those holding a university degree. The results 
show huge variations between Member States, the 
composition of the workforce appearing to be influenced 
by the availability of incentives to recruit specific groups.

Figure 6 compares the structure of the workforce in 
establishments where innovation was reported with the 
structure of the workforce in establishments that did 
not report any innovation. Differences are most obvious 
in terms of level of education: in more than two-thirds 

of establishments with no innovation, the proportion of 
employees with a university degree was below 20%. In 
only one-half of establishments that had implemented 
innovations was this the case. At least three in five 
employees held a university degree in 16% of innovative 
establishments; in establishments without innovations, 
the equivalent figure was just 12%. 

The differences between innovative and non-innovative 
establishments are also quite pronounced regarding 
gender and age. The workforce in innovative companies 
tends to be younger and have a higher proportion of 
women than establishments that are not innovative. 
In more than one-third of establishments without 
innovation, the proportion of female workers was below 
20%; this was true for only 26% of establishments in 
which innovation was reported.

Figure 6: Percentage of women, older workers and workers with university degree by use of innovation (%)

r
e
v
o
d
e
g
A

0
5

y
t
i
s
r
e
v
i
n
U

e
e
r
g
e
d

s
r
e
k
r
o
w
e
l
a
m
e
F

Innovation in at least one dimension 

No innovation 

Innovation in at least one dimension 

No innovation 

57 

50 

54 

62 

25 

11 

3 

1 

26 

14 

5 

1 

14 

9 

6 

10 

11 

6 

5 

7 

Innovation in at least one dimension 

26 

20 

26 

No innovation 

34 

20 

21 

16 

13 

11 

11 

0% 

10% 

20% 

30% 

40% 

50% 

60% 

70% 

80% 

90% 

100% 

Less than 20% 

20% to 39% 

40% to 59% 

60% to 79% 

80% or more 

Source: ECS 2013 – Management questionnaire

33

 
 
 
 
 
 
 
Figure 7: Main thematic fields and subdimensions of ECS data

Work 
organisation

Human resource 
management 
(HRM)

Employee 
participation and 
social dialogue

Collaboration 
and outsourcing

Recruitment and 
career develop-
ment

Direct employee 
participation

Internal organisa-
tion and informa-
tion management

Training

Workplace social 
dialogue

Decision-making 
on daily tasks

Working time 
flexibility

Variable pay 
scheme

Source: Eurofound (2015)

Workplace practices in changing 
environments
In the ECS overview report (Eurofound, 2015), latent 
cluster analysis identified patterns behind the main 
thematic fields of the survey and their subdimensions 
(Figure 7). 

This process made it possible to place establishments 
in five distinct groups on the basis of their practices 
in terms of work organisation, HRM and employee 
participation. 

Innovative  establishments  differ  in  many  ways  from 
those  that  did  not  report  any  innovations  –  not  only  in 
terms of structural characteristics but also regarding the 
workplace practices in place.

Figure 8 shows differences between the innovative and 
non-innovative establishments in selected practices 
across the three areas: work organisation, HRM and 
employee involvement. The data show that 79% of 
innovative establishments organised work in teams 
compared with 65% of non-innovative establishments. 
The quality of production and/or external developments 
are monitored in 73% of establishments that reported 
innovations and just 53% where no innovations were 
reported. Collaboration and/or outsourcing are also 
much more likely in establishments reporting innovation 

34

than in establishments which have not introduced 
innovation.

In terms of HRM practices, there is only a little difference 
between both types regarding working time flexibility 
measures. Distinctions are more pronounced when 
it comes to training for employees and variable pay 
schemes.

Lastly, direct employee participation is much more 
frequent in innovative establishments: 48% involve their 
employees in decision-making processes by consultation 
or joint decision-taking. This is the case in only 28% of 
establishments in the non-innovative group. Four or 
more instruments of employee involvement – such as 
employee surveys, staff meetings and suggestion boxes – 
are in place in 55% of establishments where innovations 
were reported compared with 37% of those where no 
innovations took place.

Innovative changes in European companies: Evidence from the European Company Survey 
 3 – Setting the scene: Innovation in EU establishments

Figure 8: Selected practices in establishments

k
r
o
W

n
o
i
t
a
s
i
n
a
g
r
o

M
R
H

e
e
y
o
p
m
E

l

t
n
e
m
e
v
l
o
v
n

i

Working in teams 

Monitoring of production quality/external develeopment 

Collaboration/outsourcing 

79 

65 

73 

71 

53 

51 

Time flexibility practised 

Training for employees 

Variable pay schemes in place 

4+ instruments in place 

Involved in decision-making 

37 

48 

28 

86 

81 

78 

68 
69 

54 

55 

Source: ECS 2013 – Management questionnaire

Innovators 

0 

20 
Not innovative 

40 

60 

80 

100 

For the purpose of this report, since the main focus is on 
the relationship of these work practices and innovation, 
combined measures were constructed for each of the 
three thematic fields: work organisation, HRM and direct 
employee participation9.

Furthermore,  combined  practices  of  the  three  thematic 
fields  were  computed  in  order  to  analyse  their  joint 
implementation. All indices were transformed into a range 
between 0 (which indicates that none of the practices in 
place) and 10 (all practices are implemented). 

  The index of work organisation comprises practices 
of collaboration and outsourcing, monitoring of 
production quality and external developments 
department structures and the degree of work 
autonomy and teamwork

  The  HRM  index  combines  provision  of  training  to 
employees, variable pay structures and working time 
flexibility

  The employee involvement index synthesises 

information on direct employee participation in 
the decision-making process and the instruments 
applied to support it.

Table 4 provides a breakdown of all three types of 
bundles implemented in the establishments by structural 
characteristics (such as age, size and type) and compares 
establishments that reported innovation with those that 
did not. The scores for all three bundles are higher in 
establishments where change was reported than in the 
reference group.

With regard to the innovative establishments, mean 
values of workplace practice bundles are overall higher 
in large organisations than in small or medium-sized 
establishments. It is also no surprise that subsidiary sites 
and headquarters are more likely to implement strong 
workplace practice bundles than single establishments. 

9 

See Annex 1 for a more detailed explanation.

35

 
 
 
 
 
Table 4: Bundles of workplace practices (average score out of 10)

Work organisation 
bundle

HRM bundle

Employee involvement 
bundle

Innovations implemented

no

yes

no

yes

no

yes

3.9

4.5

4.3

4.0

4.3

4.3

4.0

3.5

4.2

3.7

4.3

4.3

3.8

4.0

4.0

4.3

4.4

4.4

4.0

4.7

5.3

4.9

4.8

5.0

5.2

4.7

4.3

4.7

4.7

5.5

5.3

4.8

4.8

4.8

5.1

5.1

5.0

4.9

3.0

3.5

3.4

3.0

3.6

4.0

3.0

3.1

3.0

2.8

3.5

3.3

3.1

3.2

3.1

3.1

3.5

3.5

3.1

3.7

4.3

4.4

3.7

4.4

4.8

3.7

3.7

3.9

3.7

4.6

4.1

3.9

3.9

3.8

3.9

4.2

4.1

3.9

3.8

4.4

4.7

3.8

4.6

5.2

3.7

3.7

3.8

3.8

4.3

4.3

4.1

4.1

3.9

4.0

4.8

5.4

3.9

5.1

5.6

5.8

5.1

5.7

6.1

5.0

5.0

5.0

5.4

5.7

5.7

4.9

5.3

5.2

5.3

5.8

6.0

5.2

Type

Single establishment

Headquarters

Subsidiary site

Size (number of employees)

10–49

50–249

250+

Sector

Industry

Construction

Commerce and hospitality

Transport

Financial services

Other services

Operating since

Less than 2 years

2–9 years

10–49 years

50 years or more

Structural changes

Organisational change

Change in technology

Overall

Source: ECS 2013 – Management questionnaire

With regard to industry sectors, the financial services 
sector and the other services sector score higher 
in all bundles than the other sectors. Interestingly, 
length of operation of establishment is not significant 
when it comes to the implementation of workplace 
practices. There are no significant differences between 
establishments that have been operating for less than 
two years and those operating for longer.

Country differences
Large differences between countries are noted in the 
occurrence of workplace practices and, as a consequence, 
in the mean values of the bundles presented in Figure 
9, which compares innovative with non-innovative 
establishments across countries. Taking into account 
innovative organisations only, mean scores in the work 
organisation bundle vary from 4.0 in Slovakia, followed 
by Czech Republic and Romania (both 4.4), France and 
Croatia (both 4.5) to a high of 7.0 in Finland, followed by 

36

Sweden (6.6), Austria and Denmark (both 6.3). A similar 
range of variation is observed for the other bundles: the 
mean value for HRM ranges from 2.7 in Greece to 5.3 in 
Finland, followed by the Czech Republic and Slovakia 
(both 5.1). Finally, direct employee involvement is 
weakest among innovative establishments in Croatia, 
Italy (both 4.5) and Portugal (4.7) and strongest in Sweden 
(6.8), Finland (6.4), Austria and Denmark (both 6.2).

It can be concluded from these figures that the three 
bundles are not necessarily interrelated. Some countries – 
for example, the Czech Republic and Slovakia – have weak 
work organisation but apply strong measures of HRM. The 
strongest correlations overall were found between the 
HRM and the direct employee involvement bundles, as is 
discussed later in this report.

A  summary  of  the  extent  of  innovation  reported  by 
establishments involving employees in decision-making is 
provided diagrammatically in Figure 10. 

Innovative changes in European companies: Evidence from the European Company Survey 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 3 – Setting the scene: Innovation in EU establishments

Figure 9: Workplace practices by countries (average score out of 10)

HRM bundle

Work organisation bundle

Direct employee involvement bundle

Sweden 

Finland 

Austria 

Denmark 

Estonia 

Slovenia 

Netherlands 

Ireland 

Lithuania 

Slovakia 

Bulgaria 

Latvia 

Greece 

Czech Republic 

Poland 

Germany 

Romania 

Spain 

Malta 

Cyprus 

United Kingdom 

Belgium 

France 

Hungary 

Luxembourg 

Portugal 

Italy 

Croatia 

4.5 

5.3 

4.7 

4.9 

5.0 

3.8 

4.0 

4.0 

4.6 

5.1 

3.5 

3.6 

2.7 

5.1 

4.3 

3.9 

3.5 

3.8 

3.4 

2.8 

2.9 

3.9 

3.7 

4.0 

4.0 

3.9 

3.2 

3.1 

6.6 

7.0 

6.3 

6.3 

5.8 

5.9 

5.4 

4.7 

5.5 

4.0 

4.6 

5.4 

4.9 

4.4 

4.9 

5.4 

4.4 

4.9 

5.1 

5.0 

5.0 

4.9 

4.5 

4.8 

5.4 

4.6 

4.6 

4.5 

6.8 

6.4 

6.2 

6.2 

6.1 

5.8 

5.8 

5.8 

5.6 

5.6 

5.6 

5.5 

5.5 

5.4 

5.4 

5.3 

5.3 

5.3 

5.2 

5.2 

5.1 

5.1 

4.9 

4.9 

4.8 

4.7 

4.5 

4.5 

0.0 

3.0 

6.0 

0.0 

9.0 

3.0 

6.0 

9.0 

0.0 

3.0 

6.0 

9.0 

Innovation 

No innovation 

Figure 10: Summary of innovating establishments in EU28, 2013 (%)

Monitoring of production 
quality/external development 

Involved in decision-making 

80 
70 
60 
50 
40 
30 
20 
10 
0 

Employees with university 
degree >40% 

Training for employees 

Variable pay 
schemes in place  

No innovation 

Innovation 

37

Innovation in EU establishments

In the European context and the Europe 2020 strategy, innovation is seen as a way to achieve smart, sustainable and 
inclusive growth. Innovation is considered essential to preserve and improve Europe’s competitiveness and its ability 
to create jobs and to tackle societal challenges (European Commission, 2014). For that reason, the Innovation Union 
initiative – as part of the Europe 2020 strategy – aims to improve Europe’s capacity to innovate.

Across the EU28, more than half (56%) of the establishments reported innovations in products and services, 
marketing strategies or processes during the period 2010–2013. On average in the EU, product innovation was the 
most frequent type of innovation (in 40% of establishments), followed by innovative processes (35%) and marketing 
(32%). There is a huge range between countries, varying from reported innovation in 41% of establishments in the 
Czech Republic to 75% in Denmark.

Innovation was reported in around 40% of establishments in the construction and the transport sectors (with 
changes across the single dimensions of less than 30%). In contrast, around 60% of establishments in the commerce 
and hospitality and industry sectors reported innovation.

Around 7 in 10 large companies (250+ employees) implemented some kind of innovation in the three years preceding 
the survey. This compares with only 54% of small establishments (10–49 employees).

Differences were also seen in the characteristics of the workforce. In 16% of innovative establishments, at least three 
out of five employees held a university degree; this was the case in just 12% of establishments without innovations.

 Some 79% of innovative establishments organised work in teams, compared with 65% of non-innovative 
establishments. External ideas and/or the internal quality of production quality are monitored by 73% of innovative 
and 53% of non-innovative establishments. Training and variable pay schemes are more likely to be provided by 
establishments that report innovation than by those that do not. Furthermore, companies reporting innovation are 
more likely to involve their employees in decision-making and to encourage direct employee participation.

38

Innovative changes in European companies: Evidence from the European Company Survey4 Methodology 

Introduction4  Methodology

This chapter outlines the methodology of the quantitative 
analysis carried out to trace the links between workplace 
practices and innovation, performance and workplace 
well-being. The literature review presented in Chapter 2 and 
insights from the ECS overview report (Eurofound, 2015) 
provided input for the selection and modification of the 
models used. The ECS 2013 dataset is used for this analysis 
which, as a first step, develops four multivariate models in 
order to estimate the effects of workplace practices (and 
combinations of practices) on the overall probability of 
innovation in the establishment. 

  Model 1 considers structural characteristics of the 

establishment only. 

regressions are estimates of the difference a certain factor 
makes, after controlling for all other factors. Once the 
model is developed, the same set of variables is used in all 
regressions10.

For the analysis it is important to examine single practices, 
the interrelationships and bundling of practices and, most 
importantly, the interaction between practices. Seen in 
isolation, individual practices may appear to have a stronger 
or weaker link with change and innovation (Figure 11).

Figure 11: Schematic illustration of individual practices 
linked with innovation (Model 2)

  Model 2 includes workplace practices, controlling for 

PRACTICE 1

structural establishment characteristics. 

Change / 
innovation

Change / 
innovation

Change / 
innovation

PRACTICE 2

PRACTICE 3

Much of the literature shows that there are positive links 
between individual practices and innovation; however, 
there is a variety of practices examined in different studies. 
Sometimes, selecting ad hoc practices in a random way 
may also be found to be linked with performance and 
innovation. This makes it difficult to draw conclusions 
about the impacts. However, looking at a group of 
practices together in a bundle (or set) may provide a better 
appreciation of their links with innovation (Figure 12).

Figure 12: Schematic illustration of bundles of 
practices linked with innovation (Model 3)

PRACTICE 1

PRACTICE 2

PRACTICE 3

Change / 
innovation

  Model 3 replaces single items by bundles of workplace 

practices to estimate their effects as a whole. 

  Model 4 looks at the configurations of these bundles 

keeping other factors equal.

Next, the impact of workplace practices and their 
combinations on other outcome measures is tested with 
several ordinary least square (OLS) regressions. Two models 
are run. 

  Model 5 looks at the impact of bundles of workplace 
practices on performance (model 5.1) and well-being 
(model 5.2), controlling for structural establishment 
characteristics. 

  Model 6 focuses on the role of social dialogue, 

controlling for structural characteristics and bundles of 
workplace practices.

Bundles of practices
In this study, the primary interest was in the relationship of 
innovation to certain characteristics of work organisation, 
HRM practices and social dialogue. Of secondary interest 
was the analysis of the impact of workplace practices on 
performance and workplace well-being and an examination 
of the mediating role of social dialogue. To that end, 
multivariate logistic and linear regressions were applied.

Bivariate analyses show which characteristics of 
establishments – for example, in terms of work organisation 
or demographic information – are associated with 
innovation. However, these analyses do not help us to 
understand whether these associations are significantly 
linked to innovation after controlling for other influential 
factors. This can be done by applying regression methods, 
which show how well each factor predicts innovation, 
while controlling for other factors. The main results of the 

10  For further information, see Annex 1.

40

 4 – Methodology

Figure 13: Schematic illustration of individual practices and their bundles used in the analysis (model 4)

PRACTICE 1

PRACTICE 1

PRACTICE 2

+

PRACTICE 2

Change / 
innovation

PRACTICE 3

PRACTICE 3

Two aspects interpreted as proxies of workplace well-being 
were  contained  in  the  ECS  dataset,  forming  the  workplace 
well-being index:

  work climate

(absence of) human resource problems.

In particular, a high degree of sickness absence was 
considered to indicate physical or mental health issues 
among employees in the establishment. Similarly, 
reported difficulties in retaining employees were read as 
an indicator of challenging working conditions. Finally, 
the overview report (Eurofound, 2015) took managers’ 
perceptions of poor employee motivation and a poor or 
deteriorating work climate to represent negative aspects 
of the well-being of employees at work.

This information was condensed into two indices, which 
were subsequently transformed to range between 0 
and 100. The measure of workplace well-being was 
constructed by ‘taking the average scores on the items 
on work climate, change in work climate, problems with 
employee retention, problems with poor employee 
motivation and problems with high sick leave’ (Eurofound 
2015, p.30). The establishment performance index was 
constructed by taking the average of the standardised 
scores of the four items described above (work climate, 
employee retention, employee motivation and sick leave).

Even this approach has its own limitations. A reasonable 
question would then be: which set or bundle is better 
suited to, or more closely linked with, innovation? By 
taking into account their configurations the effect 
becomes more meaningful. These configurations 
comprise the individual practices and the interaction 
of the bundles. This is the approach this research takes 
(Figure 13).

Model specification – measures 

Innovation
The dependent variable of Models 1–4 (see below) is 
measured as the proportion of establishments that – in the 
three years preceding the interview – reported significant 
changes in any or all of the following: 

  products/services 

  processes 

  marketing strategies. 

Organisational change was not included in this variable as 
this type of change can be thought of as an intermediate 
step in reaching innovation goals and is different in nature 
from the types of change included. The key concept of 
innovation in this report refers to products, processes and 
marketing strategies that are new to the firm rather than 
new to the market.

Performance and workplace well-being
Models  5  and  6  (see  below)  use  two  further  outcome 
measures as dependant variables:

economic performance (level of performance/direction 
of development)

  workplace well-being.

Economic performance – the performance index – is 
composed of measures (a) of the establishment’s current 
financial situation and (b) of changes in its financial 
situation, labour productivity and production volume in the 
three years preceding the survey (Eurofound, 2015).

41

 
 
single establishment (rather than a subsidiary site or 
headquarters) (see Tsai, 2001; Hansen, 2002).

Another aspect of an establishment’s organisational 
structure is the number of its hierarchical levels. 
Hierarchy can be seen as antithetical to employee 
involvement and may thus provide a barrier to innovative 
behaviour (Spitzer, 2015). Furthermore a measure 
that captures increases or decreases in the number 
of employees between 2010 and 2013 is included. The 
hypothesis could go in both directions: establishments 
that had to reduce their workforces are under pressure 
to innovate in order to remain competitive. On the other 
hand, an increasing number of staff may be an indication 
of enhanced innovation and business growth (Pianta, 
2004).

Gender and age structures of employees are further 
aspects to be considered (Batt, 2002). Gender diversity is 
measured by the proportion of female employees, while 
age structure is measured as the percentage of employees 
aged 50 or older.

A full set of country dummies is used in all models, 
controlling for any eventual country variations such 
as differences in the economic situation or different 
innovation policies. One of the benefits of the ECS is that 
it provides harmonised information on all EU Member 
States.

Differences are also expected between different sectors. 
Establishments in particular sectors may face different 
technological possibilities. In line with the overview 
report (Eurofound, 2015), sectors of economic activity 
have been summarised into six broad categories.

Models 1–4
The inclusion of predictor variables was driven by the 
analyses of the overview report (Eurofound, 2015) and the 
literature on determinants of innovation (Chapter 3). The 
overview report structured the findings from the ECS 2013 
along three main thematic fields: work organisation; HRM 
management; and employee participation.

Several logistic regression models are run and marginal 
effects are shown with the aim of identifying predictors 
of innovation and explaining the observed patterns. As 
discussed above, innovation is analysed to show the 
probability of change in any of the three areas (marketing, 
products and processes). At the same time, all models for 
all three kinds of change are run and can hence identify 
particular patterns in each of these.

Table 5 gives an overview of the variables that were used 
in the models in each of the dimensions.

Table 5 lists the main descriptive statistics of all items 
used for measuring establishment performance, 
workplace well-being and social dialogue. (See above for 
the measures comprising the performance and well-being 
indices).

Workplace practices, bundles and interactions
In the ECS 2013 overview report (Eurofound, 2015), 
latent class analyses identified patterns behind the 
main thematic fields of the survey (work organisation, 
HRM, direct employee participation and social dialogue) 
and their subdimensions. This process made it possible 
to classify a large variety of combinations of practices 
across individual establishments into a few types of 
establishments with certain distinct characteristics.

The selection of the set of workplace practice variables 
built on this framework. The choices made were 
simultaneously based on existing empirical literature 
and the derived hypothesis (see above). For the purpose 
of this report, where the particular interest is in the 
relationship between these work practices and reported 
innovation, combined measures for each of the three 
thematic fields were also constructed: work organisation, 
HRM and direct employee involvement (described in 
Chapter 3). All indices were subsequently transformed 
such that they range between 0 and 10.

Social dialogue
Social dialogue variables are based on interviews with 
both management and employee representatives, and 
can thus be analysed on the basis of a limited number of 
cases only. Variables roughly measuring this dimension 
include synthetic measures and single items11. Three of 
the indices used for social dialogue – available resources, 
available information and employee representative 
influence in the decision-making process – were 
developed in the overview report (Eurofound, 2015). 
Occurrence of industrial action is taken as a proxy for 
conflictual industrial relations, whereas harmonious 
social dialogue is reflected in the level of mutual trust.

Control variables
The approach controls for company-specific 
characteristics and external factors that might either 
influence the establishment’s level of innovation directly 
or may result in an over- or underestimation of links 
between workplace practices and innovation. Variables 
prone to introduce bias – such as the sex or role of the 
respondent – were also controlled for. A total of 12 control 
variables are included.

First, the establishment size is included, taking into 
consideration that larger organisations may be more 
innovative than small firms (Watson et al, 2009). Firms 
that are part of a larger entity may have access to more 
resources and might have a greater ability to innovate. 
Hence, a dummy variable is included if the firm is a 

11  See Annex 1.

42

Innovative changes in European companies: Evidence from the European Company SurveyTable 5: Overview of variables per dimension – Models 1–4

Thematic 
fields

Model 1

Model 2

Model 3

Model 4

 4 – Methodology

Establishment 
demographics

Single dimensional items

Substitution of single 
items by bundles

Single dimensional items 
+ configurations

Size of establishment

Size of establishment

Size of establishment

Size of establishment

Establishment type

Establishment type

Establishment type

Establishment type

Sector of industry

Sector of industry

Sector of industry

Sector of industry

Increase/decrease in 
employment (2010–
2013)

Increase/decrease in 
employment (2010–2013)

Increase/decrease in 
employment (2010-2013)

Increase/decrease in 
employment (2010-2013)

Number of hierarchical 
levels

Number of hierarchical 
levels

Number of hierarchical 
levels

Number of hierarchical 
levels

% of female employees  % of female employees 

% of female employees 

% of female employees 

% of workers age 50 or 
over

% of workers age 50 or 
over

% of workers age 50 or 
over

% of workers age 50 or 
over

Organisational change

Organisational change

Organisational change

Organisational change

Collaboration and/or 
outsourcing

Monitoring of internal 
quality/external ideas

Department structure

Job rotation

Autonomous teams/task 
autonomy

Work organisation bundle 
(scale 0–10)

Collaboration

Number of monitoring 
instruments (3)

Department structure

Job rotation

Autonomous teams/task 
autonomy

HRM–work organisation 
configuration

Human capital

Human capital

Human capital

HRM bundle (scale 0–10)

Perceived need to reduce 
staff

On-the-job / paid time off

Flexi-time / accumulation 
of overtime

No. of variable pay 
instruments

Perceived need to reduce 
staff

On-the-job / paid-time off

Flexi-time / accumulation

No. of variable pay 
instruments

HRM–employee 
involvement configuration

Employee involvement in 
decision-making

Employee involvement 
bundle (scale 0–10)

Employee involvement in 
decision-making

Number of employee 
involvement instruments 
used

Number of employee 
involvement instruments 
used

Work organisation–
employee involvement 
configuration 

43

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Interaction

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Thematic 
fields

Model 1

Model 2

Model 3

Model 4

Establishment 
demographics

Single dimensional items

Substitution of single 
items by bundles

Single dimensional items 
+ configurations

e
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Employee 
representation structure 

Employee representation 
structure 

Employee representation 
structure 

Employee representation 
structure 

Sex of respondent

Sex of respondent

Sex of respondent

Sex of respondent

Role of respondent 
(owner, HR manager, 
other)

Role of respondent (owner, 
HR manager, other)

Role of respondent (owner, 
HR manager, other)

Role of respondent (owner, 
HR manager, other)

Country dummies

Country dummies

Country dummies

Country dummies

Model 1 considers only core establishment information 
such as size and sector, place of operation and workforce 
characteristics. Model 2 keeps the demographic variables 
and includes further variables that were identified as 
highly important for the three dimensions, as outlined 
above. Model 3 replaces the individual items of Model 
2 with bundles for each of the dimensions in order to 
explore the explanatory power of condensed workplace 
practices. Single items of Model 2 were kept if they were 
not part of the bundles. Also following Model 2, Model 
4 includes measures of combined practices (HRM/work 
organisation, HRM/direct employee participation, work 
organisation/direct employee participation) to examine 
whether the overall explanatory power can be increased 
by taking into account specific strategic decisions on 
combinations of work practices.

Models 5 and 6
Models 5 and 6 test the impact of workplace practices 
on performance and workplace well-being. Workplace 
practices/bundles as tested in Models 2–4 are included in 
Models 5 and 6. Finally, the component of social dialogue 
is introduced and its association with outcomes. A 
number of questions are addressed.

  To  what  extent  does  the  employee  representative 
influence  decision-making 
linked  with  company 
outcomes  (in  terms  of  performance  and  workplace 
well-being)?

  What  is  the  role  of  mutual  trust  between  managers 

and employee representatives in this process?

  What are the impacts of conflictual relationships?

OLS regressions on performance and workplace well-
being were developed and tested to investigate whether 
the effects of implementing specific workplace practices 
and their combinations are statistically significant. Two 
models were run as explained above

Limitations
Data on change in establishments were collected in 
order to assess the extent to which they used different 
combinations of workplace practices and whether 
change was a feature that characterised certain types 
of workplaces. The overall theme of the ECS 2013 was 
workplace innovation. Therefore, as mentioned earlier, 
the Oslo Manual definition of innovation was adopted 
(excluding organisational change). For this reason, and as 
space was limited, the questionnaire could not fully cover 
the complex nature of innovation. Innovation studies 
usually include detailed measures of outputs, such as 
increase in sales as a proportion of the total turnover, 
exports, revenues and productivity. Furthermore, the 
data capturing increase in volume of products or services 
do not differentiate between new (as a result of the 
innovation) and old products or services. 

The results are constrained by the types of questions 
used in the ECS 2013 and by missing responses to some 
questions. As explained in the introductory part of this 
report, the ECS was not originally designed to analyse 
innovation. The survey questions ask whether change 
had been implemented in the three years preceding 
the survey (2010–2013). Other types of change, such 
as changes in technology or HRM practices, could 
have happened before or after the introduction of new 
products, marketing strategies or processes. For this 
reason, these variables are not included in the models 
as it is supposed that change in one area cannot be 
explained with change in another but rather might 
happen concomitantly. The same holds for workplace 
practices in general which might have been in place since 
the foundation of the establishment or been introduced 
a month before the survey. Hence, it is not possible to 
draw conclusions of any causal nature and only significant 
associations and relationships can be indicated.

44

Innovative changes in European companies: Evidence from the European Company Survey 
 4 – Methodology

Naturally, as with all ex-post constructs, the measures 
of well-being and performance used in the analysis 
have their limits. First of all, an index of well-being (as 
used in Eurofound (2015) and in this report) is based 
on information given by the management side alone. 
However, the notion of workplace well-being is often 
associated with individual experiences (Barrios-Choplin 
et al, 1997; Thompson and Bates, 2009; Roche and Rolley, 
2011; Anitha, 2014). The term used in the Sixth European 
Working Conditions Survey, was ‘job quality’, taking into 
account the workers’ perspective (Eurofound, 2016b). 
Notwithstanding these limitations and for reasons of 

consistency, this report uses the same terminology 
as Eurofound (2015). As the analysis shows, all the 
performance measures turned out to be useful in the 
analysis of establishment structures and in identifying 
practices that are associated with performance. For 
instance, it was shown that establishments that were 
classified as ‘systematic and involving’ and as ‘interactive 
and involving’ scored significantly higher in the 
performance index than other types of establishments. 
The latter also scored highest in the well-being index 
(Eurofound, 2015, p. 128).

45

5 Results of the analysis

Introduction5 Results of the analysis

Patterns of innovation in terms of structural 
characteristics were discussed in Chapter 3. This 
chapter aims to explain which practices are significantly 
associated with change in establishments. This provides 
some answers to the question about which organisational 
structure in establishments promotes a tendency to 
implement innovations in their various forms. It also helps 
in identifying best practices and priority areas for business 
and innovation policies.

The second part of this chapter is dedicated to the analysis 
of how workplace practices/bundles affect performance 
and workplace well-being, with a particular focus on the 
role of social dialogue.

Determinants of innovation in 
establishments

Results: Models 1–4
The main results of Models 1–4 are presented generically 
below. A thorough discussion of these results is 
undertaken in Chapter 6. Overall, estimates are robust 
over the different specifications. Both significant levels 
and size effects are stable. Hence, the results obtained 
from the quantitative analysis can be seen as highly robust 
(Table 6).

Work organisation

Monitoring internal production quality and/or external 
ideas turned out to be the strongest determinant of overall 
innovation in the area of work organisation. This variable 
increases the probability of innovation by 9%, controlling 
for other influence factors (Model 2). This is the single 
strongest driver of innovation.

The collaboration and/or outsourcing of production, 
marketing or development also shows highly significant 
positive effects for innovation. In terms of the organisation 
of daily work, both task/job rotation and the degree of 
autonomy of teams or within tasks is positively linked 
with innovation at the 0.01 level. Finally, the structure 
of work organisation also matters. The likelihood of 
reporting innovation increases by 8% where work and 
production flow are structured by department (assigned 
to geographic, functional or product-based tasks).

Departments as organisational units dealing with different 
types of products/services or with specific geographical 
areas turned out to have a strong positive influence on 
change, with marginal effects of 0.09 across the models. 
Across the various types of innovation, marginal effects 
were strongest for changes in products/services.

HRM-related measures

Several  items  were  included  that  relate  to  HRM-related 
issues:

the percentage of employees with access to training

the  number  of  variable  pay  instruments  in  place 
(maximum of five)12

the option of flexibility in terms of starting and ending 
time and accumulating overtime

a  focus  on  skills  and  human  capital  (measured  as  the 
proportion of employees with a university degree).

Access to training (whether on the job or paid time off 
for training) was positively linked to innovation in the 
establishment, with highly significant marginal effects for 
change overall. The number of variable pay instruments 
in place was also positively linked with innovation. The 
more instruments implemented, the higher the probability 
that change was reported. Exploring each pay instrument 
individually showed, however, that the association of 
change overall and variable pay was highly significant only 
for bonuses. The association of payments by results and 
overall change was significant only at the 0.05 level and not 
significant for the other measures.

Finally, an establishment’s human capital in terms of 
skilled employees is an important determinant of change, 
as expected. Across all models, marginal effects were 
highly significant, controlling for other factors. There 
were, however, differences between different types of 
innovation. The level of skills was significant only for 
innovation in products/services, and there were no 
significant associations between human capital and 
innovation in processes or marketing.

No significant effects were found for working time 
flexibility and overall innovation. Some weak impact (at 
the 0.05 level) was, however, identified for working time 
flexibility on product innovation.

Employee involvement

Evidence is provided for the hypothesis relating direct 
employee involvement to innovative company behaviour. 
The number of instruments used for employee involvement 
(such as regular staff meetings, staff surveys or suggestion 
boxes) is positively associated with the reporting of overall 
innovation. The results show that the higher the number of 
instruments in place, the greater the probability of change 
being reported.

Furthermore, direct involvement of employees in terms 
of consultation or joint decision-making was found to be 
positively associated with innovation in the establishment. 

12  Payment by results; bonuses paid; group performance-based pay; profit -sharing; and share ownership.

48

 
 
 
 
Where employees are consulted or take part in joint 
decisions, the likelihood of innovation rises by 7%, 
controlling for other influence factors. The presence of a 
formal employee representation structure, however, is not 
itself associated with innovation, but is mediated through 
other variables. Interestingly, Model 3 found no significant 
association between innovation in products and employee 
involvement in decision-making.

Change in the organisation

As was explained in Chapter 1, organisational change was 
not included in the innovation concept used in this report. 
The main reason is that the ECS focuses on organisational 
issues. Hence, organisational change must be interpreted 
in the ECS context as one organisational characteristic. It 
was thus included as an independent variable. However, 
the results clearly show tight links between organisational 
change and reported innovation in products/services, 
processes and marketing. The likelihood of an 
establishment reporting innovation in the three areas was, 
across all models, more than 20% higher in cases where 
organisational change was implemented. This finding 
emphasises the nature of change as a process embracing 
the whole establishment. Where change in one area takes 
place, the probability of change in other areas increases.

Bundles and interactions

Model 3 replaces single items of practices in the three areas 
(work organisation, HRM, direct employee involvement) 
with synthetic bundles (with scales ranging from 0 to 

Table 6: Marginal effects across models

 5 – Results of the analysis

10), thus condensing applied workplace practices to a 
single measure. This method does not improve the overall 
explanatory power (pseudo-R2 is 18%) but indicates that 
the likelihood of innovation might be driven by strategic 
decisions on how to combine common workplace 
practices. All three bundles are significantly associated 
with reported innovation, with the strongest marginal 
effects for the direct employee involvement bundle. A 
rise in this index of one point increases the probability of 
change by 3%. The weakest association, at the 0.01 level, 
was between HRM and innovation. Still, the more measures 
that were in place or combined, the more likely it was that 
innovations were implemented in the establishment.

More interesting, however, are the results of Model 4. 
Measures of configuration/interaction between the 
various areas were built (ranging from 0 to 10) and 
their impact was tested together with the single items 
of Model 2. The inclusion of the configuration slightly 
increases the explanatory power of Model 2. With a 
few exceptions, marginal effects of the single practices 
(including collaboration/outsourcing and training) stay 
unchanged or even get stronger. Furthermore, strong 
positive effects from the interaction of work organisation 
and employee involvement as well as from the HRM and 
employee involvement can be seen. This suggests that 
establishments that consider a well-balanced mix of 
practices in these areas are more likely to innovate. On 
the other hand, negative effects are produced for the 
interaction of work organisation and HRM. 

Variables

Model 1

Model 2

Model 3

Model 4

Organisational change implemented  
(2010–2013)

0.290***

0.226***

0.234***

0.225***

Size: number of employees (Reference: 10–49) 

50–249

250+

Sector (Reference: Industry) 

Construction

Commerce and hospitality

Transport

(0.00535)

(0.00558)

(0.00559)

(0.00557)

0.0290***

(0.00745)

0.0655***

(0.0102)

-0.129***

(0.0115)

-0.000409

(0.00782)

-0.134***

(0.0119)

-0.00232

(0.00718)

0.0156

(0.00995)

-0.115***

(0.0112)

0.00853

(0.00760)

-0.0943***

(0.0117)

0.00574

(0.00720)

0.0264***

(0.00991)

-0.00242

(0.00718)

0.0150

(0.00995)

-0.119***

-0.114***

(0.0112)

-0.00387

(0.00758)

-0.113***

(0.0116)

(0.0112)

0.00945

(0.00758)

-0.0935***

(0.0117)

Financial services

-0.0687***

-0.0660***

-0.0893***

-0.0668***

(0.0153)

(0.0148)

(0.0148)

(0.0149)

Business, administration and other services

-0.0483***

-0.0430***

-0.0679***

-0.0433***

(0.00820)

(0.00820)

(0.00815)

(0.00820)

49

Variables

Model 1

Model 2

Model 3

Model 4

Establishment type (Reference: Headquarters/subsidiary sites) 

Single establishment

-0.0506***

-0.0250***

-0.0269***

-0.0249***

Number of hierarchical levels

Workforce characteristics 

Proportion of female workers is greater than 20%

(0.00668)

0.00566**

(0.00255)

(0.00651)

-0.000768

(0.00144)

(0.00653)

0.00107

(0.00167)

(0.00651)

-0.000648

(0.00143)

0.0483***

(0.00788)

0.0358***

(0.00771)

0.0343***

(0.00772)

0.0355***

(0.00770)

Proportion of workers aged 50+ is greater than 20%

-0.0322***

-0.0242***

-0.0233***

-0.0238***

(0.00698)

0.120***

(0.00686)

0.00950

(0.00731)

Number of employees increased (2010–2013)

Number of employees decreased (2010–2013)

Work organisation practices 

Collaboration and/or outsourcing

Monitoring of production quality/external ideas

Structured in departments

Task/job rotation

Autonomous teams/task autonomy

HRM-related items 

Training in place

Flexibility measures in place

Variable pay schemes in place

Skills (% of workers with university degree greater than 
20%)

Employee involvement 

Number of instruments deployed for employee 
involvement

Direct employee participation in decision-making

Employment representation structure present in 
establishment (or company) 

Bundles of workplace practices 

Bundle 1: Work organisation 

Bundle 2: HRM

50

(0.00677)

0.104***

(0.00669)

0.00874

(0.00722)

0.0535***

(0.00363)

0.0887***

(0.00627)

0.0842***

(0.00794)

0.0320***

(0.00599)

0.0164***

(0.00544)

0.000437***

(9.75e-05)

0.00125

(0.00528)

0.0197***

(0.00218)

0.0168**

(0.00681)

0.105***

(0.00675)

0.0115

(0.00677)

0.103***

(0.00670)

0.0102

(0.00707)

(0.00703)

0.0535***

(0.00456)

0.0894***

(0.00671)

0.0848***

(0.00821)

0.0320***

(0.00599)

0.0175**

(0.00838)

0.000459***

(0.000139)

0.00348

(0.00644)

0.0207***

(0.00469)

0.0168**

0.0158**

(0.00724)

(0.00726)

(0.00724)

0.0184***

(0.00198)

0.0658***

(0.00596)

0.00129

(0.00676)

0.000859

(0.00359)

0.0232**

(0.00935)

0.00239

(0.00677)

0.0240***

(0.00145)

0.0177***

Innovative changes in European companies: Evidence from the European Company Survey 5 – Results of the analysis

Variables

Model 1

Model 2

Model 3

Model 4

Bundle 3: Employee involvement 

HRM–employee involvement configuration

HRM–work organisation configuration

WO–employee involvement configuration

(0.00166)

0.0279***

(0.00139)

Pseudo-R2

Observations

14.2%

24,471

19.1%

24,455

18.1%

24,455

0.0228***

(0.00622)

-0.0270***

(0.00634)

0.0197***

(0.00514)

19.2%

24,455

Notes: Standard errors in parentheses; *** p < 0.01, ** p < 0.05, * p < 0.1; unweighted data, marginal effects and robust standard errors in brackets, 
Pseudo-R2 = 19.2% for Model 4 (best fit)

Source: ECS 2013 – Management questionnaire

Links between workplace 
practices, performance  
and well-being
In the previous section, the effects of various workplace 
practices on innovation in establishments were 
estimated. This estimate was based on the assumption 
that innovation and the associated workplace practices 
would overall have a positive impact on establishment 
outcomes. Understanding the relationship between 
outcomes and innovative activities provides crucial 
insights for both policymakers and company 
management, as well as for social dialogue at the 
establishment level. As outlined in the introduction, 
innovation is described in the Europe 2020 strategy 
as a way to achieve smart, sustainable and inclusive 
growth. Hence, it is necessary to explore the micro 
links between individual company innovation and 
company performance in order to draw conclusions on 
a broader basis. For managers, these insights can help 
to optimise decision-making processes and achieve 
effective allocation of resources. In terms of social 
dialogue, it is essential to understand the links between 
performance, innovation and win-win arrangements 
such as favourable working conditions or employee-
centred HR strategies. Well-functioning social dialogue 
is a key component for the successful design and 
implementation of reforms needed to increase the 
competitiveness of Europe’s economies and create more 
jobs, as demonstrated in previous Eurofound research 
(Eurofound, 2016a).

Against this background, the objective of this section is 
to study the effects of innovative workplace practices 
and social dialogue on the overall outcome of the 
establishment, in terms of performance and workplace 

well-being, on the basis of empirical evidence from the 
ECS.

Results: Models 5 and 6
This section explores the impact of associated work 
practices (including different configurations) on 
performance (external) and workplace well-being 
(internal). Figure 14 illustrates the conceptual framework 
of the analysis (displayed previously in Figure 2).

Figure 14: Schematic of the conceptual framework

1

Workplace 
practices 
(HRM-WO)

Products

Innovation

Process

Marketing

2

3

Social 
dialogue

Performance 
and workplace 
well-being

As described above, workplace practices and their 
combinations and interactions have a crucial role not 
only for the strategic alignment of an establishment 
towards competitive markets but also in terms of the 
company’s overall performance. In Chapter 3, evidence 

51

was provided that these practices have an impact on, or 
are at least significantly associated with, a firm’s decision 
to introduce innovation. This section explores whether 
this disposition to innovate and the associated bundles 
of practices are also interrelated with the performance 
and well-being levels of the establishment. Analysis 
also shows that correlations between performance and 
many of the variables included are comparable to the 
correlations of well-being and these same variables 
– with, however, some differences (Annex 3). Table 7 
compares the levels of performance and well-being in 
establishments that introduced innovation with levels 
in those establishments that did not innovate. It breaks 
the results down by bundles of workplace practices 
(with structures categorised as rudimentary, moderate 
or strong, depending on the number of practices 
implemented in each area) and by variables of social 
dialogue.

First, it is clear that measures of performance and 
well-being are higher in establishments reporting 
innovation. The differences are more pronounced in 
terms of performance than of well-being. Second, 

across all bundles of practices, strongly structured 
establishments (implementing a wide range of 
practices in the area) show significantly higher levels of 
performance and well-being than establishments with 
rudimentary or moderate structures in place. Notably, 
even within the categorical structures (strong/moderate/
rudimentary), establishments that reported innovations 
show significantly higher values in both measures than 
the reference group. The highest average levels of 
performance (71.3) and of workplace well-being (78.7) 
overall are achieved in establishments with strong HRM 
structures in place (offering access to training, time 
flexibility and variable pay measures to employees) and 
that introduced innovation in the three years preceding 
the survey.

Finally, interesting results are displayed in terms of social 
dialogue. Variables cover both the harmonious and 
conflict-oriented type of social dialogue. It is observed 
that levels of performance/well-being drop below 
average in cases where industrial action took place. 
Moreover, a trustworthy relationship between employee 
representation and management is associated with 

Table 7: Performance and workplace well-being by workplace bundles and change (mean)

No innovation reported

Innovation reported

Performance

Well-being

Performance

Well-being

53.1

58.7

61.9

54.5

58.4

62.4

53.7

57.2

61.0

49.3

59.7

52.6

61.4

47.7

56.5

71.5

73.2

77.0

71.7

73.4

76.1

71.2

73.3

74.5

66.1

76.3

66.5

75.7

62.2

72.6

57.7

64.6

71.3

59.5

64.5

69.7

58.3

63.3

66.2

55.8

64.0

59.2

69.6

50.9

63.5

73.5

75.0

78.7

73.1

75.5

77.6

72.6

74.5

76.4

69.3

75.4

67.1

77.3

62.1

75.0

HRM structure 

Rudimentary

Moderate

Strong

Work organisation structure 

Rudimentary

Moderate

Strong

Employee involvement structure 

Rudimentary

Moderate

Strong

Social dialogue

Industrial action

High trust in management

Low trust in management

High trust in employee representation

Low trust in employee representation

Total

Note: Scores range from 0–100.

Source: ECS 2013, weighted data

52

Innovative changes in European companies: Evidence from the European Company Survey 
 5 – Results of the analysis

higher levels of performance and well-being. However, 
the trust that managers have in employee representatives 
has a bigger impact (at least looking at bivariate links). 
Whether these factors remain significant after controlling 
for other factors is explored below.

Once the correlations and interrelations between 
workplace well-being/performance and key workplace 
practices and social dialogue are identified, the degree 
of consistency between them in a multivariate regression 
model is assessed so that the additional impact of each 
variable after controlling for the others is examined. 
For this purpose, all categorised bundles of workplace 
practices (rudimentary/moderate/strong) (with 
performance (Model 5.1) and well-being (Model 5.2) as 
dependent variables) were included first, controlling for 
structural establishment characteristics. Model 6 focuses 
on the impact of social dialogue on both measures, 

keeping other factors constant. This model includes 
a limited number of cases (6,919) as it includes only 
those establishments where interviews with employee 
representatives were carried out.

Table 8 analyses selected results of Model 5. 
Unsurprisingly, an increase in employment is significantly 
and strongly associated with a better performance. 
On average, in establishments that reported such an 
increase, performance levels were 11 points higher than in 
the reference category. Organisational change is actually 
the only item with opposite signs: while such change turns 
out to be generally favourable for performance levels, 
the impact on workplace well-being is less beneficial. 
This result is in line with previous research on uncertainty 
during organisational restructuring (Bordia et al, 2004). 
It should be taken as evident that organisational change 
needs to be accompanied by measures to cushion its 

Table 8: Regression coefficients, by dimension and change (Model 5)

Performance

Well-being

Establishment characteristics

Increases in employment

Organisational change

% of female workers >20%

% of workers aged 50+ >20%

% of skilled workers >20%

Work organisation bundle (Reference: Rudimentary) 

Moderate

Strong

HRM bundle (Reference: Rudimentary)

Moderate

Strong

Employee involvement bundle (Reference: Rudimentary) 

Moderate

Strong

11.07***

(0.336)

2.095***

(0.306)

1.352***

(0.381)

-1.686***

(0.337)

2.065***

(0.360)

1.472***

(0.323)

2.270***

(0.554)

2.661***

(0.347)

5.021***

(0.561)

1.401***

(0.387)

3.649***

(0.390)

3.398***

(0.267)

-0.775***

(0.243)

0.643**

(0.303)

-1.462***

(0.267)

1.544***

(0.286)

0.616**

(0.257)

1.679***

(0.440)

0.707**

(0.276)

3.338***

(0.445)

0.793***

(0.307)

2.940***

(0.310)

Notes: Models are controlled for establishment size, establishment type, sector, workforce characteristics, hierarchy levels and further controls 
(country, sex of respondent, role of respondent). Significance level: * p < 0.05, ** p < 0.01, *** p < 0.001

Source: ECS 2013, unweighted data

53

 
 
 
 
 
 
 
 
 
 
 
 
 
 
Further to the predictors shown in Figure 15, the model 
tested the synthetic indicators of the available resources 
for employee representatives (including sufficiency of 
allocated time, availability of training, availability of 
funding for external advice), the availability of information 
to them and the level of representatives’ influence on 
decision-making. The estimates of available information 
for employee representatives are significant at the 0.1 
level for well-being only, indicating a favourable interplay 
between positive outcomes and cooperative social 
dialogue. Also, the influence of employee representatives 
is significant for well-being only. The available resources, 
on the other hand, are not significant for any of the 
dependent variables.

It is also of interest to look at the effects of workplace 
practice bundles in the employee involvement models. 
For establishments that implemented innovation, very 
strong effects were found for strong direct employee 
involvement structures. Establishments that have these 
structures in place score on average five points higher in 
both performance and workplace well-being, compared 
with establishments with rudimentary employee 
involvement structures. Strong HRM structures – on the 
other hand – turned out to be more important for the 
establishment’s performance than for well-being.

The main conclusion to be drawn from this section is 
that there are clear links between the main dimensions 
analysed: performance, workplace well-being, workplace 
practices and social dialogue. In the bivariate analysis, it 
was found that levels of performance and well-being are 
above average across all breakdowns in establishments 
where innovation took place compared with those 
where it did not. In addition, levels of performance 
and well-being are higher where strong structures of 
work organisation, HRM measures and direct employee 
involvement are implemented. Finally, the crucial role of 
harmonious social dialogue at the workplace cannot be 
overestimated. High levels of mutual trust, in combination 
with strong instruments of direct employee participation, 
result in the highest levels of performance and create a 
beneficial atmosphere for innovative action.

negative effects, a topic also extensively studied in the 
literature (Rafferty and Griffin, 2006; Prilleltensky and 
Prilleltensky, 2007).

Notably, in terms of workplace practices, the strongest 
associations are between the HRM bundle and 
performance levels. On average, establishments with 
strongly structured HRM practices score five points higher 
than those with weak structures. The level of well-being 
level in these establishments is on average three points 
above that in the reference establishments.

Figure 15 shows the regression coefficients of social 
dialogue variables from Model 6 for both measures. 
The regression analysis confirms that industrial action 
is negatively associated with both outcome measures 
also after controlling for other determinants. If industrial 
action took place, performance levels decreased on 
average by 1.7 points and well-being levels dropped by 
2.9 points. This result is, of course, not surprising given 
the situations in which industrial action is usually taken: 
for example, in cases of restructuring, downsizing and 
budget cuts. Hence, it is important to highlight that this 
result is not to be interpreted as a causal relationship but 
may reflect associated events.

The crucial role of mutual trust is also confirmed. High 
levels of trust on the part of management in the employee 
representatives raise levels of workplace well-being by 
7.7 points on average (compared with establishments 
with low trust levels). Likewise, trust in management as 
expressed by the employee representatives positively 
affected both outcome measures, though the trust in 
management was only weakly significant for levels of 
performance (1.6).

Figure 15: Regression coefficients – Model 6

Well-being 

-2.9*** 

4.6*** 

7.7*** 

Performance 

1.6* 

3.2*** 

-1.7** 

-4 

-2 

0 

2 

4 

6 

8 

10 

High trust 
in managers 

High trust in employee
representation  

Industrial action 
occurred 

Notes: Models are controlled for establishment type, sector, workforce 
characteristics, hierarchy levels, bundles of workplace practices and 
further controls (country, sex of respondent, role of respondent). 
Significance level: * p < 0.05, ** p < 0.01, *** p < 0.001

Source: ECS 2013, unweighted data

54

Innovative changes in European companies: Evidence from the European Company Survey 5 – Results of the analysis

Links between the main dimensions

Using data from the ECS 2013, and multivariate logistic regression models, this chapter explored the relationship 
between reported change in establishments, establishment characteristics, work organisation, HRM practices 
and direct employee involvement. Furthermore, it was examined whether bundles of workplace practices and 
their configurations could further contribute to innovation. The chapter identifies clear links between the main 
dimensions analysed: performance, workplace well-being, change and associated workplace practices. The crucial 
role of harmonious social dialogue in the workplace was also highlighted.

Establishment size matters for innovation overall: The bigger the establishment in terms of the number 
of employees, the higher the likelihood that innovation was reported. However, the effect disappeared when 
including further measures, indicating that establishment size is mediated through other items and is not in itself a 
determinant of change. 

Type of establishment is important for innovation: Apart from size, the type of establishment (headquarters/
subsidiary site versus single establishment) was tested and turned out to be significantly associated with 
innovation across all models. 

Sectors differ in likelihood of introducing innovation: There are significant differences regarding the 
introduction of innovation between some sectors. The industrial sector, for example, had a much higher 
probability of introducing innovation. 

Characteristics of the workforce are relevant: Workforce related measures, such as gender and age structure 
and the increase of employment since 2010, all were significantly linked to change across all models.

Monitoring internal production quality and/or external ideas are key determinants of overall change in the 
area of work organisation. 

Collaboration in – and/or outsourcing of – production, marketing or development showed highly significant 
positive effects for change. 

Role of rotation and team autonomy: In terms of organisation of daily work, both task/job rotation and the 
degree of autonomy of teams or within tasks is positively linked with reported innovation. 

The structure of work organisation matters: departments as organisational units dealing with different types of 
products/services or with specific geographical areas were found to have a positive relationship with change.

HRM-related variables showed the following picture. 

  Access for employees to training was positively linked to innovation. 

  The association of innovation and the number of variable pay instruments was highly significant. 

  An establishment’s human capital in terms of skilled employees proved to be an important predictor of 

innovation, as expected. 

No significant effects were found for working time flexibility.

Importance of direct employee involvement: A strong link was found between innovation and direct employee 
involvement. In particular, the number of instruments in place supporting such involvement is important 
(including regular staff meetings, staff surveys, suggestion boxes) and others. Furthermore, the participation of 
employees in the decision-making process turned out to have a positive impact on overall innovation.

Importance of bundles of practices: The research moved from looking at single items of practices in the 
three areas (work organisation, HRM and direct employee involvement) to looking at bundles of practices. All 
three bundles are significantly associated with innovation, the most strongly associated being the employee 
involvement bundle, the weakest association being between HRM and innovation.

Importance of interactions between bundles: within the workplace, the bundles of practices are implemented 
together: their interaction matters. The work organisation bundle, interacting with the employee involvement 
bundle produced strong, positive effects on innovation. The same was found for the interaction between HRM 
practices and employee involvement.

Role of social dialogue on establishment economic performance and workplace well-being: Harmonious 
social dialogue matters. Measures of performance and well-being were well below average in cases where 
industrial action took place. Moreover, a trusting relationship between the employee representatives and 

55

management was associated with higher levels of performance and well-being. These results remained significant 
after controlling for other influencing factors. In addition, levels of performance and well-being levels were higher 
on average in establishments that reported innovation . 

Role of strong structuring in workplace practices: In addition, across all bundles of practices, establishments 
that were strongly structured in terms of work organisation, HRM or direct employee involvement showed higher 
levels of performance and well-being than those with rudimentary or moderate structures. Notably, even with the 
same degree of structuring, establishments with innovations had significantly higher values for both performance 
and well-being than establishments without innovations. The highest average levels of performance and of 
workplace well-being were observed in establishments with strong HRM structures in place and that had also 
implemented innovations in the three years preceding the survey.

56

Innovative changes in European companies: Evidence from the European Company Survey6 Workplace practices in 
fostering innovation

Introduction6  Workplace practices in fostering 

innovation

As said in Chapter 1, innovation in companies implies 
a complex, continuous and non-linear interaction 
between ideas, development, implementation, 
experiences and iterative adaptations. In order to 
understand this complexity, it is essential to address 
innovation from an organisational and a process 
perspective. The organisational form and work 
systems adopted by companies may facilitate, foster 
or hinder innovation. Any company’s HRM system 
essentially includes the management of work and the 
management of people. So, in the broadest sense there 
are two types of practices; work practices and HRM 
practices (Boxall and Macky, 2009). The former refers 
to the design of the production process (transforming 
inputs into outputs) and the organisation of work 
processes (how employees can effectively deploy their 
skills, use their creativity, innovate, work in teams, 
solve problems, and be involved in decision-making). 
The design of such systems can affect the quality of 
products or services and become a determinant of 
company innovative action and performance (and 
eventually success).

At the same time, HRM practices, such as recruitment, 
selection, redundancies, dismissals, training and 
development skills for innovation, appraisal and 
remuneration and, more generally, motivating and 
rewarding employees for creative ideas and innovation 
can assist companies in improving performance. 

Both practices, work and HRM, can affect the 
organisation (at both the individual/ employee and 
collective level) and can potentially make a significant 
contribution to innovation and performance. The 
implementation of work practices and their association 
with performance is analysed and not taken as 
evidence of ‘superior’ performance.

In this chapter, the results of the statistical analysis, 
informed by the insights of the relevant literature, are 
discussed in detail. Again, it needs to be stressed that 
the quantitative analysis has its limits due to the design 
and purpose of the original survey questionnaire. It is 
therefore important to put the quantitative findings in 
a broader context of interpretation in order to make 
them meaningful.

Role of work organisation in 
innovation
The various forms of work organisation adopted reflect 
a company’s choice to combine different practices, 
different internal control and coordination systems, 

58

and different strategies in order to establish adequate 
operational modes and systems of resource allocation 
(Sparrow et al, 2015). Innovation and change is very 
much linked to the flexibility to adapt these structures 
to economic challenges.

The literature review has shown that the design of work 
organisation matters for innovation – especially the 
organisation of work in teams (Van de Ven et al, 2000; 
Lam and Lundvall, 2006). Different work organisation 
models can produce different outcomes. Collective 
working methods are useful for generating and 
implementing ideas. Autonomy and cooperation are 
important dimensions linked to innovation (Stoker et 
al, 2001). In addition, it is known from the literature on 
HPWP that different configurations of organisational 
practices can enhance both the company’s efficiency 
in its work processes and the quality of products 
and processes. Practices that increase employee 
participation in decision-making, problem-solving and 
quality control can contribute to better organisational 
performance.

Work organisation practices
The ECS 2013 contained three sets of work organisation 
practices to be analysed for their contribution to, 
and association with, change at the workplace level. 
These only tentatively cover the entire range of work 
organisational settings. They are as follows:

collaboration and outsourcing

  decision-making on daily tasks

internal organisation, information management and 
technology – including monitoring of quality of the 
production  process  or  service  delivery,  monitoring 
of external ideas and department structure.

The statistical analysis of the previous chapter 
examined individual work organisation practices but 
also different configurations, as explained above. 
The following single practices were significantly and 
positively associated with the implementation of 
change:

collaboration and outsourcing

  quality management and knowledge transfer

task rotation

  employee autonomy in decision-making.

 
 
 
 
These practices are also among the nine key factors 
that Smith et al (2008) identified as affecting innovation 
management – including knowledge management, 
corporate strategy, organisational structure and culture.

With regard to collaboration, it is known from previous 
research  that  companies  usually  cooperate  with  each 
other as a response to:

the need to strengthen competitiveness

strategic resource development

social and institutional needs

the use of a partner’s assets and resources.

Companies prioritise strategic cooperation with a view 
to increase knowledge and learning in certain areas; to 
improve  efficiency  and  play  a  bigger  role  in  the  global 
market. (Mazzola and Perrone, 2013).

Similarly, outsourcing is considered a way to increase 
efficiency, foster innovation by accessing other firms’ 
expertise and specialised resources, and to transfer 
knowledge and skills (Mowery et al, 1996; McCarthy 
and Anagnostou, 2004; Holcomb and Hitt, 2007; 
Mazzola and Perrone, 2013). It is also a well-established 
practice: in innovation projects and processes, most 
firms rely on external sources and collaboration with 
other organisations. Such outsourcing or collaboration 
schemes involve both public and private institutions 
and are often not confined to domestic partnerships. 
From a strategic point of view, the collaboration of a 
firm with technology providers or intermediaries such 
as research and consultancy firms promotes the vital 
exchange of knowledge and facilitates mutual learning, 
which in turn boosts innovation (Storper and Venables, 
2004). The analysis contained in this report confirms 
the importance of collaboration (in design, marketing 
and/or development) for innovation (see Chapter 3).

The analytical results demonstrate that quality 
management and knowledge transfer practices play 
a role in an establishment’s tendency to innovate. 
Practices more often used by innovative companies 
include the adoption of quality management through 
developing a quality mentality, formal quality 
management policies and procedures, and quality 
circles. Innovative companies encourage their 
employees to collect external stimuli with a view to 
improving access to new products or services or new 
technologies, and to dealing with emerging societal 
challenges. Transferring knowledge from the outside 
world into the company can boost the internal 
innovative capacity.

In this statistical analysis, practices associated with 
quality management include monitoring of quality of 
production or delivery of service, monitoring external 
ideas or keeping records of best practices. They were 
all found to be positively associated with innovation in 
the establishments that use them, confirming previous 
insights.

 6 – Workplace practices in fostering innovation

Task rotation allows employees to move from one task 
to  another.  Under  certain  circumstances  this  provides 
opportunities for learning and can potentially stimulate 
creativity,  much  needed  for  innovative  organisations. 
Organisations  can  become  more  flexible  by  enhancing 
the  capacity  of  their  staff  to  perform  and  alternate 
different tasks.

The quantitative exercise also showed that a certain 
degree of autonomy for employees regarding 
the planning and execution of daily tasks or the 
organisation of teamwork seems to be beneficial 
for the overall tendency to introduce innovation in 
the establishment. Extensive research on employee 
autonomy in decision-making has documented its 
manifold benefits on both the workforce and the 
organisation (Nicholson et al, 2005). In highly skilled 
business environments, in particular, work autonomy 
has a beneficial impact on employee behaviour, leading 
in turn to greater motivation, better skills utilisation 
and more job satisfaction. Autonomy also provides 
workers with resources to make use of their creative 
potential (Černe et al, 2016). Solving business-related 
problems and finding creative approaches requires 
employees to have expert knowledge and exercise 
autonomy.. Conversely, lack of employee autonomy 
is related to higher staff turnover, absenteeism and 
enhanced health problems (Head et al, 2007; Eller et al, 
2009; Schaufeli et al, 2009).

Conventional wisdom associates innovation with 
breakthrough changes, such as inventions, possibly 
envisioned by a single individual. However, reality 
shows that, first, even the visionary individual 
needs a team to implement ideas and, second, that 
innovations often take place in an incremental way and 
require group work and organisation. This does not 
undermine the role of the individual innovator; instead, 
it highlights the importance of joint efforts towards 
an organisational objective and as a source of creative 
ideas and, consequently, innovation. A joint effort 
could include solving production or service delivery 
problems, testing new solutions and ideas, and revising 
until the final product or service is ready for the market. 
In conclusion, the presence of teams as such may not 
automatically lead to creative or innovative solutions 
but teams can be understood as a means to organise 
and channel implicit and tacit knowledge towards 
overarching objectives. In this report, teams were 
found to be significantly associated with change in 
the workplace. Moreover, teams need to have specific 
structural characteristics to make these approaches 
work. These characteristics include the freedom and 
independence to make decisions about procedures, 
task autonomy and a spirit of community. Top-down 
approaches might endanger the unfolding of a team’s 
full potential and can even have negative impacts in 
terms of performance, identity or motivation. However, 
the role of the supervisor is essential in encouraging 
the successful functioning of autonomous teamwork, 

59

 
 
 
 
especially when it comes to the implementation of 
innovative ideas (Rosing et al, 2011).

In other words, although a worker can develop 
new and highly creative ideas on their own, the 
implementation of these ideas is enhanced ‘when 
employees are both able (competence) and enabled 
(relatedness) to participate in decision-making, 
which both stem from supportive supervision’ (Černe 
et al, 2016, p. 172). This final remark also illustrates 
the interplay of work organisation, HRM, employee 
participation and workplace well-being.

Synergistic effect of work organisation with 
other workplace practices
The individual practices discussed above appear to 
affect innovation, as described earlier. However, it was 
essential to assess the synergistic effect of bundles 
of practices and their interaction with the individual 
measures. Single practices per se may have an effect 
on innovation that is distinct from the impact of a 
strategic bundle of practices or from the interaction 
between them. Previous research indicated the 
limitations of individual HRM and work organisation 
practices (implemented in isolation) in fostering 
innovation (Jiménez-Jiménez and Sanz-Valle, 2005). 
In line with this, the statistical analysis proved that 
interactions between bundles increase the explanatory 
power of the model to estimate the likelihood of 
innovation. Two types of interactions were sought with 
a view to identifying their impact on innovation:

  work organisation and HRM practices (bundles and 

individual practices)

  work organisation and employee involvement 

(bundles and individual practices).

The first configuration – work organisation and HRM 
– produced negative results as regards the likelihood 
of change or innovation. This means that, despite the 
positive effect of individual work organisation or HRM 
practices on innovation, their combined effect in the 
absence of employee participation fails to produce 
the desired overall positive effect on innovation. In 
other words, there is no indication that accumulation 
of positive individual practices will in itself positively 
affect innovation. This suggests once more that it is the 
strategic approach that matters.

However, the second configuration – work organisation 
and direct employee involvement – produced a 
strong effect on the likelihood of reported innovation. 
This means that a (strategic) combination of strong 
structures of work organisation, together with distinct 
measures of direct employee participation, boosts 
the probability of innovation at the establishment 
level even more than if each of these measures 
were implemented loosely and individually. To give 
a practical example, the probability of innovation 
(product/process/marketing) is 9% higher in 
establishments that monitor the quality of the 
production process and/or external ideas than in 

60

establishments that do not. The probability increases 
by another 2% if the same establishment also involves 
its employees in the decision-making process 
(consulting them or taking decisions jointly with them). 
However, if the establishment decided to combine 
these measures strategically (indicating a specific 
organisational culture), the likelihood that innovation 
would be introduced rises by another 4%, compared 
with establishments that did not take such a decision. 
This example shows that an establishment’s capacity 
to innovate also depends on strategic decisions 
in terms of the way work is organised and how 
organisational settings encourage employees to be 
directly involved in relevant and crucial choices.

HRM practices
In a highly competitive environment, well-designed 
HRM policies play a key part in enhancing a company’s 
performance and the overall functioning of the 
organisation. The HRM literature (as mentioned 
earlier) has investigated the role that HRM policies and 
practices play in increasing company performance, 
particularly as regards:

  enhancing employees’ knowledge, skills and 

behaviours, which can positively affect company 
performance

innovative capacity (and thus performance), which 
can be strengthened by investing in employees’ 
skills, learning and motivation.

Literature on the links between HRM and innovation 
supports the idea that the above practices enhance 
the likelihood of company innovation. For example, the 
application of knowledge obtained through training 
promotes skills needed for innovation. Furthermore, 
recruiting a person with the right skills to fit the 
organisational structure enables companies to tap 
into the expertise needed for introducing innovation 
in their products, processes or marketing strategies. 
Designing attractive forms of motivation (variable pay 
schemes, time autonomy and appraisal systems) as 
employee incentives will increase the organisation’s 
capacity to develop creativity. The Ability, Motivation 
and Opportunities (AMO) model (Bailey, 1993) 
proposes that practices that allow individuals the 
space to carry out duties in their own manner enhance 
overall commitment and offer opportunities to exert 
personal and collective capabilities. Ability refers 
to the employees’ skills level and includes practices 
such as training and development and recruitment for 
the right skills . The opportunity dimension includes 
participation in decision-making, team autonomy, 
collaboration and improving quality which can further 
contribute to innovation. Finally, motivation in the 
form of financial and non-monetary incentives for 
exercising discretionary effort increases the likelihood 
of innovative action.

Innovative changes in European companies: Evidence from the European Company Survey 
The analysis of the ECS empirically supports the central 
arguments of the AMO model. Individual HRM practices 
confirmed as being positively linked to innovation are:

training

recruitment of skilled workers

variable pay.

More  importantly,  the  analysis  also  assessed  the  way 
these  practices  and  their  bundles  interact  with  each 
other.

The role of training in the different phases of work 
processes has been explored by researchers. In 
particular, focused training was found to be crucial 
for a favourable outcome. For example, in the early 
phases of developing a product, service or process, 
the appropriate training could encourage employees 
to engage in more free, lateral thinking to arrive at a 
range of original solutions (Shipton et al, 2006). A later 
stage of development might necessitate group work 
and interaction with clients and suppliers, which can 
be stimulated by training.

A highly skilled workforce with a large proportion 
of employees (more than 20%) holding a university 
degree appears to contribute to an increased 
likelihood of innovation, as expected (Taggar, 2002). 

Variable pay (such as bonuses, group-performance-
based pay and profit-sharing) is a further central HRM 
practice that has long been part of the discussion on 
performance. While studies that took place before the 
1990s painted a mixed picture, more recent studies 
emphasise positive associations between rewards 
and performance. However, variable pay can also 
inhibit change as it encourages the repetition of 
practices that have been successful in the past, rather 
than new approaches (see McCullers, 1978; Kohn, 
1993; Amabile, 1996; McGraw, 2015). Still, innovative 
activities and variable pay schemes have often been 
found to be interlinked (Lazear, 2000; Shearer, 2004; 
Ederer and Manso, 2013), as is also supported by the 
results presented in this report. Detailed analysis of 
variable pay practices included in the ECS revealed 
the strongest positive effects for payment-by-results 
(significantly associated with all three kinds of 
change). Bonuses were found to be linked to process 
and product innovation. However, the final model 
indicated that the number of variable pay instruments 
in place is important.

Synergistic effect of HRM with other 
practices
A basic premise of HRM strategy is that organisations 
are not an aggregation of individuals working together; 
organisations are systems of interacting elements 
including organisational structures, practices and 
behaviours. This research shows that individual HRM 

13  Working time flexibility on its own is not linked to innovation.

 6 – Workplace practices in fostering innovation

practices and also bundles of HRM practices produce 
strong effects on innovation, particularly when 
combined with employee-involvement practices. 
In other words, combining employee-oriented HRM 
practices that also encourage employee participation 
can be very potent and can reinforce the link between 
single HRM measures and innovation.

These findings imply that a coherent set of HRM 
policies with an emphasis on employee involvement 
creates a facilitating environment for innovative action 
in the establishment. The combination of practices 
that can contribute to better chances of introducing 
innovation include variable pay, training (facilitating 
employees’ gaining a high level of skills), together 
with measures of time flexibility13 . Additionally, 
direct employee involvement instruments include 
different tools (for example encouraging employees to 
contribute suggestions for improvement) as well as a 
role for employees in the decision-making process.

In conclusion, HRM practices do matter for the 
likelihood of a company introducing innovation. 
However, the HRM-employee participation 
configuration of practices functions as an even 
stronger promoter of innovative activities. Ultimately, 
innovation depends on the generation and, more 
importantly, the implementation of ideas.

Employee participation and 
social dialogue
The interplay of direct employee participation with 
bundles of work organisation and HRM has already 
been discussed. This section will focus on the overall 
role that involving employees in decisions and 
participation schemes plays in creating an innovative 
environment. Employee involvement is at the heart 
of the concept of HIWs (Lawler, 1986), suggesting 
favourable overall outcomes where such practices are 
in place.

HIWS are a managerial approach to work organisation 
through the involvement of employees, countering 
the Taylorist model of work organisation. A movement 
towards a high-involvement work environment 
entails better use of employees’ capacities for 
problem-solving and personal development. Such 
a work environment encourages information-
sharing and provides opportunities for employee 
participation in decision-making. This research 
examined the opportunities that employees are 
given for direct participation. Our analysis shows 
that direct participation of employees in the 
organisation is strongly associated with innovation in 
the establishment. All direct participation practices 
that were examined, such as the number of direct 
participation instruments provided by management 

61

 
 
 
employee participation practices in place, showing the 
significant links between direct participation and the 
establishment’s disposition to innovate.

The HRM and work organisation bundles that included a 
wide range of practices were found to be strongly linked 
with both performance and workplace well-being. The 
effect of the employee involvement bundle of practices 
was greater in companies that had introduced innovation 
in the last three years than in companies that had not.

The above findings confirm other research findings 
about the positive effect of certain bundles of workplace 
practices on an organisation’s performance. Previous 
research evidence has demonstrated that a management 
philosophy that includes employee involvement has 
strong, positive effects on company performance 
(Lawler, 1992; Huselid, 1995; Vandenberg et al, 1999). 
Employee involvement enables organisations to produce 
high-quality products or services, increase the speed 
of work operations and innovation. Workplaces that 
practise different employee involvement schemes (a 
central feature of the HIWS model) are outside the 
Taylorist model of production, whereby decision-making 
and problem-solving stays in the hands of management. 
They also go further to capitalise on employee 
knowledge of production or service delivery. As this 
study shows, these practices have the potential for win–
win outcomes in certain contexts and in an environment 
of trust and harmonious social dialogue, as discussed in 
the next section.

Mediating role of social dialogue
In exploring the role of participation at the workplace 
level, several researchers have distinguished between 
direct and representative participation. Sometimes 
the two forms are seen as mutually exclusive or 
competitive. However, a large body of research points 
to the complementarities and the mutually reinforcing 
nature of the two forms (Lucio and Stuart, 2002; Teague, 
2005; Kim et al, 2012; Lehr et al, 2015). Representative 
participation or social dialogue plays an important role in 
influencing how people engage with work and how they 
use and develop their skills and creativity. A Eurofound 
report using the ECS 2009 data indicates that social 
dialogue can be expressed formally through structures 
and procedures clearly identified at a strategic level 
as well as informally in daily tasks and when putting 
strategic decisions into operation (Eurofound, 2012).

Directive 2002/14/EC, which establishes a general 
framework for informing and consulting employees, 
provides for the rights and opportunities of employees 
to access work-related information. Social dialogue 
structures and practices enable both the individual 
and the collective voice at the workplace level.

and employee participation in decision-making, have a 
strong link with the likelihood of innovation.

Social dialogue as an indirect form of participation 
has been less researched in terms of its contribution 
to innovation. A recent study identified three pathways 
through which representative employee participation 
has a positive influence on innovation (Hermans and 
Ramioul, 2015). It may occur firstly through the effects 
of the increased expression of (individual) employee 
voice, which contributes to employee retention, secondly 
through (the requests for) provision of training and 
thirdly through the (creation of) support for effective 
and sustained adoption of innovation-increasing HRM 
practices such as HIWs.

Two of these pathways (namely, training and employee 
voice) can at least indirectly be confirmed by the analysis 
of the ECS data. First, it was found that consultation 
with employees and joint decision-taking have a positive 
effect on innovation. Hence, a trusting attitude of 
management towards employees’ capacity to play a 
role in the strategic objectives of the company seems 
important for the implementation of change. Second, the 
more general impact of employee voice as a pull-factor 
for innovation can partly be confirmed. While no specific 
instrument of employee voice guarantees innovative 
impact, the use of a well-balanced mix of tools such as 
regular meetings between employees and immediate 
managers, regular staff meetings open to all employees, 
suggestion schemes, employee surveys and online 
discussion boards were found to be positively associated 
with innovation. Later in this chapter, the mediating role 
of social dialogue is examined as part of its contribution 
to performance.

It is important to emphasise that both practitioners 
and researchers of innovation need to focus on the way 
employees generate, use and share (tacit) knowledge, 
the way they initiate changes in tasks, products, 
processes and procedures, and the way they are involved 
in and deal with innovations initiated by management in 
their daily work.

Performance and workplace  
well-being
This research has looked at the impact of work 
organisation, HRM and employee involvement on 
performance and well-being.

Among the establishments that introduced any change 
in product, process or marketing, both establishment 
performance and workplace well-being were found 
to be higher (above average) than in establishments 
that had not introduced changes. Managers who 
reported that their company had introduced any of 
the above changes in the three years preceding the 
survey (2010–2013) saw increased performance and 
also higher levels of workplace well-being. Additionally, 
most of these managers reported that they had strong 

62

Innovative changes in European companies: Evidence from the European Company Survey 6 – Workplace practices in fostering innovation

Interaction of practices
In line with the analysis above, individual social dialogue 
practices play a role in the constellation of organisation 
practices but their synergistic impact needs to be 
identified. As in previous sections, three configurations 
of practices were examined: HRM practices, work 
organisation and employee involvement practices. In 
establishments that have social dialogue structures 
in place, the strongest drivers of performance were 
innovative action, combined with extensive measures 
of direct employee involvement and HRM. This shows 
the complementarity of direct employee involvement 
with representative forms of participation, and indicates 
an encouraging workforce commitment achieved by 
HRM means. It can also be argued that social dialogue 
structures in a trusting environment that encourages 
the employee voice can strengthen or enhance 
employee participation. Effective partnership between 
management and employees can deal with change and 
find solutions to upskill employees and meet business 
challenges. As Totterdill et al (2013) have argued, social 
dialogue can act as a bridge for knowledge-sharing 
between different levels of the organisation.

The importance of the employee voice is that it 
is linked with greater employee involvement and 
commitment to the organisation, as argued above. 
This is demonstrated in reduced absence, staff 
turnover and conflict, and higher performance 
(Appelbaum and Batt, 1994; Huselid, 1995). Mutual 
gains can be achieved through information-sharing 
and higher levels of trust. Batt and Appelbaum 
(1995) also identified positive impacts of employee 
involvement on performance. The ECS overview 
report (Eurofound, 2015) states that, in terms of social 
dialogue, the extensive and trusting and the moderate 
and trusting types of establishments were more likely 
to be associated with higher levels of performance 
and workplace well-being14. In a follow-up study, 
Eurofound (2016a) found that the trusting types of 
establishments were more likely to report mutual 
benefits, even in times of economic hardship.

With research evidence showing the beneficial effects 
of employee voice and social dialogue, the statistical 
analysis presented here explored the links between social 
dialogue and performance. The results, as presented 
above, clearly show the positive influence of trusting 
social dialogue practices on both performance and 
workplace well-being. A central conclusion of this analysis 
is that high levels of mutual trust, in combination with 
strong instruments of direct employee participation, 
trigger the highest levels of performance and create a 
beneficial atmosphere for innovative action. Low levels 
of trust and a conflictual approach to social dialogue 
significantly reduce the possibilities of flourishing 
performance and workplace well-being.

14 

In the ECS 2013, four distinct types of establishments were identified, based on their social dialogue practices and the prevalence of industrial action. The 
‘extensive and trusting type’ of establishment was the most prevalent. Employee representatives are well resourced, well-informed, are involved in making 
decisions about work organisation and have influence on those decisions. Management and employee representation enjoy mutual trust, which is reflected in 
little industrial action. In the ‘moderate and trusting’ type, employee representatives are not as well-resourced and receive less information. Their perceived 
level of influence on key decisions is much lower and they feel less involved in organisational changes. A relatively high level of mutual trust is coupled with a 
low incidence of industrial action (Eurofound, 2015).

63

HRM practices and innovation

This  chapter  provided  an  analysis  of  the  statistics  and  a  discussion  of  the  findings.  It  began  with  an  analysis  of 
individual  practices  in  the  area  of  HRM  and  work  organisation  to  identify  their  association  with  innovation  in 
products, processes or marketing.

A number of HRM practices (including training, a highly skilled workforce, and variable pay) were found to be 
positively associated with change. Similarly, in the area of work organisation, it was found that collaboration and 
outsourcing, quality management and knowledge transfer, task rotation and employee autonomy in decision-
making had a positive association with change.

Different authors have argued strongly that a coherent set of workplace practices with a horizontal fit (applied 
across the organisation) are expected to have better performance results than others (Wood and de Menezes, 
2008; Appelbaum et al, 2000). Coherent practices in this context essentially refers to complementarity, synergies 
and the forming of an integrated system. The results of this analysis support this argument, particularly as 
complementarities and synergies have been found in workplace practices with a strong emphasis on employee 
involvement. HRM, work organisation and employee involvement bundles were analysed and their interplay with 
individual practices was examined.

The results of this analysis show that two configurations of practices were more likely to have a positive effect on 
innovation:

  work organisation and employee involvement;

  HRM and employee involvement.

Analysis also sought to explore performance and well-being outcomes. In the ECS sample examined here, 
establishments that opted for changes in their products, processes and/or marketing in the three years prior to 
the survey had also chosen to put in place HRM and work organisation practices that suited their business model. 
A common element in both these sets of practices was the inclusion of employee participation schemes to a great 
extent.

The analysis revealed strong relationships between HRM, work organisation and employee involvement bundles 
of practices on one side and performance and workplace well-being on the other. The effect of employee 
involvement is much stronger in terms of performance and well-being in companies that had introduced 
innovation than in those that had not. Additionally, a trusting relationship between management and employee 
representatives and a harmonious social dialogue climate in combination with direct employee involvement are 
linked with higher levels of performance and workforce well-being.

64

Innovative changes in European companies: Evidence from the European Company Survey7 Conclusions:  

The changing workplace

Introduction7  Conclusions:  

The changing workplace

Innovation can contribute to a company’s 
competitiveness and can improve overall living standards. 
Often, innovation is associated with breakthrough 
projects but other forms are equally beneficial to the 
organisation. This is the case in evolutionary change, 
whereby organisations build on a series of incremental 
changes. Innovation can be of different types: innovation 
in products, processes or marketing and organisational 
innovation. Evidence from the ECS 2013 shows that 
three out of five establishments in the EU introduced 
new or significantly changed products, processes or 
marketing methods between 2010 and 2013. However, 
the situation varies widely between Member States – at 
a time when the speed of innovation and technological 
development is changing the global industrial landscape. 
Large differences between countries regarding the 
incidence of different workplace practices remain and, as 
analysis shows, other national characteristics, legislation, 
innovation policies and incentives (beyond the scope of 
this research) may account for those differences.

While large companies (those with more than 250 
employees) were more likely to introduce any type of 
innovation, small companies (10–49 employees) and 
medium-sized companies (50–249 employees) tended 
to innovate more often than not in products and 
processes. A sectoral analysis reveals that organisations 
in the financial services sector reported organisational 
innovation more often than in any other sector. 
Among the different forms of innovation, firms in the 
commerce and hospitality sector, in industry and in the 
other services sector predominantly reported product 
innovation. It is often noted in empirical studies that 
some companies tend to combine product and process 
innovation. In this analysis, it was found that a large 
number of organisations in the industry sector did indeed 
introduce product (43%) as well as process innovation 
(41%). 

Participatory change
In the light of this analysis, it can be concluded that the 
implementation of work organisation practices, HRM 
practices and employee participation workplace practices 
do matter for a company’s likelihood of introducing 
innovations in products, processes and marketing.

This research set out to explore whether bundles of HRM, 
work organisation and employee participation practices 
are significantly associated with innovation introduced in 
establishments (in products, processes, marketing) and 
whether there are links with performance and workforce 
well-being. Having examined the practices individually 

66

and in bundles, it is concluded that companies were more 
likely to have introduced changes in the three areas above 
if they had in place either of the two configurations of 
practices with strong employee involvement schemes: 

combining work organisation measures with 
employee involvement schemes (work organisation–
employee involvement)

combining HRM with employee involvement schemes 
(HRM–employee involvement). 

In other words, company managers who sought new or 
significantly improved products, services, processes, 
or marketing methods are more likely to have done so 
by making interventions with HRM or work organisation 
measures in tandem with employee participation 
practices. Those combinations of practices are 
significantly associated with the innovation that took 
place in the three years prior to the ECS Survey (2010–
2013).

The configurations of practices that were found to be 
closely associated with innovation primarily included 
practices that enhanced employees’ abilities and 
motivation. Clearly, the HRM-employee involvement 
configuration favours practices that promote the ability 
and motivation of employees, with a particular emphasis 
on:

training for skills development

ensuring that people with the right skills are 
attracted to the company through a recruitment and 
development policy that addresses changes in skill 
needs, technological advances and demographic 
composition

  financial motivation to achieve desired results and 

steer employee behaviour towards the organisation’s 
objectives.

As organisations change (for instance, new lines of 
products are added or new business models are 
introduced), jobs must be redesigned to adapt to the new 
needs; this in turn changes the organisation’s skills needs. 
The ECS 2013 establishments that undertook innovation 
have used training to update employees’ skills; this can 
potentially result in (more) innovation.

Furthermore, motivation in the form of variable pay 
was more likely to be provided by those firms that had 
introduced innovation in the last three years. Variable 
pay is very strongly associated with innovation and plays 
an important role in the HRM–employee involvement 
configuration. As other research has suggested, the 

 
 
 
 
success of an individual HRM practice often depends 
on the way it is implemented. A characteristic feature 
of this configuration of practices is that the employee 
involvement practices sit well with the motivational 
practices introduced by the management.

Company practices within the work organisation–
employee involvement configuration gave opportunities 
to the employees to use their discretionary effort through 
participatory work practices. Organisations pursuing 
such a configuration of workplace practices more often 
than not encourage knowledge transfer and the sharing 
of good work practices among employees. Research and 
practice show that employees who engage in monitoring 
the quality of products and services on a continuous basis 
can consequently improve their knowledge of the process 
of production, delivery and customer satisfaction.

Moreover, organisations using the work organisation–
employee involvement configuration were likely to 
pursue collaboration efforts with other organisations or 
establishments for the development, production, delivery 
or marketing of goods and services. Collaboration with 
other organisations opens up possibilities for employees 
and management to access new information and 
knowledge as well as to appreciate new methods and 
to benefit from mutual learning, which can stimulate 
innovative activity. Similarly, outsourcing as part of 
a firm’s activities requires mutual commitment and 
resource specialisation. It is often associated with quality 
improvements as well as efficiency and effectiveness. 
Researchers have argued that, when managed properly, 
the outsourcing of activities can foster innovation as it 
allows access to cutting-edge technologies, specialised 
resources and learning opportunities for employees.

Providing employees with the opportunity to rotate 
tasks with other employees under certain conditions 
can improve productivity as employees can undertake a 
variety of tasks and thus meet production needs. At the 
same time, employees can benefit from learning new 
tasks and enhance their skills. Previous research (Greenan 
and Lorenz, 2009) has found that job rotation is related 
to innovation. This research also confirms that exercising 
autonomy in taking decisions and resolving problems 
with production and service can have a beneficial effect 
on employees and enhance their motivation.

Overall, companies that use the work organisation–
employee involvement configuration use practices that:

encourage collaboration with other companies or 
other institutions to expand their knowledge and 
increase efficiencies

improve the quality of their product or service and 
monitor new developments in their sector or other 
industries so that they can possibly adopt new ideas 
early

encourage their employees to rotate tasks so that 
they can learn through a variety of situations and 
share good work practices

 7 – Conclusions: The changing workplace 

  provide employee autonomy in decision-making.

The message of this analysis is that more inclusive or 
participatory organisational practices have stronger links 
with innovation in products, processes and marketing 
and innovation at the workplace level.

Performance and well-being: 
mutual gains
This research sought to investigate outcomes for 
the organisation as well as for workforce well-being. 
Companies that had introduced innovation (of any type – 
products, processes or marketing) had better outcomes 
in terms of performance and workplace well-being than 
companies that not introduced innovations. It is also 
important to stress that establishments were found to 
have better outcomes when they implemented a wide 
range (or strong structures) of work organisation, HRM 
and employee involvement practices compared to those 
that had only weak practices in place. However, strong 
HRM-structured establishments had the highest average 
performance and workplace well-being. This means that 
enhancing the skills and cultivating talent, motivating the 
workforce and providing opportunities for participation 
within the organisation could be linked with better 
outcomes for the organisation as well as workplace well-
being.

In companies with employee representation structures 
that are characterised by a trusting relationship between 
management and employee representatives there are 
high levels of both performance and well-being. This 
suggests that the mediating role played by employee 
representatives, for example through influencing 
decisions on HRM issues, can generate win–win 
outcomes. As the main elements of this configuration 
include training, skills and incentive pay practices, it can 
be inferred that the employee representative role may 
have had some influence on these HRM practices. More 
importantly, it should be stressed that these practices 
appear to have beneficially impacted on performance and 
workplace well-being.

While it is widely recognised that attitudes, work 
organisation methods and organisation structures 
need to adapt and embrace change in order for the 
organisation to survive, there is no single best response. 
Caution is recommended regarding the implementation 
of organisational change. HR policies need to take into 
consideration the potential negative effects of actions to 
implement organisational change on workplace well-
being.

67

 
 
 
Policy pointers
Against the backdrop of the EU policy objectives for 
smart and inclusive growth, and the need for increased 
competitiveness in a challenging global economic 
environment, this research identifies non-technological 
factors and identifies workplace practices associated with 
innovation – specifically, the introduction or significant 
renewal of products/services, processes or marketing 
strategies. It also looks at the factors linked with 
performance and well-being, at the establishment level.

Encourage Member States to adopt pro-innovation 
workplace practices: European initiatives and national 
programmes associated with innovation and the future of 
work (at national or regional level) should acknowledge 
the role of organisational practices and encourage 
Member States to:

  promote  new  work  organisation  and  HRM  practices 

combined with employee participation 

encourage  capacity-building  and  mutual 
about innovation-enhancing measures.

learning 

In particular, they should take into account work 
organisation and HRM practices that encourage employee 
involvement. Significant differences exist between 
countries in the level of innovation and the adoption of 
workplace practices linked to innovation, performance 
and workforce well-being. Hence, policymakers may wish 
to look closely at different country experiences.

Enable companies to tap into external ideas and 
research and collaborate with bodies to help them 
improve their products or services: Improving the 
quality of products or services is rightly emphasised 
in several national programmes. Equally, national or 
regional programmes should provide ample opportunities 
to companies, particularly small companies, to tap into 
external ideas, new research, collaboration with other 
firms and research institutes in order for them to improve 
their products or services. Relevant European networks 
can facilitate such an exchange.

Facilitate the contribution of local actors: As experience 
in some Nordic countries has shown, national programmes 
that promote workplace renewal and innovation, such 
as those in Finland and Norway, can bring the research 
community together with business, workers’ organisations 
and firms (Alasoini, 2009; Alasoini, 2015). Taking a bottom-
up approach (rather than best examples) and exploiting 
the needs of local or regional business actors and 
employees is a way to create value that benefits all these 
bodies in a targeted fashion.

Support beneficial synergies of innovation, business 
outcomes and well-being: National and regional 
programmes to support innovation should encourage 
the linking of work practices with innovation initiatives – 
given the positive impact of these practices on innovation, 
business outcomes and workforce well-being. Emphasis 
should be placed on bundles rather than individual 
practices, with employee participation as an essential 

68

element. Planning for the workplace of the future should 
also include workplace development programmes 
that support companies to assess and adopt new work 
practices that contain the essential elements presented 
in this research. As the association of certain bundles 
of workplace practices with innovation is quite strong, 
policymakers and practitioners should develop national or 
regional programmes with an emphasis on bundles rather 
than individual practices, with employee participation as 
an essential element.

Encourage pro-innovation HRM practices: Considering 
the strong effect of skills levels and training on innovation, 
national programmes should continue efforts to support 
employee development. In addition, the use of different 
forms of variable pay for employees, adjusted to their 
workplace, could also be discussed with social partners 
at sectoral level. Sectoral collective agreements could 
provide the framework for an equitable and fair way of 
implementation while company agreements could adjust 
to the local actors’ needs.

Facilitate a culture of innovation-readiness in start-
ups and SMEs: In an effort to revive the economy, many 
governments have introduced measures to support 
start-ups or small companies. Work practices that 
facilitate innovation can be instrumental for the future 
success of these companies. Governments and the 
business community could further assist small businesses 
to embrace pro-innovation workplace practices so as 
to further enhance their innovative potential. Small 
companies, often unaware of the benefits or impacts of 
these practices, may associate them with a higher cost 
– in the case of training, for example. Managers of small 
companies may be reluctant to adopt different work 
organisation or HRM practices as they may think that they 
are hard to introduce or time-consuming.

Raise awareness of benefits of pro-innovation 
workplace practices: Raising awareness of the economic 
and societal benefits of these workplace practices 
through public debates can support the economic and 
social impact of national and regional programmes, as 
experience in certain EU Member States has shown. The 
benefits of such practices go beyond the workplace: 
they enhance the development, capability and learning 
capacity of both the workforce and organisation and also 
the communities that establishments are part of. 

Review participation structures and practices at 
workplace level: ‘Participative change’ can produce 
mutual gains: it nurtures an environment of trust between 
management, employees and their representatives. 
Institutions such as social dialogue make employees 
aware of the need for adaptation, promote employee 
involvement in operations and engage the workforce 
in a debate about the future of the company. Mindful of 
social dialogue traditions in each country, governments 
and social partners may wish to review participation 
structures and practices at workplace level. Similarly, 
European-level social partners, at both cross-sector and 
sectoral level, may wish to address this issue as their role 

Innovative changes in European companies: Evidence from the European Company Survey 
requires a close relationship with national-level social 
partners.

Future research on innovation

Innovation as a process
A review of the relevant empirical research on 
innovation shows some gaps about the exact modes of 
implementation: how exactly innovation as a process 
is embedded in organisational structures and work 
practices, including the role and impact of employees in 
this process. The conditions for employee involvement in 
innovation mostly concern elements associated with high-
involvement work practices– HIWPs – (such as teamwork, 
autonomy, information provision and participation in 
decision-making) as well as the need for skilled and 
trained employees and corporate adaptability.

In order to explore how innovation processes are 
organised, it is important not only to focus on the 
‘technical’ aspect of the transformation process (how 
input is transformed into output) and the division of 
labour in this process, but also to include more explicitly 
the regulatory aspect or the control structure as all 
activities related to the transformation process have to 
be coordinated and regulated. Regulation or coordination 
happens at the operational, tactical and strategic level 
of the organisation and is therefore assigned to different 
hierarchical levels, including that of workers. If regulatory 
capacity is assigned at the lowest operational level as 
much as possible, it is easier for workers to solve problems 
and to deploy innovative behaviour as defined. In other 
words, ‘innovation’ can be regarded as a control activity 
(Lekkerkerk, 2016) and can take place at the strategic, 
tactical and operational level.

Operationalising an extended concept of 
innovation
The outlined approach considers innovation as 
intertwined with all activities and all levels in the 
organisation and also with the way these activities are 
regulated and controlled.

The current conceptual framework as outlined in the Oslo 
Manual is still relevant in surveying organisational change 
and innovation. However, it is necessary to not only 
investigate the conditions and impacts of innovation but 
also to include questions related to the control structure 
in future surveys.

In order to operationalise such an extended concept of 
innovation and to identify how innovation processes are 
embedded at all levels of the organisation, several issues 
need to be taken into account, as outlined below.

First, it is necessary to make a clear distinction between 
formal, top-down initiated innovations, innovations 
at the intermediate level and employee-led innovative 
behaviour.

Second, top-down innovations stem from strategic 
innovation decisions and are usually organised on a 

 7 – Conclusions: The changing workplace 

project-by-project basis which at some point implies 
formal steps, initiatives and/or approval by higher 
hierarchical layers. Top-down innovations usually imply 
a combination of different types of innovation (product/
process, process/organisation, product/marketing or 
other combinations) and are often taken-up by a dedicated 
project team that includes employees from other 
departments, other companies or institutions (such as 
universities, technology providers or consultancy firms). 
Questions could be designed to elicit more information on 
innovation structures at this strategic level.

Third, innovation at the intermediate level implies 
that individual workers or their teams are formally 
participating in (possibly temporary) project teams 
working on an issue such as a product development, 
changes in procedures, or the installation of equipment at 
the level of their department. Such forms of participation 
may be initiated by either workers/teams themselves 
and supported by management or might be initiated by 
different hierarchical levels.

Fourth, at the operational level, employee innovative 
behaviour refers to workers themselves effectively 
changing operational tasks, equipment, products, 
processes or procedures. This is possible if operational 
control is decentralised to the lowest level (such as is the 
case in high-performance work practices (HPWP).

Next, in order to map innovation processes and effective 
employee participation at these different levels, it is 
important to investigate at what stage, with what aim, 
at what intensity and with what organisational support 
employees are involved in innovation at these different 
levels (strategic, intermediate, operational).

Another question to be explored is how the innovation 
process at each of these levels is supported by 
management as well as the leadership role. For each 
of these forms of innovation, tools for employee 
participation can be identified, several of which are 
included in the ECS 2013 questionnaire. Examples include 
interdisciplinary groups, quality circles, suggestion boxes 
and similar procedures for collecting, managing and 
rewarding the ideas of employees and teams, and systems 
and tools for information sharing.

Further questions for reflection are: Who initiated the 
innovation? What was the problem that had to be solved 
(for example, market position, technical problem or lack 
of efficiency)? How are ideas transformed into concrete 
actions and how are these implemented? How are they 
diffused in the wider organisation? What was the effect 
of input from employees on the choices made by the 
management and on the actual innovation outcome and 
implementation?

Finally, indirect or representative participation in 
innovations refers to social dialogue channels at the 
establishment level. Questions about the functioning 
of these social dialogue channels in a survey could be 
complemented with questions about their involvement in 
innovation processes and projects.

69

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75

Annex 1: Methodology

Logistic regressions
Logistic regression assumes that the dependent variable is a stochastic event. Has change been implemented or not? 
Since it can only be either of these two states, logistic regression thinks in likelihoods of change being implemented 
or not. Multivariate regression provides an indication of the individual contribution of any single factor and possibly 
identifies dominant patterns. Typically, the method assumes that the variation of a specific item can be decomposed and 
attributed to a partial relationship with the predictor variable. The characteristics which are thought to contribute to the 
outcome must therefore be specified in a well-formulated model. For convenience, the analysis is restricted to innovation 
only and disregards possible interactions.

The logit, which is the underlying mathematical concept of a logistic regression, is the natural logarithm of an odds ratio. 
To illustrate this, consider a case in which the distribution of a dichotomous dependent variable (such as employed or 
unemployed) is paired with a dichotomous predictor variable (university degree/no university degree). One could, for 
instance, apply a test of independence (such as Chi2). Alternatively, it is also possible to assess the non-graduate’s odds 
of being unemployed. The result is an odds ratio, for example of 3.3415, suggesting that the risk of being unemployed is 
3.34 times higher for the non-graduate than for the person with a university degree. Logistic regression is a very popular 
approach to analyse the relationship of a dichotomous single dependent variable (such as reported change yes/no) which 
represents the occurrence or non-occurrence of an event and a number of independent variables.

‘Generally’ as Peng et al (2002) put it, ‘logistic regression is well suited for describing and testing hypotheses about 
relationships between a categorical outcome variable and one or more categorical or continuous predictor variables’. The 
outcome variable in this case is whether any kind of change in terms of marketing, organisation, products or processes 
took place within the three years preceding the survey. Logistic regressions produce odds ratios for all independent 
variables which are related in the case of categorical variables to the reference category. In the case of continuous 
variables, the odds ratio refers to an increase of one unit in the independent variable when all other predictors are 
constant. In more technical terms ‘odds ratio means the change in the odds of Y given a unit change in Xj’ (Peng et al, 
2002). For a more intuitive interpretation, marginal effects are computed. In the current context, marginal effects will 
show the effect of a unit change in a predictor on the likelihood of reporting innovation. For binary variables the change is 
from 0 to 1, while for continuous items it represents the instantaneous change.

Synthetic measures
Many of the measures used in this report, were originally developed for the overview report of the ECS 2013 (Eurofound, 
2015). In order to ensure the validity of synthetic measures – that is, that they measure what they are supposed to 
measure – a broad spectrum of validity dimensions was analysed. Variables that comprise indices were selected in such 
a way that they comprehensively covered the majority of the domain of concepts in question, thus assuring their content 
validity. They were also selected on the basis of their relevance to the theoretical definition of the concept and previous 
research (conceptual validity).

Workplace well-being
A continuous variable for workplace well-being was created.

1.  The frequency was counted at which the manager answered ‘Yes’ to the following question: Does the management 
encounter any of the following problems at this establishment currently? High level of sickness leave (KOSICK). 
Difficulties in retaining employees (KORETEN). Low motivation of employees (KOLOMOT). (Yes, No).

2.  This newly created variable was then standardised to range between 0 and 1. The same was done for the variables 

capturing the answers to the questions: ‘How would you rate the current general work climate in this establishment? 
Is it very good, good, neither good nor bad, bad, or very bad? (KCLIMATE)’ and ‘Since the beginning of 2010, the 
general work climate in this establishment… (Improved, Worsened, Remained about the same)? (KCLIMACH)’.

3.  The average of these three variables was taken and the resulting scores were transformed such that they ranged 

between 0 and 100, with 100 indicating extremely good workplace well-being and 0 indicating extremely poor well-
being.

15  The real odds ratio is derived from two odds (in this example, 95% of graduates are employed compared to 5% who are unemployed versus 75% of non-

graduates being employed and 25% unemployed => 95/5 : 85/15 = 3.34).

76

 Annex 1: Methodology

Establishment performance
A continuous variable for establishment performance was also created. It is based on four questions:

‘Since the beginning of 2010, has the amount of goods and services produced by this establishment ... (Increased, 
Decreased, Remained about the same)?(KGOSEPR)’16.

‘How would you rate the financial situation of this establishment? Is it very good, good, neither good nor bad, bad, or 
very bad? (KFINAN)’.

‘Since the beginning of 2010, has the financial situation of this establishment... (Improved, Worsened, Remained about 
the same)? (KFINANCH)’.

‘Since the beginning of 2010, has the labour productivity of this establishment... (Improved, Worsened, Remained 
about the same)? (KLABPRCH)’.

These variables were standardised, after which the average was calculated and again transformed to range between 0 
(indicating extremely poor establishment performance) and 100 (extremely good establishment performance).

Bundles of workplace practices
These are continuous variables ranging between 0 (minimal number of practices applied) and 10 (maximal number of 
practices). First, variables were constructed indicating whether or not a specific practice or a combination of practices was 
in place. The answers were then analysed and collated as described below

Work organisation bundle: (collaboration AND outsourcing in development AND/OR production AND/OR marketing) 
+ (Monitoring of internal quality production OR monitoring of external ideas) + (departments based on functions OR 
departments dealing with different types of products/services OR departments dealing with specific geographical areas) + 
(task autonomy AND autonomous teams) + teamwork in place.

Questions involved: GCOLDEDE; GCOLPROD; GCOLMARK; GOUTEDE; GOUTPROD; GOUTMARK; EMONQUA; EEXTEMON; 
DDEPFUN; DDEPTYP; DDEPGEO; EPLANN; FTEASIN; FTEAMEX.

HRM bundle: (on-the-job training OR paid time-off for training) + (flexibility in starting and ending times OR possibility to 
accumulate overtime) + (number of variable pay instruments in place).

Questions involved: HTRAIPC; HONJOBPC; HFLEXIPC; HACCUOV; HVBPRES; HVPINPER; HVPGRPE; HVPPRSH.

Direct employee involvement (EI) bundle: (degree of involvement of employees in the decision-making process) + 
(number of instruments of direct employee involvement in place).

Questions involved: JREGMEE; JSTAFFME; JADHOC; JDISSINF; JSOMEDI; JSUGGS; JSURVEY; E0eA-C.

Finally, the scores were transformed to range between 0 and 10.

Resource index
This is a continuous variable ranging between 0 (minimal resources for the employee representation, ER) and 100 (maximal 
resources for employee representation). First, a variable was constructed indicating whether or not the employee 
representative has sufficient time for their duties by combining the answers to the questions:

  Q11. Is there a designated number of hours per week of your working time that you are entitled to spend on your duties 
as an employee representative? (Yes; No, I am not entitled to use my working time; No, but I can use as much of my 
working time as is necessary; A full-time employee representative).

  Q13. Is the designated time usually sufficient for fulfilling your duties as an employee representative? (Yes, No).

The answers were combined so that those who answered ‘Yes’ to both Q11 and Q13, or who answered, ‘No, but I can use as 
much of my working time as is necessary’ or ‘A full-time employee representative’ were coded as Yes and the others as No.

Subsequently, it was counted how often employee representatives answered ‘Yes’ to this newly constructed variable and to 
Q14: ‘In the last 12 months have you received training related to your role as employee representative? (Yes, No)’; and Q15: 
‘Does the [ER-body] have access to funding for external advice? (Yes, No)’.

Finally, the scores were transformed to range between 0 and 100.

16  A small group of establishments was classified as providing public services based on the sampling frame, but was classified as carrying out market activities 
based on the answers of the manager to the question ‘What is the main activity of the establishment? (DMAINACT)’. Because of their initial classification they 
were asked ‘Since the beginning of 2010, has the amount of services provided by this organisation… (Increased, Decreased, Remained about the same)? 
(KSERPROV)’. These answers have been added to an updated version of KGOSEPR.

77

 
 
 
 
Information index
This is a continuous variable ranging between 0 (minimal information for employee representation) and 100 (maximal 
information for employee representation). The variable was constructed by counting how many times the employee 
representative answered ‘Yes’ to the following Yes/No questions:

  Q21. In the last 12 months, has management provided the [ER-body] with any information on the following issues: 

The financial situation of the establishment? (Q21_A); The employment situation of the establishment? (Q21_B); The 
introduction of new or significantly changed products or services in the establishment? (Q21_C); The introduction of 
new or significantly changed processes to produce goods or provide services in the establishment? (Q21_D); Strategic 
plans with regard to the establishment? (for example, business targets, plans for investments, plans to expand activities) 
(Q21_E).

  Q22. You mentioned that management provided information on the financial situation of the establishment. Did this 

include expectations for the future?

  Q23. You mentioned that management provided information on the employment situation of the establishment. Did this 

include expectations for the future?

  Q24. Thinking about all the information management has provided you with in the last 12 months, did you usually receive 

it in good time?

  Q25. And, in general, was the quality of the information satisfactory?

The scores were subsequently transformed to range between 0 and 100.

Employee representatives’ level of influence
A continuous variable was constructed, ranging between 0 (minimal influence) and 100 (maximal influence). The variable was 
constructed by taking the average score of the answers to two questions:

  Q38. Still thinking about the decision in the area of [sole or most important topic] in this establishment, would you say 

the [ER-body] had no influence, some influence or a strong influence on the management decision? (No influence, Some 
influence, Strong influence).

  Q40. You identified other areas in which the management of this establishment recently took major decisions. Would you 
say the [ER-body] had no influence, some influence or a strong influence on the management decisions in the following 
areas: The organisation of work processes? (Q40_A); Recruitment and dismissals? (Q40_B); Occupational health and 
safety? (Q40_C); Training and career development? (Q40_D); Working time arrangements? (Q40_E); Restructuring 
measures? (Q40_F).

The scores were subsequently transformed to range between 0 and 100.

Employee representatives’ trust in management
The variable is based on the answers to the following question: Question 42a-c:Do you agree or disagree with the following 
statements ...? (Strongly agree, agree, disagree, strongly disagree):

  The management can be trusted.

Management’s level of trust in the employee representation 
The variable is based on managers’ answers to the following question: Q15: ‘I will now read out a few statements describing 
views on employee representation at the establishment. Please tell me – based on your experiences with the employee 
representation at this establishment – whether you agree or disagree with them? (Strongly agree, Agree, Disagree, Strongly 
disagree)’:

  The employee representation can be trusted (IERTRUS; scores reversed).

Descriptive statistics
Table A.1.1 provides the main descriptive statistics of all items used for the measurement of establishment performance, 
workplace well-being and social dialogue. The performance index and workplace well-being indices are composed of 
the following indicators. Economic performance – the performance index – is composed of (a) on the assessment of the 
establishment’s current financial situation and (b) on the assessment of changes in its financial situation, labour productivity 
and production volume in the three years preceding the survey (Eurofound, 2015).

Two aspects interpreted as proxies of workplace well-being were contained in the ECS dataset, forming the workplace well-
being index:

  work climate;

(absence of) human resource problems.

78

Innovative changes in European companies: Evidence from the European Company Survey 
 Annex 1: Methodology

In particular, a high degree of sickness absence was considered to indicate physical or mental health issues among 
employees in the establishment. Similarly, reported difficulties in retaining employees were read as an indicator of 
challenging working conditions. Finally, the overview report (Eurofound, 2015) took managers’ perceptions of poor 
employee motivation and a poor or deteriorating work climate to represent negative aspects of the well-being of 
employees at work.

This information was condensed into two indices, which were subsequently transformed to range between 0 and 100. The 
measure of workplace well-being was constructed by ‘taking the average scores on the items on work climate, change 
in work climate, problems with employee retention, problems with poor employee motivation and problems with high 
sick leave’ (Eurofound 2015, p.30). The establishment performance index was constructed by taking the average of the 
standardised scores of the four items described above (work climate, employee retention, employee motivation and sick 
leave).

Items related to social dialogue mainly stem from the employee representative questionnaire and thus are based on fewer 
observations. Trust in the employee representative could only be asked in establishments that had formal employee 
representation in place.

Table A.1.1: Descriptive statistics

Dimension

Variable/index

Observations

Mean

Standard 
deviation

Min.

Max.

Performance

Performance index

Financial situation

Change in the financial situation

Change in production volume

Change in labour productivity

Workplace  
well-being

Well-being index

Work climate

Work 
organisation

Change in work climate

Low work motivation

High levels of sick leave

Collaboration/outsourcing

Monitoring processes

Department structure

Task rotation

Team/task autonomy

HRM practices

Perceived need to reduce staff

Training provided to employees

Flexi-time practices in place

Variable pay schemes in place

Human capital

Employee 
involvement

Number of instruments for employee 
involvement

Employee involvement in decision-
making

Social dialogue

Resource index

Information index

Influence index

Level of involvement of employee 
representatives

Occurrence of industrial action

Trust in management

24,471

24,471

24,471

24,471

24,471

24,471

24,471

24,471

24,471

24,471

24,471

24,471

24,471

24,471

24,471

24,471

24,471

24,471

24,471

24,471

24,455

24,471

6,918

6,905

6,905

6,905

6,878

6,919

Trust in employee representation

12,600

62.0

2.6

2.3

3.0

1.9

73.1

2.0

1.9

1.9

1.9

1.0

0.7

0.9

0.7

1.0

0.2

33.7

1.0

1.7

2.5

3.9

0.4

59.2

73.4

42.8

78.8

0.2

2.0

2.1

25.05169

1.398869

1.538434

9.665588

1.362328

18.24111

0.732924

0.987656

0.976197

0.616283

0.796

0.447

0.354

0.464

0.527

0.402

31.229

0.562

1.441

1.665

1.688

0.488

28.19834

30.12887

13.1373

39.34737

0.391659

0.718236

0.682841

0

1

1

1

1

0

1

1

1

1

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

100

9

9

99

9

100

9

9

9

9

2

1

1

1

2

1

100

2

5

7

7

1

100

100

100

99

1

3

3

79

Dimension

Variable/index

Observations

Mean

Workplace 
practices 
bundles

Interactions of 
bundles

HRM bundle

WO bundle

EI bundle

WO–EI

WO–HRM

EI–HRM

24,471

24,471

24,455

24,455

24,471

24,471

3.9

4.9

5.2

2.7

2.2

2.0

Standard 
deviation

Min.

Max.

1.962

2.192

2.276

1.893

1.636

1.533

0

0

0

0

0

0

10

10

10

10

10

10

Note: ‘WO’ = work organisation; ‘EI’ = employee involvement. 

Source: ECS 2013 – Management and Employee Representative Questionnaires

Model validation
The final model (4) was assessed on the basis of several goodness-of-fit measures. First, the likelihood ratio test (comparable 
to the F-test of an OLS regression) which examines the global explanation power of the predictors was carried out. Likelihood 
ratio tests, which involve estimating and comparing two different models, were applied. The log likelihoods of the two models 
are compared and differences are tested for statistical significance. Several models were tested against each other using 
different domain variables until the best model was fitted.

Second the Hosmer–Lemeshow Chi2 test was performed, dividing subjects into groups (10) on the basis of predicted probabilities 
(Lemeshow  and  Hosmer,  1982).  It  then  computes  Chi2  from  observed  and  expected  frequencies.  The  Hosmer–Lemeshow 
statistics show a value of 7.56 with a p-value of 0.48. Hence, the null-hypothesis that the model fits the data cannot be rejected.

Third, receiver operating characteristic (ROC) curves were produced to estimate the performance of the model and to assess 
the resulting probability maps. The ROC technique measures ‘the relationship between expected and real changes and 
calculates the percentage of false-positives and the true-positives for a range of thresholds, and relates them to each other in 
a chart’ (Pontius and Schneider, 2001). The area under the curve varies from 0.5 to 1. The closer the value is to 1 the better the 
probability assignment is. If the area is 0.5 (45 degrees) the model has no predictive power. Model 4 of this study has an area of 
0.79 as can be seen from Figure A.1.

Multicollinearity was checked by looking at correlation matrices and performing variance inflation factor (VIF) tables. In 
practice, multicollinearity is not relevant, unless identical information is represented in various variables (for example, ‘size of 
establishment’ and ‘number of employees’). Correlation coefficients of independent variables were computed and no problems 
were identified. A judgement can be made by checking related statistics, such as the tolerance values or VIF, Eigenvalue and 
condition number. The tolerance value is calculated as 1-R2k. VIF is just the reciprocal of a tolerance value, thus low tolerances 
correspond to high VIF. VIF shows how ‘inflated’ the variance of the coefficient is, compared with what it would be if the variable 
were uncorrelated with any other variable in the model (Allison, 1999, pp. 48–50). Multicollinearity is not seen as a problem 
when tolerance values are less than 0.1 or VIF smaller than 10 and the mean VIF of all independent variables should not 
considerably exceed 1, which would roughly indicate significant multicollinearity. In model 4, no variable had a value above 10 
and the overall mean VIF was 2.0.

Finally, several pseudo-R2 measures were compared, indicating the variance that can be explained by the model. As 
distinguished from OLS regressions, model estimates from logistic regressions are maximum likelihood estimates achieved 
through an iterative process. Thus, they are not computed to reduce variance. Several pseudo-R2 measures have been 
developed to compensate for this shortfall. However, they cannot be interpreted in the same way as R2 measures from OLS and 
different measures will show different results. The pseudo-R2s that are produced as standard output from Stata show values 
of 0.146 for model 1 (demographic information only), 0.191 for model 2 (demographic and single items), 0.181 for model 3 and 
0.192 for model 4 (single item + interaction terms)17. Consequently, up to 19.2% of data variation can be explained by the best 
model. This is obviously not a lot, but represents an average of results from large-scale data analyses where a lot of variation 
remains unobserved. For model 4, the McFaden-R2 shows a value of 0.192 and the McKelvey and Zavoina’s R2 a value of 0.316.

Reporting
Logistic regressions produce odds ratios for all independent variables which are related in the case of categorical variables to 
the reference category. In the case of continuous variables, the odds ratio refers to an increase of one unit in the independent 
variable when all other predictors hold constant or in more technical terms ‘odds ratio means the change in the odds of Y given 
a unit change in Xj’ (Peng et al, 2002). The odds ratios are directly derived from the regression coefficients and must meet three 
conditions before they can be interpreted sensibly: the independent variable Xj (i) must not interact with another predictor 
variable, (ii) must be represented by a single term in the model and (iii) a one unit change in the variable must be meaningful.

17 

 Applying ER weights and including corresponding variables of the dimension ’employee representation’ lead to a value of 0.17 but include only a very limited 
number of observations.

80

Innovative changes in European companies: Evidence from the European Company Survey Annex 1: Methodology

Table A.1.2: Odds ratios of establishment demographics for change in the establishment (model 1)

VARIABLES

Model 1

Model 2

Model 3

Model 4

Organisational change implemented (2010–2013)

0.290***

ESTABLISHMENT SIZE (Reference: 10–49 employees) 

50–249 employees

250+ employees

SECTORS (Reference: Industry) 

Construction

Commerce and hospitality

Transport

(0.00535)

0.0290***

(0.00725)

0.0655***

(0.00974)

-0.129***

(0.0115)

-0.000409

(0.00785)

-0.134***

(0.0120)

0.226***

(0.00559)

-0.00232

(0.00718)

0.0156

(0.00994)

-0.115***

(0.0112)

0.00853

(0.00763)

-0.0943***

(0.0117)

0.234***

(0.00558)

0.00574

(0.00718)

0.0264***

(0.00986)

-0.119***

(0.0112)

-0.00387

(0.00763)

-0.113***

(0.0117)

0.225***

(0.00558)

-0.00234

(0.00717)

0.0151

(0.00992)

-0.115***

(0.0112)

0.00949

(0.00762)

-0.0935***

(0.0117)

Financial services

-0.0687***

-0.0660***

-0.0893***

-0.0667***

Business, administration and other services

(0.0152)

-0.0483***

(0.00811)

ESTABLISHMENT TYPE (Reference: Headquarters/subsidiary sites) 

Single establishment

Number of hierarchical levels

WORK FORCE CHARACTERISTICS 

Share of female workers >20%

(0.0149)

-0.0430***

(0.00815)

-0.0250***

(0.00649)

-0.000768

(0.00146)

-0.0506***

(0.00663)

0.00566***

(0.00170)

0.0483***

(0.00787)

0.0358***

(0.00764)

(0.0149)

-0.0679***

(0.00809)

(0.0149)

-0.0433***

(0.00815)

-0.0269***

-0.0250***

(0.00651)

0.00107

(0.00149)

0.0343***

(0.00768)

(0.00648)

-0.000636

(0.00146)

0.0355***

(0.00763)

Share of workers aged 50+ >20%

-0.0322***

-0.0242***

-0.0233***

-0.0239***

(0.00696)

0.120***

(0.00687)

0.00950

(0.00730)

Number of employees increased (2010-2013)

Number of employees decreased (2010-2013)

WORK ORGANISATION PRACTICES 

Collaboration AND/OR outsourcing

Monitoring of production quality/external ideas

Structured in departments

Task/job rotation

Autonomous teams/task autonomy

HRM-RELATED ITEMS 

Training in place

Flexibility measures in place

Variable pay schemes in place

Skills (% of workers with university degree >20%)

0.0483***

(0.00675)

0.104***

(0.00669)

0.00874

(0.00720)

0.0535***

(0.00363)

0.0887***

(0.00628)

0.0842***

(0.00801)

0.0320***

(0.00598)

0.0164***

(0.00540)

0.000437***

(9.69e-05)

0.00125

(0.00522)

0.0197***

(0.00218)

0.0358***

(0.00680)

0.105***

(0.00674)

0.0115

(0.00708)

0.0343***

(0.00675)

0.103***

(0.00669)

0.0102

(0.00702)

0.0535***

(0.00451)

0.0894***

(0.00672)

0.0848***

(0.00830)

0.0321***

(0.00598)

0.0173**

(0.00836)

0.000459***

(0.000139)

0.00347

(0.00637)

0.0207***

(0.00467)

0.0355***

81

VARIABLES

Model 1

Model 2

Model 3

Model 4

(0.00787)

(0.00764)

(0.00768)

(0.00763)

EMPLOYEE INVOLVEMENT 

Number of instruments deployed for employee 
involvement

Direct employee participation in decision-making

Employee representation structure present in 
establishment (or company) = 1, Yes

BUNDLES OF WORKPLACE PRACTICES 

Bundle 1: Work organisation (WO)

Bundle 2: HRM

Bundle 3: Employee involvement (EI)

HRM–EI configuration

HRM–WO configuration

WO–EI configuration

Country (Reference: Belgium)

Bulgaria

Czech Republic

Denmark

Germany

Estonia

Ireland

Greece

Spain

France

Croatia

Italy

Cyprus

Latvia

Lithuania

82

0.0184***

(0.00198)

0.0658***

(0.00592)

0.00129

0.0219***

(0.00744)

0.00252

0.00176

(0.00679)

(0.00683)

(0.00677)

0.0240***

(0.00142)

0.0177***

(0.00166)

0.0279***

(0.00138)

0.0549**

(0.0227)

-0.114***

(0.0200)

0.0239

(0.0208)

-0.0225

(0.0179)

0.0235***

(0.00528)

-0.0276***

(0.00566)

0.0204***

(0.00419)

0.0448*

(0.0229)

-0.113***

(0.0200)

0.0406**

(0.0205)

-0.00925

(0.0177)

-0.0897***

-0.112***

(0.0242)

-0.0350

(0.0242)

0.0681***

(0.0194)

0.0177

(0.0178)

-0.00134

(0.0177)

0.00299

(0.0240)

0.0540***

(0.0173)

0.0939***

(0.0230)

-0.123***

(0.0243)

-0.0473*

(0.0242)

(0.0242)

-0.0389

(0.0241)

0.0365*

(0.0198)

0.0100

(0.0177)

-0.00112

(0.0175)

-0.0369

(0.0243)

0.0442**

(0.0172)

0.0678***

(0.0235)

-0.154***

(0.0243)

-0.0534**

(0.0245)

0.0696***

(0.0238)

0.0441*

(0.0230)

-0.0864***

-0.114***

(0.0206)

0.0852***

(0.0212)

0.0126

(0.0185)

-0.00649

(0.0246)

-0.00404

(0.0251)

0.0664***

(0.0204)

0.0284

(0.0187)

-0.0121

(0.0187)

-0.0138

(0.0254)

0.0368**

(0.0184)

0.115***

(0.0240)

-0.0826***

(0.0253)

-0.00877

(0.0250)

(0.0200)

0.0432**

(0.0205)

-0.00866

(0.0177)

-0.111***

(0.0242)

-0.0387

(0.0241)

0.0362*

(0.0198)

0.00956

(0.0177)

-0.000792

(0.0176)

-0.0369

(0.0244)

0.0449***

(0.0172)

0.0675***

(0.0236)

-0.153***

(0.0244)

-0.0513**

(0.0245)

Innovative changes in European companies: Evidence from the European Company Survey Annex 1: Methodology

VARIABLES

Model 1

Model 2

Model 3

Model 4

0.117***

(0.0233)

0.0799***

(0.0225)

0.0991***

(0.0222)

0.0808***

(0.0224)

-0.0745***

-0.0768***

-0.0604***

-0.0796***

Luxembourg

Hungary

Malta

Netherlands

Austria

Poland

Portugal

Romania

Slovenia

Slovakia

Finland

Sweden

United Kingdom

Female sex of respondent

Role of respondent (Reference: Manager)

Owner/proprietor

HR manager / Personnel manager

Other

No answer

Observations

(0.0204)

0.0836***

(0.0296)

0.0109

(0.0203)

0.0296

(0.0210)

0.00952

(0.0189)

0.107***

(0.0196)

0.0977***

(0.0233)

0.0251

(0.0248)

-0.0209

(0.0245)

-0.00798

(0.0211)

-0.0492**

(0.0209)

-0.00895

(0.0187)

0.0264***

(0.00635)

-0.00546

(0.0108)

-0.0279***

(0.00796)

-0.0474***

(0.00908)

-0.0683

(0.0528)

24,471

(0.0195)

0.0616**

(0.0283)

-0.0342*

(0.0193)

-0.0310

(0.0203)

-0.00280

(0.0181)

0.102***

(0.0185)

0.0757***

(0.0221)

-0.0594**

(0.0244)

-0.0586**

(0.0236)

-0.135***

(0.0208)

-0.131***

(0.0200)

-0.0279

(0.0181)

0.00851

(0.00618)

0.00867

(0.0104)

-0.0262***

(0.00771)

-0.0342***

(0.00878)

-0.0414

(0.0519)

24,455

(0.0195)

0.0745***

(0.0282)

-0.0277

(0.0194)

-0.0438**

(0.0206)

-0.00401

(0.0181)

0.106***

(0.0186)

0.0874***

(0.0221)

-0.0509**

(0.0245)

-0.0546**

(0.0237)

-0.134***

(0.0209)

-0.144***

(0.0201)

-0.0218

(0.0181)

0.0163***

(0.00620)

0.00677

(0.0105)

-0.0265***

(0.00776)

-0.0361***

(0.00884)

-0.0369

(0.0522)

24,455

(0.0194)

0.0581**

(0.0283)

-0.0338*

(0.0193)

-0.0317

(0.0203)

-0.00297

(0.0180)

0.100***

(0.0185)

0.0743***

(0.0221)

-0.0596**

(0.0243)

-0.0605**

(0.0237)

-0.137***

(0.0209)

-0.133***

(0.0200)

-0.0283

(0.0180)

0.00878

(0.00617)

0.00821

(0.0104)

-0.0262***

(0.00771)

-0.0342***

(0.00877)

-0.0404

(0.0516)

24,455

Notes: Standard errors in parentheses; *** p < 0.01, ** p < 0.05, * p < 0.1; Pseudo-R2 = 0.146.

Source: ECS 2013 – Management questionnaire

In the course of this report, the results of various models with changing dependent and independent variables were 
presented. Hence, the question of comparability of regression coefficients came up. Mood (2010) prominently stated that 
logistic regression estimates are affected by omitted variables (unobserved heterogeneity) ‘even when these variables 
are unrelated to the independent variables in the model’. The implication of this is that odds ratios cannot be interpreted 
straightforwardly as effect measures and cannot be compared ‘for similar models across groups, samples, or time points, 
or across models with different independent variable in a sample’ (Mood, 2002, p. 67). Mood herself but also others 
(Auspurg and Hinz, 2011) suggested the use of average marginal effects for group comparisons instead of odds ratios. In 
these analyses, the proposal to report average marginal effects when it comes to comparisons of different models was 
followed.

83

Annex 2: Regression tables

Table A.2.1: Marginal effects and robust standard errors of models 1–4

Variables

Model 1

Model 2

Model 3

Model 4

Organisational change implemented (2010–2013)

Establishment size (number of employees) (Reference: 10–49) 

50–249

250+

Sector (Reference: Industry)

Construction

Commerce and hospitality

Transport

Financial services

Business, administration and other services

0.290***

(0.00535)

0.0290***

(0.00745)

0.0655***

(0.0102)

-0.129***

(0.0115)

-0.000409

(0.00782)

-0.134***

(0.0119)

0.226***

(0.00558)

-0.00232

(0.00718)

0.0156

(0.00995)

-0.115***

(0.0112)

0.00853

(0.00760)

-0.0943***

(0.0117)

0.234***

(0.00559)

0.00574

(0.00720)

0.0264***

(0.00991)

-0.119***

(0.0112)

-0.00387

(0.00758)

-0.113***

(0.0116)

0.225***

(0.00557)

-0.00242

(0.00718)

0.0150

(0.00995)

-0.114***

(0.0112)

0.00945

(0.00758)

-0.0935***

(0.0117)

-0.0687***

-0.0660***

-0.0893***

-0.0668***

(0.0153)

-0.0483***

(0.00820)

(0.0148)

-0.0430***

(0.00820)

(0.0148)

(0.0149)

-0.0679***

-0.0433***

(0.00815)

(0.00820)

Establishment type (Reference: Headquarters/subsidiary sites) 

Single establishment

-0.0506***

-0.0250***

-0.0269***

-0.0249***

Number of hierarchical levels

Workforce characteristics

Proportion of female workers >20%

(0.00668)

0.00566**

(0.00255)

0.0483***

(0.00788)

(0.00651)

-0.000768

(0.00144)

0.0358***

(0.00771)

(0.00653)

0.00107

(0.00167)

(0.00651)

-0.000648

(0.00143)

0.0343***

(0.00772)

0.0355***

(0.00770)

Proportion of workers aged 50+ >20%

-0.0322***

-0.0242***

-0.0233***

-0.0238***

Number of employees increased (2010–2013)

Number of employees decreased (2010–2013)

Work organisation practices

Collaboration and/or outsourcing

Monitoring of production quality/external ideas

Structured in departments

Task/job rotation

84

(0.00698)

0.120***

(0.00686)

0.00950

(0.00731)

(0.00677)

0.104***

(0.00669)

0.00874

(0.00722)

0.0535***

(0.00363)

0.0887***

(0.00627)

0.0842***

(0.00794)

0.0320***

(0.00681)

0.105***

(0.00675)

0.0115

(0.00677)

0.103***

(0.00670)

0.0102

(0.00707)

(0.00703)

0.0535***

(0.00456)

0.0894***

(0.00671)

0.0848***

(0.00821)

0.0320***

 
 
 
 
 
 
 
 
 
 
 
 
Variables

Model 1

Model 2

Model 3

Model 4

 Annex 2: Regression tables

Autonomous teams/task autonomy

HRM-related items

Training in place

Flexibility measures in place

Variable pay schemes in place

Skills (% of workers with university degree >20%)

Employee involvement

Number of instruments deployed for employee involvement

Direct employee participation in decision-making

Employee representation structure present in establishment 
(or company) 

Bundles of workplace practices

Bundle 1: Work organisation (WO)

Bundle 2: HRM

Bundle 3: Employee involvement (EI)

HRM–EI configuration

HRM–WO configuration

WO–EI configuration

Country (Reference: Ireland)

Belgium

Bulgaria

(0.00599)

0.0164***

(0.00544)

0.000437***

(9.75e-05)

0.00125

(0.00528)

0.0197***

(0.00218)

0.0168**

(0.00724)

0.0184***

(0.00198)

0.0658***

(0.00596)

0.00129

(0.00676)

0.0158**

(0.00726)

0.0240***

(0.00145)

0.0177***

(0.00166)

0.0279***

(0.00139)

0.00404

(0.0251)

0.0736***

(0.0271)

0.0387

(0.0241)

0.0827***

(0.0259)

0.0350

(0.0242)

0.0899***

(0.0258)

(0.00599)

0.0175**

(0.00838)

0.000459***

(0.000139)

0.00348

(0.00644)

0.0207***

(0.00469)

0.0168**

(0.00724)

0.000859

(0.00359)

0.0232**

(0.00935)

0.00239

(0.00677)

0.0228***

(0.00622)

-0.0270***

(0.00634)

0.0197***

(0.00514)

0.0390

(0.0241)

0.0837***

(0.0258)

Czech Republic

-0.0824***

-0.0751***

-0.0793***

-0.0744***

Denmark

Germany

Estonia

Greece

(0.0251)

(0.0243)

0.0892***

0.0819***

(0.0258)

0.0167

(0.0235)

-0.00245

(0.0280)

0.0704***

(0.0243)

0.0589**

(0.0254)

0.0126

(0.0228)

(0.0243)

0.0796***

(0.0253)

0.0296

(0.0227)

(0.0253)

0.0300

(0.0228)

-0.0723***

-0.0547**

-0.0734***

(0.0275)

0.0749***

(0.0276)

0.103***

(0.0275)

0.0755***

85

 
 
 
 
 
 
 
 
Variables

Model 1

Model 2

Model 3

Model 4

Spain

France

Croatia

Italy

Cyprus

Latvia

Lithuania

Luxembourg

Hungary

Malta

Netherlands

Austria

Poland

Portugal

Romania

Slovenia

Slovakia

Finland

Sweden

United Kingdom

Male gender of respondent

LPOSIT [R2] What position do you hold? = 2,  
Owner/proprietor

(0.0247)

0.0324

(0.0235)

-0.00802

(0.0236)

-0.00978

(0.0292)

0.0408*

(0.0235)

0.119***

(0.0280)

(0.0238)

0.0482**

(0.0227)

0.0379*

(0.0227)

0.00180

(0.0281)

(0.0235)

0.0527**

(0.0228)

0.0337

(0.0227)

0.0380

(0.0281)

(0.0237)

0.0491**

(0.0226)

0.0379*

(0.0227)

0.00218

(0.0279)

0.0835***

0.0891***

0.0834***

(0.0226)

0.106***

(0.0274)

(0.0225)

0.129***

(0.0271)

(0.0225)

0.107***

(0.0274)

-0.0786***

-0.114***

-0.0881***

-0.115***

(0.0288)

-0.00473

(0.0283)

0.121***

(0.0274)

-0.0705***

(0.0249)

0.0876***

(0.0324)

0.0150

(0.0252)

0.0337

(0.0254)

0.0136

(0.0238)

0.111***

(0.0242)

0.102***

(0.0276)

0.0291

(0.0289)

-0.0168

(0.0288)

-0.00394

(0.0257)

-0.0452*

(0.0257)

-0.00492

(0.0235)

0.0264***

(0.00638)

-0.00546

(0.0108)

(0.0279)

-0.0126

(0.0282)

0.119***

(0.0267)

-0.0381

(0.0239)

0.100***

(0.0315)

0.00447

(0.0243)

0.00763

(0.0248)

0.0359

(0.0229)

0.141***

(0.0231)

0.114***

(0.0265)

-0.0208

(0.0284)

-0.0199

(0.0279)

(0.0279)

-0.0123

(0.0274)

0.134***

(0.0264)

-0.0254

(0.0239)

0.110***

(0.0316)

0.00733

(0.0243)

-0.00872

(0.0249)

0.0310

(0.0228)

0.141***

(0.0231)

0.122***

(0.0263)

-0.0159

(0.0288)

-0.0195

(0.0278)

(0.0279)

-0.0142

(0.0281)

0.120***

(0.0266)

-0.0406*

(0.0238)

0.0971***

(0.0315)

0.00517

(0.0243)

0.00724

(0.0248)

0.0361

(0.0228)

0.139***

(0.0230)

0.113***

(0.0265)

-0.0206

(0.0285)

-0.0216

(0.0280)

-0.0965***

-0.0994***

-0.0983***

(0.0253)

-0.0919***

(0.0246)

0.0108

(0.0226)

0.00851

(0.0254)

-0.109***

(0.0247)

0.0132

(0.0227)

0.0163***

(0.0254)

-0.0944***

(0.0247)

0.0107

(0.0225)

0.00879

(0.00620)

(0.00624)

(0.00619)

0.00867

(0.0104)

-0.0262***

(0.00772)

0.00677

(0.0104)

0.00828

(0.0104)

-0.0265***

-0.0262***

(0.00778)

(0.00772)

LPOSIT [R2] Human resource manager / Personnel manager

-0.0279***

(0.00800)

86

Innovative changes in European companies: Evidence from the European Company Survey Annex 2: Regression tables

Variables

Model 1

Model 2

Model 3

Model 4

LPOSIT [R2] What position do you hold? = 4, Other

LPOSIT [R2] What position do you hold? = 9, [No answer]

-0.0474***

(0.00912)

-0.0683

(0.0515)

-0.0342***

(0.00882)

-0.0414

(0.0487)

-0.0361***

-0.0342***

(0.00891)

(0.00882)

-0.0369

(0.0496)

-0.0404

(0.0484)

Observations

24,471

24,455

24,455

24,455

Notes: Standard errors in parentheses; *** p < 0.01, ** p < 0.05, * p < 0.1.

87

Table A.2.2: Regression coefficients and standard errors of models 5–6

Variables

Model 5

Model 6

Organisational change implemented  
(2010–2013)

Performance

Well-being

Performance

Well-being

2.095***

-0.775***

1.734***

-0.779*

(0.306)

(0.243)

(0.571)

(0.467)

Establishment size (number of employees) (Reference: 10–49) 

50–249

250+

Sectors (Reference: Industry)

Construction

Commerce and hospitality

Transport

Financial services

Business, administration and other services

Establishment type (Reference: headquarters/subsidiary sites)

Single establishment

Number of hierarchical levels

Workforce characteristics

Proportion of female workers >20%

Proportion of workers aged 50+ >20%

Number of employees increased (2010–2013)

Number of employees decreased (2010–2013)

Work organisation structure (Reference: Weak structure) 

Moderate

Strong

HRM structure (Reference: Weak structure)

Moderate

Strong

Direct employee involvement structure (Reference: Weak structure)

Moderate

Strong

88

1.039***

(0.350)

1.513***

(0.469)

-5.931***

(0.549)

-1.998***

(0.388)

-1.694***

(0.575)

1.404**

(0.713)

-2.379***

(0.399)

0.115

(0.320)

0.0978

(0.0748)

1.352***

(0.381)

-1.686***

(0.337)

11.07***

(0.336)

-13.41***

(0.346)

1.472***

(0.323)

2.270***

(0.554)

2.661***

(0.347)

5.021***

(0.561)

1.401***

(0.387)

3.649***

(0.390)

-2.832***

(0.278)

-4.387***

(0.372)

-0.977**

(0.436)

0.854***

(0.308)

-0.492

(0.457)

2.198***

(0.566)

0.513

(0.317)

0.213

(0.254)

-0.254***

(0.0594)

0.643**

(0.303)

-1.462***

(0.267)

3.398***

(0.267)

-7.080***

(0.275)

0.616**

(0.257)

1.679***

(0.440)

0.707**

(0.276)

3.338***

(0.445)

0.793***

(0.307)

2.940***

(0.310)

0.608

(0.705)

1.525*

(0.854)

-4.328***

(1.108)

-2.192***

(0.815)

-1.692

(1.057)

2.898**

(1.183)

-2.256***

(0.735)

0.262

(0.575)

0.228*

(0.120)

1.814***

(0.701)

-0.294

(0.631)

9.655***

(0.660)

-11.92***

(0.633)

0.494

(0.669)

1.952*

(1.004)

2.373***

(0.742)

5.725***

(1.037)

1.637*

(0.844)

4.742***

(0.833)

-2.553***

(0.577)

-3.449***

(0.699)

-0.654

(0.907)

-0.0545

(0.667)

-0.0936

(0.865)

3.182***

(0.968)

0.00426

(0.601)

-0.329

(0.471)

-0.216**

(0.0979)

0.559

(0.574)

-0.183

(0.517)

2.345***

(0.540)

-7.423***

(0.518)

0.0874

(0.547)

1.409*

(0.821)

1.170*

(0.607)

3.373***

(0.849)

1.336*

(0.691)

4.207***

(0.681)

Innovative changes in European companies: Evidence from the European Company Survey 
 
 
 
 
 
 
 
 
 
 
 
 Annex 2: Regression tables

Variables

Model 5

Model 6

Performance

Well-being

Performance

Well-being

Social dialogue

Resource index (0–100)

Information index (0–100)

Influence index (0–100)

Industrial action occurred

High trust in employee representation (Reference: low 
trust)

High trust in management (Reference: low trust)

Employee representation involvement (Reference: Not informed) 

Informed

Consulted

Involved in joint decision-making

Country dummies (Reference: Belgium)

Bulgaria

Czech Republic

Denmark

Germany

Estonia

Ireland

Greece

Spain

France

Croatia

Italy

Cyprus

Latvia

Lithuania

-0.0105

(0.0106)

0.0122

(0.0102)

0.0204

(0.0127)

-1.660**

(0.754)

3.218***

(0.986)

1.587*

(0.957)

0.488

(1.139)

-2.049*

(1.211)

-1.920*

(1.125)

5.074**

(2.560)

5.868***

(2.079)

8.750***

(1.593)

3.374*

(1.834)

11.21***

(2.320)

3.753

(2.640)

-2.993

(2.353)

-8.679***

(1.582)

0.818

(1.615)

4.800**

(2.191)

-4.378**

(1.744)

-4.702**

(2.293)

6.630**

(3.118)

8.877***

0.00158

(0.00868)

0.0155*

(0.00831)

0.0283***

(0.0104)

-2.941***

(0.617)

7.676***

(0.807)

4.582***

(0.783)

1.436

(0.932)

-0.168

(0.991)

0.226

(0.921)

7.643***

(2.095)

0.973

(1.701)

9.275***

(1.304)

-4.493***

(1.501)

0.0194

(1.898)

2.322

(2.161)

7.719***

(1.925)

2.223*

(1.294)

1.233

(1.321)

0.170

(1.793)

-2.931**

(1.427)

10.32***

(1.877)

0.841

(2.552)

-0.280

89

0.431

(1.193)

5.156***

(0.987)

8.887***

(0.992)

6.419***

(0.898)

10.42***

(1.193)

5.444***

(1.200)

-3.273***

(0.989)

-9.767***

(0.892)

1.161

(0.892)

0.553

(1.231)

-8.922***

(0.885)

-6.025***

(1.235)

6.301***

(1.198)

4.837***

3.961***

(1.492)

3.371***

(1.135)

10.71***

(1.423)

-0.516

(1.085)

0.513

(1.409)

2.805*

(1.500)

2.004

(1.300)

-0.0609

(1.121)

-0.291

(1.090)

2.373*

(1.430)

-4.551***

(1.106)

5.162***

(1.644)

-0.722

(1.390)

-2.698*

 
 
 
 
 
 
 
 
Variables

Model 5

Model 6

Performance

Well-being

Performance

Well-being

(1.197)

6.835***

(1.184)

-2.004**

(0.972)

4.526***

(1.463)

2.209**

(0.969)

7.438***

(0.986)

6.067***

(0.906)

-5.280***

(0.971)

7.400***

(1.191)

-2.198*

(1.196)

4.464***

(1.196)

3.136***

(1.009)

5.477***

(0.984)

9.341***

(0.899)

1.936***

(0.308)

-3.336***

(0.543)

-0.212

(0.389)

-0.504

(0.446)

-2.186

(2.599)

51.55***

(1.127)

24,471

0.272

(1.451)

0.728

(1.603)

-4.381***

(1.125)

0.388

(1.986)

4.420***

(1.214)

3.298**

(1.313)

-1.108

(1.113)

-1.452

(1.280)

6.397***

(1.547)

-4.041***

(1.508)

1.886

(1.362)

4.000***

(1.310)

8.847***

(1.256)

7.455***

(1.105)

-0.219

(0.391)

-0.310

(0.659)

-0.702

(0.494)

-0.980*

(0.545)

4.304

(2.821)

71.64***

(1.385)

9,329

0.140

(2.221)

6.930***

(1.966)

-3.203*

(1.840)

4.523

(3.579)

1.661

(1.644)

7.098***

(1.748)

10.16***

(1.566)

-5.140**

(2.481)

9.012***

(1.933)

-0.829

(1.911)

6.275***

(2.162)

3.615**

(1.579)

(1.818)

0.466

(1.609)

-8.886***

(1.506)

1.837

(2.929)

1.068

(1.345)

1.456

(1.431)

2.149*

(1.282)

-2.075

(2.031)

6.814***

(1.582)

-3.669**

(1.564)

-0.263

(1.770)

3.101**

(1.292)

4.904***

7.366***

(1.563)

1.457

(2.189)

2.562***

(0.571)

-1.397

(1.481)

-0.733

(0.747)

-1.364

(0.890)

5.474

(6.808)

48.05***

(2.370)

6,863

0.246

(1.279)

2.117

(1.791)

1.175**

(0.467)

0.850

(1.212)

-1.321**

(0.612)

-1.844**

(0.729)

-2.337

(5.572)

57.86***

(1.940)

6,863

0.183

Luxembourg

Hungary

Malta

Netherlands

Austria

Poland

Portugal

Romania

Slovenia

Slovakia

Finland

Sweden

United Kingdom

Other

Male respondent

LPOSIT. [R2] What position do you hold? = 2, Owner/
proprietor

LPOSIT. [R2] What position do you hold? = 3, Human 
resource manager/Personnel manager

LPOSIT. [R2] What position do you hold? = 4, Other

LPOSIT. [R2] What position do you hold? = 9, [No 
answer]

Constant

Observations

R-squared

Notes: Standard errors in parentheses; *** p < 0.01, ** p < 0.05, * p < 0.1.

90

Innovative changes in European companies: Evidence from the European Company Survey 
 
 
 
Annex 3: Correlations between 
performance and well-being

What can be seen from Table A.3.1 is that there are strong correlations between performance and well-being suggesting 
solid links of internal and external outcomes (0.41). As a consequence it can be expected that factors explaining one of 
the variables will also be valid predictors for the other. It can actually be seen from the analysis that correlations between 
performance and many of the variables included are comparable to the correlations of well-being and these variables. 
There are however also notable differences.

Correlations of workplace practice bundles are moderate but strongest between well-being/performance and direct 
employee involvement, while higher correlations are observed between the HRM bundle and performance (0.167) than 
between HRM and well-being (0.089).

Among the items covering social dialogue, the highest (negative) but still very moderate correlations are observed 
between the occurrence of industrial action and both well-being (-0.124) and performance (-0.112). This is an indication 
that a conflictual organisational climate has negative impacts on the overall outcome of the establishment, a result which 
is also in line with former research.

Table A.3.1: Correlations between key variables

l
a
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s
u
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n

i

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o
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r
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o
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a

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o
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e
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b
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E

1  

0.405

0.1669

0.1154

0.1767

1

0.0885

0.1092

0.1679

1

0.2624

1

0.3088

0.2943

1

-0.1126

-0.124

n.s.

n.s.

n.s.

1

n.s.

n.s.

0.0453

0.0492

0.0825

-0.0389

1

Performance

Well-being

HRM bundle

WO bundle

EI bundle

Occurrence of 
industrial action

Resource index

Information index

0.0867

0.0843

0.1265

0.1139

0.1382

-0.0607

0.1791

1

Influence index

0.0518

0.0741

n.s.

n.s.

0.0339

-0.0472

0.1706

0.2498

1

Notes: All correlations shown are significant at the 0.01 level.

Source: ECS 2013, unweighted data

91

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
EF/17/07

Innovation is an important driver of improved 
competitiveness, productivity and growth 
potential. This report explores which workplace 
practices have the strongest links to innovative 
company behaviour, looking at innovation in the 
form of new or significantly changed products or 
processes, new or improved marketing methods, 
and organisational change. It also explores links 
between innovation and company performance 
and workplace well-being, and examines the role 
of social dialogue in enhancing performance, 
well-being and innovation. The use of monitoring 
instruments for internal quality and external 
developments turned out to be among the 
strongest determinants of overall innovation; 
the degree of workers’ autonomy was another 
important factor. The probability of innovation 
is boosted when strong work organisation 
structures are combined with direct employee 
participation – for instance, involvement in 
solving problems or improving the quality of 
production.

T
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ISBN 978-92-897-1578-2