Workplace learning : determinants and consequences : insights from the 2019 European company survey.
Date: 2022-01-14
Institutions: Cedefop
Subjects: European company, adult education, digitisation, in-service training, knowledge management, labour market, learning, professional qualifications, sample survey, vocational training, wage earner, workplace

Working paper series
No 7 / December 2021

WORKPLACE LEARNING: 
DETERMINANTS AND 
CONSEQUENCES
Insights from the 2019 
European company survey

Miloš Kankaraš
expert

WORKPLACE LEARNING: 
DETERMINANTS AND 
CONSEQUENCES
Insights from the 2019 
European company survey

Workplace learning is a critical tool for both employees and organ-
isations  in  their  continuing  adjustment  to  several  global  trends 
reshaping our workplaces, economies, and societies. This study 
uses the newly published data from the fourth round of the Euro-
pean  company  survey  (ECS  2019)  to  examine  key  drivers  and 
consequences of workplace learning. It shows that EU companies 
have several distinct workplace learning environments that differ 
greatly in their conduciveness to workplace learning. Findings also 
show that managers’ perceptions of the value of workplace learn-
ing and the level of skill demand are some of the key determinants 
of the scope of learning opportunities. Workplace learning is found 
to be the most important predictor of employee wellbeing and one 
of the strongest correlates of company performance. Results also 
show that most EU companies are still not offering optimal learn-
ing  environments  and  opportunities  to  their  workers,  a  situation 
that hurts both employees and companies.

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Europe 123, Thessaloniki (Pylea), GREECE
Postal: Cedefop service post, 570 01 Thermi, GREECE
Tel. +30 2310490111, Fax +30 2310490020
Email: info@cedefop.europa.eu

www.cedefop.europa.eu

ISBN 978-92-896-3284-3

 
 
 
 
 
 
The European Centre for the Development of Vocational Training (Cedefop) 
is the European Union’s reference centre for vocational education and training, 
skills and qualifications. We provide information, research, analyses and 
evidence on vocational education and training, skills and qualifications for policy-
making in the EU Member States. 
Cedefop was originally established in 1975 by Council Regulation (EEC) No 
337/75. This decision was repealed in 2019 by Regulation (EU) 2019/128 
establishing Cedefop as a Union Agency with a renewed mandate. 

Europe 123, Thessaloniki (Pylea), GREECE 
Postal: Cedefop service post, 570 01 Thermi, GREECE 
Tel. +30 2310490111, Fax +30 2310490020 
Email: info@cedefop.europa.eu 
www.cedefop.europa.eu 

Jürgen Siebel, Executive Director 
Nadine Nerguisian, Chair of the Management Board 

Please cite this publication as: 
Kankaraš, M. (2021). Workplace learning: determinants and consequences: insights 
from the 2019 European company survey. Luxembourg: Publications Office of the 
European Union. Cedefop working paper; No 7. 
http://data.europa.eu/doi/10.2801/111971  

Luxembourg: Publications Office of the European Union, 2021 

© Cedefop, 2021. 
Creative Commons Attribution 4.0 International (CC BY 4.0). 

This  working  paper  should  not  be  reported  as  representing  the  views  of  the 
European Centre for the Development of Vocational Training (Cedefop). The views 
expressed are those of the authors and do not necessarily reflect those of Cedefop. 

PDF 

ISBN 978-92-896-3284-3 
ISSN 1831-2403 
doi:10.2801/111971 
10.2801/92218 
TI-BA-21-006-EN-N 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Acknowledgements  

The author would like to acknowledge the Eurofound and Cedefop research teams 
lead by Giovanni Russo and Gijs van Houten, who prepared and administered the 
fourth round of the European company survey (ECS 2019), data from which were 
used in this study. We are also thankful to Giovanni Russo, Cedefop expert, who 
peer-reviewed this paper, and Antonio Ranieri, Head of Cedefop’s Department of 
VET  and  skills,  for  valuable  guidance  and  feedback  throughout  the  drafting 
process. 

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Cedefop working paper series – No 7 / December 2021 

 
 
Contents 
Contents ................................................................................................... 2 

Executive summary .................................................................................. 5 

1. 

Introduction ....................................................................................... 9 

1.1.  Workplace learning – the concept and its types .................... 9 
1.1.1.  Defining workplace learning .................................... 9 
1.1.2.  Types of workplace learning .................................. 10 

1.2. 

The analytical framework of the study ................................. 11 
1.2.1.  Broader organisational context .............................. 12 
1.2.2.  Components of workplace learning environment... 13 
1.2.3.  Workplace learning ................................................ 15 
1.2.4.  Outcomes: employee wellbeing and company 

performance .......................................................... 16 

2.  Study methodology ......................................................................... 18 

3.  Results ............................................................................................ 20 

3.1. 

Types of learning organisations in EU ................................. 20 
3.1.1.  Typical learning environment ................................. 21 
3.1.2.  Extensive learning environment............................. 21 
3.1.3.  Traditional/lean learning environment ................... 22 
3.1.4.  Restrictive learning environment ........................... 22 
3.1.5.  Encouraging learning environment ........................ 23 

3.2.  Prevalence of different types of learning organisations across 
institutional and socio-economic categories ........................ 23 
3.2.1.  Types of workplace learning environments and 

structural characteristics ........................................ 23 

3.2.2.  Types of workplace learning environments and 

market characteristics ............................................ 24 

3.2.3.  Type of workplace learning environment and 

innovativeness ....................................................... 25 

3.2.4.  Types of the workplace learning environment and 

employee and company outcomes ........................ 26 

3.3.  Relationship between aspects of learning environment and 

employee and company outcomes ...................................... 27 
3.3.1.  Relationship with employee wellbeing ................... 28 
3.3.2.  Relationship with company performance ............... 32 
3.3.3.  Simultaneous analysis of relationships with both 

outcomes - General Linear Model ......................... 34 

3.4.  Relationship between aspects of the workplace environment 

and learning opportunities ................................................... 35 
3.4.1.  Relationship with informal learning opportunities .. 36 

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Contents 

3.4.2.  Relationship with formal and non-formal learning 

programs ............................................................... 37 
3.4.3.  A general model with all learning opportunities ..... 39 

4.  Concluding discussion .................................................................... 41 

4.1.  Prevalence of workplace learning conditions and practices in 
EU companies ..................................................................... 41 

4.2.  Relationship between aspects of the learning environment 

and employee and company outcomes ............................... 42 

4.3.  Relationship between aspects of the workplace environment 

and learning opportunities ................................................... 43 

4.4.  Methodological considerations ............................................ 44 

4.5.  Conclusions ......................................................................... 46 

References ............................................................................................. 47 

Annex ..................................................................................................... 52 

Tables and figures 

Tables 

1. 

2. 

3. 

4. 

5. 

Characteristics of the five workplace learning types across  
EU establishments ............................................................................ 21 
Characteristics of the five workplace learning types across  
EU establishments ............................................................................ 31 
Characteristics of the five workplace learning types across  
EU establishments ............................................................................ 33 
Results of hierarchical regression analysis on informal learning 
opportunities   ................................................................................... 36 
Results of hierarchical regression analysis on formal and  
non-formal learning opportunities ..................................................... 38 

Figures 

1. 

Employee wellbeing and company performance by the type of 
establishment’s workplace learning environment ............................... 6 
Characteristics of the formal, non-formal and informal forms  
of the workplace learning .................................................................. 11 
3.  Workplace learning - analytical framework of the study ................... 12 

2. 

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Workplace learning: determinants and consequences:  
insights from the 2019 European company survey 

4. 

5. 

6. 

7. 

8. 

9. 

Proportion of establishments with different types of workplace 
learning settings by establishment size, age, type and economic 
sector ................................................................................................ 24 
Proportion of establishments with different types of workplace 
learning settings by dominant business strategy, and market’s 
competitiveness and predictability .................................................... 25 
Level of company innovativeness across different types  
of workplace learning settings .......................................................... 26 
Employee wellbeing and company performance by the type of 
establishment’s workplace learning environment ............................. 27 
Strengths of effects of different predictors on employee wellbeing and 
company performance in EU establishments ................................... 35 
Strengths of effects of different predictors on informal and  
formal/non-formal learning opportunities in EU companies .............. 40 

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Cedefop working paper series – No 7 / December 2021 

 
Executive summary 

Prevalence of workplace learning conditions and 
practices in EU companies 

traditional, 

five  distinct 

typical,  extensive, 

types  of  workplace 

learning  environments 

Analysis of patterns of workplace learning characteristics or bundles of practices 
in  EU 
identified 
organisations: 
restrictive  and  encouraging. 
‘Extensive’ and ‘restrictive’ types of learning environments are at the opposite end, 
with  those  belonging  to  the  ‘typical’  category  falling  neatly  between  the  two. 
Companies that belong to ‘traditional’ category have much lower skill demand and 
slightly  fewer  learning  practices  and  opportunities.  Establishments  from  the 
‘encouraging’  category  have  higher  levels  of  informal  learning  opportunities  and 
management encouragement for employee engagement.  
The five types of workplace learning environments fall in linear fashion along the 
line  of  extensive-restrictive  dimension.  Findings  show  that  larger,  younger 
companies working in service sectors are more likely to offer conductive learning 
environments  than  smaller  and  older  companies  or  establishments  working  in 
manufacturing sectors. Results also confirm the influence of market conditions on 
the propensity of various forms of learning opportunities and practices, indicating 
that  more  stable  and  predictable  environments 
learning 
opportunities.  However,  types  of  learning  environments  do  not  differ  markedly 
across  companies’  product  market  strategies  or  the  reported  levels  of  skill 
(mis)match.  The  extensive-restrictive  dimension  of  the  workplace  learning 
opportunities  also  has  a  positive 
individual  and 
organisational  outcomes  (Figure  1).  Such  results  offer  clear  evidence  of  the 
beneficial potential of workplace learning to both employees and employers. 

linear  relationship  with 

to  better 

lead 

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Cedefop working paper series – No 7 / December 2021 

 
Workplace learning: determinants and consequences:  
insights from the 2019 European company survey 

Figure 1. 

Employee wellbeing and company performance by the type of 
establishment workplace learning environment 

Learning environment and employee and company 
outcomes 

Analyses of the relationship between selected workplace learning practices, and 
their broader context, on employee wellbeing and company performance showed 
that different workplace aspects have markedly varied influence on employee and 
organisational outcomes.  

Employee  wellbeing  had  by  far  the  strongest  relationship  with  informal 
learning opportunities, though there is a lack of substantive effects from formal and 
non-formal learning opportunities on employee wellbeing. This could be because 
these programmes cover less relevant topics. In many cases participation in these 
programmes  is  compulsory,  which  can  inhibit  workers’  intrinsic  motivation  and 
interest. Probably the main reason behind these results is the fact that formal and 
non-formal  learning  programmes  are  usually  much  less  prevalent  than  informal 
learning opportunities.  

Job  autonomy  and  open  and  constructive  communication  are  also  strong 
determinants  of  employee  wellbeing,  along  with  the  national  context  and 
establishment  characteristics.  Market  conditions  are  not  that  important,  after 
controlling  for  other  aspects.  Skill  demand  is  found  to  have  slight  negative 
correlation  with  employee  wellbeing  and  extrinsic  motivation,  measured  through 
the presence of variable pay schemes as well as the level of skill (mis)match, does 
not seem to influence employee wellbeing much.  

Company innovativeness is the strongest predictor of company performance, 
followed by organisational characteristics, especially organisations’ age. National 

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Executive summary 

context and market conditions and strategies are less important for this outcome. 
Informal  learning  opportunities  and  job  autonomy  are  important  predictors  of 
company performance as well, while formal and non-formal learning opportunities 
do not have substantial influence.  

Workplace environment and learning opportunities 

The strongest predictor of the volume of informal learning opportunities is found to 
be  managers’  perception  of  its  value  and  importance.  Need  for  learning  (skill 
demands)  and  the  national  context  also  have  substantial  influence  on  informal 
learning  provisions.  Market  conditions  are  found  to  be  much  less  related  to 
workplace learning. Among organisational characteristics, the service sector is the 
category  that  has  the  highest  effect  on  the  prevalence  of  informal  learning 
opportunities.  

Skill demands are the strongest predictor of formal and non-formal learning. 
Structural  conditions  such  as  national  context  and  organisational  characteristics 
are the strongest predictors of the prevalence of formal and non-formal learning 
opportunities.  Market  conditions  are  not  related  to  the  frequency  of  training 
provisions in establishments but managers perceived value of training is found to 
be strong predictor of formal and non-formal learning opportunities.  

Concluding remarks 

Workplace  learning  is  critical  tool  for  both  employees  and  organisations  in  their 
continuous adjustment to a growing number of global trends that are reshaping our 
workplaces, economies and societies. Workers learn most when engaging in new 
and challenging activities in which they are granted sufficient autonomy to solve 
issues  themselves  or  in  collaboration  with  their  colleagues  or  mentors.  Informal 
learning  is  shown  to  be  the  key  aspect  of  workplaces  in  terms  of  company 
performance and employee wellbeing. Such findings call for more attention from 
policy-makers  and  organisations’  management  to  various  forms  of  informal 
learning at the workplace. This is particularly the case when considering apparent 
lack  of  beneficial  effects  of  formal  and  non-formal  learning  on  both  employee 
wellbeing and company performance. These findings illustrate the overwhelming 
prominence of informal learning at the workplace in comparison to formal and non-
formal  learning  forms,  but  they  also  indicate  the  learning  potential  that  exists  at 
workplaces. Analysis of the prevalence of various learning practices, as well as of 
different  types  of  learning  environment,  show  that  most  companies  are  still  not 
offering optimal learning environments and opportunities to their workers. Such a 

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Workplace learning: determinants and consequences:  
insights from the 2019 European company survey 

situation  hurts  both  employees  and  companies  but  presents  an  opportunity  for 
action, at organisational, national and international levels. Such an action will aim 
to  create  institutional  conditions,  legal  frameworks,  learning  resources,  and 
incentives  for  companies  to  start  organising  their  workplaces  in  a  way  that  will 
facilitate workplace learning, especially its various informal forms.  

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Cedefop working paper series – No 7 / December 2021 

 
CHAPTER 1.  
Introduction 

Workplace  learning  is  increasingly  seen  as  one  of  the  key  determinants  of  a 
successful response by economies and societies to the increasing pace of societal, 
demographic  and  technological  change.  The  COVID-19  pandemic  has  further 
exacerbated the critical role of skill development in adjusting to unpredictable and 
rapid changes across different aspects of work and personal lives. These trends 
place  growing  emphasis  on  individual,  organisational  and  societal  capacities  to 
create  conditions  that  will  allow  for  lifelong  learning,  including  learning  at  the 
workplace. 

This study aims to address these concerns through insights into the topic of 
workplace learning, its determinants and consequences. The paper presents the 
results  of  an  empirical  analysis  of  the  workplace  learning  characteristics  and 
practices  and  their  implications.  We  use  data  from  the  newly  released  fourth 
European company survey (2019), which collected responses from representative 
samples  of  EU  companies  in  all  EU-27  countries.  We  aim  to  answer  several 
important questions regarding workplace learning EU companies. First, we identify 
and  describe  different  types  of  EU  companies  in  terms  of  their  learning 
environments. We then explore the benefits of workplace learning practices, both 
for  individuals  and  organisations.  Finally,  we  investigate  how  these  different 
aspects of workplace learning environments affect formal and informal workplace 
learning. 

1.1.  Workplace learning: concept and types 

1.1.1.  Defining workplace learning 
Over recent decades, there has been an increasing realisation that the workplace 
is an environment not only where learning new knowledge and skills can happen 
but where learning should be happening (Hager 2004, Boud and Middleton, 2003). 
However, despite its ever-increasing importance, there is no broad consensus on 
what workplace learning is, with many definitions simply stating that it involves all 
learning that happens at the workplace (Tynjälä, 2008, 2013; Eraut, 2004; Billett, 
2002).  

In  this  paper,  we  define  workplace  learning  as  a  process  of  acquiring 
knowledge,  skills,  and  other  mental  capacities  that  occurs  while  employees 
complete  their  work  tasks  and  roles,  leading  to  improved  individual  and 

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Workplace learning: determinants and consequences:  
insights from the 2019 European company survey 

organisational performance (Hicks et al., 2007). The process is not passive and 
cannot be investigated as an activity isolated from its broader social, economic and 
cultural  context.  If  understood  too  narrowly,  it  risks  not  only  missing  out 
manifestations of various forms of informal learning but also ends up developing 
superficial  knowledge  and  skills  that  are  of  little  use  either  to  employees  or 
organisations (Cullen et al., 2000; Matthews, 1999; Winch and Ingram, 2002).  

Although the concept of workplace learning is quite broad and encompasses 
a  wide  range  of  learning  activities  and  situations,  it  still  does  not  account  for  all 
work-related learning. In this sense, it could be understood as a subcategory of a 
broader  concept  of  work-based  learning.  Cedefop  (2014)  defines  work-based 
learning  as  the  ‘acquisition  of  knowledge  and  skills  through  carrying  out  –  and 
reflecting  on  –  tasks  in  a  vocational  context,  either  at  the  workplace  (such  as 
alternance training) or in a VET institution’. Thus, work-based learning includes not 
only workplace learning, i.e. learning that happens at the workplace, but also work-
related learning in VET institutions.  

In this study, we focus on workplace learning for two reasons. First, our data 
source – the European company survey – does not include information on workers’ 
vocational learning in VET institutions. Second, our research focus in this study is 
learning in the workplace, where most work-related learning happens.  

1.1.2.  Types of workplace learning 
In  academic  research,  workplace  learning  is  most  often  divided  into  formal  and 
informal learning activities and practices (Manuti et al., 2015; Rintala et al., 2018). 
In  policy  settings  and  related  research,  the  non-formal  learning  forms  are  also 
outlined as a separate learning type between these two more distinct categories 
(Cedefop,  2009;  OECD,  2010;  Marsick  and  Watkins,  2001; Hager  and  Halliday, 
2007).  

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Cedefop working paper series – No 7 / December 2021 

CHAPTER 1. 
Introduction 

Figure 2.  Characteristics of the formal, non-formal and informal forms of the 

workplace learning 

Formal workplace learning is defined as ‘learning that occurs in an organised 
and structured environment (such as in an education or training institution or on 
the  job)  and  is  explicitly  designated  as  learning  (in  terms  of  objectives,  time  or 
resources)’ (Cedefop, 2014). Formal learning is intentional from the learners’ point 
of view and typically leads to certification (Cedefop, 2014).  

Non-formal learning is defined as ‘learning embedded in planned activities not 
explicitly designated as learning (in terms of learning objectives, learning time or 
learning  support)’  (Cedefop,  2014).  However,  it  refers  to  various  structured  and 
semi-structured learning activities and is understood to be intentional from the point 
of view of the learner; its outcomes may be validated and may lead to certification 
(Cedefop, 2014). 

Informal learning is defined as ‘learning resulting from daily activities related 
to work, family or leisure’ (Cedefop, 2014). It is not organised or structured and, in 
most cases, it is unintentional from the learner’s perspective. This type of learning 
can also be validated and certified, although this is still rarely the case.  

1.2.  The analytical framework of the study 

The study seeks to analyse the relationship between the broader institutional and 
economic context, aspects of the workplace learning environment, and social and 
organisational  performance  outcomes.  In  order  to  achieve  these  objectives,  we 
need to answer several research questions that can be summarised as follows: 
(a)  how  can  European  companies  be  classified  according  to  their  workplace 
learning practices? Are companies more likely to implement specific bundles 
of learning practices together?  

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Workplace learning: determinants and consequences:  
insights from the 2019 European company survey 

(b)  how  do  different  types  of  workplace  learning  systems  affect  social  and 
learning 

organisational  performance?  Are  companies  with  better 
environments more profitable and is employee wellbeing improved?  

(c)  which  aspects  of  workplace  learning  systems  are  the  most  important 

promotors of positive employee and company outcomes?  

(d)  what are the factors influencing the degree of informal, formal and non-formal 
learning  opportunities  in  companies?  For  example,  are  establishments 
functioning in different institutional and market settings more or less likely to 
build stimulating workplace learning environments?  

The analytical framework that will guide the empirical work of the study, with 
the workplace learning systems at the centre of the analysis, can be depicted as 
follows (Figure 3). 

Figure 3.  Workplace learning - analytical framework of the study 

Broader organisational context 

1.2.1. 
Box 1 reflects the organisational characteristics and broader institutional, market 
and socioeconomic context in which a workplace learning system is developed and 
engrained.  

These  contextual  factors  first  refer  to  a  country  in  which  organisations  are 
located. This information serves as an analytical proxy for the potential influence 
of the complex network of institutional, regulatory, legal, and financial systems but 
also of various cultural characteristics and social norms that differ across national 
contexts. From the workplace learning perspective, this national embeddedness is 
particularly  exemplified  through  the  type  of  training  available  and  the  level  of 
employee skills (Estevez-Abe et al., 2001; Thelen, 2004; Bosch et al., 2017).  

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CHAPTER 1. 
Introduction 

type 

their  size, 

The economic sector in which a company is functioning is another broad contextual 
determinant  that  can  influence  work  organisation  and  workplace  learning 
environment in a company (Eurofound and Cedefop, 2020; Eurofound, 2015). 
Companies'  structural  characteristics,  such  as 
(single 
establishment,  subsidiary  branch  or  headquarters),  and  their  age  (year  of 
establishment)  are  also  found  to  be  related  with  workplace  learning  settings 
(Eurofound  and  Cedefop,  2020;  Eurofound,  2015).  Market  conditions  and 
strategies  are  also  important  factors  in  management  decisions  regarding  work 
organisation  in  general  and  workplace  learning  environment  in  particular.  For 
example, it  is considered that HPW systems can be  used  to increase efficiency 
and  performance  of  companies  functioning  in  highly  competitive  environments 
(usually exposed to foreign competition) (e.g. Appelbaum et al., 2001). Similarly, 
market predictability is thought to create more stable conditions, allow for longer-
term planning, and motivate companies to invest more in the skill development of 
its workforce (Warhurst and Luchinskaya, 2018).  

Components of workplace learning environment 

1.2.2. 
In this study, we have divided workplace learning environments into four aspects: 
those describing skill demand in the workplace, motivational levers, job design and 
learning opportunities, each of which we describe in more detail below: 

1.2.2.1.  Skill demand and skill use 

The degree of learning in a particular workplace activity will depend on the interplay 
between job’s skill demand and workers’ skill supply (Warhurst and Luchinskaya, 
2018). Skill demand will generally depend on the complexity of work tasks and their 
pace of change, with the latter usually playing a greater role. The innovativeness 
of a company is, therefore, another driver of skill demands. Innovations in products, 
procedures  or  internal  organisation  lead  to  changes  in  job  requirements,  work 
tasks  and  workplace  conditions  that  often  necessitate  the  development  of  new 
competences and knowledge. 

Skill demand and skill supply will determine skill utilisation. According to the 
skill  (mis)match  approach,  effective  skill  utilisation  occurs  only  when  there  is  a 
match between skills required by a job and skills possessed by an employee (e.g. 
Cedefop,  2010;  Eurofound  and  Cedefop,  2020,  de  Grip,  2015,  Warhurst  and 
Findlay, 2012). However, skills and knowledge include knowing how and when to 
use existing skills: for example, a novice employee might not utilise some of the 
required  competences  due  to  the  lack  of  knowledge  of  job-specific  information 
needed for performing certain tasks. In addition, the gap between skill demand and 
skill  utilisation  can  be  affected  by  the  discretionary  behaviour  of  individual 

Cedefop working paper series – No 7 / December 2021  

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Workplace learning: determinants and consequences:  
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employees.  This  is  why  companies  need  to  motivate  employees  to  use  their 
existing skills to fulfil their job tasks rather than simply mandate their completion.  

1.2.2.2.  Motivational levers 

Workplace learning is a participative process involving social interaction and joint 
construction of knowledge, requiring an active role from all participants in deciding 
how they engage and participate (Billett, 2004). Research has shown that workers 
select  learning  activities  in  which  they  engage  depending  on  their  interests, 
preferences, perceived professional development needs, and perceived effort that 
such engagement requires (Billett, 2001; Illeris, 2003). 

This  is  why  worker  motivation  and  workplace  engagement  is  one  of  the 
strongest determinants of workplace learning. Human motivation is often divided 
into intrinsic and extrinsic (Deci and Ryan, 1985). Intrinsic motivation is defined as 
a  behaviour  that  is  driven  by  satisfying  internal  rewards:  the  activity  itself  is 
rewarding  and  is  not  dependent  on  external  stimulations  or  incentives.  Extrinsic 
motivation  is  driven  by  the  goal  of  obtaining  some  external  reward,  which  is 
separate from the activity itself. 

Workers'  intrinsic  motivations  and  individual  agency  contribute  not  only  to 
better  use  of  existing  learning  opportunities;  they  can  also  ameliorate  negative 
effects of poor workplace conditions (Smith, 2003). A range of workplace aspects 
and  characteristics  can  affect  worker  motivation,  including  communication  with 
management,  involvement  in  decision-making,  and  management  practices  that 
foster  autonomous,  discretionary  behaviours  and  employee  engagement  (Ryan 
and Deci,  2017; Harvard Business Review, 2019; Mishra, Boynton, and Mishra, 
2014).  In  contrast,  extrinsic  motivation  of  employees  will  be  promoted  by 
remuneration,  promotion  opportunities,  variable  pay  schemes  and  other 
performance-based rewards (Gerhart and Fang, 2014).  

1.2.2.3.  Job design 

Job  design  and  organisation  of  work  is  one  of  the  most  important  factors 
influencing  work  learning  (Tynjala,  2008;  Eraut,  2004;  Rintala  et  al.,  2018).  Job 
autonomy  is  consistently  found  as  one  of  the  key  drivers  of  workplace  learning 
(Rintala et al., 2018; Tynjala, 2008; 2013, Bakker and Demerouti, 2007). Autonomy 
nurtures workers' sense of agency, of their perception of themselves as decision-
makers and independent actors in the social environment of the workplace (Billett, 
2001,  2002,  2011).  It  develops  their  intrinsic  motivation  and  their  initiative  and 
engagement (Deci and Ryan, 1985; Ryan and Deci, 2017). The level of difficulty 
or  challenging  work  is  another  important  job  design  factor  found  in  workplace 
learning (Eraut, 2004).  

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CHAPTER 1. 
Introduction 

Employees  whose  job  tasks  involve  solving  problems  and  dealing  with 
different  challenges  will  learn  more  and  develop  their  skills  faster  than  those 
working in jobs whose tasks are more monotonous and less difficult. Challenging 
work and engagement in problem-solving activities enable learning-by-doing forms 
of informal learning  as well as learning  by insight and learning  through trial and 
error. Each new problem and issue prompts the creation of new knowledge or skills 
for its solving, representing a new learning opportunity.  

The opportunity to work in teams is also beneficial to workplace learning as it 
creates  ample  opportunities  for  interactions  with  colleagues  that  can  induce 
learning and skill development. Teams that enjoy a wider range of autonomy are 
especially beneficial for skill development and the creation of learning opportunities 
for their members (European Commission, 2015; Eurofound, 2015). 

1.2.2.4.  Learning climate 

Management’s  own  perception  of  the  worth  of  learning  is  an  important  factor  in 
creating a conducive workplace climate for learning. Employees in organisations 
in which management actively promotes learning, and demonstrates their regard 
for  it  and  its  perceived  value  by  creating  appropriate  practices,  will  be  more 
motivated  to  make  use  of  any  learning  opportunities.  The  value  of  learning  in 
management’s  eyes  is  not  only  perceived  through  their  explicit  statements  but 
even more so through their learning policies.  

1.2.3.  Workplace learning 

1.2.3.1.  Learning provisions 

The degree of direct learning opportunities and provisions directly determines the 
scope of workplace learning in an establishment. Companies with comprehensive 
learning provisions and opportunities provided to their employees ensure their skill 
development  and  positive  learning  outcomes.  These  learning  provisions  and 
opportunities can be divided into formal, non-formal, and informal, depending on 
how they are organised and conducted. Informal learning opportunities are more 
difficult to assess as they are hard to distinguish from various work tasks and wider 
workplace conditions: this is why the way work is organised and jobs are designed 
are important factors enabling workplace  learning. We refer to these aspects as 
indirect  (implicit)  opportunities  for  informal  learning.  However,  there  are  other 
aspects of workplaces that are specifically and intentionally designed to facilitate 
workplace learning. These are, for example, job rotation schemes, a pairing of less 
experienced  with  more  experienced  colleagues,  or  explicit  encouragement  for 
experiential (trial and error) learning. 

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Workplace learning: determinants and consequences:  
insights from the 2019 European company survey 

1.2.3.2.  Learning activities 

The existence of formal learning programmes or non-formal training schemes is 
usually equated with workplace learning as it is assumed that learning takes place 
through the act of participation in these programmes. However, a number of other 
contextual  and  individual  characteristics  will  affect  the  learning  process  and 
moderate its outcomes. This is even more the case for informal learning activities, 
where direct and indirect informal learning opportunities might not always lead to 
learning.  

Outcomes: employee wellbeing and company performance 
1.2.4. 
Some workplace practices are aimed at improving the productivity and profitability 
of companies, while others are set up to improve job satisfaction and the overall 
wellbeing of the company’s employees. However, there are workplace practices 
and bundles of practices that are found to be mutually beneficial to both employees 
and  companies  (Eurofound,  2015;  Eurofound  and  Cedefop,  2020).  Workplace 
learning is one of the aspects of the workplace with clear ‘mutual gains’ potential, 
i.e. with the possibility to bring positive effects for both social outcomes (employee 
wellbeing)  and  organisational  performance.  The  establishment  of  such  ‘win-win’ 
situations  for  both  employees  and  employers  could  be  seen  as  one  of  the  key 
policy goals in work organisation and employee relations. 

However, social outcomes and organisational performance do not have to be 
aligned  with  one  another.  Depending  on  intentional  or  implicit  organisation 
strategy, these two sets of outcomes can be conflicting goals, with some workplace 
practices  benefiting  employers  that  are  not  beneficial  or  even  harmful  to 
employees. Further, some workplace practices have potentially both positive and 
negative  effects  on  different  aspects  of  employee  wellbeing  and  have  induced 
controversy in the public debate (Appelbaum, 2013). In our analytical framework, 
employee  wellbeing  can  be  broadly  described  as  the  overall  quality  of  the 
employee’s experience at his or her workplace (Van der Voorde et al., 2012). Three 
main dimensions of employee wellbeing are distinguished:  
(a) 
job satisfaction (Appelbaum, 2013);  
(b)  quality of relationships (Bartel 2004) and  
(c)  employee health (Appelbaum. 2013; Orlitzky and Frenkel 2005).  

Job  satisfaction  refers  to  subjective  functioning  and  experiences  at  the 
workplace,  as  measured  by  job  satisfaction  scales  (Grant  et  al.,  2007).  This 
dimension  also  includes  an  aspect  of  employee  commitment.  The  relationships 
dimension  reflects  the  interactions  and  quality  of  the  relationships  or  dialogues 
between  employees  and  between  employees  and  their  supervisors  (the  work 
climate.  The  health  dimension  covers  the  overall  state  of  mental  and  physical 

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CHAPTER 1. 
Introduction 

health, including the absence of both acute and chronic work-related illnesses and 
impairments and other detrimental health effects. It is most often assessed through 
administrative data on employee sick leave and absenteeism and the incidence of 
work-related  medical  conditions.  This  aspect  of  employee  wellbeing  has  often 
been  ignored  in  analyses  of  the  outcomes  of  various  workplace  practices  on 
employee wellbeing (Van der Voorde et al., 2012).  

The  company  performance  outcomes  are  usually  assessed  through  two 
dimensions  or  criteria  (e.g.  Paauwe,  2009):  financial  outcomes  (profit,  market 
share)  and  organisational  outcomes  (output,  efficiency  or  productivity).  In  most 
cases  the  two  dimensions  correspond  with  each  other  but  there  are  situations 
where an increase in production is not followed with positive financial statements 
or where profitability lags efficiency improvements. This is why it is important to 
take  a  comprehensive  approach  when  assessing  company  performance,  taking 
into account both of its dimensions.  

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CHAPTER 2.  
Study methodology 

In this study, we used data from the fourth round of the European company survey 
(ECS 2019), jointly conducted by the Eurofound and Cedefop EU agencies in the 
first  half  of  2019.  ECS  2019  obtained  data  from  HR  managers  and,  where 
available, employee representatives. The survey investigated workplace practices 
on  work  organisation,  human  resource  management,  skills  use  and  skills 
strategies, direct and indirect employee participation, and digitalisation, innovation 
and business marketing strategies. 

The unit of inquiry for all ECS surveys is the establishment: the local unit or 
site with 10 or more employees in economic sectors engaged in ‘market activities’ 
in  all  EU-27  Member  States  and  the  United  Kingdom.  Sampling  was  conducted 
through  a  multistage  random  sampling  approach,  stratified  by  establishment  or 
company size (10 to 49 employees, 50 to 249 employees, 250+ employees) and 
the broad sector of activity (production, construction, services).  

The push-to-web methodology used in this survey achieved a relatively low 
response rate. In the EU27, 16% of establishments agreed to participate and only 
35% of these actually completed the questionnaire, resulting in an overall yield rate 
of only 5%. 

The  resulting  ECS  2019  dataset  contains  data  from  the  21 869  completed 
management  interviews  (ranging  from  122  in  Cyprus  to  1 498  in  Italy).  It  also 
includes  data  collected  from  3 073  employee  representatives  (ranging  from  3  in 
Cyprus  to  467  in  Finland).  Because  of  the  relatively  small  sample  sizes  and 
response rates of the employee representative sample, we only used data from 
the ECS 2019 management sample.  

The analysis is conducted in three stages. 
First,  we  examine  how  these  individual  practices  are  bundled  together  into 
different organisational learning settings using a latent class analysis. We also look 
at the distribution of identified types of learning settings across a set of background, 
contextual, and outcome characteristics. Before running latent class models, some 
variables  are  first  grouped  into  indexes/latent  variable  indicators  using  principal 
component analysis (for details of the data preparation procedures, see annex).  

Second,  we  then  study  the  role  and  importance  of  each  of  the  individual 
learning  practices  and  learning  opportunities  in  terms  of  their  relationship  with 
employee  and  company  outcomes.  For  these  purposes,  we  make  use  of 
hierarchical regression analysis and multivariate general linear model (GLM). 

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CHAPTER 2. 
Study methodology 

Third,  we  investigate  the  relationship  between  individual  aspects  of  the 
learning environment on formal and  informal learning opportunities. Hierarchical 
regression analysis and multivariate GLM models are used in these analyses as 
well. 

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19 

CHAPTER 3.  
Results 

3.1.  Types of learning organisation in the EU 

In this section, we analyse the patterns of workplace learning characteristics that 
can be identified across EU establishments. These workplace patterns, or bundles 
of  practices,  can  be  seen  as  relatively  distinct  types  of  workplace  learning 
environments  for  a  given  selection  of  workplace  aspects  that  are  used  for  their 
identification.  
We  used  the  latent  class  analysis  approach  to  identify  categories  or  types  of 
workplace learning environments in EU establishments. In line with our theoretical 
framework, we used the following 11 workplace aspects: 
(a)  demand for continuous learning; 
(b)  skill (mis)match; 
(c)  external motivators; 
(d)  direct communication with employees; 
(e)  employee influence on management decisions; 
(f)  encouraging employee engagement; 
(g) 
(h) 
(i) 
(j) 
(k) 

job autonomy; 
teamwork; 
importance of training; 
formal and non-formal learning opportunities; 
informal learning opportunities. 

As  explained  in  the  section  on  methodology,  each  of  these  aspects  is 
represented  by  a  separate  composite  index  that  denotes  a  summary  indicator 
based on several relevant questions or scales from the ECS 2019 survey. In the 
latent  class  analysis,  we  used  these  indices  to  identify  the  categories  of 
establishments that share similar patterns across these 11 indicators. This analysis 
enabled us to identify unobserved patterns of similarities and differences across 
establishments on these 11 dimensions.  

Based  on  this,  we  identified  five  different  types  of  workplace  learning 
environments that differ in size (number of companies belonging to each type) and 
their patterns of values across various workplace learning aspects (Table 1). 

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CHAPTER 3. 
Results 

Table 1. 

Characteristics of the five workplace learning types across EU 
establishments 

Types of workplace learning settings 

Typical  Extensive  Traditional/lean  Restricted  Encouraging 

Learning demand 

Extrinsic motivation 

110.2 

142.6 

110.6 

125.2 

Communication 

105.0 

135.1 

102.1 

133.0 

59.3 

92.8 

97.8 

93.6 

71.3 

69.1 

72.3 

64.3 

100.0 

64.1 

90.9 

98.9 

90.4 

130.6 

94.5 

65.0 

139.3 

Intrinsic 
motivation 

Influence on 
decisions 

Encouraging 
engagement 

Job design 

 Job autonomy 

106.3 

132.8 

 Teamwork 

105.6 

119.2 

Importance of training 

92.3 

139.3 

Learning 
opportunities 

Skill match 

Formal learning 

105.5 

138.1 

Informal learning 

99.1 

151.7 

86.8 

97.3 

89.4 

84.6 

84.7 

74.2 

80.4 

54.6 

61.4 

50.2 

93.7 

89.4 

131.8 

94.8 

116.0 

0.684 

0.704 

0.710 

0.722 

0.727 

Overall proportion of EU 
establishments in the five 
workplace learning categories  

36.5% 

22.1% 

18.9% 

14.9% 

7.6% 

NB: 

All variables except skill match indicator are standardised and are placed on a scale with an EU 
average of 100 and standard deviation of 50; Skill match indicator represents a proportion of 
workers in an establishment who have matching skills with job requirements. 

Source:  European company survey, 2019. 

3.1.1.  Typical learning environment 
Around a third of EU companies belong to the typical type of workplace learning 
environment. While most of the workplace aspects for this group are around the 
average  of  all  EU-27  establishments,  there  are  exceptions.  Some  tend  to  use 
variable  pay  schemes  that  encourage  extrinsic  motivation  greater  than  the 
average. This use of performance-based remuneration practices is coupled with a 
somewhat  reduced  focus  on  promoting  discretionary  behaviours  (encouraging 
engagement)  and  fewer  perceived  employee  training  benefits.  Despite  this,  the 
proportion  of  employees  with  reported  skills  matching  their  job  requirements  is 
similar to the average (70.4% versus 71.1%, respectively).  

3.1.2.  Extensive learning environment 
The highest values characterise the ‘extensive’ learning type of establishments on 
almost  all  selected  workplace  aspects.  Almost  a  quarter  of  establishments 

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Workplace learning: determinants and consequences:  
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for  employee  engagement 

belonging  to  this  category  have  much  higher  workplace  learning  demands  and, 
perhaps  consequently,  promote  both  extrinsic  and  intrinsic  motivation  of  their 
employees. Establishments belonging to this type created procedural and formal 
conditions 
through  direct  communication  with 
employees  and  mechanisms  that  allow  employees  to  influence  management 
decisions.  Employees  have  extensive  autonomy  in  their  work  and  ample 
opportunities to collaborate with their colleagues in teams. Companies in this type 
provide good contexts for learning. They also directly promote learning through a 
wide scope of training and informal learning opportunities that are more than one 
standard deviation higher than the average for all establishments. However, the 
proportion of employees with skills matching their job requirements is exactly the 
same  as  the  overall  average.  Such  a  result  may  indicate  that  this  workplace 
dimension is not aligned with the rest of the learning aspects: the skill (mis)match, 
at  least  as  measured  in  this  survey,  does  not  relate  to  key  workplace  learning 
practices. 

3.1.3.  Traditional/lean learning environment 
The  ‘traditional/lean’  type  of  workplace  learning  setting  represents  those 
organisations  –  about  one  fifth  of  all  EU  companies  –  that  have  much  lower 
learning demand and take a more traditional approach to learning. They are less 
prone  to  using  variable  pay  schemes  and  generally  allow  employees  fewer 
opportunities to influence decisions. Employees in these establishments also have 
fewer  opportunities  to  work  independently  from  their  managers.  Formal  and 
informal learning opportunities are also constrained, although their managers are 
no  more  restrictive  in  comparison  with  other  companies  in  terms  of  promoting 
discretionary  behaviours  of  their  employees  and  direct  communication  with 
employees.  This  may  indicate  that  worse  learning  opportunities  in  these 
establishments  are partly due to companies’ circumstances, such as the lack of 
means  to  create  a  workplace  learning  environment  and/or  the  lack  of  pressing 
need for the development of employee skills in their market niche. Despite this, the 
proportion of employees with skills matching their job requirements is somewhat 
higher than the average for EU-27 companies (X and Y).  

3.1.4.  Restrictive learning environment 
The ‘restrictive’ learning type of establishments, with around 1 in 7 companies, has 
the  worst  workplace  learning  environment  among  the  five  groups.  It  has  low 
demand for skill development coupled with very low levels of motivating practices, 
such as variable pay and direct communication with employees. It has especially 
low  levels  of  employee  influence  on  management  decisions  and  encouraging 
discretionary behaviours of employees, allowing little room for the development of 

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CHAPTER 3. 
Results 

employee intrinsic motivations. Job autonomy and teamwork are also constrained 
in comparison with other establishments. There are very few training opportunities 
and even less perceived benefit from the training of employees. The most striking 
feature  of  this  type  of  establishment  is  the  degree  to  which  informal  learning 
opportunities  are  restricted,  with  the  informal  learning  indicator  one  standard 
deviation below the average for all companies. The proportion of employees with 
matching  skills  is  relatively  high,  and  even  somewhat  higher  than  the  EU-27 
average, in spite of an apparently constrained learning environment. 

Encouraging learning environment 

3.1.5. 
About  8%  of  all  EU  companies  belong  to  the  ‘encouraging’  type  of  workplace 
learning establishments. They tend to offer more opportunities for informal learning 
but  less  formal  and  non-formal  learning  opportunities  than  the  average  EU-27 
company. They have an average level of learning demand and a somewhat lower 
level of direct communication with employees. Variable pay schemes are also used 
less  often,  and  employees  have  slightly  fewer  autonomy  and  teamwork 
opportunities than in an average company. Where establishments belonging to this 
category excel is in their support for employees' discretionary behaviours and their 
views  on  the  importance  of  training.  Although  they  might  not  use  as  many 
motivational  levers  as  companies  in  the  ‘extensive’  learning  group,  they  value 
learning and discretionary engagement of employees almost as strongly. Although 
they  provide  above-average  learning  opportunities,  the  proportion  of  employees 
with  skills  matching  their  job  requirements  is  somewhat  lower  than  the  overall 
overage and the corresponding proportion in other groups. 

3.2. 

Learning organisations across institutional and 
socioeconomic categories  

The  different  types  of  workplace  learning  organisations  can  now  be  analysed 
according  to  several  attributes:  their  structural  and  market  characteristics, 
innovativeness, and outcomes. 

3.2.1.  Types of workplace learning environment and structural 

characteristics 

As shown in Figure 4, extensive learning types are most pronounced in the larger 
and  younger  companies  and  in  subsidiary  sites,  while  the  opposite  is  true  for 
establishments belonging to restricted learning types. The traditional learning type 
is  much  more  frequent  in  older  companies  with  a  single  establishment,  while 
encouraging  learning  settings  occur  more  often  in  smaller  establishments.  The 

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Workplace learning: determinants and consequences:  
insights from the 2019 European company survey 

proportion of the typical learning type of establishments does not vary much across 
these three structural characteristics.  

The  findings  presented  indicate  that  the  type  of  workplace  learning 
environment is largely influenced by the economic sector a company belongs to. 
Establishments  with  extensive  learning  environments  are  more  than  two  times 
more likely to belong to service sectors than to industry and construction sectors; 
a  restricted  learning  environment  is  almost  two  times  more  likely  to  be  found  in 
companies  in  transport  and  construction  industries  than  those  in  the  service 
industries.  Traditional 
the 
manufacturing sectors (industry and construction) than in the service sectors.  

learning  environments  are  more  prevalent 

in 

Figure 4. 

The proportion of establishments with different types of workplace 
learning settings by establishment size, age, type and economic sector 

Source: European company survey, 2019. 

3.2.2.  Types of workplace learning environments and market characteristics 
Dominant business strategy also seems to influence the type of workplace learning 
environment  the  company  will  develop  (Figure  5).  Companies  that  focus  on 
customisation, innovation, or use a combination of strategies are twice as likely to 
employ an extensive learning environment than companies that focus on product 
price as their dominant strategy. Those companies that prioritise prices are more 
likely  to  create  a  restricted  learning  environment  than  those  focusing  on 
customisation or innovation. The other three workplace learning types do not differ 

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CHAPTER 3. 
Results 

much  in  their  distribution  across  the  establishments  that  implement  these  five 
market strategies. 
Companies functioning in highly competitive and predictable market conditions are 
more  likely  to  develop  extensive  learning  environments  and  less  likely  to  have 
restrictive  learning  settings.  Conversely,  traditional  learning  environments  are 
more prevalent in companies with moderate market competition and predictability. 

Figure 5. 

The proportion of establishments with different types of workplace 
learning settings by dominant business strategy, and market 
competitiveness and predictability  

Source: European company survey, 2019. 

3.2.3.  Type of workplace learning environment and innovativeness 
Recent  changes  in  products,  processes,  and/or  marketing  activities  in  an 
establishment, which is marked as an indicator of establishment innovativeness, 
are  strongly  related  to  the  type  of  company  workplace  learning  environments 
(Figure 6). In particular, and as expected, the establishments that create extensive 
learning environments have  a substantially higher degree of innovation than the 
average  establishment.  At  the  same  time,  innovativeness  is  much  lower  in 
establishments  that  employ  restricted  learning  settings.  Such  results  could  be 
expected,  given  that  any  changes  introduced  in  companies’  production  and 
processes  necessitate  some  degree  of  employee  learning.  The  relationship 
between company innovativeness and its learning environment can be assumed 
as  mutually  supportive,  with  higher  innovativeness  encouraging  the  creation  of 

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Workplace learning: determinants and consequences:  
insights from the 2019 European company survey 

more  supportive  learning  environments.  In  return,  this  helps  promote  further 
innovation. 

Figure 6. 

Level of company innovativeness across different types of workplace 
learning settings 

Note: All innovation indicator is standardised and is placed on a scale with an EU average of 100 and 

standard deviation of 50.  

Source: European company survey, 2019. 

3.2.4.  Types of workplace learning environment and employee and company 

outcomes 

In order to investigate how the different types of workplace learning can potentially 
lead to positive or negative outcomes for the company and its workers, we have 
constructed two composite indices: 
(a) 

the employee wellbeing index is created using survey questions on the degree 
of  employee  absenteeism,  their  perceived  high  work  motivation  and  good 
relations  with  management,  and  the  degree  to  which  management  has 
difficulties in retaining employees in their company;  
the  company  performance  index  is  calculated  using  the  information  on  the 
company’s  profit  performance,  employment  and  production  growth,  and 
planned increase in employment.  

(b) 

 As presented in Figure 7, companies that employ extensive learning settings 
have much better employee wellbeing and company performance. Establishments 
that substantially restrict  the learning opportunities of their employees are much 
more  likely  to  have  lower  performance  and  even  lower  levels  of  employee 
wellbeing. Companies with encouraging learning settings achieve better levels of 
employee  wellbeing  but  are  still  lagging  in  company  performance.  Traditional 

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CHAPTER 3. 
Results 

learning  environments  seem  to  lead  to  somewhat  depressed  outcomes  at  both 
employee and company levels. Typical learning settings lead to average results in 
both outcome dimensions, as could be expected. 

Figure 7. 

Employee wellbeing and company performance by the type of 
establishment workplace learning environment  

Note:   Size of the bubbles in the graph indicates the proportion of establishments that belong to a given 

type; employee wellbeing and company performance indices are standardised and are placed on a 
scale with an EU-27 average of 100 and standard deviation of 50. 

Source:   European company survey, 2019. 

3.3.  Aspects of learning environment and employee 

and company outcomes 

In  the  previous  section,  we  examined  how  these  various  workplace  practices 
create  types  of  learning  environments  with  distinct  characteristics  and  different 
employee and company outcomes. However, analysis of the relationships between 
various types of learning settings and social and company outcomes cannot inform 
us of the importance of each of the individual aspects of the learning environment.  

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Workplace learning: determinants and consequences:  
insights from the 2019 European company survey 

This  section  will  present  results  of  analyses  that  aimed  to  examine  the 
individual role and contribution of the selected workplace learning practices and 
their broader context on employee wellbeing and company performance. We start 
with  the  presentation  of  the  results  of  hierarchical  regression  models  of  various 
predictors on employee wellbeing.  

3.3.1.  Relationship with employee wellbeing 
We conducted a hierarchical regression analysis, adding groups of predictors over 
several steps. This analysis aimed not only to explore the relative contribution of 
each of the predictors in accounting for the observed variation in the composite 
index of employee wellbeing; it also allows for exploration of the added predictive 
power of the new group of predictors over and above the predictive power of the 
previously included group of predictors. This feature of the hierarchical regression 
models  enables  us  to  understand  better  the  mutual  relationships  between 
predictors of interest and the dependent variable, employee wellbeing. However, 
unlike  simultaneous  regression  models,  hierarchical  models  require  stronger 
causal inferences, as the order in which the blocks of predictors are added to the 
model depends on the assumed primacy of their causal effects on other predictors 
and the dependent variable. In the absence of such causal inferences, the order 
of blocks will be arbitrary. Therefore, the results will depend on the particular choice 
of the order of blocks and the variables belonging to each block. In such a situation, 
simultaneous regression analysis is a more fitting choice of the statistical model.  
Table 2 presents the results of our hierarchical regression model on employee 
wellbeing. The model included nine hierarchical steps, each involving the inclusion 
of  one  or  more  additional  predictors.  Presented  coefficients  are  related  to  the 
changes in accounted variation per each step (R-square statistics) as well as the 
individual  regression  coefficients  of  each  of  the  predictors  in  the  final  model  in 
which all predictors were included.  

Taken together, the 20 predictors included account for 26% of the variation in 
the composite index of employee wellbeing. This can be considered a relatively 
large proportion, especially when considering that both predictors and dependent 
variables  include  unknown  degree  of  measurement  error  that  attenuates  their 
relationship  coefficients.  However,  there  is  large  variation  among  the  individual 
predictors  regarding  their  sign  and  strength  of  relationship  with  the  dependent 
variable. The country in which the company is located has an important influence 
on employee wellbeing, accounting for a little over 5% of its variation. This is not 
surprising given that country of location acts as a proxy variable for a wide set of 
potential employee wellbeing predictors, such as national institutional framework, 
culture,  and  economic  situation.  Establishment  characteristics  account  for  an 
additional  4%  of  the  variation  in  the  employee  wellbeing  index.  Most  of  this 

28  

Cedefop working paper series – No 7 / December 2021 

CHAPTER 3. 
Results 

predictive power comes from the influence of company size (number of employees) 
on employee wellbeing, with smaller companies having higher employee wellbeing 
levels  than  those  in  larger  companies.  Employees  in  single  establishment 
companies  are  also  slightly  better  off  than  those  in  headquarters  or  subsidiary 
sites. The company's tenure does not seem to influence employee wellbeing when 
accounting for all other included predictors. The economic sector affects wellbeing, 
with employees in retail and service sectors better off than those in industry and 
construction sectors. 

(additional  1%),  when 

Market  characteristics  and  company  market  approach  only  slightly  improve 
employee  wellbeing  prediction 
taking  all  other 
characteristics into account. The degree of market competitiveness does not seem 
to influence employee wellbeing in a company, but market predictability has a small 
but  statistically  significant  relationship,  with  companies  functioning  in  more 
predictable  markets  tending  to  have  higher  levels  of  employee  wellbeing. 
Employees  in  companies  whose  dominant  business  strategy  focuses  on  quality 
tend to be slightly better off than those in companies that promote any of the other 
dominant strategies, with other conditions kept equal. 

The  level  of  company  innovativeness,  i.e.  degree  of  introduced  changes  in 
their  processes  and  products,  does  not  seem  to  affect  employee  wellbeing  in  a 
company. However, the degree of changing skill requirements seems to be related 
to employee wellbeing, in an inverse way. Employees who work in companies that 
require constant training and have continuous changes in skills needed to do the 
tasks correctly are worse off than their colleagues who work in establishments with 
lower  skill  development  demands.  This  is  an  especially  important  finding, 
considering  that  it  considers  differences  among  companies  in  other  relevant 
characteristics, including those regarding learning opportunities. It indicates that a 
certain level of stability of skill requirements at the workplace is desirable from the 
point  of  view  of  employee  wellbeing,  independent  of  whether  a  company  has 
provided for an adequate learning environment and ample learning opportunities. 
Various  ways  in  which  employee  intrinsic  and  extrinsic  motivation  are 
improved  lead  to  a  considerable  increase  in  the  model's  predictive  power, 
accounting  for  an  additional  6%  of  the  variability  in  the  index  of  employee 
wellbeing. Among the four motivational levers, direct and involving communication 
with  employees  is  the  most  strongly  related  to  employee  wellbeing,  followed  by 
encouraging  employee  engagement 
through  performance  evaluation. 
Performance-based  variable  pay  practices  do  not  seem  to  influence  employee 
wellbeing once other characteristics are considered. This result might be surprising 
to  some  managers  and  policy-makers,  given  that  performance-based  pay  is 
usually considered an effective HR practice for increasing employee engagement 
and job satisfaction.  

Cedefop working paper series – No 7 / December 2021  

29 

Workplace learning: determinants and consequences:  
insights from the 2019 European company survey 

As  expected,  employees  who  enjoy  higher  job  autonomy  levels  are  much 
more likely to have higher degrees of wellbeing, even after controlling for all other 
19 company characteristics. This finding is in line with a broad scope of evidence 
of  beneficial  effects  of  job  autonomy  on  employee  morale,  engagement, 
productivity  and  job  satisfaction.  In  contrast,  teamwork  does  not  seem  to  have 
much effect on employee wellbeing: the little effect that seems to exist is actually 
negative, with employees working in multiple teams seemingly worse than those 
working in one team or working individually.  

Companies in which management perceive training as an important tool for 
improving company and employee outcomes tend to have slightly higher levels of 
employee wellbeing, all other things being equal. However, the provision of more 
formal  and  non-formal  learning  opportunities  in  a  company  does  not  seem  to 
improve  employee  wellbeing  when  other  characteristics  are  kept  constant.  This 
might  be  seen  as  surprising,  given  the  usual  focus  on  formal  and  non-formal 
learning  opportunities  when  discussing  workplace  learning  practices  and  their 
relations  with  employee  wellbeing  and  company  performance.  However,  most 
formal  and  non-formal  learning  opportunities  are  organised  with  the  implicit  and 
explicit objectives of improving employee productivity rather than their wellbeing. 
Such  formal  learning  opportunities  are  usually  of  short  and  intermittent  duration 
and do not offer enough of the opportunity for substantial influence on employee 
wellbeing. 

The opposite is true of informal learning opportunities. This is the strongest 
predictor of employee wellbeing, accounting for almost 9% of the variation in its 
index after controlling for differences in other predictors. This result is especially 
striking when considering that it represents a relationship independent of the scope 
of  formal  and  non-formal  learning  opportunities  available  to  employees  in  a 
company. Opportunity to learn outside of formal learning programmes is critical, 
not  just  for  employee  skill  development  and  productivity  but  also  for  general 
wellbeing.  

The proportion of employees whose skills match their job requirements also 
have a small but positive relationship with employee wellbeing, after controlling for 
the differences in other predictors. Although in the expected direction, the influence 
of  this  aspect  of  the  workplace  learning  environment  might  not  be  as  strong  as 
expected, especially from the perspective of the skill (mis)match literature.  

30  

Cedefop working paper series – No 7 / December 2021 

CHAPTER 3. 
Results 

Table 2. 

Characteristics of the five workplace learning types across EU 
establishments 

Blocks of 
predictors 

Individual predictors 

Cumulative 
R-square 

R-square change 
per block of var. 

Regression 
coefficient 

.243*** 

-.129*** 

-.033*** 

-.039*** 

-.007 

.002 

.078*** 

.018* 

.035*** 

.062*** 

-.007 

.049*** 

.051*** 

.020 

.002 

-.003 

-.011 

-.076*** 

.016 

.058*** 

.021* 

.036*** 

.136*** 

-.003 

-.036*** 

Country 

Country 

Country 

.051*** 

.051*** 

Size 

Size 

Type (reference: 
single establ.) 

Headquarters 

Subsidiary s. 

Age 

Age 

Establishment 
characteristics 

Construction 

.091*** 

.040*** 

Sector 
(reference: 
industry) 

Retail 

Transport 

Financial 

Other services 

Competitiveness  Competitiveness 

 Predictability 

Predictability 

Market 
conditions 

Business 
strategy 
(reference: 
Price) 

Quality 

Customisation 

Innovation 

No dominant str. 

Skill demand 

Motivational 
levers 

Innovation 

Innovation 

Need for 
learning 
Extrinsic 
motivation 
Direct 
communication 
Influence on 
decisions 
Encouraging 
engagement 

Need for 
learning 
Extrinsic 
motivation 
Direct 
communication 
Influence on 
decisions 
Encouraging 
engagement 

Job autonomy 

Job autonomy 

.101*** 

.010*** 

.110*** 

.009*** 

.170*** 

.060*** 

One team 

.190*** 

.020*** 

Job design 

Importance of 
training 
Learning 
opportunities 

Teamwork 
(reference: no 
teams) 

Importance of 
training 
Formal learning 
opportunities 
Informal 
learning 
opportunities 

Multiple teams 

Importance of 
training 
Formal learning 
opportunities 
Informal 
learning 
opportunities 

.200*** 

.010*** 

.051*** 

.251*** 

.051*** 

.014 

.293*** 

Skill match 

Skill match 

Skill match 

.260*** 

.009*** 

.095*** 

Cedefop working paper series – No 7 / December 2021  

31 

 
 
 
Workplace learning: determinants and consequences:  
insights from the 2019 European company survey 

Note: All variables except skill match indicator are standardised and are placed on a scale with an EU 
average of 100 and standard deviation of 50; skill match indicator represents a proportion of 
workers in an establishment who have matching skills with job requirements. 

Source: European company survey, 2019. 

3.3.2.  Relationship with company performance  
internal  contextual 
The  20  predictors  describing  various  external  and 
characteristics  and  organisational  practices  have  less  explanatory  power  in 
relation to company performance, where they account for 14.2% of the variation in 
the  company  performance  index  (Table  3).  Although  less  than  in  the  case  of 
employee wellbeing, this is still a substantial proportion of accounted information, 
especially when taking into account measurement noise in the indicators.  

The country in which companies are located is still a significant predictor of 
the  company  performance,  accounting  for  1.5%  of  the  variation  in  its  index. 
However, its effect is more than three times smaller than in the case of employee 
wellbeing. Establishment structural characteristics account for the same proportion 
of variance in company performance as they did in the case of employee wellbeing, 
at  4%,  yet  different  characteristics  are  important  for  company  performance  in 
comparison with employee wellbeing. The number of years since a company was 
created is the strongest predictor of company performance among the four in this 
group,  with  younger  companies  being  much  more  likely  to  perform  well.  Single 
establishment  and  larger  companies  also  have  slightly  higher  chances  of  better 
performance. Companies in the construction and transport sectors are also slightly 
better off than those in the industry sector. 

As  expected,  predictable  market  conditions  and  lower  competitiveness  are 
beneficial  for  company  performance.  Companies  whose  dominant  business 
strategy  focuses  on  quality,  customisation  and  innovation  are  more  likely  to 
function well than those who focus on the price of their product. 

In line with previous research and theory, company innovativeness is strongly 
related  to  performance.  Frequent  changes  in  skill  needs  also  have  a  small  but 
positive relationship with company performance. 

Variable  pay  schemes  and  employee  influence  on  decisions  are  positively 
related  to  company  functioning.  At  the  same  time,  direct  communication  and 
encouraged  engagement  do  not  seem  to  have  significant  effects  once  other 
predictors are taken into account. Job autonomy and teamwork both have slight 
positive  effects,  while  the  degree  to  which  management  finds  training  important 
does not seem to influence the performance of companies.  

Formal and non-formal learning opportunities do not have a significant effect 
on company performance, as was the case for employee wellbeing. In contrast, 
informal  learning  opportunities  are  one  of  the  strongest  predictors  of  company 

32  

Cedefop working paper series – No 7 / December 2021 

CHAPTER 3. 
Results 

performance  in  our  model,  even  after  accounting  for  differences  in  the  other  19 
predictors. 

Table 3. 

Characteristics of the five workplace learning types across EU 
establishments 

Blocks of 
predictors 

Individual predictors 

Cumulative 
R-square 

R-square 
change per 
block of var. 

Regression 
coefficient 

Country 

Country 

Country 

.015*** 

.015*** 

Size 

Size 

Type (reference: 
single establ.) 

Headquarters 

Subsidiary s. 

Age 

Age 

Establishment 
characteristics 

Construction 

.055*** 

.040*** 

Sector 
(reference: 
industry) 

Retail 

Transport 

Financial 

Other services 

Competitiveness  Competitiveness 

 Predictability 

Predictability 

Market 
characteristics 

Business 
strategy 
(reference: 
Price) 

Quality 

Customization 

Innovation 

No dominant str. 

.072*** 

.017*** 

Skill demand 

Motivational 
levers 

Job design 

Importance of 
training 
Learning 
opportunities 

Innovation 

Innovation 

Need for 
learning 
Extrinsic 
motivation 
Direct 
communication 
Influence on 
decisions 
Encouraging 
engagement 

Need for 
learning 
Extrinsic 
motivation 
Direct 
communication 
Influence on 
decisions 
Encouraging 
engagement 

Job autonomy 

Job autonomy 

.123*** 

.051*** 

.135*** 

.012*** 

Teamwork 
(reference: no 
teams) 

Importance of 
training 
Formal learning 
opportunities 
Informal 
learning 
opportunities 

One team 

.137*** 

.002*** 

Multiple teams 

Importance of 
training 
Formal learning 
opportunities 
Informal 
learning 
opportunities 

.137*** 

.000 

.141*** 

.004*** 

.123*** 

.055*** 

-.057*** 

-.013 

-.167*** 

.046*** 

.001 

.030** 

-.029** 

-.003 

-.025* 

.087*** 

.103*** 

.082** 

.038*** 

.022* 

.173** 

.041*** 

.079*** 

.000 

.025** 

.015 

.041*** 

.021* 

.020 

-.011 

-.017 

.085*** 

Cedefop working paper series – No 7 / December 2021  

33 

 
Workplace learning: determinants and consequences:  
insights from the 2019 European company survey 

Blocks of 
predictors 

Individual predictors 

Cumulative 
R-square 

R-square 
change per 
block of var. 

Regression 
coefficient 

Skill match 

Skill match 

Skill match 

.142*** 

.000 

-.006 

Note: All variables except skill match indicator are standardised and are placed on a scale with an EU 
average of 100 and standard deviation of 50; skill match indicator represents a proportion of 
workers in an establishment who have matching skills with job requirements. 

Source: European company survey, 2019. 

3.3.3.  Simultaneous  analysis  of  relationships  with  both  outcomes:  general 

linear model 

The  previous  sections  examine  relationships  between  predictors  and  two  main 
outcomes  –  employee  wellbeing  and  company  performance  –  in  separate 
hierarchical  regression  models.  However,  the  two  outcomes  are  correlated  with 
one another (r=.20), which means that the relationships between their predictors 
and outcomes might be somewhat different once taken into account.  

In  Figure  8,  we  present  results  of  the  multivariate  general  linear  model,  in 
which we regressed the same set of predictors on the two outcomes at the same 
time,  thus  accounting  for  the  correlation  between  the  dependent  variables.  As 
expected,  the  results  are  largely  similar  to  those  obtained  in  the  previous  two 
separate hierarchical regression models. However, there are still some differences 
worth noticing.  

The influence of establishment size on both employee wellbeing and company 
performance is stronger than was the case when the two outcomes were analysed 
separately. Similarly, the influence of skill mismatch on employee  wellbeing and 
company performance is somewhat stronger than seemed to be the case in the 
hierarchical  regression  model.  In  contrast,  the  influence  of  market  strategy  on 
company performance is reduced in these models, compared to the hierarchical 
regression model on company performance. 

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CHAPTER 3. 
Results 

Figure 8. 

Strengths of effects of different predictors on employee wellbeing and 
company performance in EU establishments  

NB: Strength of relationships is presented in terms of sum of squares. 
Source: European company survey, 2019. 

3.4.  Workplace environment aspects and learning 

opportunities 

This  section  examines  learning  opportunities  in  companies  and  the  factors  that 
determine  the  scope  of  such  opportunities.  We  particularly  want  to  study  what 
broad contextual characteristics and internal workplace aspects influence the level 
of formal and non-formal learning opportunities and informal learning opportunities. 
As seen in Section 2, institutional theories consider wider national institutional and 
cultural  contexts  as  the  key  determinant  of  learning  opportunities.  In  contrast, 
business  strategy  theory  considers  market  conditions  as  a  critical  factor  in 
companies’  decisions  about  providing  learning  to  their  employees.  To  address 
these  questions,  we  used  hierarchical  regression  models  and  a  multivariable 
general linear model (GLM). Two hierarchical regression models explored how a 
set  of  19  predictors  can  explain  ‘informal  learning’  and  ‘formal  and  non-formal 
learning’ opportunities in a company. 

Cedefop working paper series – No 7 / December 2021  

35 

  
 
Workplace learning: determinants and consequences:  
insights from the 2019 European company survey 

3.4.1.  Relationship with informal learning opportunities 
The selected set of 19 predictors accounts for a relatively high proportion (33%) of 
the  variation  in  informal  learning  opportunities  across  EU  companies  (Table  4). 
Management’s  perceived  importance  of  training  plays  the  most  important  role 
(12.4%), along with the indicators of skills demand (11%), national context (5%) 
and company characteristics and economic sector (3%). Market environment and 
business strategy are responsible for only 1.6% of the variation in informal learning 
opportunities, much less than what might be expected based on market condition 
theories. Various aspects of work organisation have very little or no influence on 
informal  learning  opportunities,  such  as  the  proportion  of  managers  in  the 
workforce,  proportion  of  employees  with  permanent  contracts  and  number  of 
hierarchical  levels.  The  proportion  of  employees  whose  pace  is  determined  by 
machines  has  a  slight  negative  influence,  while  teamwork  has  a  slight  positive 
effect on the number of informal learning opportunities. Skill (mis)match indicators 
have an only marginal influence on learning opportunities and in the unexpected 
direction  of  influence:  higher  proportions  of  underskilled  employees  are  related 
with lower levels of informal learning opportunities.  

Table 4. 

Results of hierarchical regression analysis on informal learning 
opportunities 

Blocks of 
predictors 

Individual 
predictors 

Predictors and 
their individual 
categories 

Cumulative  
R-square 

R-square 
change per 
block of var. 

Regression 
coefficient 

Country 

Country 

Country 

.046*** 

.046*** 

.0214*** 

Size 

Size 

Type (reference: 
single establ.) 

Headquarters 

Subsidiary s. 

Age 

Age 

.011 

.012 

.003 

-.032*** 

Establishment 
characteristics 

Construction 

.079*** 

.032*** 

.050*** 

Sector 
(reference: 
industry) 

Retail 

Transport 

Financial 

Other services 

Competitiveness  Competitiveness 

.027** 

.017* 

.024** 

.101*** 

.013 

Market 
characteristics 

Predictability 

Predictability 

.94*** 

.016*** 

.029*** 

Quality 

.038*** 

36  

Cedefop working paper series – No 7 / December 2021 

CHAPTER 3. 
Results 

Blocks of 
predictors 

Individual 
predictors 

Predictors and 
their individual 
categories 

Cumulative  
R-square 

R-square 
change per 
block of var. 

Regression 
coefficient 

Business 
strategy 
(reference: 
Price) 

Customization 

Innovation 

No dominant str. 

Innovation 

Innovation 

Need for 
learning 
Finding skilled 
empl. 

Need for 
learning 
Finding skilled 
empl. 

% of managers  % of managers 

Permanent 
employ. 
Hierarchical 
levels 
Pace 
determined by 
machines 

Teamwork 

Permanent 
employ. 
Hierarchical 
levels 

Pace determined 
by machines 

One team 

Multiple teams 

Skill demand 

Work 
organisation 

.201*** 

.107*** 

.205*** 

.004*** 

.036*** 

.028** 

.022* 

.099*** 

.204*** 

.033*** 

.005 

-.002 

.005 

-.021** 

.026** 

.057*** 

Importance  of 
training 

Importance of 
training 

Importance of 
training 

Skill (mis)match  Skill match 

Skill match 

Underskilled 

Underskilled 

.329*** 

.124*** 

.380*** 

.332*** 

.003*** 

-.022* 

-.068*** 

Notes:   Statistics marked with *, ** and *** have statistical significance at .05, .01 and .001 levels, 

respectively. 
Predictor variables ‘innovation’, ‘need for learning’, ‘importance of training’ and dependent variable 
‘informal learning opportunities’ are standardised; ‘skill match’ variable represents a proportion of 
workers in an establishment who have matching skills with job requirements. ‘Underskilled’ variable 
represents a proportion of workers who have skills that are insufficient for their jobs. 

Source:   European company survey, 2019. 

3.4.2.  Relationship with formal and non-formal learning programmes 

Table 5 presents the  results of the hierarchical regression model on  formal and 
non-formal learning opportunities in an  establishment, using the same set of 19 
predictors. We can see that these predictors account for a much lower proportion 
of  variation in  training  provision  (21%)  than  was  the  case with  informal  learning 
opportunities. Strengths of effects of broader contextual variables and skill demand 
indicators  are  similar  across  the  two  models.  Work  organisation  aspects  have 
somewhat  larger  effects  on  the  probability  of  having  training  opportunities. 
Companies  with  a  higher  proportion  of  managers,  more  hierarchical  levels  and, 
especially, higher proportion of employees on permanent contracts tend to offer 
their employees slightly more formal and non-formal learning opportunities. 

Cedefop working paper series – No 7 / December 2021  

37 

 
Workplace learning: determinants and consequences:  
insights from the 2019 European company survey 

The main difference  compared with informal learning  opportunities is in the 
effects of management’s perceived importance of training. This predictor accounts 
for more than 12% of variation in informal learning opportunities and only 2.5% of 
the  variation  in  formal  and  non-formal  learning  opportunities.  This  is  surprising, 
especially  when  considering  that  managers  are  asked  about  the  importance  of 
training (formal and non-formal learning programmes) rather than the importance 
of informal learning opportunities. Such results indicate that managers might not 
be  thinking  of  training  courses  specifically  but  rather  of  workplace  learning 
opportunities in general when answering this question. These results could also 
indicate  that  managers'  positive  attitudes  toward  workplace  learning  more  often 
translate into the creation of informal learning opportunities than in formal and non-
formal learning programmes.  

Table 5. 

Results of hierarchical regression analysis on formal and non-formal 
learning opportunities 

Blocks of 
predictors 

Individual 
predictors 

Predictors and 
their individual 
categories 

Cumulative 
 R-square 

R-
square 
change 
per 
block of 
var. 

Regression 
coefficient 

Country 

Country 

Country 

.050*** 

.050*** 

.224*** 

Size 

Size 

Type (reference: 
single establ.) 

Headquarters 

Subsidiary s. 

Age 

Age 

-.006 

.060*** 

.016* 

-.016 

Establishment 
characteristics 

Construction 

.082*** 

.032*** 

.008 

Sector 
(reference: 
industry) 

Retail 

Transport 

Financial 

Other services 

Competitiveness  Competitiveness 

Predictability 

Predictability 

Market 
characteristics 

Business 
strategy 
(reference: 
Price) 

Quality 

Customisation 

Innovation 

No dominant str. 

Innovation 

Innovation 

.088*** 

.006*** 

.010 

-.002 

.066*** 

.059*** 

.002 

.018* 

.044*** 

.030** 

.025** 

.013 

.050 

Skill demand 

Need for 
learning 
Finding skilled 
empl. 

Need for learning 

.180*** 

.091*** 

.254 

Finding skilled 
empl. 

.043 

38  

Cedefop working paper series – No 7 / December 2021 

CHAPTER 3. 
Results 

Blocks of 
predictors 

Individual 
predictors 

Predictors and 
their individual 
categories 

Cumulative 
 R-square 

R-
square 
change 
per 
block of 
var. 

Regression 
coefficient 

Work 
organisation 

% of managers  % of managers 

Permanent 
employ. 
Hierarchical 
levels 
Pace 
determined by 
machines 

Teamwork 

Permanent 
employ. 

Hierarchical levels 

Pace determined 
by machines 

One team 

Multiple teams 

.185*** 

.005*** 

.024** 

.048*** 

.024** 

-.016 

.036*** 

.018 

Importance 
training 

of 

Importance of 
training 

Importance of 
training 

Skill (mis)match 

Skill match 

Skill match 

Underskilled 

Underskilled 

.210*** 

.025*** 

.172*** 

.210*** 

.001* 

-.005 

-.027** 

NB:  

Statistics marked with *, ** and *** have statistical significance at .05, .01 and .001 levels, 
respectively. 
Predictor variables ‘innovation’, ‘need for learning’, ‘importance of training’ and dependent variable 
‘informal learning opportunities’ are standardised; ‘skill match’ variable represents a proportion of 
workers in an establishment who have matching skills with job requirements. ‘Underskilled’ variable 
represents a proportion of workers who have skills that are insufficient for their jobs. 

Source:   European company survey, 2019. 

A general model with all learning opportunities 

3.4.3. 
Considering the high inter-correlation (r=.36) between two dependent variables of 
‘informal’  and  ‘formal  and  ‘non-formal’  learning  opportunities,  we  conducted  a 
multivariable general linear model (GLM) regressing the same set of 19 predictors 
simultaneously on the two learning outcomes. 

Results  of  the  multivariate  GLM  are  presented  in  Figure  9  and  allow  for  a 
clearer representation of the comparative strength of effects of different predictors 
on the two learning outcomes. Although generally in line with the results of the two 
hierarchical  regression  models,  these  findings  also  incorporate  some  important 
differences. For example, the influence of national context, which was largely the 
same in regression models, is now much stronger for formal than informal learning 
opportunities.  Similarly, 
learning  needs  (changing  skill 
requirements) is a stronger predictor of training provisions in this model while in 
individual  regression  models,  the  opposite  was  true.  The  absolute  strength  of 
coefficients has also changed in some cases. Characteristics of companies, such 
as age, size, type, and their economic sector, have less of an effect on either of 
the two dependent variables than they seemed to have in regression models.  

influence  of 

the 

The  most  striking  takeaway  from  GLM  results  is  the  fact  that  only  three 
company aspects overwhelmingly influence both types of learning opportunities in 

Cedefop working paper series – No 7 / December 2021  

39 

 
Workplace learning: determinants and consequences:  
insights from the 2019 European company survey 

companies:  its  national  context,  its  level  of  changing  skill  needs,  and  its 
managements’ perception of the importance of training. The relative importance of 
each of these three aspects differs across the two outcomes, with  the perceived 
importance  of  training  being  much  more  important  for  informal  learning 
opportunities and the other two factors being stronger predictors of formal and non-
formal learning opportunities.  

Figure 9. 

Strengths of effects of different predictors on informal and formal/non-
formal learning opportunities in EU companies  

NB: 
Source:  European company survey, 2019. 

Strength of relationships is presented in terms of sum of squares (type IV). 

40  

Cedefop working paper series – No 7 / December 2021 

 
 
CHAPTER 4.  
Concluding discussion 

4.1.  Workplace learning conditions and practices in 

EU companies 

five  distinct 

types  of  workplace 

learning  environments 

Analysis of patterns of workplace learning characteristics or bundles of practices 
identified 
in  EU 
organisations: typical, extensive, traditional, restrictive and encouraging. Around a 
third  of  companies  belonging  to  the  typical  type  of  learning  environment  have 
average levels of workplace learning practices. Extensive and restrictive type of 
learning environments are largely opposites. Almost a quarter of companies that 
belong to the extensive type offer a higher prevalence of learning practices and 
learning  opportunities,  while  14%  of  companies  that  belong  to  the  restrictive 
category  have  fewer  learning  opportunities  and  a  generally  less  stimulating 
environment.  About  one  fifth  of  companies  that  belong  to  the  traditional  or  lean 
category have much lower skill demand and a slightly below-average frequency of 
learning  practices  and  opportunities.  The  8%  of  companies  belonging  to  the 
encouraging  category  have  higher  levels  of  informal  learning  opportunities  and 
much  higher  levels  of  management  belief  in  the  value  of  training  and  their 
encouragement for employee engagement.  

The five types of workplace learning environments differ along the line of the 
extensive-restrictive dimension and are, as such, mostly in line with the expansive-
restrictive continuum model promoted by Fuller and colleagues (Fuller and Unwin, 
2003; Fuller et al., 2004; Fuller et al., 2005). These results again confirm that larger 
and younger companies, and those working in service sectors, are more likely to 
offer  conducive  learning  environments  than  smaller  and  older  companies  or 
establishments  working  in  manufacturing  sectors.  Results  also  confirm  the 
assumed  influence  of  market  conditions  on  the  propensity  of  various  forms  of 
learning  opportunities  and  practices,  indicating  that  more  stable  and predictable 
environments  lead  to  better  learning  opportunities.  Such  results  might  be 
expected, as an investment in skill development is less likely in conditions of great 
market uncertainty. Market competitiveness is also found to be mainly conducive 
to  workplace  learning  conditions,  indicating  that  companies  are  incentivised  to 
invest in the creation of learning opportunities and skill development when facing 
harsher competition.  

Although  some  theories  (e.g.  Schuler  and  Jackson,  1987;  Porter,  1980) 
assume product market strategies to be some of the most important determinants 
of workplace learning, this does not seem to be the case in our findings. Similarly, 

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Workplace learning: determinants and consequences:  
insights from the 2019 European company survey 

our findings are not aligned with the skill (mis)match literature that higher levels of 
skill mismatch will be one  of the key factors determining the type  and quality of 
workplace learning environments. Such a result could be attributed to the lack of 
relevance of skill (mis)match on workplace learning opportunities but could also be 
attributed to the methodological limitations behind the skill (mis)match indicators 
(see  discussion  of  these  limitations  in  the  section  below).  However,  an  almost 
linear  alignment  of  the  five  identified  types  of  workplace  learning  environment 
across the expansive-restrictive dimension indicates that the selected aspects of 
the workplace learning environment are aligned with one another and are capturing 
a distinct and relevant dimension. Further, their relationship with wider structural 
and  organisational  indicators  is  generally  in  line  with  theoretical  expectations, 
further confirming the validity of the observed typology. Their similar relationship 
with the individual and organisational outcomes illustrates the potential of learning 
workplaces to lead to win-win situations for both employees and employers.  

4.2.  The learning environment and employee and 

company outcomes 

Analyses  of  the  relationship  between  selected workplace  learning  practices  and 
their broader context on employee wellbeing and company performance showed 
that  different  workplace  aspects  have  a  markedly  varied  influence  on  employee 
and organisational outcomes.  

Employee  wellbeing  had  by  far  the  strongest  relationship  with  informal 
learning opportunities. This is a very important finding as it empirically verifies the 
positive effects of workplace learning on workers.  However, results also show a 
lack  of  substantive  effects  of  formal  and  non-formal  learning  opportunities  on 
employee wellbeing. This might be because these programmes cover less relevant 
topics. In many cases, participation in these programmes is compulsory, inhibiting 
workers’ intrinsic motivation and interest, but probably the strongest reason behind 
these results is that formal and non-formal learning programmes are usually much 
less prevalent than informal learning opportunities.  

Job  autonomy  is  another  strong  determinant  of  employee  wellbeing,  in  line 
with previous research and theory (e.g. Eurofound, 2015; Eurofound and Cedefop, 
2020).  Both  national  context  and  establishment  characteristics  are  found  to 
influence employee wellbeing to a substantial degree. Market conditions are not 
that important after controlling for other aspects. Skill demand is found to have a 
slight negative correlation with employee wellbeing, in line with the discussion on 
the  potential  negative  consequences  of  job  intensification.  Motivational  levers, 
especially  open  and  constructive  communication  and  an  encouraging 

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CHAPTER 4. 
Concluding discussion 

environment, strongly influence employee wellbeing. However, extrinsic motivation 
measured  through  variable  pay  schemes  does  not  seem  to  influence  employee 
wellbeing  much.  Skill  (mis)match  is  not  found  to  influence  employee  wellbeing 
once other aspects are considered.  

Company innovativeness is the strongest predictor of company performance, 
followed by organisational characteristics, especially organisations’ age. National 
context and market conditions and strategies are less important for this outcome. 
Job autonomy  is  an important predictor of company performance as well, along 
with informal learning opportunities. Formal and non-formal learning opportunities 
do  not  have  substantial  influence  once  other  workplace  aspects  are  taken  into 
account.  

Taken together, these results offer striking empirical confirmation of the value 
and  importance  of  informal  learning  opportunities  and,  in  general,  stimulating 
learning environments. They are especially valuable given the comprehensive set 
of workplace aspects that we could include and simultaneously control for in these 
regression  models.  Such  strong  predictive  relationships  of  informal  learning 
opportunities  with  company  performance,  and  even  more  so  with  employee 
wellbeing,  are  especially  important  in  comparison  with  small  or  statistically 
insignificant relationships of most of the other examined aspects of workplaces. In 
this  sense,  the  only  other  aspect  that  has  shown  a  substantial  and  consistent 
positive relationship with both outcomes is job autonomy.  

4.3.  Aspects of the workplace environment and 

learning opportunities 

Analysis of the workplace conditions most strongly related to formal and informal 
learning  opportunities  showed  that  the  strongest  predictor  of  the  number  of 
informal learning opportunities turned out to be managers’ perceptions of the value 
and importance of workplace learning. This shows the importance of managerial 
attitudes  on  work  organisation  and  workplace  learning  opportunities.  It  also 
illustrates how much discretionary power managers have in terms of improving the 
workplace learning environment.  

Need for learning (skill demands) and the national context also substantially 
influence informal learning provisions. Market conditions are found to be much less 
related  to  workplace  learning.  Among  organisational  characteristics,  the  service 
sector  is  the  category  that  has  the  highest  effect  on  the  prevalence  of  informal 
learning opportunities.  

As  expected,  skill  demands  are  the  strongest  predictor  of  formal  and  non-
formal learning. Structural conditions such as national context and organisational 

Cedefop working paper series – No 7 / December 2021  

43 

Workplace learning: determinants and consequences:  
insights from the 2019 European company survey 

characteristics are the strongest predictors of the prevalence of formal and non-
formal learning opportunities. Market conditions are not related to the frequency of 
training provisions in establishments, offering further refute to the theories arguing 
their importance for workplace learning. Here again, managers' perceived value of 
training  is  found  to  be  a  strong  predictor  of  formal  and  non-formal  learning 
opportunities.  

In summary, these results illustrate the importance of managers as key factors 
in  the  organisation  of  work  processes  and  structures,  in  allocating  necessary 
learning resources and conditions, and in creating formal and, especially, informal 
learning opportunities. The findings obtained in the case of informal learning are 
particularly important as they challenge some of the preconceptions in the area of 
workplace learning. For example, it is usually assumed that managers and their 
discretionary  powers  are  much  more  important  in  the  case  of  formal  and  non-
formal learning and that their hands are more tied in the case of informal learning 
opportunities.  The  results  suggest  such  assumptions  are  in  contradiction  with 
these empirical findings.  

4.4.  Methodological considerations 

Before final remarks on the findings, a word of caution is due. As with any empirical 
data, ECS 2019 has its own set of methodological limitations representing potential 
measurement error sources. First, although the ECS aimed to draw representative 
samples of EU establishments in private sectors employing 10 or more workers, 
its overall response rate through its ‘push-to-web’ sampling strategy was only 5%. 
Second, although several statistical corrections through stratification variables and 
weighting procedures were implemented to account for observed non-response, 
potential non-response bias could have affected results in unpredictable ways.  

Further,  the  ECS  data  were  obtained  from  the  establishment’s  human 
resource  managers  or  other  establishment  representatives,  meaning  that  the 
reports  represent  one  perspective  that  could  entail  numerous  biases  and 
constraints.  One  potential  limitation  of  such  reports  is  the  possible  lack  of 
information that a reporting HR representative has on various aspects of workplace 
organisation, processes and practices. For example, the question on the degree 
of skill (mis)match requires in-depth insight into the skillset of the establishment 
workforce and, simultaneously, skill requirements of the entire set of job positions 
in an establishment. Such detailed and comprehensive knowledge of these issues 
on the part of the reporting representative might be unlikely, especially in cases of 
middle to large establishments.  

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CHAPTER 4. 
Concluding discussion 

Another even more serious validity threat is possible biased reporting on the 
situation at the workplace. For example, establishment reporting representatives 
might be influenced by social desirability tendency or by acquiescence response 
style  (tendency  to  choose  the  ‘agree’  answer  option  irrespective  of  the  actual 
situation  regarding  the  topic  in  question).  Each  of  these  response  biases  would 
lead to the common method bias in the resulting statistical analyses (Kankaraš et 
al.,  2019).  Such  common  method  biases  could  spuriously 
inflate  some 
intercorrelations in statistical analyses, leading to erroneous conclusions. We have 
tried to control for these methodological threats by careful data examination and 
building analytic models based on the well-tested theoretical frameworks. Through 
the comprehensive approach of including a variety of the most relevant variables 
from the dataset, we have tried to minimise the possibility of spurious effects of 
unaccounted  factors.  Large  differences  in  intercorrelations  across  variables 
indicate  that  common  method  bias,  even  if  present,  is  not  the  overwhelming 
presence,  since  otherwise,  these  intercorrelations  would  be  of  similar  strength 
across variables of related constructs. However, the ultimate test of the validity of 
the  ECS  2019  and  presented  findings  will  be  shown  in  the  results  of  further 
empirical  research  in  this  area.  This  will  be  particularly  true  for  those  results 
obtained from employees themselves but also in those rare, but analytically very 
important, cases where both employee and employer reports are obtained, and a 
composite representation of the workplace learning situation is created. 

The cross-sectional nature of ECS 2019 is another methodological constraint 
as it does not allow for straightforward examination of causal relationships between 
these variables. In several instances in our regression models it might be assumed 
that it would be possible, and sometimes even plausible, that some predictor and 
outcome  variables  could  exchange  their  places  in  the  model.  For  example, 
although the degree of company innovativeness and general level of change in the 
production  processes  and  products  is  usually  assumed  to  be  one  of  the  key 
determinants of the need for skill developments, it could also be the case that good 
workplace  learning  practices  act  as  one  of  the  key  enablers  of  company 
innovativeness.  Similarly, 
learning 
opportunities and a company’s performance is usually, as in this paper, analyses 
from  the  perspective  of  learning  activities  as  factors  that  positively  influence 
company performance, it is also possible that company performance determines 
the  frequency  and  type  of  learning  opportunities.  Such  reversive  and  circular 
relationships  cannot  be  fully  investigated  with  cross-sectional  ECS  2019:  they 
would instead need longitudinal studies that would track down the dynamics and 
causal relationships between different factors. 

relationship  between  workplace 

the 

It should also be noted that ECS 2019 does not capture more detailed forms 
of workplace learning, their intensity, and prevalence. This is especially true for the 

Cedefop working paper series – No 7 / December 2021  

45 

Workplace learning: determinants and consequences:  
insights from the 2019 European company survey 

various  types  of  informal  learning,  such  as  learning  by  doing,  collaborative 
learning,  learning  from  more  experienced  colleagues  or  mentors,  and  incidental 
learning.  Lack  of  such  information  constrained  our  ability  to  explore  potential 
differences  in  drivers  and  consequences  of  different  learning  forms.  Finally,  the 
fact that ECS 2019 data are obtained from establishment representatives, and that 
its questions were referring to establishments as a whole, means that the proper 
unit of analyses of such data is establishments rather than individual workers. This 
limits  the applicability of our findings  to this group level.  It means that observed 
relationships  between  variables,  some  of  which  refer 
individual-level 
characteristics (e.g. employee wellbeing), are valid at establishment level but do 
not  necessarily  hold  at  the  level  of  individual  workers.  Whether  or  not  these 
observed relationships at the establishment level mimic those at the individual level 
would need to be investigated through data obtained from employees themselves. 

to 

4.5.  Conclusions 

Workplace learning is a critical tool for both employees and organisations in 
their adjustment to a growing number of global trends reshaping our workplaces, 
economies,  and  societies.  Workers  learn  most  when  engaging  in  new  and 
challenging activities in which they are granted a sufficient amount of autonomy to 
solve  issues  themselves  or  in  collaboration  with  their  colleagues  or  mentors. 
Informal  learning  is  the  key  aspect  of  workplaces  in  terms  of  company 
performance, especially employee wellbeing. Such findings call for more attention 
from  policy-makers  and  organisation  management  to  various  forms  of  informal 
learning at the workplace. This is especially true when  considering the apparent 
lack of beneficial effects of formal and non-formal learning on employee wellbeing 
and  company  performance.  These  findings  again  illustrate  the  overwhelming 
prominence  of  informal  learning  at  the  workplace  compared  to  formal  and  non-
formal learning forms. But they also indicate the learning potential that exists at 
workplaces.  As  seen  through  the  analysis  of  the  prevalence  of  various  learning 
practices and of different types of learning environments, most companies are still 
not offering optimal learning environments and opportunities to their workers. Such 
a  situation  hurts  both  employees  and  companies.  It  also  presents  an  incredible 
opportunity  for  action,  at  organisational,  national  and  international  levels.  Such 
action must will aim to  create institutional conditions, legal frameworks, learning 
resources,  and  the  right  incentives  for  companies  to  start  organising  their 
workplaces  in  a  way  that  will  facilitate  workplace  learning,  especially  its  various 
informal forms.  

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Warhurst,  C.  and  Findlay,  P.  (2012).  More  effective  skills  utilisation:  shifting  the 
terrain of skills policy in Scotland. SKOPE Research Paper No 107, pp. 1-30. 
https://www.researchgate.net/publication/267381449_More_Effective_Skills_
Utilisation_Shifting_the_Terrain_of_Skills_Policy_in_Scotland 

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References 

Warhurst,  C.  and  Luchinskaya,  D.  (2018).  Skills  utilisation:  definition,  theories, 
approaches  and  measures.  Working  Paper.  Dublin:  Eurofound. 
http://wrap.warwick.ac.uk/112554   

Winch,  A.  and  Ingram,  H.  (2002).  Re-defining  the  focus  of  workplace  learning. 
International.  Journal  of  Contemporary  Hospitality  Management,  Vol.  14, 
No 7, pp. 361-367. https://doi.org/10.1108/09596110210440666 

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Annex 

Data preparation process 

ECS  2019  contains  hundreds  of  variables  describing  various  aspects  of 
establishments. We made use of factor analysis to identify groups of variables that 
were  measuring  the  same  latent  construct,  which  was  then  used  in  subsequent 
analyses as independent variables.  

In  many  cases,  these  were  sets  of  questions  about  the  same  topic.  For 
example, three questions on company innovativeness asked managers to report if 
their  company  has  recently  introduced  new  products,  processes,  or  marketing 
methods. Factor analysis of these three questions revealed one distinct common 
factor  that  accounts  for  almost  two-thirds  of  the  variation  found  in  responses  in 
these three questions. Given the content of these questions, we assumed that this 
new  composite  index  represented  the  degree  of  company  innovativeness  and 
used  it  in  subsequent  analyses.  In  some  other  cases,  questions  about  slightly 
different  workplace  practices  are  found  to  correspond  with  one  another. 
Theoretical expectations drove our initial grouping of variables in these composite 
indices: by knowledge of what aspect of organisational practices a given question 
was  trying  to  measure  and  with  what  other  questions  it  should  correspond. 
However,  once  groups  of  aligned  questions  are  analysed,  those  questions  that 
were not found to be related to other variables through relationship with a common 
latent factor were excluded from the resulting composite index.  

Apart from using principal component analyses to create several composite 
indices, we have also derived a number of variables from original variables in the 
ECS  2019  dataset.  This  is  because  respondents  could  either  give  the  exact 
number  of  employees  or  a  percentage  category  for  some  questions.  These 
questions were then compiled into one composite variable by converting numbers 
to percentage categories. These composite variables were denoted with suffix “_d” 

Employee wellbeing 
We  derived  a  standardised  continuous  variable  for  employee  well-being, 
representing  a  composite  index  of  various  aspects  of  this  construct.  We  used 
variables assessing issues with employee absenteeism (SICKLEAVE), perceived 
low motivation of employees (LOWMOT), difficulties with retention of employees 
(RETAINEMP)  and  the  perceived  quality  of  relationships  between  management 
and employees (QWPREL). The composite index was calculated using exploratory 
factor  analysis.  The  resulting  index  of  employee  wellbeing  is  a  standardised 

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Annex 

variable with a mean zero and standard deviation of 1 when weighted across the 
EU-27 countries.  

Company performance 
The  composite  index  indicating  company  performance  was  extracted  through 
factor analysis using information from the following four variables:  
(a) 

financial results for 2018 (PROFIT_r; derived from PROFIT by excluding not-
for-profit organisations);  

(b)  change in employment since 216 (CHEMP);  
(c)  change  in  the  volume  of  production  or  service  provision  since  2016 

(d) 

(PRODVOL);  
the expected changes in employment levels in the 3 years after the survey 
(CHEMPFUT).  

Product market strategy 
Responding managers were asked to rank four product market strategies in order 
of importance for their establishment. Their answers were collapsed into a single 
variable  with  five  categories,  indicating  which  one  of  the  four  strategies  were 
ranked as most important or, when the respondent had put two or more strategies 
at the top of the ranking, that there was no dominant strategy. 

Learning demand 
We constructed a composite index using results of the factor analysis of following 
variables: 
(a) 
(b)  number of employees at jobs that require continuous training (CONTR_d); 
(c)  number of new recruits that need further training (HIRREADY_d). 

frequency of change in skill demands at work (SKILLCH); 

These three indicators were inter-correlated and have thus led to extraction of 
one common factor, which we interpreted as overall indication of learning or skill 
development demand. 

Skill mismatch 
Variables SKILLMATCH, UNDERSKILL, and OVERSKILL are used as indices of 
skill  (mis)match,  after  all  cases  for  which  the  sum  of  the  three  proportions  was 
smaller than 90% and larger than 110% are excluded.  

Innovation 
The  variable  summarising  innovative  activity  of  the  establishments  was  derived 
through  factor  analysis  of  the  three  variables  that  were  asking  managers  if  the 
introduced  a  new  product  (INNOPROD),  process 
establishment  recently 

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Workplace learning: determinants and consequences:  
insights from the 2019 European company survey 

(INNOPROC) or marketing (INNOMARK). The resulting composite index was thus 
used as a general indicator of the establishment’s innovativeness. 

Extrinsic motivation 
We used factor analysis to calculate an overall index of extrinsic motivation using 
the following four variables indicating percentage of employees using variable pay 
schemes based on: 
(a)  payment by results (VBPRES_d); 
(b)  payment by individual performance (VPINPER_d); 
(c)  payment by team performance (VPGRPE_d); 
(d)  payment by company performance (VPPRSH_d). 

We also used the variable providing the information on the frequency of use 

of monetary rewards to motivate and retain employees (MOTIMON).  

Direct communication with management 
We used factor analysis to construct a composite index of communication quality 
using the respondent answers to questions on whether following communication 
practices were used at the establishment: 
(a)  meetings with immediate managers (REGMEE); 
(b)  meetings open to all employees (STAFFME); 
(c)  dissemination through newsletters, notice boards, etc. (DISSINF); 
(d)  discussion in social media (SOMEDI); 
(e)  use of suggestion schemes (SUGGS). 

Employee influence on decisions  
Using  factor  analysis,  a  composite  index  is  created  to  indicate  the  degree  of 
influence  employees  have  on  management  decisions.  Managers  were  asked  to 
what extent employees directly influenced management decisions with regard to 
the  organisation  and  efficiency  of  work  processes  (MMEPINORG),  dismissals 
(MMEPINDISM), training and skills development (MMEPINTRAIN), working time 
arrangements (MMEPINTIME) and payment schemes (MMEPINPAY). Due to the 
relatively  high  volume  of  missing  data  in  some  of  the  five  variables  (in  several 
establishments,  no  decisions  had  been  taken  in  some  areas),  we  used  the 
technique of multiple imputation. 

Encouraging employee engagement 
A set of questions in the management questionnaire of the ECS 2019 was asking 
respondents  if  the  management  was  taking  certain  discretionary  behaviours  of 
employees  into  account  in  the  process  of  their  performance  evaluations.  In 

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Cedefop working paper series – No 7 / December 2021 

Annex 

particular, managers were reporting if the following behaviours were considered in 
order for employees to be evaluated positively: 
(a)  helping colleagues without being asked (DISCHELP); 
(b)  staying longer hours when needed (DISCHOURS); 
(c)  making suggestions for improvement (DISCSUGG). 

Factor analysis of these items resulted in one composite index summarising 
the  degree  to  which  management  is  encouraging  employee  engagement  and 
discretionary effort.  

Importance of training 
Managers in establishments that provided some type of training were asked about 
the importance of four reasons to provide training: ensuring that employees have 
the skills they need for their current job (TRSKI); allowing employees to acquire 
skills they need to do a job other than their current job, for instance, to allow for job 
rotation or career advancement (TRFLEX); increasing the capacity of employees 
to  articulate  ideas  about  improvements  to  the  establishment  (TRINN);  and 
improving  employee  morale  (TRMOT).  Using  factor  analysis,  we  constructed  a 
composite index of these four variables as an indicator of the perceived importance 
of employee training by the establishment’s management.  

Job autonomy 
We  constructed  an  index of  job autonomy by factor analysing the following four 
variables: 
(a)  percentage  of  employees  who  have  the  possibility  to  work  independently 

organising their time and task schedule [COMORG_d]; 

(b)  managers  allow  employees 

to  carry  out 

their 

tasks  autonomously 

[SUPCHECK]; 

(c)  employees work in teams where team members (and not supervisors) decide 

on the distribution of tasks within the team [TAUTON]; 

(d)  percentage of employees who have the possibility to solve problems on their 

own [COMPPROB_d]. 

Formal and non-formal learning opportunities 
We  compiled  information  on  training  programmes  and  used  factor  analysis  to 
create a composite index indicating the extent of the presence of formal learning 
opportunities. The index was created using the following variables: 
(a)  percentage  of  employees  participating  in  the  paid  training  programmes 

[PAIDTRAIN_d]; 

(b)  percentage of employees who received on-the-job training [ONJOB_d]; 

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Workplace learning: determinants and consequences:  
insights from the 2019 European company survey 

(c)  whether  workload  and  work  schedule  are  adjusted  to  accommodate  the 

employee’s participation in formal training programmes [WPSUPP]. 

Informal learning opportunities/stimulating learning environment 
We also constructed an index that captures a stimulating learning environment and 
informal  learning  opportunities  available  to  the  employees.  This  index  was 
constructed from the following variables: 
(a)  how  often  are  employees  provided  interesting  and  stimulating  work 

[MOTICHAL]; 

(b)  how often are employees provided opportunities for learning and development 

[MOTILEARN]; 

(c)  how often are employees communicated a strong mission, providing meaning 

to their work [MOTIMIS]; 

(d)  percentage  of  employees  with  limited  opportunities  to  learn  new  things 

[LEARNNONEED_d]. 

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Working paper series
No 7 / December 2021

WORKPLACE LEARNING: 
DETERMINANTS AND 
CONSEQUENCES
Insights from the 2019 
European company survey

Miloš Kankaraš
expert

WORKPLACE LEARNING: 
DETERMINANTS AND 
CONSEQUENCES
Insights from the 2019 
European company survey

Workplace learning is a critical tool for both employees and organ-
isations  in  their  continuing  adjustment  to  several  global  trends 
reshaping our workplaces, economies, and societies. This study 
uses the newly published data from the fourth round of the Euro-
pean  company  survey  (ECS  2019)  to  examine  key  drivers  and 
consequences of workplace learning. It shows that EU companies 
have several distinct workplace learning environments that differ 
greatly in their conduciveness to workplace learning. Findings also 
show that managers’ perceptions of the value of workplace learn-
ing and the level of skill demand are some of the key determinants 
of the scope of learning opportunities. Workplace learning is found 
to be the most important predictor of employee wellbeing and one 
of the strongest correlates of company performance. Results also 
show that most EU companies are still not offering optimal learn-
ing  environments  and  opportunities  to  their  workers,  a  situation 
that hurts both employees and companies.

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