The impact of workplace changes and supervisor support on employee learning: a nonlinear perspective

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The impact of workplace changes and supervisor
support on employee learning: a nonlinear
perspective
Roy B. L. Sijbom, Jessie Koen, Roy Peijen & Paul T. Y. Preenen
To cite this article: Roy B. L. Sijbom, Jessie Koen, Roy Peijen & Paul T. Y. Preenen (12
Sep 2024): The impact of workplace changes and supervisor support on employee
learning: a nonlinear perspective, Human Resource Development International, DOI:
10.1080/13678868.2024.2401302
To link to this article: https://doi.org/10.1080/13678868.2024.2401302
© 2024 The Author(s). Published by Informa
UK Limited, trading as Taylor & Francis
Group.
Published online: 12 Sep 2024.
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The impact of workplace changes and supervisor support on
employee learning: a nonlinear perspective
Roy B. L. Sijbom
a
, Jessie Koen
b,c
, Roy Peijen
b
and Paul T. Y. Preenen
b,d
a
Department of Management and Organization, School of Business and Economics, Vrije Universiteit
Amsterdam, Amsterdam, The Netherlands;
b
Sustainable Productivity and Employability, Netherlands
Organization for Applied Scientific Research (TNO), Leiden, The Netherlands;
c
Department of Work &
Organizational Psychology, University of Amsterdam, Amsterdam, The Netherlands;
d
Research Group
Employability Transition, Saxion University of Applied Sciences, Enschede, The Netherlands
ABSTRACT
In this study, we examine how workplace changes relate to employee
participation in formal learning (i.e. participating in a course or train-
ing) and informal learning (i.e. learning from tasks and people at
work). Drawing from work design principles, we propose a nonlinear
relationship between workplace changes and employee learning,
suggesting that multiple changes accelerate employee participation
in learning activities. Additionally, we propose that supervisor sup-
port for learning moderates this relationship. We examined our
hypotheses using survey data from a large subsample of employed
workers who participated in the Netherlands Working Conditions
Survey (NWCS) in 2018 and 2020. Results showed that workplace
changes generally enhance both formal and informal learning.
Specically, we observed a nonlinear relationship for formal learning,
however, the pattern of the curve was a decelerating rather than an
accelerating one. Further, supervisor support for learning was posi-
tively associated with both formal and informal learning and out-
weighed the association of workplace changes with work-related
learning: for employees who experienced high supervisor support,
informal learning depended less on workplace changes, but for for-
mal learning it enhanced the found nonlinear relationship and
resembled a positive curve that gradually attens. Results are dis-
cussed in light of their theoretical and practical contributions.
ARTICLE HISTORY
Received 18 October 2023
Accepted 29 August 2024
KEYWORDS
Formal and informal
learning; work-related
learning; change; supervisor
support; nonlinear
Introduction
Workplace changes have become increasingly common due to labour market developments
such as technological innovation and globalisation (Balliester & Elsheikhi, 2018). These
changes encompass technological advancements, modifications in production offerings, and
alterations in employee-customer interaction. To properly cope with such ongoing workplace
changes, it is essential that employees continually develop new knowledge, skills and abilities
(Armstrong & Foley, 2003; Noe et al., 2014). As such, learning in the workplace is a major
focus for human resource development (Jeong et al., 2018). Learning can occur through
CONTACT Roy B. L. Sijbom r.b.l.sijbom@vu.nl
HUMAN RESOURCE DEVELOPMENT INTERNATIONAL
https://doi.org/10.1080/13678868.2024.2401302
© 2024 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/
licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly
cited. The terms on which this article has been published allow the posting of the Accepted Manuscript in a repository by the author(s) or
with their consent.

formal learning, described as structured educational or training programmes, such as organi-
sation-funded courses and training (Colquitt et al., 2000; Manuti et al., 2015), and through
informal learning, described as unstructured experiential activities that take place outside the
formal educational system (Marsick & Volpe, 1999; Tannenbaum et al., 2010). This study
examines how workplace changes relate to participation in both types of learning.
From a theoretical work design perspective, workplace changes affect both how employ-
ees work and the conditions under which they operate (Parker et al., 2001). These changes
expose employees to new tasks and perspectives, prompting cognitive, motivational, and
behavioural processes that facilitate learning (Noe et al., 2014; Parker, 2017). For example,
technological advancements may require new skills, while new work relationships can
introduce alternative methods and fresh knowledge. Traditionally, studies have focused on
single, isolated workplace changes. However, emerging literature suggests that multiple,
ongoing changes are more representative (Albert et al., 2000; Kiefer, 2005). Rather than
focusing on a single workplace change, we shift the focus towards studying the impact of
multiple workplace changes at the same time – which can be described as the occurrence of
multiple, complementary, and competing change events that overlap in time and content
(Cullen-Lester et al., 2019; Rafferty & Griffin, 2006). We investigate how and when multiple
workplace changes are related to participation in formal and informal learning activities.
Drawing on work design and learning perspectives (Parker et al., 2021), we propose that
multiple workplace changes operate multiplicatively, accelerating participation in learning
activities exponentially. That is, the multiplicity of workplace changes increases the need for
knowledge acquisition by introducing multiple goals, plans, feedback mechanisms, and the
interconnections among these elements. Hence, multiple changes are theorised to accel-
erate employee learning (Myers, 2018; cf.; Parker, 2017) and this relationship is suggested to
be nonlinear (e.g. Wielenga-Meijer et al., 2010).
While workplace changes may compel employees to learn, contextual factors in their
immediate work environment can also encourage (proactive) learning. Supervisors are
one of those factors of influence when it comes to learning participation, because they are
charged, among other things, with bringing learning opportunities to life (Lundqvist
et al., 2023; Purcell & Hutchinson, 2007). Indeed, supervisor support is shown to be
beneficial for enhancing employees’ learning attitudes and behaviour (Kuvaas & Dysvik,
2010; Park et al., 2018) and in the transfer of learning (Blume et al., 2010). Besides directly
influencing learning participation (cf. Noe & Wilk, 1993), we therefore also investigate
supervisor support for learning as a contextual boundary condition for the nonlinear
relationship between workplace changes and employee learning.
Our study contributes to the literature in several ways. First, it explores the nonlinear
relationship between workplace changes and employee learning, revealing complexities
beyond prior research (Wielenga-Meijer et al., 2010). By specifically examining the multi-
plicity of workplace changes, we provide a more fine-grained analysis and understanding of
the assumed nonlinear pattern between workplace changes and employee learning. Second, by
considering supervisor support for learning, our study highlights leaders’ crucial role and
clarifies the boundary conditions under which workplace changes affect employee participa-
tion in learning activities (Noe et al., 2014). Third, our study includes both formal and
informal learning, offering a deeper understanding of employee learning in dynamic work
environments. Practically, our results identify how and when employee learning occurs in
evolving work environments.
2R. B. L. SIJBOM ET AL.

Theoretical background and hypotheses
Workplace changes and employee learning
Workplace changes are pervasive in contemporary organisations, affecting employees’ tasks,
roles, performance, and work conditions (Hetzner et al., 2009; Knight & Parker, 2021). These
changes often require new knowledge, skills, responsibilities, and interactions, thereby
imposing learning demands on employees. For example, employees may need to acquire
new skills to operate emerging technology or they may face new responsibilities in their role
and in their tasks. Consequently, workplace changes can be seen as a primary driver for
employees to engage in learning activities (Bauer & Gruber, 2007; Marsick & Watkins, 2003).
We adopt a work design perspective (Parker, 2017) to understand how workplace
changes affect employee learning. Using Parker’s (2017) ‘work design growth model’ and
Wielenga-Meijer et al. (2010) systematic review as theoretical lenses, we argue that
workplace changes impact both the way employees work and the conditions under
which they do so (Parker et al., 2001). These changes activate cognitive, behavioural,
and affective processes that affect employee learning and development (Parker, 2017).
For instance, workplace changes may lead to increased task roles which can broaden
perspectives and facilitate knowledge acquisition, while new work relationships may
provide more feedback, enhancing skill development (Frese & Zapf, 1994). This occurs
through cognitive processes (e.g. information about the adequacy of one’s mental model)
and motivational processes (e.g. the gap between required and expected performance
motivating a desire to learn). Moreover, workplace changes may involve executing
a broader variety of tasks, establishing new work relationships, or taking on more
responsibility. Such changes can create urgency among employees, compelling them to
acquire new skills, knowledge and abilities, and to develop more effective work strategies
and behaviours (De Witte et al., 2007; Rau, 2006).
Most research on workplace changes tends to view them as having a positive linear
relationship with employee learning (for reviews, see Noe et al., 2014; Wielenga-Meijer
et al., 2010). Yet, two reviews reported mixed findings between workplace change
demands (e.g. increased workload) and learning outcomes, suggesting that this relation-
ship may actually be nonlinear (Taris & Kompier, 2005; Wielenga-Meijer et al., 2010).
A study by Van Ruysseveldt and Van Dijke (2011) provided initial evidence for such
a nonlinear relationship between work design characteristics, workload and autonomy,
and subsequent learning outcomes. Also, Wielenga-Meijer et al. (2011) showed evidence
for a nonlinear relationship between autonomy and learning outcomes in an experi-
mental study. Building on this prior work, we propose that the relationship between
workplace changes and employee learning may be nonlinear as well.
The nonlinear relationship between workplace changes and employee learning
Change events within contemporary organisations are rarely isolated; instead, they often
lead to multiple, interconnected workplace changes. This idea aligns with sociotechnical
systems theory (Cherns, 1976), which is a work design theory that focuses on optimising
both the social and technical aspects of work. According to this theory, organisations are
complex systems comprising many interdependent components. Consequently, a change
HUMAN RESOURCE DEVELOPMENT INTERNATIONAL 3

in one aspect of work necessitates adjustment in other aspects of work to enhance overall
effectiveness (Davies et al., 2017). For example, a technological innovation in bicycle
production can change both the product assembly process and job execution, requiring
employees to master new technology and adjust the order and speed of their tasks.
Similarly, significant change events such as mergers or reorganisations can alter targets,
but also social interactions with colleagues and customers. Thus, change events often
impact multiple interdependent aspects of work design. This raises the question: what
happens when multiple changes occur concurrently?
We propose that multiple workplace changes will accelerate employee learning
exponentially. This assumption is rooted in theory and research in human factors
and work design. Research shows that combining alterations in various work design
characteristics (e.g. autonomy, feedback, job complexity and/or job challenge) can
synergistically accelerate knowledge acquisition and learning (for a review, see
Parker et al., 2021). Specifically, the demand‐control model (Karasek & Theorell,
1990; Taris & Kompier, 2005) suggests that an ‘active job’ with high demands and
high control facilitates knowledge acquisition. Likewise, Frese and Zapf (1994)
argue, based on German action theory, that job autonomy, complexity, and feedback
collectively promote learning. When combined, these work design characteristics
allow workers to engage in a ‘complete’ action sequence involving goal setting, plan
development, decision making, monitoring, and feedback. Over time, workers use
and combine these different job aspects using problem-solving and metacognitive
strategies, leading to better task understanding and enhanced knowledge acquisition
(Parker et al., 2021).
Based on the above, we expect that the nonlinear relationship between workplace
changes and employee learning will follow an accelerating pattern. When no work-
place changes are taking place, there is no need for employees to learn new skills or
abilities, because their current skills are still sufficient to execute tasks. So, there is
hardly any stimulation from the work context to learn, and thus, participation in
formal and informal learning activities will be relative low. When a single workplace
change is taking place, such as a product design modification, employees become
more compelled and engaged to acquire the necessary skills and abilities to deal
with this change. As such, the changes in the work context do stimulate employees
to a certain degree to learn. The necessity to acquire new skills will further increase
when multiple workplace changes occur at the same time because of the multi-
plicative changes that are accompanied by these changes. That is, the amount of
changes in various aspects of how the work is done will increase exponentially due
to the interconnectivity between these different elements (cf. Davies et al., 2017),
which will likely result in an accelerated and multiplicative need to acquire new
skills and abilities. This logic is supported by fundamental insights from the
creativity literature, in which any piece of new information will lead to
a multiplicative series of new combinations (cf. Quinn et al., 1996).
Thus, we propose that the combined impact of multifaceted workplace changes
necessitates a more profound learning experience. To cope and deal with these
exponential requirements in new knowledge, skills and abilities, employees’ participa-
tion in formal learning activities is likely to follow the same pattern and accelerate in
strength. We also expect that engagement in informal learning will increase
4R. B. L. SIJBOM ET AL.

exponentially, thereby enabling employees to learn from their changed work tasks.
We thus hypothesise that:
Hypothesis 1: Workplace changes have a nonlinear relationship with employee (a)
formal learning and (b) informal learning, such that the positive relationship is stronger
at higher levels of workplace changes.
The relationship between supervisor support for learning and employee learning
Work-related learning does not take place in a vacuum: other factors in employees’ direct
work environment may affect employee learning. In fact, workplace learning is
a continuous process in which employees improve themselves by acquiring new knowledge
and skills, rather than a one-time endeavour. The organisation’s learning culture, the social
workplace environment, and supervisors are pivotal examples that shape employees’
learning journey (Ford et al., 1992; Noe et al., 2014). Here, we focus on the role of supervisor
support for learning as a relevant variable for employee learning, because supervisors are
one of the most direct, important and dominant sources of social cues for employees (Chen
& Bliese, 2002) and shown to be a pivotal relational work characteristic that provides social
resources (Ng & Sorensen, 2008; Parker & Knight, 2024).
Supervisor support for learning concerns stimulating employees to acquire new skills,
abilities, and personal development (Kraimer et al., 2011; Maurer et al., 2002). This is
achieved by encouraging participation in training and development programmes and
information exchange with colleagues. By doing so, supervisors signal to employees that
they care for their development (cf. Eisenberger et al., 2002). Evidence from HRD
literature shows that by demonstrating and signalling support for learning, supervisors
motivate employees’ learning and development (Lancaster & DiMilia, 2014; Maurer et al.,
2003). In a related literature, supervisor support appears beneficial for transfer of training
(Blume et al., 2010; Burke & Hutchins, 2007). For example, supervisors may support
transfer of training by assisting in identifying situations to use new skills and in guiding
the application of trained skills (Holton et al., 2000). Our conceptualisation of supervisor
support focuses on encouraging employees to learn new skills and abilities rather than
supporting transfer of training.
Previous work suggests that supervisor support is an important relational work
characteristic critical for employee learning (e.g. Kraimer et al., 2011; Paterson et al.,
2014) and significantly improves employee workplace learning (Wang & Zhang, 2022).
Supervisor support for learning provides employees with the encouragement and assis-
tance to engage in learning (Macneil, 2001), but also conveys expectations that learning is
expected and valued by the organisation (Kuvaas & Dysvik, 2010). For example, super-
visor developmental feedback motivates workplace learning in general, and it aids
employees to (self-)regulate the gaps between their current performance and expected
goals, thus forming a clear direction for self-improvement and development (George &
Zhou, 2007). Accordingly, we hypothesise:
Hypothesis 2: Supervisor support for learning is positively related to employee (a)
formal learning and (b) informal learning.
HUMAN RESOURCE DEVELOPMENT INTERNATIONAL 5

The moderating role of supervisor support for learning
Besides a direct relationship with employee learning, supervisor support for learning
might also be an important contextual condition affecting the nonlinear relationship
between workplace changes and employee learning. Although learning is embedded in
a work context, learning might depend less on workplace changes when employees
experience high levels of supervisor support because they are encouraged to proactively
engage in learning. However, under conditions of low supervisor support, employees are
not stimulated to learn and, consequently, workplace changes may be an essential
triggering factor for learning.
The main premise of our moderating mechanism is that supportive supervisors foster
employee motivation to learn and facilitate access to necessary resources, stimulating
proactive and self-initiated learning regardless of external triggers such as changes at
work. Specifically, supervisors who advocate learning and provide a clear understanding
of available learning structures and possibilities (Kraimer et al., 2011), are more likely to
engage employees in learning activities proactively (Noe et al., 2010). Such supervisors
prioritise employee development by communicating the importance of learning and
demonstrating its value, inspiring employees to take initiative in their own development
(Crouse et al., 2011; Macneil, 2001). Moreover, supportive supervisors act as sponsors of
learning initiatives within organisations, offering both verbal and practical support, such
as making resources available for training and promoting information sharing on the job
(Kim et al., 2019). By facilitating skill acquisition, knowledge enhancement, and provid-
ing diverse learning opportunities, supportive supervisors empower employees to pursue
their goals (Wang & Zhang, 2022). Consequently, employees under supportive super-
visors likely feel empowered and motivated to take action to learn and develop them-
selves, irrespective of changes in the work environment. While some exposure to change
may prompt these employees to further engage in learning, a saturation point may be
reached where additional changes add little to their motivation in developing new skills
and knowledge. Their engagement in learning is already high, and learning also requires
time and resources. In such cases, the positive relationship between changes at work and
employee learning may weaken, as employees are already actively engaged in developing
new skills.
In contrast, when supervisors provide low support for learning, they fail to inspire and
encourage their employees to enhance their skills. These supervisors overlook opportu-
nities to prompt employees to recognise their need for new knowledge. So, learning is
neither encouraged nor conveyed as valuable (Macneil, 2001; Wang & Zhang, 2022).
Consequently, employees lack motivation and encouragement to adapt and acquire new
skills, even when workplace changes arise. However, with each additional change,
employees may begin to feel the pressure to engage in learning as a reaction to these
changes, i.e. primarily driven by necessity rather than the encouragement from their
supervisors. Thus, under conditions of low supervisor support for learning, employees
may only engage in learning when the demands of workplace changes become unavoid-
able. We anticipate that the positive relationship between workplace changes and learn-
ing will initially be weak but will strengthen with the occurrence of multiple changes. In
sum, we hypothesise the following:
6R. B. L. SIJBOM ET AL.

Hypothesis 3: Supervisor support for learning moderates the nonlinear relationship
between workplace changes and employee (a) formal learning and (b) informal learning.
Specifically, the positive relationship between workplace changes and learning is stronger
at higher levels of workplace changes, but only when supervisor support is low.
Conversely, when supervisor support is high, the positive relationship between workplace
changes and learning is weaker at higher levels of workplace changes.
Methods
Research design and procedure
To test our hypotheses, we analysed self-reported survey data from two annual samples (2018
and 2020) of employed workers in the Netherlands. The respondents participated in the
Netherlands Working Conditions Survey (NWCS) for Employees, conducted by the
Netherlands Organization for Applied Scientific Research (TNO) (Hooftman et al., 2019,
2021). The NWCS annually surveys a representative sample of the Dutch labour force,
addressing topics such as mental and physical health, working conditions, and sustainable
employability. The survey employs a sampling strategy that minimises participant overlap
across years. The NWCS is conducted in compliance with the Dutch Personal Data
Protection Act and is approved by an internal review board at TNO. Due to questionnaire
constraints, the NWCS uses abbreviated scales and simplified response options. Detailed
information on the survey methodology and validity can be found in Hooftman et al. (2019,
2021). The collaboration with Statistics Netherlands ensures robust data collection.
Participants were informed about their privacy rights and the confidentiality of their
responses, and their consent was obtained for the use of their answers for research purposes.
Participants were initially contacted with an introductory letter inviting them to take
part in the survey online, which included their login details and an information brochure.
As an incentive, participants had the chance to win a €400 gift card or an iPad for
participating. The current study used data from 2018 and 2020 to test hypotheses related
to formal learning. To test the hypotheses related to informal learning, a subsample of the
2020 data was used because the NWCS implemented a ‘split-half’ design methodology in
2020, in which different constructs are assessed for each subsample. This approach
involved randomly dividing the 2020 sample into two equal halves; questions pertaining
to informal learning were assessed in only one of these groups. For clarity, this subsample
will be referred to as 2020b.
Sample
Table 1 shows the descriptives of the used NWCS samples (2018, 2020 for formal
learning, and 2020b for informal learning). We also ran a model with the combined
2018/2020 sample, and its descriptives are included for clarity. All samples exhibit
relatively similar distributions in terms of supervisor support for learning, gender,
education level, job insecurity, job tenure, and organisational tenure. However, there is
variation in reported participation in formal learning between 2018 and 2020 (see
Table 1; ∆
2020–2018
= −5%).
HUMAN RESOURCE DEVELOPMENT INTERNATIONAL 7

Table 1. Descriptive statistics for the 2018, 2020, 2020b and 2018/2020 samples.
Formal learning
2018
(N = 60,648)
Formal learning
2020
(N = 56,350)
Informal learning
2020b
(N = 28,168)
Formal learning
2018/2020
(N = 116,998)
M SD Min Max N Missing M SD Min Max N Missing M SD Min Max N Missing M SD Min Max N Missing
Formal learning 0.54 0.50 0 1 60,648 0 0.52 0.50 0 1 56,350 0 0.53 0.50 0 1 116,998 0
Yes 0.53 0.00 0 1 32,452 0 0.48 0.00 0 1 29,128 0 0.47 0.00 0 1 55,418 0
No 0.47 0.00 0 1 28,196 0 0.52 0.00 0 1 27,222 0 0.53 0.00 0 1 61,580 0
Informal learning 2.28 0.60 1 3 28,168 0
Workplace changes 1.10 1.16 0 4 60,648 0 1.27 1.22 0 4 56,350 0 1.28 1.23 0 4 28,168 0 1.18 0.20 0 4 116,998 0
Workplace changes - squared 2.56 3.99 0 16 60,648 0 3.12 4.39 0 16 56,350 0 3.14 4.41 0 0.16 28,168 0 2.83 4.19 0 16 116,998 0
Supervisor support for learning 2.02 0.70 1 3 60,648 369 2.06 0.69 1 3 347 0.06 2.07 0.69 1 3 28,168 213 2.04 0.70 1 3 116,998 716
Not at all 0.23 0.00 0 1 14,037 n/a 0.21 0.00 0 1 11,847 n/a 0.21 0.00 0 1 5,831 n/a 0.22 0.00 0 1 25,884 n/a
To a certain extent 0.51 0.00 0 1 30,785 n/a 0.51 0.00 0 1 28,885 n/a 0.51 0.00 0 1 14,434 n/a 0.51 0.00 0 1 59,670 n/a
To a great extent 0.26 0.00 0 1 15,457 n/a 0.27 0.00 0 1 15,271 n/a 0.27 0.00 0 1 7,690 n/a 0.26 0.00 0 1 30,728 n/a
Job insecurity 0.15 0.36 0 1 60,648 0 0.16 0.37 0 1 56,350 0 0.16 0.37 0 1 28,168 0 0.16 0.36 0 1 116,998 0
Education level 2.24 0.73 1 3 60,648 0 2.31 0.73 1 3 56,350 0 2.30 0.73 1 3 28,168 28,168 2.27 0.73 1 3 116,998 0
Low educated 0.18 0.00 0 1 10.677 n/a 0.16 0.00 0 1 8,822 n/a 0.16 0.00 0 1 4,465 n/a 0.17 0.00 0 1 19,499 n/a
Intermediate educated 0.41 0.00 0 1 24,596 n/a 0.38 0.00 0 1 21,298 n/a 0.38 0.00 0 1 10,676 n/a 0.39 0.00 0 1 45,894 n/a
High education 0.42 0.00 0 1 25,375 n/a 0.47 0.00 0 1 26,230 n/a 0.46 0.00 0 1 13,027 n/a 0.44 0.00 0 1 51,605 n/a
Age 42.6 14.4 15 75 60,648 0 42.8 14.5 15 75 56,350 0 42.8 14.5 15 75 28,168 0 42.7 14.4 15 75 116,998 0
Gender 0.50 0.00 0 1 60,648 0 0.50 0.00 0 1 56,350 0 0.50 0.00 0 1 14,354 0 0.50 0.00 0 1 116,998 0
Female 0.50 0.00 0 1 30,152 n/a 0.51 0.00 0 1 28,677 n/a 0.51 0.00 0 1 14,354 n/a 0.50 0.00 0 1 58,829 n/a
Male 0.50 0.00 0 1 30,496 n/a 0.49 0.00 0 1 27,673 n/a 0.49 0.00 0 1 13,814 n/a 0.50 0.00 0 1 58,169 n/a
Organizational tenure 10.80 10.80 0.08 55.30 58,948 1,700 10.60 10.80 0.08 58.40 53,750 2,600 10.60 10.70 0.08 56.3 27,434 734 10.70 10.80 0.08 58.4 113,810 3,188
Job tenure 8.50 9.36 0.08 54.40 58,070 2,578 8.21 9.26 0.08 58.4 54,110 2,240 8.20 9.20 0.08 52.4 27,040 1,128 8.36 9.31 0.08 58.4 112,180 4,818
Note. The descriptive summary above differentiates the 2020 sample based on the distinction between formal and informal learning since not all respondents completed the questions related
to informal learning.
8R. B. L. SIJBOM ET AL.

The 2018 sample consisted of 50.3% men and 49.7% women, with an average
age of 42.6 years (SD = 14.4). In terms of education, 40.6% had vocational training,
41.8% held a bachelor’s or master’s degree, and 17.6% had a high school or other
degree. Respondents had an average job tenure of 8.5 years (SD = 9.4), 10.8 years of
organisational tenure (SD = 10.8), and worked 29.0 hours per week (SD = 11.9). In
2020, the sample consisted of 49.1% men and 50.9% women, with an average age
of 42.8 years (SD = 14.5). Of these, 37.8% had vocational training, 46.5% held
bachelor’s or master’s degrees, and 15.7% had high school or other degrees. On
average, respondents reported 8.21 years of job tenure (SD = 9.3), 10.6 years of
organisational tenure (SD = 10.8), and worked 29.3 hours per week (SD = 11.6).
Measures
The measures presented below were similar in both the 2018 and 2020 waves. Please note
that informal learning was only measured in 2020b.
Workplace change checklist
The workplace change checklist asked whether respondents experienced any significant
structural changes within the last 12 months on the following dichotomous items: (1)
changes in the technology, such as machines or information and communication technol-
ogy (ICT); (2) changes in the way jobs are done or how employees are led; (3) changes in
the products/services to be made or provided; (4) changes in the amount of contact with
customers (or patients, students, or passengers, etc.); and (0) none of those mentioned
above. Every item represents one possible change endeavour, and respondents were asked
to indicate whether this change occurred in their work (yes or no). The workplace change
index was constructed by calculating the sum of the four dichotomous items and thus
ranges from 0 (none of the changes were experienced) to 4 (all four changes were experi-
enced). This variable is used as an ‘index’ rather than a theoretical factor (cf. Kiefer, 2005).
The nonlinear function can be approximated by creating an additional variable that
squares the workplace change values. By incorporating the workplace changes-variable
and its squared counterpart in the modelling, we can evaluate the nonlinear relationship.
Supervisor support for learning
Supervisor support for learning was assessed with the following question: ‘Does your
supervisor encourage the development of your knowledge and skills?’, as outlined by
Koppes et al. (2013). Respondents could select from three response options: (1) not at all;
(2) to a certain extent; or (3) to a great extent.
Employee learning
Formal learning was assessed using a dichotomous variable where respondents indicated
(‘no’ or ‘yes’) whether they had undertaken any work-related training or courses in the
past two years (Koppes et al., 2013). Informal learning was assessed with two items asking
respondents to indicate how much they had learned from (1) tasks they perform for their
jobs; and (2) people at work, such as colleagues, supervisors and customers. Respondents
rated their learning on a scale from (1) ‘not so much’ to (3) ‘very much’. A scale was
constructed by taking the average of those two items (α = 0.73).
HUMAN RESOURCE DEVELOPMENT INTERNATIONAL 9

Control variables
Meta-analytical evidence indicates correlations between demographic variables – such as
gender, educational level, and age – and formal and informal learning behaviours (cf.
Cerasoli et al., 2018; Kleine et al., 2019). Also, research showed that perceived job
insecurity reduces participation in learning activities (Van Hootegem et al., 2023).
Therefore, we included these variables as potential control variables in our study.
Gender was coded as (0) male, (1) female; educational level was categorized as (1) low
educated (ISCED2011-Levels 0–2), (2) intermediate educated (ISCED2011-Levels 3–4),
and (3) high educated (ISCED2011-Levels 5–8); and age was treated as a continuous
variable (range 15–75). Perceived job insecurity was assessed with a single question asking
respondents if they were concerned about job retention, coded as (0) no and (1) yes.
Analytical approach
We used logistic regression models to predict the probability of formal learning and we
used OLS regression models to predict the values of informal learning. For the analyses,
we present both the log-odds/unstandardised coefficients and the standardised coeffi-
cients. The log odds in logistic regression and unstandardised coefficients (b) in regres-
sion represent the change of the outcome for a one-unit change in the predictor variable.
The standardised coefficients (β) are adjusted for the scale of the predictor variables,
allowing for direct comparison of the relative importance of each predictor variable in the
model, regardless of their original scales or units (Aiken & West, 1991). Therefore,
standardised coefficients can be interpreted as follows: effect sizes around 0.10 are said
to be small, effect sizes around 0.30 are medium, and effect sizes of 0.50 or greater are
large (Cohen, 1992).
To test our hypotheses, we entered the variables in three consecutive steps. In the first
step, we entered the linear workplace changes variable, the quadratic workplace changes
variable, and the control variables. In the second step, we entered the supervisor support
for learning variable. Specifically, we included the two dummy variables representing the
extent to which supervisors stimulate employee learning with ‘not at all’ as the reference
category to the model. In the third step, we entered the linear interaction terms between
supervisor support for learning and workplace changes and the interaction terms
between quadratic workplace changes and supervisor support for learning. For clarity,
all interaction terms were centred around their mean (Aiken & West, 1991).
For formal learning, separate analyses were conducted for the 2018, 2020, and 2018/
2020 sample. We included a dummy variable (Sample: 2018 = 0, 2020 = 1) in the combined
sample model to control for annual effects on employee learning estimates. For informal
learning, results are reported only for the 2020b subsample because this construct was not
assessed in earlier NWCS waves and due to the earlier mentioned split-half design.
Results
Tables 2 and 3 provide the results for the hypotheses related to employee’s formal
learning and informal learning, respectively. Hypothesis 1 stated that workplace
changes have a nonlinear relationship with employee formal and informal learning
in such a way that multiple workplace changes accelerate employee learning.
10 R. B. L. SIJBOM ET AL.

Table 2. Log-odds and standardized coefficients (β) for the nonlinear relationship of workplace changes and supervisor support on formal learning for 2018, 2020
and 2018/2020 sample, from logistic regression models.
Formal learning
2018
Formal learning
2020
Formal learning
2018/2020
(1) (2) (3) (1) (2) (3) (1) (2) (3)
Variables
Log-
odds β
Log-
odds β
Log-
odds β
Log-
odds β
Log-
odds β
Log-
odds β
Log-
odds β
Log-
odds β
Log-
odds β
Intercept -1.06
(0.03)
-0.51*** -2.02
(0.04)
-1.38
***
-1.99
(0.04)
-1.41*** -1.07
(0.04)
-0.54*** -2.00
(0.04)
-1.38
***
-2.02
(0.05)
-1.40
***
-1.15
(0.03)
-0.53*** -2.11
(0.03)
-1.39*** -2.11
(0.03)
-1.41***
Workplace changes 0.45
(0.02)
0.36*** 0.44
(0.02)
0.35*** 0.36
(0.05)
0.31*** 0.36
(0.02)
0.33*** 0.35
(0.02)
0.32*** 0.34
(0.05)
0.35*** 0.40
(0.01)
0.35*** 0.39
(0.02)
0.33*** 0.35
(0.03)
0.33***
Workplace changes -squared -0.06
(0.01)
-0.08*** -0.06
(0.01)
-0.08*** -0.04
(0.01)
-0.06** -0.03
(0.01)
-0.05*** -0.03
(0.01)
-0.05*** -0.02
(0.01)
-0.03 -0.05
(0.00)
-0.07*** -0.05
(0.00)
-0.07*** -0.03
(0.01)
-0.04**
Supervisor support for
learning
Not at all (ref.) – – – – – – – – – – – –
To a certain extent 1.03
(0.02)
1.03*** 0.99
(0.03)
1.05*** 0.94
(0.02)
0.94*** 1.01
(0.04)
0.95*** 0.99
(0.02)
0.99*** 1.00
(0.03)
1.00***
To a great extent 1.62
(0.03)
1.62*** 1.57
(0.04)
1.68*** 1.57
(0.03)
1.57*** 1.54
(0.04)
1.62*** 1.60
(0.02)
1.60*** 1.55
(0.03)
1.65***
Supervisor support for
learning
Not at all (ref.) x Workplace
changes
– – – – – –
Not at all (ref.) x Workplace
changes-squared
– – – – – –
To a certain extent x
Workplace changes
0.07
(0.05)
0.04 -0.03
(0.06)
-0.07 0.02
(0.04)
-0.01
To a certain extent x
Workplace changes-
squared
-0.02
(0.02)
-0.02 -0.01
(0.02)
-0.01 -0.01
(0.01)
-0.02
To a great extent x Workplace
changes
0.16
(0.06)
0.07* 0.10
(0.07)
0.03 0.13
(0.05)
0.05**
To a great extent x Workplace
changes-squared
-0.04
(0.02)
-0.06* -0.03
(0.02)
-0.05 -0.04
(0.01)
-0.05**
(Continued)
HUMAN RESOURCE DEVELOPMENT INTERNATIONAL 11

Table 2. (Continued).
Formal learning
2018
Formal learning
2020
Formal learning
2018/2020
(1) (2) (3) (1) (2) (3) (1) (2) (3)
Variables
Log-
odds β
Log-
odds β
Log-
odds β
Log-
odds β
Log-
odds β
Log-
odds β
Log-
odds β
Log-
odds β
Log-
odds β
Job insecurity -0.24
(0.02)
-0.09*** -0.06
(0.02)
-0.02* -0.06
(0.02)
-0.02* -0.37
(0.02)
-0.14*** -0.21
(0.02)
-0.08*** -0.21
(0.02)
-0.08*** -0.31
(0.02)
-0.11*** -0.13
(0.02)
-0.05*** -0.13
(0.02)
-0.05***
Education level
Low educated (ref.) – – – – – – – – – – – –
Intermediate educated 0.64
(0.02)
0.64*** 0.61
(0.03)
0.61*** 0.61
(0.03)
0.61*** 0.56
(0.03)
0.56*** 0.52
(0.03)
0.52*** 0.52
(0.03)
0.52*** 0.61
(0.02)
0.61*** 0.57
(0.02)
0.57*** 0.57
(0.02)
0.57***
High educated 1.14
(0.03)
1.14*** 1.01
(0.03)
1.01*** 1.01
(0.03)
1.01*** 0.97
(0.03)
0.97*** 0.84
(0.03)
0.84*** 0.84
(0.03)
0.84*** 1.06
(0.02)
1.06*** 0.93
(0.02)
0.93*** 0.93
(0.02)
0.93***
Sex
Male (ref.) – – – – – –
Female 0.04
(0.02)
0.02* 0.01
(0.02)
0.01 0.01
(0.02)
0.01 0.09
(0.02)
0.04*** 0.06
(0.02)
0.03*** 0.06
(0.02)
0.03*** 0.06
(0.01)
0.03*** 0.04
(0.01)
0.02** 0.04
(0.01)
0.02**
Age 0.00
(0.00)
0.05*** 0.01
(0.00)
0.08*** 0.01
(0.00)
0.08*** 0.00
(0.00)
0.04*** 0.01
(0.00)
0.08*** 0.01
(0.00)
0.08*** 0.00
(0.00)
0.05*** 0.01
(0.00)
0.08*** 0.01
(0.00)
0.08***
Year
2020 (ref.) – – – – – –
2018 0.15
(0.01)
0.08*** 0.19
(0.01)
0.09*** 0.19
(0.01)
0.09***
N 60,648 60,279 60,279 56,350 56,003 56,003 116,998 116,282 116,282
R
2
0.07 0.14 0.14 0.07 0.12 0.12 0.07 0.13 0.13
Note. ***p < 0.001, **p < 0.01, *p < 0.05, standard errors in parentheses.
12 R. B. L. SIJBOM ET AL.

Logistic regression analyses revealed that the quadratic term of workplace changes was
significant in relation to formal learning for all three samples (2018: Log-odds = −0.06,
β = −0.08, p < .001; 2020: Log-odds = −0.03, β = −0.05, p < .001; 2018/2020: Log-odds =
−0.05, β = −0.07, p < .001; see Table 2’s Model 1 and Figure 1a–c), but not significant in
relation to informal learning (2020b: b = 0.00, β = 0.00, p = .600; see Table 3’s Model 2 and
Figure 1d). Although the results support a nonlinear relationship between workplace
changes and formal learning, Figure 1(a) show that the curve of these nonlinear relation-
ships is a decelerating curve rather than the hypothesised accelerating curve. Therefore,
Hypothesis 1a and 1b were not supported.
Table 3. Unstandardized (b) and standardized coefficients (β) for the linear relationship of workplace
changes and supervisor support on informal learning for 2020b sample, from OLS regression models.
Informal learning
2020b
(1) (2) (3) (4)
Variables b β b β b β b β
Intercept 2.22
(0.01)
−0.21*** 2.23
(0.01)
−0.22*** 1.83
(0.01)
−0.83*** 1.81
(0.02)
−0.82***
Workplace changes 0.04
(0.00)
0.08*** 0.04
(0.01)
0.08*** 0.03
(0.00)
0.06*** 0.05
(0.01)
0.10***
Workplace changes – squared 0.00
(0.00)
0.00
Supervisor support for learning
Not at all (ref.) – – – –
To a certain extent 0.41
(0.01)
0.69*** 0.43
(0.01)
0.69***
To a great extent 0.75
(0.01)
1.25*** 0.78
(0.01)
1.25***
Supervisor support for learning
Not at all (ref.) x Workplace changes – –
To a certain extent x Workplace
changes
−0.02
(0.01)
−0.03*
To a great extent x Workplace changes −0.03
(0.01)
−0.06***
Job insecurity −0.13
(0.01)
−0.08*** −0.13
(0.01)
−0.08*** −0.05
(0.01)
−0.03*** −0.05
(0.01)
−0.03***
Education level
Low educated (ref.) – – – – – – – –
Intermediate educated 0.07
(0.01)
0.12*** 0.07
(0.01)
0.12*** 0.04
(0.01)
0.06*** 0.04
(0.01)
0.06***
High educated 0.22
(0.01)
0.37*** 0.22
(0.01)
0.37*** 0.13
(0.01)
0.22*** 0.13
(0.01)
0.22***
Sex
Male (ref.) – – – – – – – –
Female 0.04
(0.01)
0.04*** 0.04
(0.01)
0.04*** 0.03
(0.01)
0.03*** 0.03
(0.01)
0.03***
Age −0.00
(0.00)
−0.07*** −0.00
(0.00)
−0.07*** −0.00
(0.00)
−0.05*** −0.00
(0.00)
−0.05***
N 28,168 28,168 27,955 27,955
R
2
0.05 0.05 0.23 0.23
Note. ***p < 0.001, **p < 0.01, *p < 0.05, standard errors in parentheses.
HUMAN RESOURCE DEVELOPMENT INTERNATIONAL 13

Hypothesis 2 stated that supervisor support for learning is positively related to employee
formal (H2a) and informal learning (H2b). Results showed that high levels of supervisor
support for learning (‘to a great extent’) positively and significantly impacted formal (2018:
Log-odds = 1.62, β = 1.62, p < .001; 2020: Log-odds = 1.57, β = 1.57, p < .001; 2018/2020:
Log-odds = 1.60, β = 1.60 p < .001, see Table 2’s Model 2) and informal learning (2020b: b =
0.75, β = 1.25, p < .001, see Table 3’s Model 3) compared to low levels (‘not at all’). Moderate
levels of supervisor support for learning (‘to a certain extent’) positively impacted formal
learning (2018: Log-odds = 1.03, β = 1.03, p < .001; 2020: Log-odds = 0.94, β = 0.94, p < .001;
2018/2020: Log-odds = 0.99, β = 0.99, p < .001, see Table 2’s Model 2) and informal learning
(2020b: b = 0.41, β = 0.69, p < .001, see Table 3’s Model 3) compared to low levels, but less
prominently, supporting Hypothesis 2a and 2b.
Hypothesis 3 stated that supervisor support for learning moderates the nonlinear relation-
ship between workplace changes and formal (H3a) and informal learning (H3b). Model 3 in
Table 2 includes the interaction effects between the squared workplace changes term and the
Figure 1. Predicted probabilities of the nonlinear relationship between workplace changes and formal
learning (a, b, c) and the linear relationship between workplace changes and informal learning (d).
14 R. B. L. SIJBOM ET AL.

two dummy variables representing supervisor support. Results show a significant moderating
effect of supervisor support for learning on the nonlinear relationship between workplace
changes and formal learning for the 2018 sample (Log-odds = −0.04, β = −0.06, p = .022;
Figure 2a) and for the 2018/2020 sample (Log-odds = −0.04, β = −0.05, p = .006; Figure 2c).
The interaction effect was not significant in the 2020 sample (Figure 2b).
Figure 2. The moderating effect of supervisor support for learning on the nonlinear relationship
between workplace changes and formal learning (a, b, c) and on the linear relationship between
workplace changes and informal learning (d).
HUMAN RESOURCE DEVELOPMENT INTERNATIONAL 15

To assess the curves of the interaction in more detail, we conducted simple slope tests.
We tested the simple slopes for low (−2SD), moderate (Mean) and high levels of workplace
changes (+2SD) on the probability of formal learning (cf. Caniëls et al., 2021). For the
curve of low supervisor support, the simple slope at low levels of workplace changes
(−2SD) was positive (2018: β = 0.539, 95%CI [0.359, 0.718]; 2020: β = 0.469, 95%CI
[0.270, 0.669]; 2018/2020: β = 0.504, 95%CI [0.370, 0.638]), the simple slope at
moderate levels of workplace changes was positive but weaker (2018: β = 0.309, 95%
CI [0.260, 0.358]; 2020: β = 0.348, 95%CI [0.298, 0.398]; 2018/2020: β = 0.329, 95%CI
[0.294, 0.364]), and the simple slope at high levels of workplace changes (+2SD) further
declined in strength but remained significant in two samples (2018: β = 0.08, 95%CI
[−0.040, 0.199]; 2020: β = 0.227, 95%CI [0.082, 0.371]; 2018/2020: β = 0.154, 95%CI
[0.061, 0.247]. For the curve of high supervisor support, the simple slope at low levels of
workplace changes was positive (2018: β = 0.842, 95%CI [0.672, 1.011]; 2020: β = 0.686,
95%CI [0.517, 0.855]; 2018/2020: β = 0.759, 95%CI [0.639, 0.880], the simple slope at
moderate levels of workplace changes continued to be positive (2018: β = 0.381, 95%CI
[0.334, 0.428]; 2020: β = 0.375, 95%CI [0.332, 0.417]; 2018/2020: β = 0.376, 95%CI [0.345,
0.408], but the simple slope at high levels of workplace changes was no longer significant
(2018: β = −0.080, 95% [−0.191, 0.032]; 2020: β = 0.064, 95%CI [−0.062, 0.189]; 2018/2020:
β = −0.007, 95%CI [−0.091, 0.077]). Thus, Hypothesis 3a is partly supported. Hypothesis
3b was not supported because earlier results did not reveal a nonlinear relationship
between workplace changes and informal learning.
Exploratory analysis
Although the nonlinear relationship between workplace changes and informal
learning was not significant, a significant linear relationship was found. We
explored the moderating effect of supervisor support on this linear relationship.
Results showed that supervisor support for learning moderated this relationship
(2020b: b = −0.03, β = −0.06, p < .001; see Table 3, Model 4). Simple slope analyses
revealed that for low supervisor support for learning, the simple slope was
positive (2020b: β = 0.046, 95%CI [0.035, 0.058]). When supervisor support for
learning was high, the simple slope was still positive (2020: β = 0.019, 95%CI
[0.010, 0.029]), but significantly weaker, as indicated by non-overlapping confi-
dence intervals. Hence, workplace changes were less strongly associated with
informal learning when supervisors stimulated learning compared to when they
did not. As shown in Figure 2(d), under conditions of high supervisor support for
learning, employees were more likely to engage in informal learning and they
were less influenced by workplace changes.
Discussion
This study shows that workplace changes are positively related to employee learning,
both formal and informal. That is, people who experience a high number of work-
place changes also indicate higher engagement in learning. For formal learning, this
relationship was nonlinear, resembling a positive curve that gradually flattens: parti-
cipation in learning activities decelerated when multiple workplace changes occurred
16 R. B. L. SIJBOM ET AL.

at the same time. For informal learning, this relationship was linear rather than
nonlinear: participation in learning activities increased with the number of workplace
changes.
This study further shows that supervisor support for learning plays a significant role in
both employee formal and informal learning: high supervisor support was strongly and
positively related to both types of learning. Even moderate levels of supervisor support
had a positive impact, though to a lesser extent. Under conditions of high supervisor
support, the relationship between workplace changes and formal learning was strongly
positive with a relatively steep incline in formal learning, although this association
became weaker when workplace changes further increased. The same pattern was
found for the linear association between workplace changes and informal learning:
workplace changes had less impact when supervisors provided more support. Notably,
the strength of the association between workplace changes and formal learning under
conditions of low and high supervisor support was most prominent when workplace
changes were low (−2SD). This supports the idea that when there are few workplace
changes, supervisors have a crucial role in stimulating formal learning. Altogether, these
findings provide valuable insights into how workplace changes, supervisor support, and
learning are connected.
Theoretical implications and future research directions
Our study has several theoretical implications. First, our study shows that the likelihood
of engaging in both employee formal and informal learning increases as workplace
changes increase. Unexpectedly − and in contrast to recent research on work design
principles and learning that has speculated on accelerating effects (Noe et al., 2014;
Parker, 2017; Parker & Grote, 2020) − the results also suggest that the relationship
between workplace changes and formal learning follows a decelerating rather than
accelerating trend: the positive effect on formal learning diminished as employees
experienced an increasing number of workplace changes. In other words, while work-
place changes generally enhance engagement in learning, there appears to be a tipping
point where additional changes no longer boost, and may even hinder, participation in
formal learning.
Second, our study finds that the distinction between formal and informal learning
goes beyond their characteristics and outcomes to encompass their antecedents. While
work design theory suggests that workplace changes prompt participation in both types
of learning, our study reveals differing patterns. Specifically, we observed an initial rapid
increase in formal learning participation with workplace changes, potentially surpassing
that of informal learning activities. This trend could stem from increased attractiveness
or urgency in facilitating structured learning activities amidst multiple workplace
changes, prompting employees to prioritise investments in learning via formal learning
programmes. This aligns with Nikolova et al. (2016), who stress the organisation’s role in
supporting and safeguarding employee learning, especially during periods of work
restructuring. However, our findings go further, showing that while formal learning
initially accelerated, it eventually plateaued, whereas participation in informal learning
continued on a steady upward trajectory.
HUMAN RESOURCE DEVELOPMENT INTERNATIONAL 17

The positive yet decelerating pattern for formal learning versus the positive linear
pattern for informal learning may be attributed to the nature of these types of
employee learning. Formal learning requires considerable time and resources and is
orchestrated by organisations to align with organisational objectives, while informal
learning is more accessible, less costly, and often spontaneous as workers encounter
new challenges (Cerasoli et al., 2018; Manuti et al., 2015). Given its costly and time-
consuming nature, workplace changes may stimulate formal learning only to a limited
extent, with a point of saturation at which additional changes may not further
increase the motivation, necessity, or likelihood to participate in formal learning.
Multiple workplace changes may create high pressure and demands for employees,
limiting engagement in costly learning activities (Cerasoli et al., 2018). Some scholars
suggest that only moderate levels of demands prompt learning (e.g. Wielenga-Meijer
et al., 2010), while excessive demands can overwhelm workers (Bakker & Demerouti,
2017). Conservation of Resources Theory (Hobfoll et al., 2018) posits that high
demands deplete resources, impairing information processing and reducing employ-
ees’ willingness to learn (Eysenck & Calvo, 1992; Warr & Downing, 2000).
Consequently, under conditions of multiple workplace changes, employees may be
less inclined to engage in formal learning activities that require substantial resource
investment, preferring less resource costly and less time-consuming informal learning
activities.
Third, our study emphasises the crucial role of supervisor support for learning in
fostering employee participation in formal and informal learning activities, especially
during times of change. Supervisor support significantly enhances employee partici-
pation in formal learning programmes and increases their likelihood of informal
learning from tasks and colleagues. This aligns with literature highlighting super-
visors’ influence in promoting both types of learning (e.g. Birdi et al., 1997; Cerasoli
et al., 2018; Colquitt et al., 2000; Gerards et al., 2020; Tannenbaum et al., 2010).
Notably, we found a relatively strong positive relationship between workplace changes
and formal learning when supervisors encourage employee learning: well-supported
employees showed high engagement in formal learning activities even with few
changes, quickly scaling up, though this positive relationship weakened with more
workplace changes.
The intriguing finding that supported employees engaged in formal learning even
during periods of minimal workplace changes, where an immediate imperative may not
exist, prompts deeper exploration. From a motivational perspective, studies on super-
visor support and learning assume that social support motivates discretionary learning
activities, which can be reinforced and encouraged by others (cf. Parker et al., 2021). Our
results align with Nikolova et al.’s (2016) conclusion that an appreciation learning
climate – offering incentives for learning – motivates employees to learn even when
new skills are not urgently needed. However, our findings suggest that workplace changes
and supervisor support might stimulate employee motivation to participate in formal
learning in complementary ways. While workplace changes primarily stimulate extrinsic
learning motivations – addressing skill gaps and productivity – supervisor support fosters
intrinsic motivation, accelerating learning participation. This stimulation of intrinsic
motivation can lead to proactive learning behaviours, resulting in a rapid and steep
increase in formal learning activities when combined with initial workplace changes.
18 R. B. L. SIJBOM ET AL.

Although speculative, these insights underscore the role of leadership in fostering
employee learning amidst workplace changes.
Practical implications
This study offers two concrete, actionable insights on how HRM and managers can
effectively manage and leverage workplace changes to enhance employee learning and
development. First, our findings emphasise the importance of considering the timing and
nature of learning initiatives to stimulate employee development during workplace
changes. We found that workplace changes are associated with both formal and informal
learning. However, too many changes did not further stimulate employees’ engagement
in formal learning. Thus, investing in formal learning programmes is most valuable when
the amount of workplace changes is moderate. During periods of relative stability (i.e. no
or few changes), supervisors play a crucial role in stimulating employees in both forms of
learning. Notably, many workplaces benefit from a balanced combination of both formal
and informal learning approaches, as these cater to different types of knowledge acquisi-
tion (Manuti et al., 2015).
Second, our study revealed that supervisor support for learning had a direct positive
influence on formal and informal learning, while also enhancing the learning-inducive
properties of workplace changes. Consequently, training and guiding supervisors to
actively support and encourage employee learning is a valuable investment before and
during workplace changes. Supervisors should communicate clear expectations that the
organisation values continuous learning (Ellström & Ellström, 2014). Additionally,
providing developmental feedback can stimulate workplace learning and enhance
employees’ self-regulation regarding self-improvement and development (Kluger &
DeNisi, 1996). Establishing a culture of learning support among supervisors (i.e. an
appreciation culture, cf. Nikolova et al., 2016) can yield significant benefits for overall
employee development (Garvin, 2000). It is important to acknowledge, however, that not
all associations in the current study were consistent across various samples, underscoring
the need to customise leadership development approaches to specific contextual factors.
Limitations and directions for future research
This study has several limitations and methodological considerations. First, our study
relied on self-report data from the NWCS. Using self-reports to measure objective
workplace conditions (i.e. workplace changes) may have introduced measurement inac-
curacies (Spector & Jex, 1991). Furthermore, the cross-sectional data also prevents us
from establishing causality, even though our theoretical rationale argues for a causal
relationship (i.e. workplace changes predict employee learning; supervisor support pre-
dict learning), consistent with prior research (Blume et al., 2010; Colquitt et al., 2000;
Knight & Parker, 2021; Parker, 2014). Yet, it is possible that employee learning can
instigate workplace changes or increase supervisor support. Additionally, our data
cannot rule out the influence of third variables, such as an organisational culture
promoting innovation, on both employee learning and experienced workplace changes.
Conducting longitudinal studies or natural experiments could offer more conclusive
evidence.
HUMAN RESOURCE DEVELOPMENT INTERNATIONAL 19

Second, we did not explore how different combinations of multiple workplace
changes affect learning. Previous work design research emphasised that integrating
diverse work characteristics may particularly prompt learning. Specific combina-
tions, such as autonomy, demands, complexity, and feedback, can enhance knowl-
edge acquisition through cognitive or motivational processes (Parker et al., 2021).
This suggests that the significance of workplace changes for learning may vary
based on specific work characteristic alterations, individual motivations, or contex-
tual factors. Future research could investigate interactions between different work-
place changes, thereby advancing our understanding of the relationship between
workplace changes and employee learning. Relatedly, although it is generally
assumed that certain workplace changes may impact multiple work design char-
acteristics, we did not actually measure these characteristics. Future research should
investigate which individual work design characteristics are affected by workplace
changes.
Third, workplace changes seem to stimulate employee learning, but it is crucial to
recognise that our results suggest that too many changes can overwhelm employees,
making it harder to engage in learning activities (Cerasoli et al., 2018; Parker et al., 2021).
This finding calls for further investigation. Earlier studies indicate that excessive
demands can overload workers, impairing cognitive information processing and, conse-
quently, learning (e.g. Bakker & Demerouti, 2017; Hobfoll et al., 2018; Warr & Downing,
2000). Thus, when faced with numerous workplace changes, employees may experience
cognitive overload, hindering learning. Investigating information overload as mediating
mechanisms for the nonlinear relationship workplace changes and learning could offer
valuable insights.
Lastly, while our NWCS data provides a large and representative sample of the Dutch
labour force, the measurement scales had a limited number of items to ensure high
response rates. This decision involved a trade-off with more comprehensive measure-
ments. Also, we used relatively general measures for assessing workplace changes and
formal learning. For instance, we asked respondents whether they had participated in
a formal training programme, while such programmes can vary widely in format and
content, duration, frequency, and relevance to the work context. Hence, our findings
warrant caution in advising specific formal learning activities. Regarding workplace
changes, we inquired whether participants had experienced four types of changes but
did not assess their impact or severity. For future research, we recommend using
measurement instruments with more items to enhance measurement precision and to
provide a more fine-grained picture.
Conclusion
In conclusion, this study illuminates the complex relationship between workplace
changes, supervisor support, and employee learning. The key findings reveal that
workplace changes can serve as motivational sources for both formal and informal
employee learning, although for formal learning only up to a certain point. Supervisor
support for learning emerged as a significant factor for work-related learning,
strongly influencing employee learning itself and also boosting the motivational
force of workplace changes for formal learning. Despite limitations, this study
20 R. B. L. SIJBOM ET AL.

provides actionable insights and opens avenues for future research, enhancing our
understanding of the interplay between workplace dynamics, support, and employee
learning.
Disclosure statement
No potential conflict of interest was reported by the author(s).
ORCID
Roy B. L. Sijbom http://orcid.org/0000-0001-8473-3903
Jessie Koen http://orcid.org/0000-0001-9831-0450
Roy Peijen http://orcid.org/0000-0002-5556-3340
Paul T. Y. Preenen http://orcid.org/0000-0002-1304-282X
Data availability
The raw data supporting the conclusions of this manuscript will be available to any qualified
researcher from the second author upon request.
References
Aiken, L. S., & West, S. G. (1991). Multiple regression: Testing and interpreting interactions. Sage.
Albert, S., Ashforth, B. E., & Dutton, J. E. (2000). Organizational identity and identification:
Charting new waters and building new bridges. Academy of Management Review, 25(1), 13–17.
https://doi.org/10.5465/amr.2000.2791600
Armstrong, A., & Foley, P. (2003). Foundations for a learning organization: Organization learning
mechanisms. The Learning Organization, 10(2), 74–82. https://doi.org/10.1108/
09696470910462085
Bakker, A. B., & Demerouti, E. (2017). Job demands–resources theory: Taking stock and looking
forward. Journal of Occupational Health Psychology, 22(3), 273–285. https://doi.org/10.1037/
ocp0000056
Balliester, T., & Elsheikhi, A. (2018). The future of work: A literature review. Research Department
Working Paper No, 29. International Labour Office.
Bauer, J., & Gruber, H. (2007). Workplace changes and workplace learning: Advantages of an
educational micro perspective. International Journal of Lifelong Education, 26(6), 675–688.
https://doi.org/10.1080/02601370701711364
Birdi, K., Allan, C., & Warr, P. (1997). Correlates and perceived outcomes of four types of
employee development activity. Journal of Applied Psychology, 82(6), 845–857. https://doi.org/
10.1037/0021-9010.82.6.845
Blume, B. D., Ford, J. K., Baldwin, T. T., & Huang, J. L. (2010). Transfer of training: A
meta-analytic review. Journal of Management, 36(4), 1065–1105. https://doi.org/10.1177/
0149206309352880
Burke, L. A., & Hutchins, H. M. (2007). Training transfer: An integrative literature review. Human
Resource Development Review, 6(3), 263–296. https://doi.org/10.1177/1534484307303035
Caniëls, M. C. J., de Jong, J. P., & Sibbel, H. (2021). The curvilinear relation between work
predictability and creativity. Creativity Research Journal, 34(3), 308–323. https://doi.org/10.
1080/10400419.2021.1994204
HUMAN RESOURCE DEVELOPMENT INTERNATIONAL 21

Cerasoli, C. P., Alliger, G. M., Donsbach, J. S., Mathieu, J. E., Tannenbaum, S. I., & Orvis, K. A.
(2018). Antecedents and outcomes of informal learning behaviors: A meta-analysis. Journal of
Business & Psychology, 33(2), 203–230. https://doi.org/10.1007/s10869-017-9492-y
Chen, G., & Bliese, P. D. (2002). The role of different levels of leadership in predicting self- and
collective efficacy: Evidence for discontinuity. Journal of Applied Psychology, 87(3), 549–556.
https://doi.org/10.1037/0021-9010.87.3.549
Cherns, A. (1976). The principles of sociotechnical design. Human Relations, 29(8), 783–792.
https://doi.org/10.1177/001872677602900806
Cohen, J. (1992). A power primer. Psychological Bulletin, 112(1), 155–159. https://doi.org/10.1037/
0033-2909.112.1.155
Colquitt, J. A., Lepine, J. A., & Noe, R. A. (2000). Toward an integrative theory of training
motivation: A meta-analytic path analysis of 20 years of research. Journal of Applied
Psychology, 85(5), 678–707. https://doi.org/10.1037/0021-9010.85.5.678
Crouse, P., Doyle, W., & Young, J. D. (2011). Workplace learning strategies, barriers, facilitators
and outcomes: A qualitative study among human resource management practitioners. Human
Resource Development International, 14(1), 39–55. https://doi.org/10.1080/13678868.2011.
542897
Cullen-Lester, K. L., Webster, B. D., Edwards, B. D., & Braddy, P. W. (2019). The effect of multiple
negative, neutral, and positive organizational changes. European Journal of Work &
Organizational Psychology, 28(1), 124–135. https://doi.org/10.1080/1359432X.2018.1544896
Davies, R., Coole, T., & Smith, A. (2017). Review of socio-technical considerations to ensure
successful implementation of industry 4.0. Procedia Manufacturing, 11(June), 1288–1295.
https://doi.org/10.1016/j.promfg.2017.07.256
De Witte, H., Verhofstadt, E., & Omey, E. (2007). Testing Karasek’s learning and strain hypotheses
on young workers in their first job. Work & Stress, 21(2), 131–141. https://doi.org/10.1080/
02678370701405866
Eisenberger, R., Stinglhamber, F., Vandenberghe, C., Sucharski, I. L., & Rhoades, L. (2002).
Perceived Supervisor support: Contributions to perceived organizational support and employee
retention. Journal of Applied Psychology, 87(3), 565–573. https://doi.org/10.1037//0021-9010.87.
3.565
Ellström, E., & Ellström, P. E. (2014). Learning outcomes of a work-based training programme:
The significance of managerial support. European Journal of Training & Development, 38(3),
180–197. https://doi.org/10.1108/EJTD-09-2013-0103
Eysenck, M. W., & Calvo, M. G. (1992). Anxiety and performance: The processing efficiency
theory. Cognition & Emotion, 6(6), 409–434. https://doi.org/10.1080/02699939208409696
Ford, J. K., Quinones, M. A., Sego, D. J., & Sorra, J. S. (1992). Factors affecting the opportunity to
perform trained tasks on the job. Personnel Psychology, 45(3), 511–527. https://doi.org/10.1111/
j.1744-6570.1992.tb00858.x
Frese, M., & Zapf, D. (1994). Action as the core of work psychology: A German approach. In
H. C. Triandis, M. D. Dunnette, & L. M. Hough (Eds.), Handbook of industrial and organiza-
tional psychology (Vol. 4, pp. 271–340). Consulting Psychologists Press.
Garvin, D. A. (2000). Learning in action: A Guide to putting the learning organization to work.
Harvard Business School Press.
George, J. M., & Zhou, J. (2007). Dual tuning in a supportive context: Joint contributions of
positive mood, negative mood, and supervisory behaviors to employee creativity. Academy of
Management Journal, 50(3), 605–622. https://doi.org/10.5465/AMJ.2007.25525934
Gerards, R., de Grip, A., & Weustink, A. (2020). Do new ways of working increase informal
learning at work? Personnel Review, 50(4), 1200–1215. https://doi.org/10.1108/PR-10-2019-
0549
Hetzner, S., Gartmeier, M., Heid, H., & Gruber, H. (2009). The interplay between change and
learning at the workplace: A qualitative study from retail banking. Journal of Workplace
Learning, 21(5), 398–415. https://doi.org/10.1108/13665620910966802
Hobfoll, S. E., Halbesleben, J., Neveu, J. P., & Westman, M. (2018). Conservation of resources in
the organizational context: The reality of resources and their consequences. Annual Review of
22 R. B. L. SIJBOM ET AL.

Organizational Psychology & Organizational Behavior, 5(1), 103–128. https://doi.org/10.1146/
annurev-orgpsych-032117-104640
Holton, E. F., III, Bates, R. A., & Ruona, W. E. A. (2000). Development of a generalized learning
transfer system inventory. Human Resource Development Quarterly, 11(4), 333–360. https://doi.
org/10.1002/1532-1096(200024)11:4<333::AID-HRDQ2>3.0.CO;2-P
Hooftman, W. E., Mars, G. M. J., Janssen, B., de Vroome, E. M. M., Janssen, B. J. M.,
Pleijers, A. J. S. F., Ramaekers, M. M. M. J., & van den Bossche, S. N. J. (2019). Nationale
Enquête Arbeidsomstandigheden 2018: Methodologie en globale resultaten [National working
conditions survey 2018: Methodology and global results]. TNO.
Hooftman, W. E., Mars, G. M. J., Knops, J. C. M., van Dam, L. M. C., de Vroome, E. M. M.,
Ramaekers, M. M. M. J., & Janssen, B. J. M. (2021). Nationale Enquête Arbeidsomstandigheden
2020: Methodologie [National working conditions survey 2020: Methodology]. TNO.
Jeong, S., Han, S. J., Lee, J., Sunalai, S., & Yoon, S. W. (2018). Integrative literature review on
informal learning: Antecedents, conceptualizations, and future directions. Human Resource
Development Review, 17(2), 128–152. https://doi.org/10.1177/1534484318772242
Karasek, R., & Theorell, T. (1990). Healthy work: Stress, productivity and the reconstruction of
working life. Basic Books.
Kiefer, T. (2005). Feeling bad: Antecedents and consequences of negative emotions in ongoing
change. Journal of Organizational Behavior, 26(8), 875–897. https://doi.org/10.1002/job.339
Kim, E.-J., Park, S., & Kang, H.-S. (2019). Support, training readiness and learning motivation in
determining intention to transfer. European Journal of Training & Development, 43(3–4),
306–321. https://doi.org/10.1108/EJTD-08-2018-0075
Kleine, A. K., Rudolph, C. W., & Zacher, H. (2019). Thriving at work: A meta-analysis. Journal of
Organizational Behavior, 40(9–10), 973–999. https://doi.org/10.1002/job.2375
Kluger, A. N., & DeNisi, A. (1996). The effects of feedback interventions on performance:
A historical review, a meta-analysis, and a preliminary feedback intervention theory.
Psychological Bulletin, 119(2), 254–284. https://doi.org/10.1037//0033-2909.119.2.254
Knight, C., & Parker, S. K. (2021). How work redesign interventions affect performance: An
evidence-based model from a systematic review. Human Relations, 74(1), 69–104. https://doi.
org/10.1177/0018726719865604
Koppes, L. L. J., de Vroome, E. M. M., Mars, G. M. J., Janssen, B. J. M., van Zwieten, M. H. J., & van
den Bossche, S. N. J. (2013). Nationale Enquête Arbeidsomstandigheden 2012: Methodologie en
globale resultaten [National working conditions survey 2012: Methodology and global results].
Hoofddorp: TNO.
Kraimer, M. L., Seibert, S. E., Wayne, S. J., Liden, R. C., & Bravo, J. (2011). Antecedents and
outcomes of organizational support for development: The critical role of career opportunities.
Journal of Applied Psychology, 96(3), 485–500. https://doi.org/10.1037/a0021452
Kuvaas, B., & Dysvik, A. (2010). Exploring alternative relationships between perceived investment
in employee development, perceived supervisor support and employee outcomes. Human
Resource Management Journal, 20(2), 138–156. https://doi.org/10.1111/j.1748-8583.2009.
00120.x
Lancaster, S., & DiMilia, L. (2014). Organisational support for employee learning: An employee
perspective. European Journal of Training & Development, 38(7), 642–657. https://doi.org/10.
1108/EJTD-08-2013-0084
Lundqvist, D., Wallo, A., Coetzer, A., & Kock, H. (2023). Leadership and learning at work:
A systematic literature review of learning-oriented leadership. Journal of Leadership &
Organizational Studies, 30(2), 205–238. https://doi.org/10.1177/15480518221133970
Macneil, C. (2001). The supervisor as a facilitator of informal learning in work teams. Journal of
Workplace Learning, 13(6), 246–253. https://doi.org/10.1108/EUM0000000005724
Manuti, A., Pastore, S., Scardigno, A. F., Giancaspro, M. L., & Morciano, D. (2015). Formal and
informal learning in the workplace: A research review. International Journal of Training and
Development, 19(1), 1–17. https://doi.org/10.1111/ijtd.12044
Marsick, V. J., & Volpe, M. (1999). The nature and need for informal learning. Advances in
Developing Human Resources, 1(3), 1–9. https://doi.org/10.1177/152342239900100302
HUMAN RESOURCE DEVELOPMENT INTERNATIONAL 23

Marsick, V. J., & Watkins, K. E. (2003). Demonstrating the value of an organization’s learning
culture: The dimensions of the learning organization questionnaire. Advances in Developing
Human Resources, 5(2), 132–151. https://doi.org/10.1177/1523422303005002002
Maurer, T. J., Mitchell, D. R. D., & Barbeite, F. G. (2002). Predictors of attitudes toward a
360-degree feedback system and involvement in post-feedback management development
activity. Journal of Occupational & Organizational Psychology, 75(1), 87–107. https://doi.org/
10.1348/096317902167667
Maurer, T. J., Weiss, E. M., & Barbeite, F. G. (2003). A model of involvement in work-related
learning and development activity: The effects of individual, situational, motivational, and age
variables. Journal of Applied Psychology, 88(4), 707–724. https://doi.org/10.1037/0021-9010.88.
4.707
Myers, C. G. (2018). Coactive vicarious learning: Toward a relational theory of vicarious learning
in organizations. Academy of Management Review, 43(4), 610–634. https://doi.org/10.5465/amr.
2016.0202
Ng, T. W. H., & Sorensen, K. L. (2008). Toward a further understanding of the relationships
between perceptions of support and work attitudes: A meta-analysis. Group & Organization
Management, 33(3), 243–268. https://doi.org/10.1177/1059601107313307
Nikolova, I., Van Ruysseveldt, J., Van Dam, K., & De Witte, H. (2016). Learning climate and
workplace learning: Does work restructuring make a difference? Journal of Personnel
Psychology, 15(2), 66–75. https://doi.org/10.1027/1866-5888/a000151
Noe, R. A., Clarke, A. D. M., & Klein, H. J. (2014). Learning in the twenty-first- century workplace.
Annual Review of Organizational Psychology & Organizational Behavior, 1(1), 245–275. https://
doi.org/10.1146/annurev-orgpsych-031413-091321
Noe, R. A., Tews, M. J., & McConnell Dachner, A. (2010). Learner engagement: A new perspective
for enhancing our understanding of learner motivation and workplace learning. The Academy
of Management Annals, 4(1), 279–315. https://doi.org/10.5465/19416520.2010.493286
Noe, R. A., & Wilk, S. L. (1993). Investigation of the factors that influence employees’ participation
in development activities. Journal of Applied Psychology, 78(2), 291–302. https://doi.org/10.
1037/0021-9010.78.2.291
Park, S., Kang, H.-S., & Kim, E.-J. (2018). The role of supervisor support on employees’ training
and job performance: An empirical study. European Journal of Training & Development, 42(1–
2), 57–74. https://doi.org/10.1108/EJTD-06-2017-0054
Parker, S. K. (2014). Beyond motivation: Job and work design for development, health, ambidex-
terity, and more. Annual Review of Psychology, 65(1), 661–691. https://doi.org/10.1146/
annurev-psych-010213-115208
Parker, S. K. (2017). Work design growth model: How work charactertistics promote learning and
development. In J. E. Ellingson & R. A. Noe (Eds.), Autonomous learning in the workplace (pp.
137–161). Routledge/Taylor & Francis Group.
Parker, S. K., & Grote, G. (2020). Automation, algorithms, and beyond: Why work design matters
more than ever in a digital world. Applied Psychology, 71(4), 1171–1204. https://doi.org/10.
1111/apps.12241
Parker, S. K., & Knight, C. (2024). The SMART model of work design: A higher order structure to
help see the wood from the trees. Human Resource Management, 63(2), 265–291. https://doi.
org/10.1002/hrm.22200
Parker, S. K., Wall, T. D., & Cordery, J. L. (2001). Future work design research and practice:
Towards an elaborated model of work design. Journal of Occupational & Organizational
Psychology, 74(4), 413–440. https://doi.org/10.1348/096317901167460
Parker, S. K., Ward, M. K., & Fisher, G. G. (2021). Can high-quality jobs help workers learn new
tricks? A multidisciplinary review of work design for cognition. The Academy of Management
Annals, 15(2), 406–454. https://doi.org/10.5465/annals.2019.0057
Paterson, T. A., Luthans, F., & Jeung, W. (2014). Thriving at work: Impact of psychological capital
and supervisor support. Journal of Organizational Behavior, 35(3), 434–446. https://doi.org/10.
1002/job.1907
24 R. B. L. SIJBOM ET AL.

Purcell, J., & Hutchinson, S. (2007). Front-line managers as agents in the hrm-performance causal
chain: Theory, analysis and evidence. Human Resource Management Journal, 17(1), 3–20.
https://doi.org/10.1111/J.1748-8583.2007.00022.X
Quinn, J. B., Anderson, P., & Finkelstein, S. (1996). Managing professional intellect: Making the
most of the best. Harvard Business Review, 74(2), 71–80.
Rafferty, A. E., & Griffin, M. A. (2006). Perceptions of organizational change: A stress and coping
perspective. Journal of Applied Psychology, 91(5), 1154–1162. https://doi.org/10.1037/0021-
9010.91.5.1154
Rau, R. (2006). Learning opportunities at work as predictor for recovery and health. European
Journal of Work & Organizational Psychology, 15(2), 158–180. https://doi.org/10.1080/
13594320500513905
Spector, P. E., & Jex, S. M. (1991). Relations of job characteristics from multiple data sources with
employee affect, absence, turnover intentions, and health. Journal of Applied Psychology, 76(1),
46–53. https://doi.org/10.1037/0021-9010.76.1.46
Tannenbaum, S. I., Beard, R. L., McNall, L. A., & Salas, E. (2010). Informal learning and
development in organizations. In S. W. J. Kozlowski & E. Salas (Eds.), Learning, training and
development in organizations (pp. 303–331). Routledge/Taylor & Francis Group.
Taris, T. W., & Kompier, M. A. J. (2005). Job characteristics and learning behavior. In P. L. Perrewe
& D. C. Ganster (Eds.), Research in occupational stress and well-being: Exploring interpersonal
dynamics (pp. 127–166). JAI Press.
Van Hootegem, A., Grosemans, I., & De Witte, H. (2023). In need of opportunities: A
within-person investigation of opposing pathways in the relationship between job insecurity
and participation in development activities. Journal of Vocational Behavior, 140
(November 2022), 103825. https://doi.org/10.1016/j.jvb.2022.103825
Van Ruysseveldt, J., & Van Dijke, M. (2011). When are workload and workplace learning
opportunities related in a curvilinear manner? The moderating role of autonomy. Journal of
Vocational Behavior, 79(2), 470–483. https://doi.org/10.1016/j.jvb.2011.03.003
Wang, S., & Zhang, X. (2022). Impact mechanism of supervisor developmental feedback on
employee workplace learning. Managerial and Decision Economics, 43(1), 219–227. https://
doi.org/10.1002/mde.3379
Warr, P., & Downing, J. (2000). Learning strategies, learning anxiety and knowledge acquisition.
British Journal of Psychology, 91(3), 311–333. https://doi.org/10.1348/000712600161853
Wielenga-Meijer, E. G. A., Taris, T. W., Kompier, M. A. J., & Wigboldus, D. H. J. (2010). From task
characteristics to learning: A systematic review. Scandinavian Journal of Psychology, 51(5),
363–375. https://doi.org/10.1111/j.1467-9450.2009.00768.x
Wielenga-Meijer, E. G. A., Taris, T. W., Wigboldus, D. H. J., & Kompier, M. A. J. (2011). Costs and
benefits of autonomy when learning a task: An experimental approach. The Journal of Social
Psychology, 151(3), 292–313. https://doi.org/10.1080/00224545.2010.481688
HUMAN RESOURCE DEVELOPMENT INTERNATIONAL 25