Factors influencing employee participation in work-related learning in organizations: The interaction between environmental and personal factors.
Merlin Nieste 10553231 Begeleider: Joost Jansen in de Wal
Bachelorscriptie Onderwijskunde Universiteit van Amsterdam 14 mei 2017
Table of Contents
Abstract ... 3
Introduction ... 4
1.1 Work-related Learning ... 6
1.2 The Job Demands-Resources Model ... 7
1.3 Personal Resources ... 9
Method ... 11
2.1 Research Question ... 11
2.2 Search Strategy and Selection Criteria ... 11
Findings ... 12
3.1 Types of learning ... 12
3.2 Job demands, job resources and work-related learning ... 13
3.3 Personal resources as a moderator in the relationship between job demands, job resources and employee learning. ... 22
Conclusion and Discussion ... 27
4.1 Which job demands and job resources influence the participation in work-related learning? ... 27
4.1.1 Job demands and work-related learning ... 27
4.1.2 Job resources and work-related learning ... 29
4.2 To what extend does current literature provide evidence that personal resources moderate the relationship between job demands, job resources and work-related learning? ... 30
4.3 Which environmental and personal factors influence employee participation in work-related learning in organizations and do they interact with each other? ... 30
4.4 Limitations ... 33
4.5 Implications for practice and suggestions for further research ... 34
Abstract
Employee participation in work-related learning is an essential instrument for organizations to keep a competitive advantage. Multiple studies have shown that different antecedents can influence participation in work-related learning. To identify these factors the Job Demands – Resources (JD-R) model and personal resources were used to systematically analyse empirical research and answer the question: which environmental and personal factors influence employee participation in work-related learning and do they interact with each other? The JD-R model distinguishes two categories: job demands (e.g., workload, work pressure) and job resources (e.g., organizational support, job autonomy). Job demands have a dual character that can be explained by dividing job demands into challenges (e.g., demands that promote mastery) and hindrances (e.g., demands that hinder learning). Personal resources were used as moderator resources that could turn a demand into a challenge or a hindrance. 41 studies have been analysed and multiple characteristics were identified, showing environmental factors (e.g., job demands and job resources) can influence work-related learning in a positive and negative way. Personal resources were proven to act as a moderator that enhances the positive effects of job resources and changes
demands in challenges or hindrances. The findings suggested that organizations should focus on resources like organizational support, job control and job autonomy when they want to influence work-related learning in their organizations.
Furthermore, it was suggested that even though personal resources are characteristics of the self, employers can affect these resources by changing the work environment by, for example, creating more resourceful job characteristics.
Introduction
Factors Influencing Employee Participation in Work-related Learning
Participation in work-related learning (e.g., taking a formal course or training, reflecting with colleagues, participating in on-the-job training experimenting, learning by the ideas from others and learning by doing) is an essential instrument for
organizations to keep a competitive advantage in a rapidly growing and changing knowledge economy (Groot & Maassen van den Brink, 2000; Gijbels, Raemdonck & Vervecken, 2010). This rapid and on-going change demands continuous learning from organizations and their employees, since the amount of hours employees put into training and work-related learning, determine for a great deal the competence and innovative abilities of an organization (Kyndt & Baert, 2013; Schulz & Stamov Roßnagel, 2009; Maximiamo, 2012; Gijbels et al., 2010; Tynjälä 2008).
Positive consequences of work-related learning do not only exist at an
organizational level. According to a study by Booth and Bryan (2002) participating in, mainly formal, work-related learning has a positive effect on the employees’ wages at both the current and future employers. Moreover, employees who have participated in on-the-job training have a greater chance to find new employment (Groot & Maassen van den Brink, 2000). Nevertheless, participation by employees in work-related learning is not self-evident, even though organizations are willing to make work-related learning more accessible (Maximiano & Oosterbeek, 2007). Furthermore, Deloitte reported in 2005 that only a quarter of the Dutch organisations, and their current staff population, were capable to respond to the rapid economical and technical changes at that moment. Therefore, these organizations are starting to realize that hiring new talent is not enough, they also have to make sure their own employees keep developing by participating in work-related learning activities. Mapping factors that influence this attendance can be of assistance when developing or adjusting learning policy and guiding employees while they grow and learn professionally.
Previous research shows there are different factors influencing the participation in work-related learning like: previous participation in training, job-security and self-efficacy (Kyndt & Baert, 2013; Maximiamo, 2012; Hurtz & Williams, 2009). In this thesis these kinds of antecedents will be divided into environmental and personal factors, since employee behaviour results from an
interaction between personal and environmental factors (Schaufeli & Taris, 2014). To identify the environmental factors, the Job Demands-Resources model (JD-R model) will be used. This model, designed by Demerouti, Bakker, Nachreiner and Schaufeli in 2001, divides environmental factors in two categories: job demands and job resources. Within the JD-R model lies the assumption that job resources can buffer the negative effects of job demands, but also have motivational potential and foster employees’ growth, learning and development (Bakker & Demerouti, 2007; Evers, Kreijns, van der Heijden & Gerrichhauzen, 2011).
Personal factors are proven to moderate the effects and influence the
perception of environmental factors (Schaufeli & Taris, 2014). To identify personal factors that influence participation in work-related learning, this thesis will take personal resources (e.g., self-efficacy, positivism, the big five personality traits, autonomy) into account as moderators, since personal resources can function not only as an independent component of the JD-R model but also influence the effect of job demands and resources (Xanthopoulou, Bakker, Demerouti & Schaufeli, 2007; Salanova, Bakker & Llorens, 2006).
The JD-R model, mainly used in human resource research, has been an inspiration for many researchers. The JD-R model is proven to be robust and is successfully applied and cross-validated in several studies. It is used as a conceptual framework and specific parts of the JD-R model have been studied, where they proved for example the mitigating effects of job resources (Schaufeli & Taris, 2014). Furthermore, it has been proven helpful to identify the important factors that influence employee’s growth and development. Moreover, the JD-R model is able to predict certain organizational outcomes (e.g., turnover intentions, absence, organizational commitment) (Schaufeli & Taris, 2014; Bakker & Demerouti, 2007). The JD-R model has not been used often in educational research, even though job demands and job resources are directly linked with learning and personal growth (Evers et al., 2011). There have been review studies that focused on participation in work-related learning before. These studies however, did not use the JD-R model combined with personal resources in their analysis. The main studies concentrated on the antecedents of work-related learning using the theory of reasoned action (Kyndt and Baert 2013) or zoomed in on multiple job characteristics and how these characteristics influence work-related learning (Wielenga-Meijer, Taris, Kompier and Wigboldus, 2010).
Taris and Kompier in van Ruysseveldt, Verboon and Smulders (2011) did use the JD-R model to investigate the relationship between job demands and work-related learning, but could not find definitive negative or positive relations. The
inconclusiveness about the effects of job demands on work-related learning is the reason this thesis combines the JD-R model with personal resources. Personal resources can moderate the effect of job demands and possibly turn them into a challenge or a hindrance. This could explain the dual character of job demands, since a challenge can promote mastery and growth, while hindrances frustrate learning and development (Schaufeli & Taris, 2014; Lepine, Lepine & Jackson, 2004).
In the next sections this thesis will provide a schematic analysis of literature regarding environmental and personal factors that can influence work-related learning in organizations. Therefore, the constructs work-related learning, the JD-R model and personal resources are further defined. Secondly, the main research question will be presented, as well as the search strategy and selection criteria. Thirdly, the findings of the analysed studies will be presented. Finally a conclusion will be drawn, limitations will be discussed and implications for practice and further research will be given.
1.1 Work-related Learning
Before learning can occur there must be a discrepancy: the existing knowledge of an individual is not sufficient anymore to solve a problem or issue. It is a process where new knowledge is acquired or where existing knowledge is used in new combinations or contexts (Verloop & Kessels, 2006; Eraut, 2000). In literature it is common to distinguish between formal and informal (or non-formal) learning. Formal learning is mainly characterized by schooling executed by licensed educational
institutions. These institutions can be part of an organization (e.g., learning and development department) or hired externally. Formal learning activities take place in a structured manner in terms of money, time, space and support. These formal learning activities are often characterized by maintaining a curriculum and using learning objectives. Additionally, learners generally receive a diploma or certificate when successfully finishing the course or training (Borko, 2004; Marisck & Watkins, 2001; Malcolm, Hodkinson & Colley, 2003, Eraut, 2000).
Informal learning on the other hand is not defined by structure. The
knowledge an individual acquires in an informal way is his or her own responsibility. Activities can occur during on- and off-the-job (work-related) activities and are not,
contrary to formal learning, goal-oriented. In addition, the informal learning
environment is not always learner friendly. Consequently, it is not always clear what the learning outcome of informal learning is. Nevertheless, informal learning can be stimulated by the organization (Eraut, 2004; Eraut, 2000; Billet, 2002; Kyndt & Baert, 2013).
Despite the distinct differences between formal and informal learning in recent literature this thesis will include both constructs, since learning (formal or informal) takes place where there is a need and the motivation to learn (Marsick & Watkins, 2001). In this thesis, informal learning will only entail deliberate learning activities (e.g., when learning takes place in time especially set aside for that purpose alone), since these activities account for satisfying a large part of employee learning needs (Eraut, 2000; Lambert & Popova-Nowak, 2009). Moreover, this kind of informal learning is not bound by a specific format. Learners are responsible for their own learning by setting goals and monitoring their process and this self-directed learning is, according to literature, becoming more standard in organizations (Schulz & Stamov-Roßnagel, 2010; Hurtz & Williams, 2009).
1.2 The Job Demands-Resources Model
The Job Demands-Resources model is based on the proposition that an employee’s wellbeing is the result of a balance between negative and positive work characteristics (job demands and job resources, respectively) and was originally developed to understand and predict burnout (Schaufeli & Taris, 2014). Demerouti et al. (2001, p.501) define job demands as physical, social or organizational aspects of the job that require sustained physical or mental effort. Examples of job demands are: work overload, job insecurity or interpersonal conflict. Although job demands are not necessarily negative they may turn into job stressors when additional effort must be exerted to achieve work goals (Bakker & Demerouti, 2006).
Job resources can be defined as a physical, social or organizational aspect of the job that may aid in completing work goals, reduce job demands or stimulate personal growth and development (Demerouti et al., 2001, p.501). Job resources can be located on an organizational level (e.g., pay, career opportunities, involvement), a personal/social level (e.g., relation with co-workers or supervisor) or at a work/task level (e.g., participation in decision making, task identity) (Bakker & Demerouti, 2007).
The main hypothesis within the JD-R model is that different combinations of job demands and resources determine employee wellbeing and predict burnout. However, in 2004, Schaufeli and Bakker published a revised version of the JD-R model where they added work engagement. Work engagement is characterized by vigour (e.g., high levels of energy), dedication and absorption (e.g., being focused and happily engaged in one’s work). With adding work engagement to the model, JD-R not only sought to explain the negative outcome (e.g., burnout) but also its positive counterpart (Schaufeli & Taris, 2014; Bakker & Demerouti, 2007; Evers, Kreijns, van der Heijden & Gerrichhauzen, 2011).
With adding work engagement to the JD-R model, the two characteristics (e.g., job demands and job resources) can create two psychological processes, a health impairment process and a motivational process. Coping with high job demands, that require sustained effort, can tire employees and lead to exhaustion and health problems (Xanthopoulou et al., 2007). The motivational process, in contrast to the health impairment process, leads to organizational commitment and growth. The availability of job resources, and their potential to foster intrinsic and extrinsic motivation, can assist employees in meeting their goals and becoming more committed to their job (Schaufeli & Bakker, 2004; Xanthopoulou et al., 2007).
As stated above, job resources can foster high levels of motivation by enhancing employees’ growth, learning and development (Evers et al., 2011). Job demands on the other hand are not associated to active learning and growth, whilst de Jonge and Dormann in Evers et al. (2011), link both demands and resources to
positive learning outcomes. This can be explained by approaching job demands in a different way. Literature shows that it is not only possible, but also beneficial to divide job demands into challenges (e.g., the difficulty of the work required) and hindrances (e.g., the inability to clearly understand what is expected of you). Whereas a challenge promotes mastery, personal growth and future gains, a hindrance does not enhance these gains and has a negative relation with motivation to learn. This can have potential implications for the way learning environments have to be managed (Cavanaugh, Boswell, Roehling, Boudreau, 2000; Lepine, Lepine & Jackson, 2004). Taking into account what Jonge and Dormann in Evers et al., (2011) stated, it is possible to change a demand in an effective (learning) action by the use of a specific and matching resource. In this thesis, personal resources will be used as moderator resources that can turn a demand into a challenge or a hindrance.
1.3 Personal Resources
By definition, personal resources are characteristics of the self that can help an individual cope with stress and are generally associated with resiliency and the ability to control your own environment in a positive way (Schaufeli & Taris, 2014; Hobfoll, 2002). They also play a distinctive role in an employee’s functioning within an organization, because the larger an individual’s personal resources are, the more positive and intrinsically motivated they are to pursue their goals and aim for higher performance (Luthans & Youssef, 2004; Shaufeli & Taris, 2014; Schaufeli, Taris & van Rhenen, 2008). Additionally, personal resources are assumed to reduce job demands and increase job resources, as personal resources can influence the employee’s awareness and comprehension of job demands and resources (van den Broeck, van Ruysseveldt, Smulders & de Witte, 2010). In short, personal resources are functional in achieving goals, protect from job demands and stimulate personal growth and development. Furthermore, it has been shown that positive
self-evaluations relate strongly to numerous aspects of work-related wellbeing and it is likely that individuals enjoy high levels of congruence between the goals they set and their capabilities. This could have a positive effect on work-related learning, since goal setting is essential for motivating employees to learn (Xanthopoulou, Bakker, Demerouti & Schaufeli, 2009, Bolhuis, 2003).
Several personal resources that relate negatively to job demands and positively with job resources are identified in research: efficacy, organizational based self-esteem (OBSE), optimism, active coping styles, resilience, hope, proactivity,
proactive behaviour, assertiveness, flexibility, autonomy and the big five personality traits (Xanthopoulou et al., 2007; Bakker & Demerouti, 2008; Vink, Ouweneel & Le Blanc, 2011; Schaufeli & Taris, 2014). As a personal resource, self-efficacy is
positively related with work engagement. Employees who show more self-confidence (indicative for self-efficacy) are inclined to see job demands more as a challenge than a hindrance and have the tendency to classify experiences at work as positive instead of negative (Laguna, Razmus & Zalinski, 2017). Equivalently, optimism (e.g., believing that one will generally experience good outcomes at work and in life) is related to higher levels of wellbeing. Optimists are also better in coping with job demands, since they adopt effective coping strategies and as a result they adapt well at work (Luthans & Youssef, 2007; Scheier, Carver & Bridges, 2001). Moreover, studies state, that other personal resources (e.g., positive self-evaluations, big five personality
traits, autonomy) can also be used in explaining goal orientation, motivation to learn and job satisfaction (Bakker, Demerouti & ten Brummelhuis, 2011; Amah, 2014; Nguyen, Kuntz, Naswall & Malinen, 2016).
From the analysis of empirical and theoretical research by Schaufeli and Taris (2014) it is possible to conclude the following: personal resources may influence the perception of job characteristics and it is safe to assume they can play an important part in the JD-R model. Taking the influencing quality of personal resources into account, the following theoretical framework is used to systematically analyse the literature:
Figure 1. Theoretical framework
The model in figure 1 shows there are several expectations regarding the factors that influence participation in work-related learning: 1) job resources have a positive effect on work-related learning, 2) job demands affect work-related learning, but in two different ways. By making the distinction between hindering job demands and challenging job demands, it is expected that job demands will have a negative and positive influence on work-related learning, 3) personal resources will moderate the experience of a job demand in such a way that the employee will see them as a challenge, creating a positive relationship between job demands and work-related learning, 4) low personal resources will moderate the effect of job demands in a way employees experience them as hindrances, therefore obstructing work-related learning and 5) personal resources enhance the positive effects of job resources.
Job resources
Job demands
Personal resources
Method 2.1 Research Question
Based on the abovementioned theoretical notions we can assume there are multiple factors (environmental and personal) that can influence work-related learning and employee participation in work-related learning in a positive or negative way. Furthermore, these relations can be affected by additional factors (e.g., personal resources). Based on these assumptions the following research question is constructed:
Which environmental and personal factors influence employee participation in work-related learning in organizations and do they interact with each other?
To answer this question, literature will be analysed using the following sub-questions: 1. Which job demands and job resources influence the participation in
work-related learning in organizations according to current literature?
2. To what extent does current literature provide evidence that personal resources moderate the relationship between job demands, job resources and work-related learning?’
2.2 Search Strategy and Selection Criteria
A review contains more than only a summary of existing literature. Therefore, it is important to use a clear strategy when searching for empirical and theoretical studies that are relevant for answering research questions (Kitchenham, 2004). In this thesis it was first determined which databases were going to be used, which search terms fitted best within the literature and what criteria the yielded studies should meet.
To find as much suitable literature as possible the following databases were used: Web of Science, Psychinfo, ERIC (Educational Resource Information Centre), Academic search premier and Journal citation reports. The general search terms about work-related learning were: organizational learning, learning, development, training,
work-related learning and employee(s). These terms were in several different manners
combined with the following items regarding personal resources as stated in Schaufeli and Taris’ appendix (2014): self-efficacy, personality traits, motivation, self-esteem,
optimism, autonomy and resilience. In total the search yielded N = 49 results.
Literature was selected using several criteria: 1) the article was written in English, 2) published in 2005 or later, 3) published in peer-reviewed journals, 4) focused on work-related learning, participation in work-related learning and at the
time of the research participants where employed in a organization and 5) included, (in)dependent variables that could be classified as either a job demand, job resource or personal resource. When a study did not meet criteria 2, it could be included based on the amount of times the paper had been cited. This made the total of analysed studies
N = 41.
Findings 3.1 Types of learning
Of the N = 41 reviewed articles n = 22 had informal, deliberative, learning as main focus, five studies concentrated on formal learning, seven included both types of learning. Seven articles did not use learning as an outcome, but did give interesting and usable information about job demands, job resources and/or personal resources. Studies including teachers as respondents characterized informal learning activities such as reflection, experimenting, learning by the ideas from others, reading literature of their content area and learning by doing (de Neve, Devos & Tuytens, 2015;
Hoekstra, Korthagen, Brekelmans, Beijaard & Imants, 2008; Proost, van Ruysseveldt & van Dijke, 2012; Lohman, 2003). Research concentrating on employees defined informal learning activities as: problem solving, learning through non-interpersonal sources, learning by doing, reflecting, elaborating and experimenting (Raemdonck, Gijbels & van Groen, 2013; van Ruysseveldt & van Dijke, 2011; van Ruysseveldt, Verboon, Smulders, 2011; Tews, Michel & Noe, 2017).
Formal learning was in several studies described by activities such as on-the-job training, formal courses and attending seminars (Kyndt, Onghena, Smet & Dochy, 2013; Major, Turner & Fletcher, 2006; Kyndt, Govaerts, Claes, de la Marche & Dochy, 2013). Some studies included, both formal and informal learning and made no distinction between the two forms of learning in their questionnaires (Maurer, Weiss & Barbeite, 2003; Crouse, Doyle & Young, 2011; Lejeune, Mercuri, Beausaert & Raemdonck, 2016; Park & Kwon, 2004). The survey used in research by Hurtz and Williams (2009) on the other hand made a distinction in activities by separating formal activities and on the job experiences. Also, Nikolova, van Ruysseveldt, de Witte and Syroit (2014) used different constructs in their survey when measuring participation in learning activities (e.g., new acquired knowledge, opportunities for reflection and opportunities for experimenting).
3.2 Job demands, job resources and work-related learning
There is much research on job demands and resources, but not a lot with a focus on work-related learning. Nonetheless, the following findings come from research regarding, in one way or another, above-mentioned constructs and how they are related to work-related learning and participation in work-related learning (for an overview of the definitions of the job demands, job resources and personal resources identified in this thesis, see Table 1). Hoekstra and colleagues (2009), for example conducted a 14-month study with 32 teachers. Quantitative data was used to compare these 32 teachers with each other. Based on this comparison, they conducted a
qualitative interview with two teachers who significantly differed in their perception of conditions for workplace learning. The study yielded the following results; collaboration with colleagues reduced workload, but did not foster learning or participation in learning for both teachers. Experiencing autonomy gave one teacher the freedom to develop her own way of working and learning by experimenting with new tasks and methods. The other teacher experienced this autonomy as a lack of direction.
The study also shows that the way an employee interprets job demands (e.g., strictness, no shared norms) can have a direct positive consequence for the effort an employee puts in his learning. One teacher interpreted the norms regarding student promotion as loose and experienced a lack of shared responsibility. She found this to be frustrating but could teach by her own norms, which resulted in more possibilities to experiment and learn. The other teacher interpreted the norms as very strict. This strictness had a direct influence on the responsibility he felt for his students’ results. When teachers feel strong moral responsibility, they may feel a need to stay on top of current developments in their field and are more willing to participate in work-related learning (Thoonen, Sleegers, Oort, Peetsma & Geijsel, 2011).
Table 1
Identified job demands, job resources and personal resources and their definition
Factors Definition
Job Demands
Strictness Characterized by acting in close conformity to requirements or principles.
Work pressure Quantitative demands such as the pace of work and workload.1
Workload Perceived amount of work.
Emotional demands /exhaustion
Emotional demands refer to the extent to which the (teaching) job requires emotional investments.1
Lack of time No possibilities to pursue learning activities due to lack of time.2
Lack of proximity Employees cannot learn together or from each other, while they are located too far apart or have no communal space to get together2.
Lack of funds Lack of substantial amounts of money in the organization reserved for learning activities2.
Turnover intentions Turnover intention is a measurement of whether a business' or organization's employees plan to leave their positions or whether that organization plans to remove employees from positions.3
Job Resources
Autonomy Perceiving that one is in charge of his or her own behaviour.4
Collaboration with colleagues
Opportunities for teachers to work together to solve problems and to provide feedback and information.5
Job control The latitude to make decisions and the freedom to select the most appropriate skills to complete a task.6
Learning Climate An innovative learning climate at work that encourages new thinking, openness to new ideas, collective
Supervisor support, Organizational support, support from colleagues
Four functions of social support:
-‐ Instrumental, with the support being oriented toward the accomplishment of tasks
-‐ Emotional, with the support being oriented toward the emotional aspects of accomplishing the task -‐ Informational support enables individuals to help
themselves to proceed with their tasks and may include a variety of practical help.
-‐ Appraisal support entails the transmission of information that is relevant for self-evaluation.8 The learning value of the job The extent to which the job nourishes the employee’s
further professional development5
Good supervision The employee’s perception of the managerial strategy of the supervisor.9
Choice independence See: autonomy Organizational- / managerial
support
How much an organization cares about their employees opinion, is willing to help or shows concern.10
Managerial support for fun Characterized as the degree to which individuals'
supervisors permit and encourage them to have fun on the job.11
Increased technological resources
Access to computers and the web for retrieval of new reading materials.12
Learning opportunities Conceptualized as work characteristics, indicating the extent to which employees perceive their workplace as requiring the use of existing knowledge and skills and offering them opportunities to develop new skills and practices.13
Open communication Open communication is characterized by listening carefully and effectively in interactions with other colleagues,
receiving and providing positive and collegial feedback.14 Less routine/repetition Routine or repetition is typically explained using to two
dimensions.
encountered in the work process that presents little variability.
-‐ Task analysability: The standardized step followed in performing a task and concentration of
information on problem solving.14
Transformational leadership A style of leadership where a leader works with his employees to identify needed change, creating a vision to guide this change and executing the change with committed employees.5
Active problem solving Active problem solving occurs when an individual takes discrete steps to solve his or her problem.15
Reflective dialogue Are characterized by in depth conversations with each other about educational or work issues.16
Personal Resources
Self-efficacy Self-efficacy is identified as sets of beliefs that people create about their ability to achieve desired outcomes.17 Intrinsic motivation The initiation of, and persistence in behaviour in order to
attain a desired outcome or goal.18 Self-directed learning
behaviour
Self-directed learning behaviour can be divided in two ways: 1) A process where the employee takes the initiative, with or without help, when identifying their learning needs, formulating goals and choosing learning strategies and evaluating their learning and 2) as personal characteristics with a learning aim. This means, workers with a self-directed learning orientation discover learning
opportunities, take the initiative to learn and will persevere in their attempts to learn, if they come up against obstacles.
19,20
Learning preparedness Factors that should help enable or prepare employees to pursue development of work-related skills.21
Autonomy Perceiving that one is in charge of his or her own behaviour.4
by those others, and having a sense of belongingness both with other individuals and with one's community.4
The big five personality traits The big five personality traits model is based on patters of correlations between: Extraversion, Agreeableness, Conscientiousness, Emotional Stability/Neuroticism and Openness/Intellect.22
Extraversion Extravert people are likely to like people, prefer being in large groups, and desire excitement and stimulation.23
Agreeableness Agreeable people are recognisable by their tendency to be altruistic, cooperative, and trusting.23
Conscientiousness Conscientiousness can be viewed as a measure of trait-oriented work motivation, and it appears to influence performance in all jobs through the ‘will do’ motivational component. Conscientious people can be purposeful, organized, reliable, determined, and ambitious.24 Emotional stability Also known as low neuroticism. Is characterized by
reflecting the tendency to be confident, secure, and steady25 Neuroticism Neurotic people often experience negative feelings like
fear, sadness, embarrassment, anger, guilt, and disgust.23 Intellect Intellect is characterized by processing abstract and
perceptual information effectively. 26
Openness When having an open personality you often have an active imagination, aesthetic sensitivity, intellectual curiosity, and are attentive to feelings.23
Zest Zest is defined as living life with a sense of excitement, anticipation, and energy. 27
Coping skills Coping skills are characterized by positive interpretations or rational planning to cope with problems and demands.28
1Kwakman, 2003; 2Lohman, 2006; 3Janssen, de Jonge & Bakker, 1999; 4Ryan & Deci, 2002; 5Thoonen
et al., 2011; 6Abraham, 2000; 7Fagerlind et al., 2013; 8 Evers et al., 2015; 9 Vanthournout et al., 2014; 10Kyndt et al., 2014; 11Tews et al., 2017; 12Crouse et al., 2011; 13Proost et al., 2012; 14Jeon & Kim,
2012; 15 Quinones, Jurska, Fener & Miranda, 2015; 16 Neve et al., 2015; 17Bandura, 1977; 18Deci & Ryan, 2000; 19Bolhuis, 2003; 20Lejeune et al., 2016; 21Maurer et al., 2003; 22Sorić et al., 2017; 23 Major et al., 2006; 24Bakker et al., 2012 p. 557; 25Judge & Bono, 2001; 26 DeYoung, Hirsh, Shane, Papademetris, Rajeevan & Gray, 2010; 27 Noe et al., 2013; 28 Bermejo-Toro et al., 2016.
The positive effects of job demands can also be supported by de Lange, Taris, Jansen, Kompier, Houtmans and Bongers (2010). They examined the causal
relationships between job demands and job resources (e.g., job control) and learning-related behaviour (e.g., motivation to learn and active problem solving) among N = 1237 Dutch workers. This study showed there is a positive effect for job demands as well as job control in predicting learning. Research by Else-Ouweneel, Taris, van Zolingen and Schreurs (2009) also found that not only job control, but high job demands too are each associated with high levels of learning in the workplace.
Furthermore, Evers, van der Heijden, van der Kreijns and Vermeulen (2015) stated that job demands like work pressure (e.g., the pace of work, workload) and job resources (e.g., learning climate, social support from one’s immediate supervisor, social support from one’s close colleagues, the learning value of the job) are positively related to teachers’ professional development at work. Vanthournout, Noyens, Gijbels and van den Bossche (2014) found similar results in their study conducted with N = 202 knowledge workers from Flanders. The results of their model suggested that job resources (e.g., good supervision, choice independence) and job demands (e.g., workload) have significant positive effects on the employee’s
approach to learning, although the effects differ in degree. Choice independence and workload have a large effect, where good supervision has a moderate effect.
Furthermore, they argued that resources like good supervision and choice
independence have a moderate effect on motivation to learn. They, however, did not find a significant effect for workload on motivation to learn.
Even tough multiple studies show the positive effects of perceived job control, this resource did not play a role in enhancing voluntary employee participation in a study by Hurtz and Williams (2009). Also, control had no significant effect on learning intentions. This was supported as well in research among N = 837 employed workers by Raemdonck, Gijbels and van Groen (2014). Contrary to the researchers’ expectations, job control did not appear to be a good predictor for work-related learning.
Besides the positive effects of job demands on work-related learning, there are also studies that show the negative effects of job demands on work-related learning. These negative effects can be found in several studies whose outcomes underline the dual character of job demands. For example, Evers and colleagues (2015) found in their research, conducted among 211 Dutch teachers, that job demands (e.g., work
pressure, emotional demands) are negatively related to flexible competence. Flexible competence is defined as being competent or an expert in your profession and able to effectively cope with change, which in its turn is correlated with learning (Evers et al., 2015).
Crouse and colleagues (2011), support these findings. They argue that several job demands prevented learning among 13 Canadian HRM practitioners. The
respondents stated that barriers like high workload negatively affected their participation in work-related learning. In the same study, job resources (e.g.,
organizational and managerial support, increased technological resources) are found to be positively related to learning in the workplace. These results are also found in a study by van den Broeck, van Ruysseveldt, Smulders & de Witte (2011). They used a survey that measured two job demands (e.g., workload and emotional demands) and two job resources (e.g., job autonomy and learning opportunities). Their results show that both job resources are significantly positively related with work engagement, which is a predictor for work-related learning (Evers et al., 2011). The negative relation between workload and learning is also significant. The relation between emotional exhaustion and learning, however, is not. This result was also found in a study by van Ruysseveldt et al., 2011. They found that emotional demands are not significantly related to learning. Workload, however, does frustrate participation in work-related learning. Research by Kwakman (2003), as well, did not find significant effects for emotional exhaustion.
Organizational or managerial support is found in multiple studies to be a positive job resource in predicting work-related learning. Kyndt and colleagues (2013) found that when low-qualified employees perceive their organization to be supportive, the higher the learning intention would be. This result was also found in a study by Crouse et al., 2011 and in a study by Hurtz and Williams (2009). The study by Hurtz and Williams (2009) suggest that the perceived organizational support might increase the employee’s feeling that important people would like them to participate, which can predict employee participation in work-related learning. Additionally, Raemdonk and colleagues (2014) found that support is a small but significant
predictor in work-related learning behaviour. Subsequently, manager support for fun is significantly related to learning from oneself. This type of managerial support is characterized as the degree in which employees are allowed to have fun on the job (Tews et al., 2017). Finally, Else-Ouweneel and others (2009) also found a positive
significant relationship between support from colleagues, support from the organization and learning. However, de Lange et al. (2010) found no significant effects for supervisor support in relation to work-related learning, just like Lejeune and colleagues (2016). Additionally, Kwakman (2003) even found a significant negative relation between management support and individual learning activities. This result, however, may not be interpreted as such because the negative effect might be a consequence of a suppressor-effect caused by high correlations between predictor variables.
We can assume that organizational support is an important predictor in work-related learning. Jeon and Kim (2012) concluded in their study that beside
organizational support (e.g., top management leadership), open communication, less routine and less repetition in tasks are important resources as well. Less routine and repeated work influence learning by constantly creating a new situation where the employee can learn by doing. Moreover, transformational leadership also seems to have an important role in stimulating teachers’ engagement in professional learning (Thoonen et al., 2011).
There are also studies that found a reversed effect between work-related learning opportunities, learning related behaviour and job demands and resources. These studies consider learning to be a job resource in itself, which might indicate a recursive effect. Learning as a resource buffers the effect of job demands. This could foster learning, which means that learning, as a resource, could be it’s own catalyst.
For instance, Proost et al. (2012) concluded there is a negative effect between learning opportunities and emotional exhaustion and turnover intentions. Furthermore, they found a buffering effect of learning in the relationship between unmet
expectations and emotional exhaustion. De Lange and colleagues (2010) found, as well, that learning related behaviour (e.g., active problem solving) has a significant negative effect on job demands. Research by van Ruysseveldt and colleagues (2011) support this statement. They not only found that job resources like autonomy and task variety have a positive effect on learning, they also found that learning opportunities partially mediated between these resources and job demands (e.g., emotional
exhaustion). By stimulating learning at work, autonomy and task variety indirectly decreased emotional exhaustion.
Eventually, one study stated that a lack of job resources could also influence participation in work-related learning. Lohman (2006) concluded that a lack of job
resources inhibits employees to engage in learning: lack of time, lack of proximity to colleagues’ work areas and lack of funds. Lack of time and proximity were found to discourage teachers from informal learning (e.g., sharing materials and resources). The lack of funds ranged from teachers not participating in peer teaching observation because their school could not afford substitute teachers to cover their classes, to purchase and share computer hardware, software and other material for instruction.
These findings regarding job demands and resources identify multiple environmental factors that influence work-related learning. Figure 2 shows an overview of these environmental factors.
Job resources + Supervisor/ organizational support + Autonomy + Job Control + Good supervision + Choice independence + Learning opportunities + Open communication + Less routine and repetition + Technical resources + Learning value + Lack of shared norms Job resources - Lack of time - Lack of proximity to colleagues - Lack of funds - Autonomy Job demands + Work pressure + Work load + Strictness Job demands - Work pressure - Workload - Emotional demands Work-related learning
Figure 2. Theoretical framework showing the factors identified as job demands and
job resources and their relation, positive (+) or negative (–) with work-related learning. The certainty of the relation is colour coded from black = very certain (multiple studies found the same results) to light grey = uncertain (only one study found this result, multiple studies found opposite results or there was no significant effect).
3.3 Personal resources as a moderator in the relationship between job demands, job resources and work-related learning.
It has been argued that employees not only rely on job resources like learning opportunities and organizational support to achieve work goals, but might also benefit from having personal resources like eagerness to learn, self-efficacy, autonomy and autonomous motivation (see Table 1 for definitions of these and following
constructs). Furthermore, it is possible that personal resources can act as moderator resources and change the experience of job demands in a challenge or a hindrance (de Neve et al., 2015; Jansen in de Wal, den Brok, Hooijer, Martens & van den Beemt, 2014).
Research by Raemdonck and colleagues (2014) state that a personal resource (e.g., self-directed learning behaviour) can moderate the effect of job demands. Their results show that high job demands in combination with a high degree of self-directed learning result in a significant positive interaction with work-related learning. As an explanation the study suggests that workers with high job demands and high self-directed learning behaviour often find themselves challenged instead of hindered, so they are able to learn as part of their regular day to day work. These findings can be supported by Kyndt and colleagues (2014) and Lejeune and colleagues (2016). In both studies self-directedness is the strongest predictor for employees’ learning intention.
Maurer et al. (2003) found a moderator effect for another personal resource: self-efficacy. When employees believe that favourable benefits will result from participation in learning and development and they also have a sense of self-efficacy, this will lead to greater intentions to participate. These intentions in their turn lead to participation in work-related learning. Maurer and colleagues (2003) define
favourable benefits in two types of benefits: extrinsic benefits (e.g., better pay, promotion, job security) and intrinsic benefits (e.g., having more interesting work,
enjoyment, reaching one’s potential). They also found that the personal resource learning preparedness (e.g., factors that should help, enable or prepare employees to pursue development of work-related skills) has a relationship with self-efficacy and perceived benefits of development participation and is also indirectly related to involvement in learning.
Likewise, a study by Amah (2014), found that self-efficacy could moderate the employee’s perception of a job demand. This moderation results from the employee positively evaluating his or her ability to operate in any circumstance. Kyndt and colleagues (2014), however, found in their study, amongst 1243 Flemish employees, no significant effect for self-efficacy.
Perceived feelings of autonomy, used in the previous chapter as a job resource, can also serve, to some extent, as a personal resource (Paradnikė and Bandzevičienė, 2015). Van Ruysseveldt and van Dijke (2011) concluded in their research that autonomy is used as a moderator between job demands (e.g., high workload) and work-related learning. Their results show that at low levels of autonomy, workload was always negatively related to work-related learning and this negative relationship became progressively stronger at higher levels of workload. On the other hand, when the employee’s autonomy increased, workload was always positively related to work-related learning but this relationship became increasingly weaker at high levels of workload.
Gorozidis and Papaioannou (2014) suggest that external rewards (e.g., extra qualification) could have a positive effect on participation in work-related learning. However, participation was accompanied by a greater workload. Their research showed that this demand was acceptable to employees who experienced a great feeling of autonomous motivation, yet their less autonomously motivated colleagues found it difficult to cope with the additional workload. Peeters and Rutte (2005) also found positive effects for high levels of autonomy in regard to job demands (e.g., emotional exhaustion) in their study among 123 Dutch teachers. Teachers who experienced high level of autonomy felt less emotional exhaustion and more personal accomplishment, which could be a positive indicator for participating in informal learning activities (Kwakman, 2003).
Fagerlind, Gustavsson, Johansson and Ekberg (2013) also emphasize, the importance of autonomy. They argue that autonomy enables the use of job resources, which could predict work-related flow. This work-related flow can be compared with
work engagement, according to Makikangas, Bakker, Aunola and Demerouti (2010). In this study, flow is an experience of enjoyment, intrinsic motivation and absorption. The results by Fagerlind and colleagues (2013) show that job resources (e.g., active jobs, high degree of social capital, innovative learning climate) increase the likelihood of work-related flow. The results further argue that to benefit from job resources, work-related flow is dependent on the degree of autonomy. Because high job demands, in relation with a low degree of autonomy, have been found to frustrate flow and consequently hinder learning opportunities.
Stated in Soric, Penezic and Buric (2017), the big five personality traits (e.g., extraversion, agreeableness, conscientiousness, emotional stability and intellect) are also important predictors for learning and academic achievement. Schaufeli and Taris (2004) used multiple characteristics of the big five in their research as personal resources. There are also interesting results in regard to the big five as a personal resource and moderator in the relationship between demands and resources and work-related learning.
For example, Noe, Tews and Marand (2013) used a questionnaire to measure individual differences as personal resources (e.g., the big five, zest) and their
influence on work-related learning, among N =180 US managers. Their results show that work-related learning is influenced by the big five and zest. However, when putting both constructs in one regression model only zest is a significant predictor. This is notable given the dominance of the big five in predicting work-related learning. But those high in zest, according to Noe and colleagues, moderate job demands (e.g., emotional demands) by having the emotional energy and cognitive liveliness necessary to engage in work-related learning.
Bakker and colleagues (2011) did find a significant effect for one of the big five personality traits. The results in their study show that work engagement, which can be boosted by job resources (Bakker, Hakanen, Demerouti, & Xanthopoulou, 2007), on its own did not increase performance and active learning. However, employees who are also high in conscientiousness did show increased performance and active learning. Major and colleagues (2006), found the same results for conscientiousness, but also for extraversion and openness. In their research these factors are all positive moderators for the effects of job resources on motivation to learn.
Moreover, research by Nguyen et al. (2016) found that other personality traits (e.g., optimism and proactive personality) were significant predictors of employee resilience. Resilience on its turn can buffer the negative effects of job demands (Shaufeli & Taris, 2014; Schaufeli et al., 2008; Bakker et al., 2008). Furthermore, Nguyen and colleagues found that optimism seemed to compensate for low resources (e.g., low levels of leader recognition).
Finally, Bermejo-Toro, Prieto-Ursua and Hernandez (2016) concluded in their research among N = 413 Spanish teachers, that personal resources (e.g., coping skills) can moderate the effects of job demands on teacher wellbeing. They state that these results show that personal resources have much importance, maybe even more than job resources.
In the following figure (Figure 3) the model from Figure 2 is expanded with personal resources as a moderator and some additional environmental factors that were identified as job resources (e.g., extrinsic and intrinsic benefits, active jobs, social capital). As seen in Figure 3, the personal resources that moderate job resources al have a boosting effect. They enhance the already positive relation between job resources and work-related learning. The personal resources that moderate the effects of job demands also affect them in a positive manner. This means personal resources, according to the analysed literature, moderate the negative effects of job demands on work-related learning. There are no arrows from personal resources to the positive effects of job demands, because there are no findings about these relationships.
Figure 3. Theoretical framework presenting the factors identified as job demands and
resources and moderator factors that qualify as personal resources. In this model the direction of the moderation is indicated with a “+” or a “–”. The certainty of the relation is colour coded from black = very certain (multiple studies found the same results) to light grey = uncertain (only one study found this result, multiple studies found opposite results or there was no significant effect).
Job resources +Supervisor/ organizational support + Autonomy + Job Control + Good supervision + Choice independence + Learning opportunities + Open communication + Less routine and repetition + Innovative learning climate + Extrinsic benefits + Technical resources + Intrinsic benefits + Learning value + Lack of shared norms + Active jobs + Social capital Job resources - Lack of time - Lack of proximity to colleagues - Lack of funds - Autonomy Job demands + Work pressure + Work load + Strictness Job demands - Work pressure - Workload - Emotional demands Personal resource + Conscientiousness + Self-efficacy + Learning preparedness + Autonomy + Extraversion + Openness Personal resource + Self-directed learning behaviour + Autonomy + Self-efficacy + Zest + Optimism + Pro-active behaviour + Coping skills Work-related learning
Conclusion and Discussion
This thesis focused on which environmental and personal factors could
influence employee participation in work-related learning in organizations and if they interact with each other. To identify these factors the JD-R model was used. Job demands were defined as factors that require sustained physical or mental effort, whereas job resources were factors that may aid in completing work goals, reduce job demands or stimulate personal growth and development (Bakker & Demerouti, 2006).
The main research question in this thesis was: “which environmental and personal factors influence employee participation in work-related learning in
organizations and do they interact with each other? To answer this question two sub-questions were constructed: 1) which job demands and job resources influence the participation in work-related learning in organizations according to current literature and 2) to what extent does current literature provide evidence that personal resources moderate the relationship between job demands, job resources and work-related learning? Personal resources, in this thesis, are aspects of the self that can help an individual cope with stress and are generally associated with resiliency and feeling able to control your own environment in a positive way (Schaufeli & Taris, 2014; Hobfoll, 2002; Shahpouri, Namdari & Abedi, 2016).
4.1 Which job demands and job resources influence the participation in work-related learning?
4.1.1 Job demands and work-related learning
When analysing the results four job demands, that have a positive or negative influence on work-related learning and participation in work-related learning, were identified: strictness, work pressure, workload, emotional demands/exhaustion. Other studies just referred to these factors as job demands and did not specify which demand they measured (de Lange et al., 2010; Else-Ouweneel et al., 2009).
Five studies found positive effects for job demands (e.g., strictness, lack of shard norms, work pressure, workload) on work-related learning (e.g., approach to work-related learning, participation in work-related learning) (Hoekstra et al., 2009; de Lange et al., 2010; Else-Ouweneel et al., 2009; Evers et al., 2015; Vanthournout et al., 2014). Taken into account that job demands can lead to exhaustion, health
work-related learning in a negative way, these positive results could seem very incoherent. However, research by Crawford, Lepine and Rich (2010) shows, job demands could be differentiated into two categories: challenges and hindrances. Whereas both categories tend to be demanding, challenges have the tendency to promote learning and personal growth.
This means, like, Schaufeli and Taris (2014) argue, that it is highly unlikely for job demands to be a positive influence on their own, but in combination with a certain resource (e.g., job control) the demand could have a positive influence on work-related learning. The positive effects could also be explained by suggesting that employees with high job demands often find themselves challenged in their work and are able to learn as part of their regular day-to-day work (Wielenga-Meijer et al., 2010; Amah, 2014; Janssen, 2000).
Four analysed studies, found negative effects for several job demands (e.g., work pressure, workload, emotional demands) (Evers et al., 2015; Crouse et al., 2011; van den Broeck et al., 2011; van Ruysseveldt et al., 2011). In line with Crawford and colleagues (2010) we can assume that job demands in these studies were experienced as hindrances. These stressors tend to decrease the employee’s capability to control their own work environment, which can negatively affect the employee’s ability to function efficient (Bakker, Demerouti & Verbeke, 2004). Furthermore, when
experiencing high levels of job demands, employees might experience the need to use existing problem solving behaviour to cope with work problems. This could
negatively affect the learning potential of the job, since the employee sees no possibility to engage in (in)formal learning activities (Ellstrom, 2001).
Finally, there were three studies that did not find a significant result for job demands and their relationship with work-related learning (van den Broeck et al., 2011; van Ruysseveldt et al., 2011; Kwakman, 2003). Emotional demands and emotional exhaustion had no significant effect on participation in learning, and workload had no significant effect on motivation to learn. The results are, according to Ruysseveldt and colleagues (2011), in line with existing studies. In their research they cite Taris and Kompier (2004) who investigated eighteen studies and could not find a clear-cut negative or positive relationship between job demands and work-related learning.
4.1.2 Job resources and work-related learning
One study found a negative effect for one job resource (autonomy). However, this study by Hoekstra (2009) was a qualitative study and this outcome was the experience of one teacher. He experienced autonomy as a lack of direction and felt hindered to learn. This negative experience of autonomy is not in line with the results of existing empirical research, where the autonomy to create your own learning and life goals and learning strategies have a positive effect on learning (Bolhuis, 2003; McGrath, 2001). However, when comparing these results one must keep in mind that the negative effect of autonomy is the opinion of one man and cannot be generalized to the population. Furthermore, competence in this kind of self-directed learning needs to be developed, otherwise it is difficult for learning to occur (Bolhuis, 2003). Therefore, it could be possible that this typical employee did not develop enough competence to regulate and direct his own learning, hence his negative experience. It could also mean that not autonomy on its own caused the negative relation with learning, but the combination with a lack of structure. Autonomy supportive environments can create too many possibilities and overwhelm learners with too many choices, which can have a negative influence on learning. By also offering structure support, the learning environment becomes less chaotic and therefore reduces stress. This way the learner knows what is expected and how to accomplish learning goals (Sherer & Spillane, 2011; Guay, Ratelle & Chanal, 2008; van Loon, Ros & Martens, 2012).
However, of all analysed research, N = 11 studies found positive effects for job resources (de Lange et al., 2011; Else-Ouweneel et al., 2009; Evers et al., 2015; Vanthournout et al., 2014; van den Broeck et al., 2011; Kyndt et al., 2013; Crouse et al., 2011; Raemdonck et al., 2014; Tews et al., 2017; Jeon & Kim, 2012; Thoonen et al., 2011). Identifying factors like: autonomy, job control, positive learning climate, social support from colleagues and supervisors, learning value of the job, good supervision, choice independence, organizational support, increased technological resources, learning opportunities, open communication, less routine and repetition, transformational leadership and opportunities for social encounters. These findings are in line with the argument that job resources stimulate personal growth, learning and development (Xanthopoulou, et al., 2007; Xanthopoulou, et al., 2009).
When analysing the literature there were three studies that suggested work-related learning or learning opportunities could be job resources on their own and
have a negative or buffering effect on job demands (emotional exhaustion) or act as a mediator between job demands and job resources (Proost et al., 2012; de Lange et al., 2010; van Ruysseveldt et al., 2011). Holman & Wall (2002) explain this by stating that obtaining greater knowledge and skills through learning results in an employee who is able to manage job demands more effectively and consequently experiences less stress.
4.2 To what extend does current literature provide evidence that personal resources moderate the relationship between job demands, job resources and work-related learning?
All fifteen analysed studies regarding personal resources proved that it is possible for these resources to act as a moderator in the relationship between job demands or job resources and work-related learning. Ten analysed studies showed that personal resources are able to moderate the effects of job demands and therefore positively affect work-related learning (Raemdonck et al., 2014; Kyndt et al., 2014; Lejeune et al., 2016; Amah, 2014; van Ruysseveldt & van Dijke, 2011; Gorozidis & Papaioannou, 2014; Peeters & Rutte, 2005; Noe et al., 2013; Nguyen et al., 2016; Bermejo et al., 2016). Five analysed studies supported the expectation in this thesis that personal resources could enhance the effects of job resources (Maurer et al., 2013; Fagerlind et al., 2013; Bakker et al., 2011; Major et al., 2006). These findings indicate that by influencing how people comprehend their environment and react to it, personal resources are able to change a job demand into a challenge and promote learning and development, but can also enhance the positive effects of job resources (Xanthopoulou et al., 2007; Shaufeli & Taris, 2004; van Yperen & Snijders, 2000).
In this thesis several personal resources were identified: self-efficacy, intrinsic motivation, autonomy, relatedness, self-directed learning behaviour, zest,
conscientiousness, extraversion, openness, optimism, pro-active personality and coping skills.
4.3 Which environmental and personal factors influence employee participation in work-related learning in organizations and do they interact with each other?
The main question in this thesis was: which environmental and personal factors influence participation in work-related learning and do they interact with each other? By dividing the characteristics in three categories (e.g., job demands, job resources, personal resources), it was possible to identify multiple factors that,
directly and indirectly, influenced work-related learning in different ways (see Figure 3 for an overview of these factors and their relationship with work-related learning). First the environmental factors (e.g., job resources, job demands) will be discussed, then personal factors (e.g., personal resources) and how these factors moderate the effects of environmental factors.
Of the environmental factors that were defined as job demands, work pressure and workload seemed to be the most important factors. Workload was a strong positive predictor for work-related learning. Work pressure was not only reported to be a strong positive predictor, but also influences work-related learning in a negative way. This is not surprising, since the expectations in this thesis went two ways to begin with. When high job demands are combined with high resources these stressors result in active jobs. This can result in employees who adapt themselves to the high demands they are experiencing by upgrading their skills and abilities, which can be defined as learning (Dwyer & Ganster, 1991, Janssen, 2000; Bakker & Demerouti, 2006; Evers et al., 2011; Schaufeli & Taris, 2014).
This means work pressure is not a definite negative environmental factor. It does mean, however, that when work pressure is high, job resources also must be high for employees to compensate for these stressors. A comparable conclusion can be drawn for workload. The findings show there is a positive relationship between high workload and work-related learning, which indicates that employees perceive workload more like a challenge than a hindrance. It is however, not possible to conclude that workload is also a negative predictor for work-related learning, as only one study could find this relationship between the two constructs. Still, it is likely to assume that workload could be experienced as a hindrance and as a consequence negatively influence participation in work-related learning.
For organizations trying to enhance participation in work-related learning it is important to know that when employees experience high workload or work pressure, this not automatically means they cannot learn or there is no possibility to participate in work-related learning activities. As long as employees also experience high resources they are able to see these demands as challenging, which benefits learning and development (Lepine et al., 2004; Crawford et al., 2010).
For the factors strictness and emotional demands it is not possible to draw any definite conclusions. The, in this thesis, analysed studies did not find significant results for the relation between emotional demands and work-related learning and
only one study found strictness to be a positive influence on work-related learning. Therefore, it is not possible to conclude with certainty that these factors are predictors for work-related learning.
Of all job resources, organizational support was the most frequently identified resource. Followed by job control and job autonomy. The importance of
organizational support found in this thesis is consistent with other empirical research that found organizational support negatively affected turnover intentions, absence and exhaustion and positively influenced job performance, job satisfaction and learning (Allen, Shore & Griffith, 2003; Galluci, Devoogt van Laren, Yoon & Boatright, 2010). The same conclusion can be drawn for job control and job autonomy. Studies have shown that perceived job control and job autonomy can not only buffer job demands, but also have a positive effect on work-related learning (Evers et al., 2011; Parker & Sprigg, 1999; Bond, Flaxman & Bunce, 2008).
Therefore, it is possible to conclude that these three resources (organizational support, autonomy and job control) are the most certain to influence work-related learning. Consequently, these resources should gain the most attention from
employers. When trying to enhance employee participation in work-related learning, it is highly probable that when employers make sure their employee feels supported, autonomous and in control this will have a positive effect on the worker’s willingness to participate in work-related learning activities.
The same conclusion cannot be drawn for the other job resources (e.g., good supervision, choice independence, learning opportunities, open communication, active jobs, innovative learning climate, extrinsic benefits, technical resources, intrinsic benefits, learning value of the job, lack of shared norms, social capital). The findings were incoherent with other studies, only found in one study or resulted from
interviews where only one respondent found certain resources to be a positive
influence for their willingness to learn. Therefore, it is advisable that further research is conducted before any conclusions about the relationship between these job
resources and work-related learning are made. The findings also show it is likely that a lack of resources will have a negative relation with participation in work-related learning. This assumption, however, is only based on qualitative studies and the fact that the presence of job resources positively affects work-related learning.
In regard to personal factors, self-directed learning behaviour and autonomy were found in several studies to have a strong positive influence on how employees
experience environmental factors like job demands. The findings show that both personal resources buffer the negative effects of job demands like workload, which in turn results in a positive relation with work-related learning.
For organizations this means they should surround themselves with employees who are self-directed and autonomous. This way they have employees who do not crumble when coping with high job demands, since these employees experience them as challenging. It could also be possible to design work environments in such a way they could foster personal resources. Although, this raises the question if personal factors can be affected or enhanced by their environment?
The other personal factors (e.g., self-efficacy, zest, optimism, pro-active behaviour, coping skills) that were found to moderate the effects of job demands couldn’t with certainty be identified as personal resources. They do, however, show that more personal factors are able to influence the effects of job demands. The same can be said about the personal resources identified that moderated the effects of job resources (e.g., learning preparedness, autonomy, extraversion).
To summarize, it is possible to conclude there are multiple factors (personal and environmental) that can influence participation in work-related learning in different ways, positive or negative. Personal factors, in this thesis referred to as personal resources, were proven able to moderate environmental effects, thus confirming the interaction between the two types of factors.
4.4 Limitations
Before moving on to the implications for practice and further research, the limitations of this thesis will be discussed. First of all, like every literature review or systematic literature analysis this thesis is limited by a possible selection bias.
Although selection criteria were used, it is still probable that because of the subjective nature of this review, my own view could have coloured the interpretation of the literature. However, by using a theoretical framework and clear focus, I tried to forestall this.
Secondly, the studies analysed in this thesis mainly focused on informal learning, causing an unbalanced distribution of the types of learning within the thesis. This, however, should not be an extensive problem while this thesis focused on deliberative learning. This means, employees have to make the decision to participate
