The relationship between intrapreneurial behavior and job

BENEFITS OF INTRAPRENEURIAL BEHAVIOR

The relationship between intrapreneurial behavior and job performance,

and the influence of self-efficacy and psychological well-being on this

relationship

Master thesis Human Resource Studies

The academic year 2019-2020

Student Tessa Drijfhout (S2030145)

ANR 404349

Theme Intrapreneurship

Supervisor Dr. Wieby Altink

Second reader Dr. Brigitte Kroon

Tilburg University

School of Social and Behavioral Sciences

January 2019

BENEFITS OF INTRAPRENEURIAL BEHAVIOR 2

Abstract

This study examines the relationship between intrapreneurial behavior and job performance,

and the influence of psychological well-being and self-efficacy on this relationship.

Organizations have been looking for ways to create competitive advantage. Consequently,

employees need to adapt to an intrapreneurial way of working, which makes intrapreneurship

an important subject for both research and practice. It is hypothesized that there is a positive

direct and indirect relationship between intrapreneurial behavior and job performance.

Furthermore, it is hypothesized that there is a positive relationship between intrapreneurial

behavior and self-efficacy, between self-efficacy and psychological well-being, and between

psychological well-being and job performance. The predictions were tested with a mediation

analysis conducted with the PROCESS tool of Hayes. In total, 163 respondents participated in

this study. The results showed no direct relationship between intrapreneurial behavior and job

performance. However, the results showed an indirect positive relationship between

intrapreneurial behavior and job performance, via self-efficacy and psychological well-being.

This entails that self-efficacy and psychological well-being fully mediate the relationship

between intrapreneurial behavior and job performance. Implications of these findings and

recommendations for future research are discussed in the discussion section.

Keywords: intrapreneurship, self-efficacy, psychological well-being, job performance


Introduction

Intrapreneurship has gained importance in organizational research and practice. Due

to the competitive economic environment, organizations have been looking for ways to manage

innovation and to create a competitive advantage (Blanka, 2018). In the broadest sense,

intrapreneurship entails entrepreneurship within an existing organization (Preenen, Liebregts,

Dhondt, Oeij, & Van der Meulen, 2014). Main differences between intrapreneurs and

entrepreneurs are the following; intrapreneurs operate within organizations in which they are

employed, they are able to use the existing resources of the organization, and the organizations

in which they work already have their own policies and bureaucracy, which is not the case for

entrepreneurs (Blanka, 2018). There are different perspectives on intrapreneurship in the

research field (Preenen et al., 2014). This research focuses on intrapreneurial behavior, which

entails work behavior that is initiated by the individual employee and which every employee

within an organization can display (Preenen et al., 2014). Nowadays, employees gain more

responsibility and are expected to be flexible, proactive and innovative. Respectively, they need

to adapt increasingly to an intrapreneurial way of working (Neessen, Caniëls, Vos, & De Jong,

2018).

Research has focused on how the intrapreneurial behavior of employees relates to

beneficial organizational outcomes, such as innovativeness and firm growth (Gawke,

Gorgievski, & Bakker, 2017). Yet, there is little research on how the intrapreneurial behavior

of employees impacts employee outcomes (e.g. well-being and performance) (Gawke et al.,

2017). Since intrapreneurial behavior is growing in importance (Neessen et al., 2018), the

impact of intrapreneurial behavior on employee outcomes such as well-being and performance

is important to address. The question arises about whether or not intrapreneurial behavior has

benefits for individual employees. Research has shown that well-being (i.e. happiness) is linked

to desirable outcomes, such as a higher level of productivity (Oswald, Proto, & Vitterso, 2015).

This makes psychological well-being an interesting variable for research and organizations.

This study aims to contribute to the current literature by providing insights into if and how

intrapreneurial behavior relates to psychological well-being and job performance. This is a

relevant issue for the field of human resources (HR) because employee attitudes, behaviors and

respectively employee outcomes are an important interest of HR.

In general, there seems to be only one study that focuses on the costs and benefits of

intrapreneurial behavior. Gawke, Gorgievski, and Bakker (2018) found that employee

intrapreneurship positively relates to employee innovativeness, in-role performance, and


decreased work avoidance via work engagement. Furthermore, employee intrapreneurship is

positively related to exhaustion. However, the intrapreneurship-performance relationship still

remains unclear, making the variable job performance important for research (Blanka, 2018).

In addition, this study aims to investigate whether self-efficacy (i.e. people’s beliefs in their

capabilities) influences the relationship between intrapreneurial behavior and psychological

well-being and job performance. This is because intrapreneurial behavior could lead to success

experiences, resulting in feeling more efficacious (Gawke et al., 2017). Moreover, self-efficacy

is important for employee well-being, since it affects processes involved in self-regulation,

motivation, and stress (Van Seggelen-Damen & Van Dam, 2016). Self-efficacious individuals

have strong beliefs in their abilities, which results in increased effort in the persuasion of their

goals (Avey, Wernsing, & Mhatre, 2011). Consequently, the probability of success experiences

increases, which is associated with positive outcomes such as well-being (Avey et al., 2011).

In sum, the research question of this study is:

“To what extent does intrapreneurial behavior lead to job performance, and to what extent do

self-efficacy and psychological well-being influence this relationship?”

Theoretical framework

In the next sections, the direct relationship between intrapreneurial behavior and job

performance will be discussed. Moreover, the indirect relationship between intrapreneurial

behavior and job performance will be explained, including a mediator path with self-efficacy

and psychological well-being as mediators. To explain this mediator path, first, the relationship

between intrapreneurial behavior and self-efficacy will be explained. Second, the relationship

between self-efficacy and psychological well-being will be explained. Lastly, the relationship

between psychological well-being and job performance will be explained. The relationships are

displayed in the conceptual model presented below (figure 1).

The direct relationship between intrapreneurial behavior and job performance

In this research, intrapreneurial behavior is defined as intrapreneurial work behavior,

which all employees can show. Intrapreneurial work behavior entails behavior that is initiated

by the individual employee (i.e. bottom-up process) and involves being innovative, proactive

and taking risks within an existing organization (Preenen et al., 2014). The following definitions

are given to the three dimensions of intrapreneurial behavior. Innovative behavior entails

individual behavior focused on the initiation and deliberately introduction of new and useful

ideas, processes, products and procedures within an organization, team or function (Preenen et


al., 2014). Proactive behavior involves taking self-initiated and future-focused actions that are

meant to improve the individual or the situation (Preenen et al., 2014). Taking risks means that

time, effort or money is invested while the outcomes are uncertain. Furthermore, it means

breaking with the status quo, deviate from existing, standard procedures and persisting while

receiving no help from supervisors (Preenen et al., 2014). These three dimensions together

shape the variable intrapreneurial behavior. The dimensions of this variable may independently

vary in strength (Stull & Singh, 2005).

Another important variable in this current study is job performance. Job performance is

defined as “the total population of behaviors and activities that are judged to be important for

accomplishing the goals of an organization” (Campbell et al., 1990, p. 278). The behaviors and

activities that are considered in this current study are the behaviors and activities that are

described in the job description of an employee. More specifically, the behaviors and activities

capture the quality and quantity of work. This current study focuses on overall job performance

instead of focusing on a specific type of performance (e.g. task performance) because the

relationship between intrapreneurial behavior and job performance is still unclear and

intrapreneurial behavior might influence multiple types of job performance. This research

focuses on subjective job performance (i.e. self-ratings). Subjective evaluations are often used

in situations in which objective criteria are difficult to collect and where it is hard to control

situational influences (Heidemeier, 2005). Subjective evaluations have disadvantages, these

will be discussed in the discussion section.

There seems to be little research on the effect of intrapreneurial behavior on the

individual employee. Gawke and colleagues (2018) found that employee intrapreneurship

positively relates to employee innovativeness (i.e. a dimension of intrapreneurial behavior), in-

role performance, and decreased work avoidance via work engagement. The strength of the

indirect relationships between employee intrapreneurship and the different performance

measures are the following; β = .10 for innovativeness, β = .13 for in-role performance, and β

= -.09 for work avoidance (Gawke et al., 2018). Moreover, a direct relationship between

employee intrapreneurship and innovativeness (β = .34) and work avoidance (β = .27) was

found. These results suggest that intrapreneurial behavior has an effect on the individual

employee. The direct relationship between employee intrapreneurship and in-role performance

was not significant (Gawke et al., 2018). In-role performance reflects how an employee

accomplishes core job tasks (Gawke et al., 2018). Gawke and colleagues (2018) measured in-

role performance with colleagues’ ratings. However, the direct relationship between


intrapreneurial behavior and subjective job performance remains unclear. Moreover, Gawke

and colleagues (2018) mention that more research on the benefits of employee intrapreneurship

is needed. Therefore, the present study examines the direct relationship between intrapreneurial

behavior and job performance (i.e. subjective). Above mentioned research suggests a positive,

indirect relationship between intrapreneurial behavior and job performance. Because of the

expected positive indirect relationships between intrapreneurial behavior and job performance,

it is hypothesized that a potential direct relationship is also positive. Moreover, the

Conservation of resources (COR) theory can be used to explain this relationship. The COR

theory states that individuals strive to access, maintain, protect, and foster their resources

(Hobfoll & Shirom, 2001). These resources can be defined as objects, conditions, personal

characteristics, and energy resources (Hobfoll & Shirom, 2001). An implication of the COR

theory is that individuals can use their resources to gain other resources and that an initial

resource gain can cause further resource gain (Hobfoll & Shirom, 2001). Intrapreneurial

behavior involves being proactive, innovative and taking risks, and might therefore lead to a

higher level of resources. This resource gain might increase an individual’s ability to perform

on the job. To sum up, it is hypothesized that:

H1: There is a positive relationship between intrapreneurial behavior and job performance.

In this study, two mediators (i.e. self-efficacy and psychological well-being) are assessed. Next,

the three links in the two-mediator serial model displayed below will be explained. Namely, (1)

intrapreneurial behavior and self-efficacy, (2) self-efficacy and psychological well-being, and

(3) psychological well-being and job performance.

Intrapreneurial behavior and self-efficacy

In this research, self-efficacy is defined as “the belief in one’s competence to cope with

a broad range of stressful or challenging demands” (Luszczynska, Scholz, & Schwarzer, 2005,

p. 439). Self-efficacy is usually defined as being either task or domain-specific (Luszczynska,

Scholz, & Schwarzer, 2005). However, the generalized definition of self-efficacy fits better

within this research, since intrapreneurial behavior covers a wide array of task areas. The

general definition refers to a broad and stable sense of personal competence to deal effectively

with a variety of stressful situations (Luszczynska, Scholz, & Schwarzer, 2005). Additionally,

there is a discussion within the literature about conceptualizing self-efficacy as a state-like

construct or as a trait-like construct. Both indicate beliefs about one’s ability to achieve desired

outcomes, however, the constructs differ in the scope of the performance domain examined


(Chen, Gully, & Eden, 2001). The trait-like construct of self-efficacy contains one’s “tendency

to view themselves as capable of meeting task demands in a broad array of contexts” (Chen et

al., 2001, p. 63). Opposed to the state-like construct of self-efficacy, which focuses on the

perception of being capable to meet certain situational demands (Chen et al., 2001). Researchers

suggest that the trait-like dimension might positively influence the state-like construct of self-

efficacy (Chen et al., 2001).

In this research, self-efficacy is seen as a trait-like construct. Trait-like self-efficacy is

more resistant to temporary influences and appears in one’s life span as one accumulates

successes and failures across different task domains (Chen et al., 2001). As intrapreneurial

behavior covers a wide array of task areas and is not limited to certain situations, the trait-like

construct of self-efficacy fits better within this study.

An important element in building self-efficacy is the achievement of action goals that

relate to success experiences (Bandura, 1997). Employees who have succeeded in work-related

tasks are expected to have more confidence to complete identical tasks in the future (i.e. high

self-efficacy) than employees who have been unsuccessful (i.e. low self-efficacy). Moreover,

the level of self-efficacy can influence success experiences (Bandura, 1997). To illustrate, a

chain of successful performances can increase self-efficacy and the growth in self-efficacy can

consequently lead to more successful performances (Shipherd, 2019). Intrapreneurial behavior

could lead to such success experiences. Gawke and colleagues (2017) mention the example that

an employee who engages in intrapreneurial behavior successfully conceptualizes an innovative

idea. As a consequence, the employee feels more efficacious and expects similar positive

experiences when engaging in intrapreneurial behavior in the future (Gawke et al., 2017).

Hence, intrapreneurial behavior could positively influence the level of self-efficacy.

With regard to entrepreneurship, research has already shown that entrepreneurship is

highly associated with self-efficacy (i.e. self-efficacy as a predictor variable) (Frese & Gielnik,

2014; Hmieleski & Baron, 2008). Individuals high in self-efficacy tend to set challenging goals

and persist even under stressful circumstances. Moreover, they recover quickly from failure.

These characteristics are beneficial in the context of entrepreneurship, and might also be

beneficial for intrapreneurship. This is because these characteristics can reduce the negative

effects of an entrepreneurial context, which are identified by information overload, uncertainty,

and time pressure (Hmieleski & Baron, 2008). The research of Gawke and colleagues (2017)

also demonstrate the relationship between intrapreneurial behavior and self-efficacy. They

found that employee intrapreneurship predicted a positive change in personal resources


(including self-efficacy) over time, and personal resources predicted higher work engagement

over time. When individuals engage in intrapreneurial behavior they increase their personal

resources (i.e. ego-resilience, optimism and self-efficacy), which results in higher work

engagement. This research (i.e. Gawke et al., 2017) shows that the personal resource self-

efficacy can be increased by intrapreneurial behavior and can act as a mediator between

intrapreneurial behavior and an employee outcome. Thus, self-efficacy (i.e. mediator) can

explain the relationship between intrapreneurial behavior and an employee outcome.

Consequently, self-efficacy is seen as a mediator in the present study.

The first link in the two-mediator model (i.e. intrapreneurial behavior and self-efficacy) is

explained, the next link will focus on the relationship between self-efficacy and psychological

well-being. Regarding the relationship between intrapreneurial behavior and self-efficacy, it is

hypothesized that:

H2: There is a positive relationship between intrapreneurial behavior and self-efficacy.

Self-efficacy and psychological well-being

The concept of well-being has been found as complex and controversial. Ryan and Deci

(2001) define well-being as “optimal psychological functioning and experience” (p. 142).

However, theorists debate about what defines optimal psychological functioning and

experience (Ryan & Deci, 2001). One way to give meaning to the concept of well-being is with

the use of positive and negative affect (Jovanovic, 2015). Positive affect (PA) reflects an

individual’s level of pleasurable engagement, a high level of PA is described by terms such as

excited, active and determined. Low PA is defined by indicators of depression and apathy, such

as tiredness and inactive (Kuesten, Chopra, Bi, & Meiselman, 2013). Negative affect (NA) is a

general factor of subjective distress, a high level of NA involves a range of aversive mood

states, such as nervous, afraid and angry. Low NA represents calmness and involves terms such

as relaxed (Kuesten et al., 2013). Only the high ends of PA and NA represent the experience of

affect, low ends reflect the absence of emotional involvement (Kuesten et al., 2013). PA and

NA are seen as two independent dimensions of mood, and the two dimensions are not seen as

opposites. Thus, a large PA value does not mean a small NA value (Kuesten et al., 2013). Since

this research focuses on the benefits of intrapreneurial behavior for employees, the focus will

be on the dimension positive affect.

The findings of Van Seggelen-Damen and Van Dam (2016) supported the

importance of self-efficacy for employee well-being. Self-efficacy affects processes involved

in self-regulation, motivation, and stress. Self-efficacy relates to the idea that individuals can


exercise control over what they do, and thus can engage in problem-focused coping (Van

Seggelen-Damen & Van Dam, 2016). Furthermore, Avey, Wernsing, and Mhatre (2011) found

a positive relationship between psychological capital and well-being (β = .54). Psychological

capital is considered to be a construct that entails the components self-efficacy, hope, optimism,

and resilience. According to Avey et al. (2011), self-efficacious individuals tend to have

stronger beliefs in their abilities and capabilities to perform diverse tasks, which results in

increased effort and persistence in the pursuit of their goals. Consequently, this increases the

probability of success experiences which are associated with positive outcomes (i.e. well-

being). Lastly, Roemer and Harris (2018) also found a positive relationship between

psychological capital (including self-efficacy) and well-being (β = .56). Roemer and Harris

(2018) explain this relationship with the job demands-resources (JD-R) theory and the

conservation of resources (COR) theory. Both theories will be explained below since they can

help to explain the relationship between self-efficacy and psychological well-being. The authors

(Roemer & Harris, 2018) describe that employees high in psychological capital may have the

attitude, energy, and strength that keep them from negative consequences of stress at the

workplace. The employees may, therefore, experience higher levels of well-being (Roemer &

Harris, 2018).

The JD-R theory takes job demands, job resources, and personal resources into

account to make predictions about well-being and performance (Bakker & Demerouti, 2014).

The JD-R model proposes that personal resources are an important predictor of motivation.

Personal resources have motivational potential and could, therefore, lead to desirable outcomes

such as job satisfaction, engagement, and performance (Bakker & Demerouti, 2014). When an

individual’s personal resources are high, the more positive the person’s self-regard is and the

more goal self-concordance is assumed to be experienced. Individuals with goal self-

concordance are intrinsically motivated to pursue their goals and consequently, they provoke

high performance and satisfaction (Bakker & Dermerouti, 2014). Self -efficacy can be

considered as a personal resource (Bakker & Demerouti, 2014) and thus can have motivational

potential, which might lead to positive outcomes, such as psychological well-being.

The COR theory states that individuals accumulate, maintain, and protect their

resources. These resources can help them in dealing with stress (Hobfoll & Shirom, 2001). An

inference of the COR theory is that individuals with greater resources are less vulnerable to

resource loss and more capable of resource gain (Hobfoll & Shirom, 2001). An increase in

resources leads to an improvement in coping mechanisms (i.e. strategies to deal with stress).


Consequently, individuals are better able to withstand (future) stressors, which could positively

influence their psychological well-being (Hobfoll & Shirom, 2001). Hence, self-efficacy might

make individuals better able to deal with stressors, which may positively influence their level

of well-being. Therefore, it is hypothesized that:

H3: There is a positive relationship between self-efficacy and psychological well-being.

Psychological well-being and job performance

Researchers have consistently demonstrated that psychological well-being is related to

various measures (e.g. subjective and objective) of job performance and different types of job

performance (e.g. task performance, extra-role performance) (Wright & Cropanzano, 2004;

Wright, Cropanzano, Denney, & Moline, 2002; Wright & Cropanzano, 2000). The broaden -

and- build theory of positive emotions (Fredrickson, 2001) can be used to explain the

relationship between psychological well-being and job performance. According to this theory,

positive emotions (including the experience of psychological well-being) have the capacity to

“broaden” an individual’s momentary thought-action repertoires (i.e. thoughts and actions that

come to an individual’s mind). This broaden effect happens through expanding the selection of

possible thoughts and actions that come to mind (Fredrickson, 2001). For example, interest

encourages the urge to explore and to create new experiences. Moreover, positive emotions in

turn “build” an individual’s personal resources (e.g. psychological, intellectual, and social)

(Fredrickson, 2001). The experience of positive emotions (e.g. interest, joy) stimulates

employees’ positive meaning in their work. Consequently, due to the personal fulfillment that

an individual’s job can bring, the employee may be more productive (Wright & Cropanzano,

2004). Furthermore, the experience of positive emotions is important to mentally flourish and

psychologically grow. This flourishing or psychologically growth appears to make

psychologically well (or happy) people more proactive and resilient, which could further

enhance employee development (Wright & Cropanzano, 2004). Individuals who have a higher

score on psychological well-being are more able to “broaden-and-build” themselves and so

increase their personal resources and become more productively effective (Wright &

Cropanzano, 2004). Lastly, research of Lin, Yu, and Yi (2014) also showed a positive effect (β

= .67) of an individual’s sense of well-being on his or her job performance.

Therefore, it is hypothesized that:

H4: There is a positive relationship between psychological well-being and job performance.


To summarize the serial two mediator model, intrapreneurial behavior could lead to

success experiences, resulting in feeling more efficacious. Consequently, self-efficacy

stimulates processes involved in motivation, which might lead to psychological well-being.

Psychological well-being leads to job performance, due to positive emotions stimulating

perceptions of enhanced meaning and increasing personal fulfillment. This psychological

growth makes individuals perform better. Therefore, it is hypothesized that:

H5: There is a positive indirect relationship between intrapreneurial behavior and job

performance, via self-efficacy and psychological well-being.

This hypothesis entails partial mediation, as the direct relationship between intrapreneurial

behavior and job performance is still expected to be significant after introducing the mediators.

So, there are expected to be multiple paths between intrapreneurial behavior and job

performance. Important to note is that the paths between intrapreneurial behavior and job

performance do not have to be causal, causal inferences are outside the scope of this study.

More details about the design of this study will be given in the method section.

Intrapreneurial behavior and psychological well-being

The direct effect of intrapreneurial behavior on psychological well-being seems to

be unknown. Therefore, this study includes explorative research on the direct relationship

between intrapreneurial behavior and psychological well-being, since it might provide insights

into the impact of intrapreneurial behavior on employee outcomes. Based on the positive

indirect relationship between intrapreneurial behavior and psychological well-being, and the

reasoning (i.e. research and literature) behind this indirect relationship, it is hypothesized that a

potential direct relationship is also positive. It is hypothesized that:

H6: There is a positive relationship between intrapreneurial behavior and psychological well-

being.


Figure 1

The conceptual model: The relationship between intrapreneurial behavior and job

performance, mediated by self-efficacy and psychological well-being. Notes: + entails a

positive relationship.

Methods

Research design

The hypothesized relationships are examined with a cross-sectional, explanatory, and

quantitative research design. Because data is gathered at one moment in time, this study is a

cross-sectional study (Straits & Singleton Jr., 2017). The advantages of a cross-sectional design

are that it is relatively inexpensive, many outcomes can be assessed, and there is no loss to

follow-ups (Levin, 2006). In addition, since this study focuses on explaining relationships

between multiple variables by seeking answers to hypotheses, it is an explanatory study (Straits

& Singleton Jr., 2017). Lastly, because quantifiable data is gathered and is analyzed with

statistical analysis, it is a quantitative study (Straits & Singleton Jr., 2017). To collect data, a

questionnaire was developed. This questionnaire contains several scales since it was part of a

larger research project. In total five students used this questionnaire for their theses with the

main topic intrapreneurship.


Sample

The population of this study consists of Dutch employees, which are individuals who

execute work in exchange for receiving compensations (Kluijtmans, 2014). The respondents

need to be 18 years and older and employed within an organization (that is not their own) for

at least 12 hours per week. The hours are based on the Dutch labor force, in which an individual

is included when one works for at least 12 hours (CBS, n.d.). To make sure respondents meet

these particular features of the research population, demographic questions are asked at the

beginning of the survey. Based on the G*power tool (Faul, Erdfelder, Buchner, & Lang, 2009),

using an F test, the required sample size should be 138. This is based on an effect size of 0.15,

a confidence interval of 95%, a margin error of 5%, and five predictors. Therefore, it can be

argued that the sample size of the present study, which is 163, is large enough to reach a

sufficient power level. Regarding the respondents, 62.5 % are female and 37.5 % are male. The

average age of the respondents is 31.48 years (SD= 12.28) and the average years that

respondents have been working for their current employer is 4.9 years (SD=7.7). Moreover,

4.9% of the respondents have lower secondary education, 6% have a high-level secondary

education, 19.6% have vocational education, 42.4% have higher vocational education, and

27.2% have a university degree.

Procedure

The data gathered for this study has been retrieved through convenience sampling,

which means that all five students approached their own network. The advantages of

convenience sampling are that respondents are easily approachable, and the required sample

size can be achieved in a relatively fast way (Straits & Singleton Jr., 2017). The respondents

are contacted personally, via e-mail or WhatsApp. Moreover, the questionnaire was handed out

online via social media, such as LinkedIn and Facebook. The questionnaire was distributed

digitally, via a link to Qualtrics. After approximately a week, a reminder was sent. Before

respondents could start the questionnaire, they had to give consent for the use of their data for

scientific research. Moreover, a cover letter was included in which the procedure further was

explained and anonymity and confidentiality were ensured. The procedure included the link to

the website, at which results of the studies will be published and the e-mail address for further

questions. Respondents could choose between a Dutch and English questionnaire, because all

original English scales, which did not have a validated Dutch translation, have been translated

to Dutch using the back-translation technique. The questionnaires were collected digitally by

Qualtrics and imported in IBM SPSS Statistics 24.


Measures

The questionnaire consists of 87 items, this study used the scales for intrapreneurial

behavior, self-efficacy, psychological well-being, and job performance (Appendix A). The

scales are developed and tested in previous studies, which entails that the scales are previously

validated. Moreover, using existing scales enables a comparison between the findings of this

current study and with those from other studies. All variables are measured at the individual

level by employees. In order to ensure the expected single dimension for each scale, a factor

analysis was conducted to examine whether the items on a scale are measuring the same variable

of interest. Prior to performing the factor analysis, the suitability of the data was assessed. To

meet the criteria for factor analysis, the KMO measure needed to be above .6 and Bartlett’s test

of sphericity significant (Pallant, 2016). To interpret the factor analysis, the eigenvalue (factors

should have an eigenvalue of one or more) and the rotated component matrix (every item should

correlate with one factor, with a value of .3 or above) are checked (Pallant, 2016). In addition,

Catell’s scree test is used. Factors to the left of the breakpoint in the scree plot should be retained

(Pallant, 2016). To test for the reliability of each scale, the Cronbach’s alpha (needs to be above

.7) is checked (Pallant, 2016). In addition, the column alpha if item deleted is examined, in

which the values are compared with Cronbach’s alpha (i.e. the values needed to be lower than

alpha) (Pallant, 2016). Appendix B provides the output of the factor and reliability analyses.

Intrapreneurial behavior

Intrapreneurial behavior is measured using a 15-item scale developed by Stull and Singh

(2005) and validated in previous studies carried out in The Netherlands (Wakkee, Elfring, &

Monaghan, 2010) and Spain (Moriano, Molero, Topa, & Mangin, 2014). In the original study

(Stull & Singh, 2005) Cronbach’s alpha is 0.76. The scale consists of three dimensions that may

independently vary in strength and effect, namely proactiveness (e.g., “I take the initiative to

start projects”), risk-taking (e.g., “I take calculated risks despite the possibility of failure”), and

innovativeness (e.g., “I develop new processes, services or products”). A 5-point Likert scale

is used, ranging from completely disagree to completely agree. Regarding the factor analysis,

the KMO measure is .84 and Bartlett’s test is significant (p < 0.001), making the data suitable

for factor analysis (i.e. the KMO measure states whether or not enough items are predicted by

each factor). The factor analysis revealed the presence of 4 factors with eigenvalues exceeding

one, however, the first factor has the highest eigenvalue (5.42), explaining 36.14% of the

variance. The other factors showed eigenvalues around 1 and explained only 7 to 10% of the


variance. An inspection of the scree plot revealed a break after the first component, suggesting

a one-factor solution. The rotated component matrix showed that most items load quite strongly

(above .4) on the first factor. Loadings of .4 are typically considered to be strong loadings

(Pallant, 2016). Based on this information and previous studies (i.e. which stated that the three

dimensions measure intrapreneurial behavior), it was decided to retain one factor. In this study,

the Cronbach alpha coefficient was .85, which satisfies the above-mentioned guideline of .7. In

addition, the average inter-item correlation is .29.

Self-efficacy

Self-efficacy is measured using the New General Self-efficacy (NGSE) Scale of Chen,

Gully, and Eden (2001). This scale contains eight items and uses a 5-point Likert scale, ranging

from strongly disagree to strongly agree. The NGSE scale is often used in organizational

research (Chen et al., 2001). The scale focuses on general self-efficacy, which is the trait-like

dimension of self-efficacy (Chen et al., 2001). This fits with the definition of self-efficacy used

in this study since that also focuses on the generalized definition of self-efficacy. Chen and

colleagues (2001) reported a Cronbach’s Alpha of 0.87, 0.88, and 0.85 respectively. An

example item of the scale is “When facing difficult tasks, I am certain that I will accomplish

them”. Regarding the factor analysis, the KMO measure was .83 and Bartlett’s test was

significant (p < 0.001), making the data suitable for factor analysis. The factor analysis revealed

the presence of 2 factors with eigenvalues exceeding one. However, the first component has the

highest eigenvalue (3.41), explaining 42.65% of the variance. An inspection of the scree plot

revealed a clear break after the first component, suggesting a one-factor solution. In addition,

the rotated component matrix showed that most items load on the first component quite strongly

(>.5). Loadings of .4 are typically considered to be strong loadings (Pallant, 2016). Moreover,

the loadings on the first component are stronger than the loadings on the second component.

Based on this information and previous studies, it was decided to retain one factor. In this study,

the Cronbach alpha coefficient was .8, which satisfies the above-mentioned guideline of .7. In

addition, the average inter-item correlation is .34.

Job performance

Job performance is measured using the self-rated scale developed by Heilman, Block,

and Lucas (1992), which includes 5 items. The scale is often used in organizational research

(e.g. Lam, Chen, & Schaubroek, 2002; Wayne, Shore, & Liden, 1997). A 7-point Likert scale

was used, ranging from very low quality to very high quality and from very low to very high.


An example of an item used in the scale is “How would you judge the overall quality of your

work?” The scale focuses on perceived competence (Heilman et al., 1992), which fits with the

definition of job performance used in this research since this definition focuses on subjective

job performance (i.e. self-ratings). This scale has been used in research before (Sleegers, 2012;

Kolste, 2012). These studies reported a Cronbach’s alpha of 0.84 and 0.83 respectively. In these

studies (Sleegers, 2012; Kolste, 2012), factor analyses showed that the items loaded on one

factor. Regarding the factor analysis in this current study, the KMO measure was .7 and

Bartlett’s test was significant (p < 0.001), making the data suitable for factor analysis. The

factor analysis revealed the presence of 2 factors with eigenvalues exceeding one, explaining

74.44% of the variance. An inspection of the scree plot revealed a break after the second

component. In addition, the rotated component matrix showed that 3 items load quite strongly

(>.8) on the first component and 2 items load quite strongly (>.8) on the second component.

Although the results suggest a two-factor solution, it was decided to retain one factor, because

of literature and previous studies. In this study, the Cronbach alpha coefficient was .73, which

satisfies the above-mentioned guideline of .7. In addition, the average inter-item correlation is

.38.

Psychological well-being

Psychological well-being is measured by the short form of the positive and negative

affect schedule (PANAS) (Thompson, 2007). Thompson (2007) reported a Cronbach’s Alpha

of 0.80 and found a two-component PA and NA factor structure. The PA and NA dimensions

are used in studies in several disciplines, such as psychology, business, and politics (Thompson,

2007). In this research, only the PA items are used. The PANAS is claimed to provide

independent measures of PA and NA, and the two dimensions are not thought to be opposites

(Kuesten, Chopra, Bi, & Meiselman, 2013), which makes it possible to only include the PA

items. Moreover, the PA scale fits better within this research design. The scale contains 5 items

and uses a 5-point Likert scale, ranging from never to always. An example item is “Thinking

about yourself and how you normally feel, to what extent do you generally feel inspired?”

Regarding the factor analysis, the KMO measure was .68 and Bartlett’s test was significant,

making the data suitable for factor analysis. The factor analysis revealed the presence of 2

factors with eigenvalues exceeding one, explaining 61.26% of the variance. An inspection of

the scree plot revealed a break after the first component. The item ‘alert’ showed a low

individual KMO value of .56. Furthermore, the correlation matrix showed that this item has low

correlations with the other items. When this item is deleted, results show a one-factor solution,


with one factor with eigenvalues exceeding one (1.95), explaining 48.7% of the variance.

Moreover, the item correlations and individual KMO’s are higher. Based on this information,

it was decided to delete the item alert, since it does not add considerably to the construct. In this

study, the Cronbach alpha coefficient was .60, which shows questionable reliability. If the item

‘alert’ would be deleted, alpha would be .64. When the item ‘attentive’ would additionally be

deleted, alpha would be .66. Since it was decided to delete the item alert, Cronbach’s alpha is

.64. The item attentive was not deleted because this item does add considerably to the construct

and deleting this item could affect the meaning of the scale. A Cronbach’s alpha of .64 is still

questionable however, some authors (e.g. Cho & Kim, 2015) are against using strict guidelines

for the evaluation of Cronbach’s alpha.

Control variables

To check the possibility of a spurious association, the control variables age and

educational level are included. Age is related to job performance (Skirbekk, 2003) and

innovation (Camelo-Ordaz, Sousa-Ginel, & Ruiz-Navarro, 2012), which is a dimension of

intrapreneurial behavior. Individual job performance is found to decrease from around 50 years

old (Shirbekk, 2003). Moreover, as age increases, resistance to change rises and security values

become more important. Consequently, the employee will tend to adopt more conservative

strategies, which will translate into lower innovation (Camelo-Ordaz et al., 2012). Educational

level is also related to job performance (Ng & Feldman, 2009) and to intrapreneurial behavior

(Urbano & Turro, 2013). Highly educated employees tend to have higher task performance (Ng

& Feldman, 2009). Moreover, education plays a role in the development of intrapreneurial

activities since it reinforces in the accumulation of knowledge (Urbano & Turro, 2013). Since

age and educational level are related to both intrapreneurial behavior and job performance, the

relationship between these variables might be due to age or educational level. To rule this out,

age and educational level are controlled for in this study. Educational level has the following

categories: 1) lower secondary school, 2) high levels secondary education, 3) vocational, 4)

higher vocational, and 5) university. Age is included as a continuous variable.

Analysis

SPSS is used to screen and clean the obtained data. The gathered data were checked for

missing values, outliers, and mistakes in the items or responses. The respondents who did not

belong to the target group or opened the survey but did not fill it in are deleted. A few

respondents did not fill in the survey after the demographic questions. After excluding these


respondents, missing values were coded 99. A valid N of 163 respondents remained. No outliers

or mistakes in the responses were discovered. Subsequently, the average sum scores were

created for each scale. Next, descriptive information such as means, correlations among

variables and standard deviations were computed.

The following assumptions for multiple regression are checked: linearity, normality,

homoscedasticity, and multicollinearity. The results showed that the data were normally

distributed and the relationship between variables is linear. In addition, there were no issues

with homoscedasticity and multicollinearity. The VIF was around 1 and the tolerance was not

below .6. Hence, the assumptions for regression analysis are satisfied.

Lastly, a mediation analysis was conducted using the PROCESS tool of Hayes (2018)

in SPSS. PROCESS has preprogrammed mediation models and these are specified in

command by model number. Since the proposed model is a serial multiple mediator model,

model number 6 was used. To examine whether the direct and total effects in the model are

statistically significant, the p-values in the SPSS output are checked (p <.05). To explore

whether the indirect effects in the model are significant, bootstrap confidence intervals

generated by the PROCESS tool were examined. A 95% bootstrap confidence interval based

on 5000 bootstrap samples was used. An effect is statistically significant when zero is outside

the bootstrap confidence interval. Both mediators are checked separately and the two

mediators linked in serial are checked. In order to rule out spurious association, the control

variables age and educational level are included in the analysis. The interpretation of the

effects stayed the same, only with the inclusion that the control variables are held constant.


Results

Descriptive statistics

Table 1 gives an overview of the means, standard deviations, N, and the correlations

between the predictor variables, dependent variable, and the control variables. The mean scores

on psychological well-being, self-efficacy, and intrapreneurial behavior are slightly above the

average scale score. This indicates that the respondents report a considerable amount of these

behaviors. Moreover, the mean score of job performance is also above the average scale score,

indicating that the respondents tend to score themselves high on job performance. Below, the

correlations between the variables will be shortly described. The Pearson correlation coefficient

and the p-value will be given, to clarify the relationships. Psychological well-being is correlated

with self-efficacy (r = .40, p < .05), intrapreneurial behavior (r = .47, p < .05), and job

performance (r = .41, p < .05). In addition, self-efficacy is correlated with intrapreneurial

behavior (r = .33, p < .05) and job performance (r = .49, p < .05). Lastly, the variables

intrapreneurial behavior and job performance show a correlation of .17 (p < .05). These

relationships will be further explained in the next section. The control variable age is correlated

with job performance (r = .25, p < .05) and the control variable education level is correlated

with self-efficacy (r = .17, p < .05) and intrapreneurial behavior (r = .22, p < .05). Although the

control variables are not significantly correlated to all the predictor variables and dependent

variable, they will be included in the regression analyses. By including the control variables in

the analysis, the effects of the researched variables (i.e. intrapreneurial behavior, job

performance, self-efficacy, and psychological well-being) will be corrected for the influence of

the control variables age and educational level.

BENEFITS OF INTRAPRENEURIAL BEHAVIOR

Table 1

Means, N, standard deviations and correlations

Mean Std.

deviation

N Min Max 1 2 3 4 5 6

1. Well-being 3.83 .51 163 2.50 5

2. Self-efficacy 3.83 .47 165 2.38 5 .40**

3. IB b 3.46 .52 169 1.93 4.87 .47** .33**

4. Job

performance

5.45 .62 164 3 6.80 .41** .49** .17*

5. Age 31.48 12.28 184 18 66 .08 .03 .04 .25**

6. Educational

level a

3.81 1.06 184 1 5 .07 .17* .22** -.03 -.26**

* P < .05; ** P < .01 (2-tailed) a Educational level was coded 1 (Lower secondary school), 2 (High levels secondary education), 3 (Vocational), 4 (Higher vocational

education), 5 (University) b Intrapreneurial behavior


Regression analysis

The output from the PROCESS procedure consists of a series of regression models.

First, the mediator self-efficacy (M1) is predicted using intrapreneurial behavior (X) and the

control variables. Then the second mediator (M2: psychological well-being) is predicted by X,

M1, and the control variables. Finally, job performance (Y) is predicted by X, M1, M2, and

control variables. Figure 2 presents the outcome of these regression models in the form of a

path model, including unstandardized effects (B). Hypothesis 1 proposed that intrapreneurial

behavior and job performance are positively related. Figure 2 shows that intrapreneurial

behavior is not significantly related to job performance (B = - .08, p = .3618). This means that

hypothesis 1 is rejected. Hypothesis 2 proposed that intrapreneurial behavior and self-efficacy

are positively related. Results show that intrapreneurial behavior and self-efficacy are indeed

significantly positively related (B = .29, p = .0001). This means that, as stated by hypothesis 2,

individuals who score high on intrapreneurial behavior also tend to show a high self-efficacy.

The results further show that self-efficacy and psychological well-being are

positively related (B = .29, p = .0001), which means that hypothesis 3 is supported. This entails

that individuals who score high on self-efficacy also tend to score high on psychological well-

being. Hypothesis 4 proposed a positive relationship between psychological well-being and job

performance. Figure 2 shows a positive relationship between these variables (B = .31, p =

.0010), therefore hypothesis 4 is supported. This suggests that individuals who score high on

psychological well-being also tend to score high on job performance. Figure 2 also shows a

positive relationship between intrapreneurial behavior and psychological well-being (B = .39,

p = .0000), supporting hypothesis 6. This suggests that individuals who score high on

intrapreneurial behavior also tend to have a high score on psychological well-being.

Figure 2

Researched model including unstandardized direct effects, controlling for age and educational

level. Notes: * P < .05, ** P < .01


To assess the mediation effect of self-efficacy and psychological well-being (i.e.

indirect effects), table 2 (displayed below) is used. The results show that self-efficacy mediated

the relationship between intrapreneurial behavior and job performance (B = .1597, bootstrap

interval: .0609 to .2705). Moreover, psychological well-being mediated the relationship

between intrapreneurial behavior and job performance (B = .1233, bootstrap interval: .0377 to

.2271). Hypothesis 5 proposed that there is a positive indirect relationship between

intrapreneurial behavior and job performance, via self-efficacy and psychological well-being.

A 95% bootstrap confidence interval based on 5000 bootstrap samples indicated that the

indirect effect (B = .0271) was entirely above zero (.0044 to .0671). This means that self-

efficacy and respectively psychological well-being act as mediators in the relationship between

intrapreneurial behavior and job performance. Since the direct relationship between

intrapreneurial behavior and job performance is not significant, self-efficacy and psychological

well-being fully mediate the relationship between intrapreneurial behavior and job

performance. This entails that individuals who score high on intrapreneurial behavior

experience positive emotions, belief in their competence to meet task demands in multiple

contexts and tend to score themselves high on job performance. Individuals with a high score

on intrapreneurial behavior tend to score high on job performance, however, this relationship

is explained by the influence of self-efficacy and psychological well-being. The mediation

effect shows that the experience of positive emotions (i.e. psychological well-being) and the

belief in one’s competence (i.e. self-efficacy) are important in experiencing job performance.

This confirms hypothesis 5.

Table 2

Indirect (unstandardized) effects of X on Y, controlling for age and educational level.

Effect BootSE BootLLCI BootULCI

TOTAL .3102 .0867 .1557 .4887

Ind1 (M1) .1597 .0543 .0609 .2705

Ind2 (M2) .1233 .0480 .0377 .2271

Ind3 (M1 and

M2)

.0271 .0162 .0044 .0671


Discussion

The aim of this study was to investigate the relationship between intrapreneurial

behavior and job performance, and the influence of psychological well-being and self-efficacy

on this relationship. The results showed no direct significant relationship between

intrapreneurial behavior and job performance. However, the results showed an indirect positive

relationship between intrapreneurial behavior and job performance, via self-efficacy and

psychological well-being. This entails that self-efficacy and psychological well-being fully

mediate the relationship between intrapreneurial behavior and job performance. This means

that individuals who score high on intrapreneurial behavior tend to score high on job

performance, only through self-efficacy and psychological well-being. Thus, individuals who

score high on intrapreneurial behavior tend to score high on job performance, because they

belief in their competence and experience positive emotions. The mediators self-efficacy and

psychological well-being are significantly linked in serial, but also separately act as a mediator

in the researched model. The effects of the separate mediators are stronger than both mediators

in serial (table 2 in results). This means that an individual with a high score on intrapreneurial

behavior tends to experience a high job performance because of either belief in their own

competence or the experience of positive emotions, or both. These findings will be discussed

in the next section.

Theoretical contributions

The first theoretical contribution of this study is that it takes an individual perspective

on intrapreneurship and focuses on the benefits of intrapreneurial behavior for employees. The

current study contributes to this matter by examining the relationship between intrapreneurial

behavior and psychological well-being and job performance. Moreover, it contributes to the

field by explaining how intrapreneurial behavior could lead to job performance (i.e. by

including mediators). Gawke et al. (2018) found that employee intrapreneurship is not directly

related to in-role performance but it is indirectly related, through work engagement.

Furthermore, Gawke and colleagues (2017) found that intrapreneurial behavior increases

personal resources (including self-efficacy) which consequently results in higher work

engagement. Interestingly, this current study confirms a non-significant direct relationship

between intrapreneurial behavior and job performance. Moreover, this current study also found

a significant indirect relationship between intrapreneurial behavior and job performance, via

self-efficacy and psychological well-being. These findings (i.e. full mediations) suggest that

other variables are crucial in the intrapreneurship – performance link and intrapreneurship does


not automatically result in performance, as many organizations seem to think. This current

study confirms the mediating effect of self-efficacy and contributes to the before-mentioned

research by including a different employee outcome. Self-efficacy does not only seem to

mediate the relationship between intrapreneurship and work engagement (Gawke et al., 2017)

but also mediates the relationship between intrapreneurship and job performance. Hence,

believing in one’s competence seems to be crucial in the relationship between intrapreneurship

and multiple employee outcomes. This current study also contributes to the before-mentioned

studies by including the mediator psychological well-being. Just as work engagement (Gawke

et al., 2018) and self-efficacy (Gawke et al., 2017; current study), psychological well-being

mediates the relationship between intrapreneurship and an employee outcome. Moreover, this

current study found a direct relationship between intrapreneurial behavior and psychological

well-being, which has the appearance of not being researched before. Hence, this current study

contributes by indicating that the experience of positive emotions is important in the

intrapreneurship- performance link.

Lastly, the findings of this current study support some principles of the COR theory. In

line with the assumption of the COR theory that individuals with high resources are more able

to gain resources and that an initial resource gain can cause further resource gain (Hobfoll &

Shirom, 2001), the results of this current study imply that individuals who show intrapreneurial

behavior are able to gain resources (i.e. self-efficacy), and this resource gain seems to be

associated with psychological well-being and consequently job performance (i.e. further

resource gains). Furthermore, drawing upon the JD-R theory, it was argued that self-efficacy

(as a personal resource) has motivational potential, which leads to positive outcomes such as

psychological well-being (Bakker & Demerouti, 2014). The findings of this current study

support this assumption, since a positive relationship between self-efficacy and psychological

well-being was found.

Limitations and implications for future research

This study used a cross-sectional research design. Cross-sectional data is gathered at

one moment in time, which makes it impossible to determine the causality between variables

(Straits & Singleton, 2017). However, the cross-sectional results of this study might be an

indication of a potential causal relationship. The presented cross-sectional results would be

expected when there is a causal relationship. For example, individuals with a high score on

intrapreneurial behavior tend to have a high score on self-efficacy, which can be expected when

there is a causal relationship between intrapreneurial behavior and self-efficacy (i.e. increase in


intrapreneurial behavior leads to an increase in self-efficacy). A suggestion for future research

would be to collect longitudinal data to gain insight into the causality between the researched

variables. This could, for example, be done by distributing the survey at three moments in time

to the same respondents with two months between each of the surveys. Due to this longitudinal

design, inferences about the patterns of change in the variables can be observed (Straits &

Singleton, 2017). Longitudinal research could also be used to investigate how to increase the

level of self-efficacy of individuals since this current study suggests that self-efficacy is

important in the intrapreneurship- performance link. Different interventions which are assumed

to increase self-efficacy can be investigated regarding their effect on self-efficacy.

A second limitation of this study is the self-rating of job performance. A risk of self-

ratings is that these might not reflect true performance because of deficiencies in self-ratings,

such as leniency (Heidemeier, 2005). Respondents may not be sincere and over-evaluate or

under-evaluate themselves. A suggestion for future research is to use performance ratings from

multiple sources, for example by including supervisor ratings. However, it should be noted that

supervisor ratings may also be subject to bias. For example, the halo and horns effect, which is

a cognitive bias in which one trait (good or bad) overshadows all other actions or traits (Peeters,

De Jonge, & Taris, 2014). This could lead to a supervisor unfairly underrating or overrating an

employee. Furthermore, it would be interesting to investigate if and how the supervisor

influences the level of self-efficacy of their employees since this variable seems to be important

in the intrapreneurship-performance relationship. Another suggestion is to include

organizational citizenship behavior (OCB) in the measurement of job performance. Research

in the intrapreneurship field found direct relationships between intrapreneurship and

organizational outcomes. However, as mentioned above, the direct relationship between

intrapreneurial behavior and employee outcomes is not significant. One possible explanation

for this insignificant relationship might be that employees interpret intrapreneurial behavior as

something outside their job description. Consequently, they might not include it in their

judgement of their job performance, since they think this only includes tasks presented in their

job description. Since OCB entails employees voluntarily making extra-role contributions to

the organization that is beyond their regular job duties (Jordan, Schrader, Field, & Armenakis,

2007), including OCB in the survey might lead to respondents scoring themselves higher on

job performance. It would be interesting to see whether this changes the (significance of)

relationships in the researched model. Since OCB is seen as a factor impacting the effectiveness

of an organization (Jordan, Schrader, Field, & Armenakis, 2007), this variable is also interesting

from an organizational point of view.


The third limitation of this research is that in this study psychological well-being is

defined and measured with the dimension positive affect. The present study focused on the

potential benefits of intrapreneurial behavior. It would be a suggestion for future research to

include or focus on the dimension negative affect (i.e. subjective distress), thereby investigating

the potential costs of intrapreneurial behavior. Although this research did not show detrimental

effects, previous research of Gawke and colleagues (2018) showed that employee

intrapreneurship positively relates to exhaustion, which shows that intrapreneurial behavior can

have detrimental effects. Therefore, it is important to focus on both positive and negative affect

in future research. A fourth limitation of this research is the reliability of the scale psychological

well-being (i.e. positive affect). The Cronbach’s alpha of this scale was .642, which is lower

than the used guideline of >.7. This suggests that the internal consistency of the scale items is

questionable. The effects of psychological well-being might have been stronger in the current

researched model if the scale complied with the used guidelines.

This study indicated that an individual with a high score on intrapreneurial behavior

tends to have a high score on job performance because of either belief in their own competence,

experience positive emotions or both. The last limitation of this study is that it does not explain

why the mediators self-efficacy and psychological well-being act as mediators both separately

and in serial. The question arises why some individuals (who score high on intrapreneurial

behavior) score high on job performance because of self-efficacy, some because of

psychological well-being and some individuals because of both. It would be a suggestion for

future research to investigate why these multiple pathways prevail and which individuals follow

each pathway. Hence, it would be a suggestion to include moderators in the researched model.

In this study, intrapreneurial behavior consists of the three dimensions proactivity,

innovativeness, and risk-taking. The question arises whether the non-significant direct

relationship between intrapreneurial behavior and job performance could be explained by these

different dimensions. Correlations between the three dimensions and the other variables in the

researched model (i.e. psychological well-being, self-efficacy, and job performance) are

conducted (Appendix C). Proactiveness and innovativeness are both correlated to job

performance (r = .23, p < .01 and, r = .16, p < .05 respectively). The dimension risk-taking is

not correlated with job performance. Therefore, the dimension risk-taking could be responsible

for the non-significant relationship. Future research should consequently further investigate the

underlying dimensions of intrapreneurial behavior and the direct relationship between

intrapreneurial behavior and job performance.


Practical implications

Intrapreneurship is increasingly seen as a way to revitalize organizations (Waal, Kolker,

Goedebuure, & Van der Heijde, 2013). This study aims to provide insights into the potential

benefits of intrapreneurial behavior for employees. Firstly, the results show that individuals

with a high score on intrapreneurial behavior tend to have high scores on psychological well-

being. This suggests that intrapreneurial behavior has benefits for employees. Acting in an

intrapreneurial way seems to be associated with the experience of positive emotions. This

suggests organizations should stimulate intrapreneurial behavior. Rigtering and Weitzel (2013)

give suggestions on how to stimulate intrapreneurial behavior in organizations. To stimulate

intrapreneurial behavior, a formal work context is needed that puts little constrains on

employees. This means that the work context allows for horizontal participation (i.e. jobs are

broadly defined) and provides support for the development of innovative projects (i.e.

willingness to allocate sufficient resources to employees that want to develop a new product or

service) (Rigtering & Weitzel, 2013). In addition, employees have to be able to trust their

manager that they will not sabotage their position when they show intrapreneurial behavior

(Rigtering & Weitzel, 2013). Moreover, the authors mention that when an individual deals with

a high number of formal procedures, trust in the relationship with their manager is even more

crucial. When employees show intrapreneurial behavior in these situations (i.e. lot of formal

procedures) they can be motivated to abandon formal procedures and organizational rules. In

these situations, an employee must trust their supervisor that (s) he provides support in case

things go wrong (Rigtering & Weitzel, 2013). Thus, organizations could stimulate

intrapreneurial behavior, as it is associated with the experience of positive emotions, by

providing a work context in which jobs are broadly defined, where there is a willingness to

allocate resources, and in which the relationship between employee and manager is based on

trust.

Secondly, the results show that employees who show intrapreneurial behavior tend to

score high on job performance, because of the crucial role of self-efficacy and psychological

well-being. Without self-efficacy and psychological well-being, no relationship exists between

intrapreneurial behavior and job performance. This leads to the following implication for

practice. When organizations want employees to adopt an intrapreneurial way of working to

boost performance, they should be aware that other factors are involved and influence job

performance. Consequently, when organizations implement practices to stimulate

intrapreneurial behavior, they should also focus on stimulating self-efficacy and psychological


well-being. This could, for example, be done by providing positive feedback or training (e.g.

positive psychology intervention). Self-efficacy has been studied in many research fields, such

as psychology (Maddux, 2000). As Maddux (2000, p. 277) stated: “believing that you can

accomplish what you want to accomplish is one of the most important ingredients in the recipe

for success”. This current study seems to demonstrate the importance of self-efficacy for the

field of intrapreneurship for both research and practice.

Conclusion

Most studies in the intrapreneurship field focus on intrapreneurship and organizational

outcomes. However, the relationship between intrapreneurship and employee outcomes are

equally important. The aim of this study was to examine the relationship between

intrapreneurial behavior and job performance, and the influence of psychological well-being

and self-efficacy on this relationship. The results showed no direct relationship between

intrapreneurial behavior and job performance. However, the results showed an indirect positive

relationship between intrapreneurial behavior and job performance, via self-efficacy and

psychological well-being. This study contributes to the existing literature by increasing the

knowledge on processes and effects of intrapreneurship at the individual level. Suggestions for

future research are to collect longitudinal data, include or focus on the costs of intrapreneurial

behavior (e.g. negative affect) and OCB, and to include moderators in the researched model.


References

Avey, J.B., Wernsing, T.S., & Mhatre, K.H. (2011). A longitudinal analysis of positive

psychological constructs and emotions on stress, anxiety, and well-being. Journal of

leadership and organizational studies, 18 (2), 216-228. doi: 10.1177/1548051810397368

Bakker, A. B., & Demerouti, E. (2014). Job demands-resources theory. In C. Cooper & P.

Chen (Eds.), Wellbeing: A complete reference guide (pp. 37–64). Chichester: Wiley-

Blackwell.

Bandura, A. (1997). Self-efficacy: The exercise of control. New York, NY: W. H. Freeman

Blanka, C. (2018). An individual-level perspective on intrapreneurship: a review and ways

forward. Review of managerial science, 1-43. doi.org/10.1007/s11846-018-0277-0

CBS. (n.d.) Begrippen: beroepsbevolking (12-uurgrens). Retrieved from

https://www.cbs.nl/nl-nl/onze-

diensten/methoden/begrippen?tab=b#id=beroepsbevolking--12-uursgrens--

Camelo-Ordaz, C., Fernandez-Alles, M., Ruiz-Navarro, J., & Sousa-Ginel, E. (2012). The

intrapreneur and innovation in creative firms. International Small Business Journal, 30

(5), 513–535. https ://doi.org/10.1177/02662 42610 38539 6

Campbell, C.H., Ford, P., Rumsey, M.G., Pulakos, E.D., Borman, W.C., Felker, D.B., De

Vera, M.V., & Riegelhaupt, B.J. (1990). Development of multiple job performance

measures in a representative sample of jobs. Personnel Psychology, 43, 277-300.

https://doi.org/10.1111/j.1744-6570.1990.tb01559.x

Chen, G., Gully, S.M., & Eden, D. (2001). Validation of a new general self-efficacy scale.

Organizational research methods, 4(1), 62-83.https://doi.org/10.1177/109442810141004

Cho, E., Kim, S. (2015). Cronbach’s coefficient alpha: well-known but poorly understood.

Organizational research methods, 18(2), 207-230. doi:10.1177/1094428114555994

Douglas, E.J., & Fitzsimmons, J.R. (2012). Intrapreneurial intentions versus entrepreneurial

intentions: distinct constructs with different antecedents. Springer, 115-132. doi:

10.1007/s11187-012-9419-y


Faul, F., Erdfelder, E., Buchner, A., & Lang, A.-G. (2009). Statistical power analyses using

G*Power 3.1: Tests for correlation and regression analyses. Behavior Research Methods,

41, 1149-1160.

Fredrickson, B.L. (2001). The role of positive emotions in positive psychology: the broaden-

and-build theory of positive emotions. American psychologist, 56(3), 218-226. doi:

10.1O37//0OO3-O66X.56.3.21

Frese, M., & Gielnik, M.M. (2014). The psychology of entrepreneurship. The annual review

of organizational psychology and organizational behavior, 1, 413-438. doi:

10.1146/annurev-orgpsych-031413-091326

Gawke, J.C., Gorgievski, M.J., & Bakker, A.B. (2017). Employee intrapreneurship and work

engagement: a latent change score approach. Journal of vocational behaviour, 100, 88-

100. doi: 10.1016/j.jvb.2017.03.002

Gawke, J.C., Gorgievski, M.J., & Bakker, A.B. (2018). Personal costs and benefits of

employee intrapreneurship: disentangling the employee intrapreneurship, well-being, and

job performance relationship. Journal of occupational health psychology, 23(4), 508-519.

doi: https://doi.org/10.1037/ocp0000105

Grant, A.M., Christianson, M.K., & Price, R.H. (2007). Happiness, health, or relationships?

Managerial practices and employee well-being tradeoffs. Academy of Management, 51-

63. https://doi.org/10.5465/amp.2007.26421238

Hayes, A.F. (2018). Introduction to mediation, moderation, and conditional process analysis,

second edition: a regression-based approach. New York: The Guilford Press.

Heidemeier, H. (2005). Self and supervisor ratings of job performance: a meta-analysis and a

process model of rater convergence. Friedrich-Alexander-Universität Erlangen-Nürnberg.

Heilman, M.E., Block, C.J., & Lucas, J.A. (1992). Presumed incompetence? Stigmatization

and affirmative action efforts. Journal of Applied Psychology, 77(4), 536-544. doi:

10.1037/0021-9010.77.4.536

Hmieleski, K.M., & Baron, R. (2008). When does entrepreneurial self-efficacy enhance

versus reduce firm performance? Strategic entrepreneurship journal, 2, 57-72.

https://doi.org/10.1002/sej.42

about:blank

about:blank

about:blank


Hobfoll, S. E., & Shirom, A. (2001). Conservation of resources theory: Applications to stress

and management in the workplace. In: Golembiewski, R.T. (Ed.). Handbook of

organizational behavior. New York, US: Routledge.

Jordan, M.H., Schraeder, M., Feild, H.S., & Armenakis, A.A. (2007). Organizational

citizenship behavior, job attitudes, and the psychological contract. Military Psychology,

19(4), 259-271. https://doi.org/10.1080/08995600701548122

Jovanovic, V. (2015). Beyond the PANAS: incremental validity of the scale of positive and

negative experience (SPANE) in relation to well-being. Personality and individual

differences, 86, 487-491. https://doi.org/10.1016/j.paid.2015.07.015

Kolste, C. (2012). The influence of HR attributions on employee performance: the mediating

role of psychological capital (Master thesis, Tilburg University). Retrieved from

http://arno.uvt.nl/show.cgi?fid=127517.

Kluijtmans, F. (2014) Leerboek HRM. tweede druk. Groningen/Houten: Noordhoff Uitgevers

Kuesten, C., Chopra, P., Bi, J., & Meiselman, H.L. (2013). A global study using PANAS (PA

and NA) to measure consumer emotions associated with aromas of phytonutrient

supplements. Food quality and preference, 33, 86-97. doi:

https://doi.org/10.1016/j.foodqual.2013.11.004

Lam, S.K., Chen, X., & Schaubroek, J. (2002). Participative decision making and employee

performance in different cultures: the moderating effects of allocentrism/idiocentrism and

efficacy. Academy of management journal, 45 (5), 905-914.

https://doi.org/10.5465/3069321

Levin, K. (2006). Study design III: Cross-sectional studies. Evid Based Dent 7, 24–25.

doi:10.1038/sj.ebd.6400375

Lin, Y., Yu, C., & Yi, C. (2014). The effects of positive affect, person-job fit, and well-being

on job performance. Social Behavior & Personality: an international journal., 42 (9),

1537-1547. doi: 10.2224/sbp.2014.42.9.1537.

Longo, Y., Coyne, I., Joseph, S., & Gustavsson, P. (2016). Support for a general factor of

well-being. Personality and Individual Differences, 100, 68–72. https://doi.org/

10.1016/j.paid.2016.03.082.

about:blank

about:blank


Luszczynska, A., Scholz, U., & Schwarzer, R. (2005). The General Self-Efficacy Scale:

Multicultural Validation Studies. The Journal of Psychology, 139 (5), 439-457. doi:

10.3200/JRLP.139.5.439-457

Maddux, J.E. (2000). Self-efficacy: The power of believing you can. In: Snyder, C.R., &

Lopez, S.J. (2002). Handbook of positive psychology (p. 277-287). New York: Oxford

University Press.

Moriano, J.A., Molero, F., Topa, G., & Mangin, J.L. (2014). The influence of

transformational leadership and organizational identification on intrapreneurship.

International entrepreneurship management journal, 10, 103-119. doi:10.1007/s11365-

011-0196-x

Neessen, P.C.M., Caniëls, M.C.J., Vos, B., & De Jong, J.P. (2018). The intrapreneurial

employee: toward an integrated model of intrapreneurship. International

entrepreneurship and management journal, 15(2), 545-571. doi: 10.1007/s11365-018-

0552-1

Ng, T.W.H., & Feldman, D.C. (2009). How broadly does education contribute to job

performance? Personnel Psychology, 62, 89-134. https://doi.org/10.1111/j.1744-

6570.2008.01130.x.

Oswald, A. J., Proto, E., & Sgroi, D. (2015). Happiness and productivity. Journal of Labor

Economics, 33(4), 789–822. doi.org/10.1086/681096

Pallant, J. (2016). SPSS survival manual (sixth edition). Berkshire: McGraw-Hill Education

Peeters, M., De Jonge, J., & Taris, T. (2014). An introduction to contemporary work

psychology. Cichester, West Sussex, UK: John Wiley & Sons.

Preenen, P.T.Y., Liebregts, W.J., Dhondt, S., Oeij, P.R.A., & Van der Meulen, F.A. (2014).

The intrapreneurial behaviour measure (IBM). Een meetinstrument om intrapreneurial

gedrag van werknemers en factoren die dit beïnvloeden te meten binnen organisaties.

TNO rapportage.

Roemer, A., & Harris, C. (2018). Perceived organisational support and well-being: the role of

psychological capital as a mediator. SA Journal of industrial psychology, 44(0). doi:

https://doi.org/ 10.4102/sajip.v44i0.1539.

about:blank

about:blank


Rigtering, J.P.C., & Weitzel, U. (2013). Work context and employee behavior as antecedents

for intrapreneurship. International Entrepreneurship and Management Journal, 9, 337-

360. doi: 10.1007/s11365-013-0258-3.

Ryan, R. M., & Deci, E. L. (2001). On happiness and human potentials: A review of research

on hedonic and eudaimonic well-being. Annual Review of Psychology, 52(1), 141–166.

https://doi.org/10.1146/annurev.psych.52.1.141

Shipherd, A.M. (2019). This doesn’t look too hard: a mixed methods exploration of self-

efficacy and sources of self-efficacy information in a novel puzzle task. Journal of

applied social psychology, 49, 226-238. doi: 10.1111/jasp.12579

Skirbekk, V. (2003). Age and individual productivity: a literature survey. Max Planck

Institute for Demographic Research: MPIDR WORKING PAPER WP 2003-028.

Retrieved from

https://www.researchgate.net/profile/Vegard_Skirbekk/publication/4862787_Age_and_In

dividual_Productivity_A_Literature_Survey/links/0deec52c52ffb267fa000000.pdf

Sleegers, W. (2012). High-performance work systems and employee performance: examining

the contribution of psychological capital (Master thesis, Tilburg University). Retrieved

from http://arno.uvt.nl/show.cgi?fid=127768.

Straits, B.C., & Singleton Jr, R.A. (2017). Social research: approaches and fundamentals.

US: Oxford University Press.

Stull, M., & Singh, J. (2005). Intrapreneurship in nonprofit organizations examining the

factors that facilitate entrepreneurial behavior among employees (Case Western Reserve

University). Retrieved from

https://www.researchgate.net/profile/Mike_Stull/publication/228383477_Intrapreneurshi

p_in_nonprofit_organizations_Examining_the_factors_that_facilitate_entrepreneurial_be

havior_among_employees/links/00b4952d465f9dc171000000.pdf

Thompson, E. R. (2007). Development and validation of an internationally reliable short-form

of the positive and negative affect schedule (PANAS). Journal of cross-cultural

psychology, 38(2), 227-242. doi: 10.1177/0022022106297301

Urbano, D., Turro, A. (2013) Conditioning factors for corporate entrepreneurship: an internal

and external approach. International Entrepreneurship and Management Journal, 9 (3),

379–396. https ://doi.org/10.1007/s1136 5-013-0261-8


Van Seggelen - Damen, I., & Van Dam, K. (2016). Self-reflection as a mediator between self-

efficacy and well-being, Journal of Managerial Psychology, 31 (1), 18-33. doi:

10.1108/JMP-01-2013-0022

Waal, A., Kolker, L., Goedebuure, R., & Van der Heijde, B. (2013). Intrapreneurschap als

aanjager van ‘high performance’. Holland Management Review, 150, 43-48.

Wakkee, I., Elfring, T., & Monaghan, S. (2010). Creating entrepreneurial employees in

traditional service sectors. International entrepreneurship journal, 6, 1-21. doi:

10.1007/s11365-008-0078-z

Wayne, S.J., Shore, L.M., & Liden, R.C. (1997). Perceived organizational support and leader-

member exchange: a social exchange perspective. Academy of management journal,

40(1), 82-111.

Wright, T.A., & Cropanzano, R. (2004). The role of psychological well-being in job

performance: a fresh look at an age-old quest. Organizational Dynamics, 33(4), 338-351,

doi:10.1016/j.orgdyn.2004.09.002

Wright, T.A., Cropanzano, R., Denney, P.J., & Moline, G.L. (2002). When a happy worker is

a productive worker: a preliminary examination of three models. Canadian Journal of

behavioural science, 34(3), 146-150. https://doi.org/10.1037/h0087165

Wright, T.A., Cropanzano, R. (2000). Psychological well-being and job satisfaction as

predictors of job performance. Journal of occupational health psychology, 5(1), 84-94.

doi: 10.1037//1076-8998.5.1.84


Appendix A: scales

Intrapreneurial behavior

Strongly disagree – Disagree – Neutral – Agree – Strongly agree

In the course of my work, I…

Approach new projects or activities in a cautious manner

Do things that have a chance of not working out

Avoid taking calculated risks

Engage in activities that have a chance of not working out

Will take calculated risks despite the possibility of failure

Keep ahead of changes instead of responding to them

Actively fix or improve things I don’t like

Act in anticipation of future problems, needs, or changes

Take the initiative to start projects

Tend to implement changes before they are needed

Generate useful new ideas

Develop new processes, services, or products

Approach business tasks in innovative ways

Find new ways to do things

Often do things in unique ways

Job performance

Not at all competent – Less competently – Moderate competently – Average competently – Fair

competently – Good – Very competently

All in all, how competently do you perform your job?

In your estimation, how effectively do you get your work done?

Very low – Low – Moderate – Average – Good – High – Very high

How would you judge your overall perceived competence?

How would you judge the overall quality of your work?

How would you judge the overall quantity of your work?


Self-efficacy

Strongly disagree – Disagree – Neutral – Agree – Strongly agree

I will be able to achieve most of the goals that I have set for myself

When facing difficult tasks, I am certain that I will accomplish them

In general, I think that I can obtain outcomes that are important to me

I believe I can succeed at most and endeavour to which I set my mind

I will be able to successfully overcome many challenges

I am confident that I can perform effectively on many different tasks

Compared to other people, I can do most tasks very well

Even when things are tough, I can perform quite well

Psychological well-being

Never 1 2 3 4 5 Always

Thinking about yourself and how you normally feel, to what extent do you generally feel:

Attentive

Alert

Inspired

Determined

Active


Appendix B: factor and reliability analyses

Output intrapreneurial behaviour


Output self-efficacy


Output Job performance


Output psychological well-being (without item ‘alert’)


Appendix C: correlations three dimensions intrapreneurial behavior

Documents

The relationship between intrapreneurial behavior and job