Proactivity in organizations : potential trade-offs for engaging in taking charge behaviors at work

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Proactivity in Organizations

Potential Trade-offs for Engaging in Taking Charge Behaviors at Work

Amsterdam, Date, 2015

Bachelor’s Thesis and Thesis Seminar Business Administration Student: Bram Timmers 10174230

Supervisor: R.E. (Renske) van Geffen PhD Second Supervisor: S. (Sofija) Pajic PhD Academic Year: 2014 – 2015

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Foreword

I wrote this thesis for my Bachelor degree in Business Administration at the University of Amsterdam. I hereby would like all people that helped me with working on this thesis. I would like to especially thank my supervisor, PhD R. (Renske) van Geffen, for her patience of waiting for my thesis as well as providing an interesting research topic and helping us with the analysis of the data. My research group for helping with the collection of data for our research topic and constructing the final survey . Furthermore, I would like to thank all participants that fur took in the survey as well as providing part of the survey to a colleague. Of course, I would like to thank them too. I hope u will enjoy reading my thesis!

Statement of originality

This document is written by Student Bram Timmers, 10174230, who declares to take full responsibility for the contents of this document.

I declare that the text and the work presented in this document is original and that no sources other than those mentioned in the text and its references have been used in creating it.

The Faculty of Economics and Business is responsible solely for the supervision of completion of the work, not for the contents.

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Abstract

Despite the growing need of proactive behaviors within organizations, proactive behaviors are not always rewarded. Previous research has indicated that there are often rewards and costs associated with behaving proactively. In this study we therefore sought to better understand the tradeoffs that employees make when deciding to engage in proactive behaviors. In particular, we hypothesized that the relationship between the employee’s proactive personality and his tendency to engage in taking charge behavior was positively moderated by their relatively voice climate safety, performance goal motivation, learning goal motivation and their instrumentality beliefs. Furthermore, we tested whether there was an second positive moderation effect of the instrumentality beliefs on the moderation effect of performance goal motivation. We tested these hypotheses with a sample of 72 employee-colleague dyads. Unfortunately, none of our hypotheses were supported by our study. We suggested that this was mainly due to finding no direct effect between an employee’s proactive personality score and taking charge score. Concluding, we argue that further analysis is necessary on the relationship between the employee’s proactive personality and their taking charge behaviors.

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1.0. Introduction

In an era where companies are becoming more dynamic, decentralized and operating on a global scale, the global business landscape grows more and more competitive (SHRM, 2013). As a result companies are increasing their value on their intangible assets and human capital to be able to differentiate themselves against competitors, as it has been shown that these intangible assets relate to a company’s bottom line (Noe, Hollenbeck, Gerhart, & Wright, 2012). The implication of this is that companies seek out value in human capital by increasing the knowledge, skill and abilities of their workforce (Wright et al., 2001). They demand an unique set of behaviors and attitudes from their employees that are valued in the market or their organization to remain competitive.

Proactive behavior of the employee, which is defined by Crant (2000, p. 436) as “taking initiative in improving current circumstances or creating new ones, involving

challenging the status quo rather than passively adapting to present conditions”, is now often

a requirement of companies to remain competitive (Bolino, Valcea, & Harvey, 2010). Global competition, new production concepts and a faster rate of innovation requires the employee to continuously take initiative to develop their knowledge and skills of their work (Frese & Fay, 2001). Organizations are thus looking for employees that are more flexible and go beyond mere task requirement and new aspects of the individual employee often involve expectations beyond in-role behaviors and a high commitment to the organization (Campbell, 2000).

Nowadays as proactive behaviors are often becoming part of the job requirements of the employee, scholarly research has begun to identify the possible outcomes of proactivity in organizations. For instance, it has been shown that organizations with proactive employees often outperform the market and have increased sales performance (Crant, 2000). Furthermore research has also underlined that proactive behaviors can actively shape how development and change unfolds in organizations (Grant & Ashford, 2008). Moreover, it has been shown

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7 that proactive behaviors hold some positive outcomes for the employees themselves as

proactive behaviors often lead to more career success, change job attitudes and give employees feelings of personal control and provide role clarity (Crant, 2000). Yet recent research has also underlined the negatives outcomes of proactive behaviors (Bolino, Valcea, & Harvey, 2010). For example, the high demand for proactive behaviors may leave

employees with a great amount of stress, which can undermine their overall effectiveness. Also as Campbell (2000) noted there is an ‘initial paradox’, where organizations are encouraging employees to behave proactively, but frequently punish proactive behaviors, because they perceive them as misguided. Moreover, this problem increases as more

companies are often associating proactive behaviors with rewards (Grant & Ashford, 2008). Research evidence of potential rewards and costs of behaving proactively leads to the implication that the employee engages in some sort of trade-off when behaving proactively, where they put emphasis on the possible outcomes of behaving proactively (Bolino, Valcea, & Harvey, 2010). Previous research has not yet outlined these trade-offs involving proactive behaviors, yet it can have lasting consequences for individuals or organizations. For instance, a reward approach to proactive behaviors can lead employees to behave in high levels of proactive behavior, whenever the behavior can be seen as more harmful than helpful by supervisors, stakeholders or peers. Consequently, a cost approach can lead employees to not engage in proactive behaviors at all as they are scared of receiving punishment for behaving proactively. This may serve as a source of stagnation for organizational change and

innovation.

In this study we want to contribute to the academic literature of proactive behavior by getting more insight in the potential trade-offs that employees make when behaving

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personality and engaging in taking charge behavior is moderated by the employee’s motivational and goal processes or perceived costs of engaging in such behaviors.

People with a high level of proactive personality can be seen as people who identify opportunities, act on them, show initiative and take action in organizations and perservere in their actions until meaningful change occurs. A proactive personality often serves as an antecedent for proactive behaviors at the workplace as it helps employees to identify

opportunities to improve things and can challenge the status quo of the organization (Crant, 2000). One of such proactive behaviors is taking charge behavior. Taking charge behavior can be seen as efforts by employees to affect functional change with respect to how they do their job. We mostly want to address taking charge behavior in our study, because unlike other forms of proactive behavior taking charge behavior is mostly change-oriented and aimed at improvement (Morrison & Phelps, 1999). We think that because of the dynamic business environment change-oriented behaviors are most likely in demand by organizations and therefore employees are more likely to behave in such ways. We therefore think that employees are more likely to look at trade-offs when they are looking to behave in taking charge behavior.

However the question we mostly want to address in our study is whether such a relationship is moderated by the trade-off that employees make when engaging in proactive behaviors. To provide an answer to this question, we will conduct a dyad study among the Dutch labor force, where both an employee and a subordinate of the employee complete a questionnaire. With the results of this study, an overview of four potential moderators of engaging in proactive behaviors will be presented, which would make it easier to understand which potential trade-offs employees make when wanting to behave proactively. First, we want to look at Voice Climate Safety, which measures the safety for employees to speak up within their organizations (Morrison et al., 2011). We suggest that a high level of voice

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9 climate safety would benefit the overall tendency to engage in taking charge behaviors.

Furthermore, we want to look at two goal motivations of the employee, namely a performance goal motivation and a learning goal motivation (Button et al., 1996). We think that such goal motivations may furthermore strengthen the relationship between having a proactive

personality and engaging in taking charge behaviors. Finally we want to look at

instrumentality beliefs, which measures whether the employee thinks that proactive behaviors are rewarded within the organization. We belief that these instrumentality beliefs help

employees having a proactive personality with deciding to engage in taking charge behaviors at work. Moreover, we suggest that these beliefs moderate the effect that goal motivations have on engaging in taking charge behaviors.

First this paper will follow up with a summary of the academic knowledge about proactive personality, potential trade-offs of behaving proactively and taking charge behavior. Subsequently we explain the rationale and methodology of the study, followed with the results. After that, we will conclude with the interpretation of the results and discuss potential limitations of this study. Lastly, we will discuss the managerial implications of this study.

2.0 Literature Review

2.1 Literature Review

In this section, we will address the existing literature related to the research problem. Many has been written about proactive behavior as a behavioral construct and in the following part we would like to address this knowledge to have a better representation of our research topic. First, the concept of proactive behavior will be briefly explained as well as the main view of proactive behavior taken in this study. Secondly we will explain our two behavioral constructs of proactive behavior, taking charge behavior and proactive personality, in more detail.

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10 Furthermore, we will consider some existing theoretical frameworks concerning the potential trade-offs that employees make when behaving proactively. Finally, we want to emphasize the potential value of this study and add some concluding thoughts about the research topic.

2.1.1. Proactive Behavior

In the academic literature proactive behavior has been defined and described in different ways (Bolino et al., 2010). It is therefore useful to clarify the different views of proactive behaviors and the view adopted in this study. The construct of proactive behavior originally stems from the paradigm of work motivational theories, where researchers were looking for a more central assumption of active behaviors of employees in Organizations (Grant & Ashford, 2008). Researchers argued that although work motivational theories, such as expectancy theory and goal-setting theory, already gave attention to work motivational processes within Organizations, they outline a more reactive approach towards employees. However, when recent research into social working processes and work structures had showed that employees could actually shape and change their working environment, researchers argued that a more active approach to work motivation was necessary (Grant & Ashford, 2008).

Since then, researchers have tried to integrate these active working behaviors in a new construct. First, researchers focussed more on the employees themselves and saw proactive behavior as having a behavioral tendency of employees to engage in proactive behaviors (Crant, 2000; Grant & Ashford, 2008). The view of seeing proactive behavior as a personal disposition, however, neglects situational Organizational factors (Morrison & Phelps,1999). Researchers have since then tried to combine these two factors of proactive motivation. In this study we take one of these views.

We define proactive behavior of the employee in this study by the definition of Crant (2000, p. 436) as “taking initiative in improving current circumstances or creating new ones,

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11 Furthermore we argue that these behaviors are agentic and anticipatory in nature (Grant & Ashford, 2008). Proactive behavior in this view can be both part of in-role behaviors or ex-role behaviors. For instance, employees can seek out supervisors for feedback or specific suggestions or in the case of ex-role behaviors seek feedback from their social network to improve working practices.

In his view, Crant (2000) conceptualized four different behavioral constructs of proactive behavior; proactive personality, personal initiative, role breadth self-efficacy and taking charge behavior. In our study we will focus on two of these constructs. First, we want to address taking charge behavior, because this behavior is mostly change-oriented and aimed at improvement of the four. Furthermore, we want to take a better look at proactive

personality, which is having a behavioral tendency to behave proactively. The reason for focusing specifically on these two constructs is that proactive personality has often been associated as an antecedent of other proactive behaviors (see Parker, Williams, & Turner, 2006; McAllister, Kamdar, Morrison, & Turban, 2007; Grant & Ashford, 2008). As Morrison and Phelps (1999) already noted that individual characteristics might play an important role in engaging in taking charge behaviors at work, previous research has primarily focused their research on the relationship between proactive personality and taking charge behaviors. Both Parker et. al. (2006) and Mcallister et al. (2007) found evidence that such a relationship existed. According to their argument of seeing proactive personality as an antecedent of taking charge behaviors, we belief it is best to focus our study primarily on these two behavioral constructs, as our study wants to specifically focus itself more on the potential trade-offs that employees make when engaging in proactive behaviors.

2.1.2. Taking Charge Behavior

Taking charge behavior is not an entirely new concept and stems from the literature of Organizational Citizenship Behaviors (Morrison & Phelps, 1999). Just like OCBs, taking

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12 charge behavior can be seen as extra-role behaviors undertaken by employees that in a way can be seen as functional for the organization. Taking charge is also similar in that it is not a formally required by the organization. However whether OCBs illustrate a more general concept of extra-role activities such as helping others and not taking extensive breaks, taking charge behaviors can be seen as a more direct approach of extra role behavior.

Employees who express taking charge behaviors actually challenge present state of operations in the organization to bring about constructive change (Morrison & Phelps, 1999, pp.403). In contrast to the OCB behavior voice, which is a constructive change-oriented communication intended to improve the situation, taking charge behavior involves taking concrete actions against work processes (Kim, Liu, & Diefendorff, 2015). Hence, taking charge behaviors are more change-oriented and look for improvement of current

organizational work processes. They actually challenge the status quo of organizational routines and regulation to bring change.

Research have outlined the potential value that taking charge holds for organizations. Researchers argue that employee-initiated change can improve the long-term adaptability of an Organization (Frohman, 1997). In a dynamic environment, organizations need employees who actually challenge the status quo within an organization and bring on functional change (Morrison & Phelps, 1999). Furthermore, these employees can step up against rising problems and correct faulty work practices within the organization (Staw & Boettger, 1990).

Given this, organizations have become increasingly concerned with providing contextual factors which benefit taking charge behaviors. It is not surprising that informal leaders and organization transparency have become increasingly popular recently as Morrison and Phelps (1999) already argued that these practices can help employees with engaging in taking charge behaviors.

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13 However it must be noted that taking charge behaviors come at a risk for

organizations. As employees challenge status quo and change working practices, they can be seen as threatening for supervisors or peers. Furthermore challenging the status quo and changing working practices can also wrongfully change well-structured working systems (Morrison & Phelps, 1999).

Despite this, we argue that (well used) taking charge behaviors are essential for organizations to remain competitive as they assure that change and innovation unfolds within the organization. We argue that due to the global competition and the fast rate of innovation organizations require employees that continuously take initiative to correct faulty work practices and come up with innovative and productive new concepts (Frese & Fay, 2001).

2.1.3. Proactive Personality

The idea of seeing proactive behavior as a personal tendency was first introduced by Bateman and Crant (1993) and involves the long and still going debate of whether behavior stems from internal or situational factors. Bateman and Crant (1993) hold the vision of Bandura (1977) and Schneider (1983) that behavior is a consequence of both internal and external factors and the tendency to behave a certain way involves an interaction with both factors. Thus, the person and environment are continuously influencing one another. According to Bateman and Crant proactive behavior, like all behaviors, has therefore both personal and situational causes. For instance, employees can behave quite differently in the same organizational setting as their fellow peers when a problem arises. As most situational factors stay the same in such a situation, Bateman and Crant (1993) argue that there should be a personal

disposition for employees to behave more proactively in certain situations.

As mentioned before, we see proactive personality as having such a personal disposition. Whether less proactive individuals are more passive and reactive to their environment, individuals with a proactive personality actively try to change their

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14 environment. They thus act on opportunities that arise within an Organization and actively take action and initiative until meaningful change arises (Crant, 2000, pp. 439). It is important to note that behaving proactively is not the same as having a proactive personality. Whether all employees can engage in proactive behaviors at work, employees with a proactive

personality have a personal tendency to behave proactively in life (Grant & Ashford, 2008).

Although proactive personality and taking charge behavior are both behavioral

constructs of proactive behaviors, they differ in the way they are formed (Crant, 2000). In contrast to proactive personality taking charge behavior focuses more on situational

tendencies for engaging in proactive behaviors. Taking charge behavior change in respect to how work is executed within an organization (Morrison & Phelps, 1999). Employees, who engage in taking charge behaviors try to change situational factors within the context of their jobs or working environment. They do not need to have a personal disposition for behaving proactively.

Several positive organizational and individual outcomes have been linked to

employees with a personal disposition towards behaving proactively. For instance, in a dyad study of 126 employee-supervisor relationships supervisors actually rated the job performance of employees with a proactive personality higher than their colleagues (Thompson, 2005). Although subjective supervisor ratings may not be a good representation for actual job

performance, a longitudinal study with real estate agents found a similar relationship between proactive personality and job performance with a more objective measurement of job

performance (Crant, 1995). In this study job performance was actually measured by the houses sold by the agents. Other studies also found positive associations of proactive

personality with career success (e.g. Seibert et al., 1999; Crant & Kraimer, 1999), leadership capabilities (Crant & Bateman, 2000), team performance (Kirkman & Rose, 1999) and

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15 It is thus not surprising that organizations often look for employees who have a

tendency to behave proactively. As organizations shifts from a production economy to a knowledge economy, they are more relying on their employees for organizational success (Grant & Ashford, 2008). They rely on employees, who explicitly behave proactively towards their environment and who look for innovation and change. Employees with a personal

tendency to behave this way lend themselves perfectly to this. Furthermore, these employees can hold better organizational performance as they hold better overall job performance.

Despite this, recent research has also outlined the potential negative consequences of organizations looking for their employees to behave proactively (see Erdogan & Bauer, 2005; Bolino et al., 2010). First of all, acting proactively at work can give the employee a great amount of stress. Behaving proactively at work is likely to consume resources of the

employee, such as time and energy (Bolino et al., 2010). Therefore, decreasing the resources available to do the everyday job responsibilities. Secondly, organizations mostly do not acknowledge what proactive behaviors they expect from their employees. Therefore the employee does not known when they need to behave proactively at work or show initiative. However, when they do behave proactively at work and their managers sees their behavior as misguided, they can punish their behavior. Campbell (2000) referred to this problem as the ‘imitative paradox’, where organizations tend to encourage employees to behave proactively, but frequently punish proactive behaviors that they see as misguided. The implication of this is, as Erdogan and Bauer (2005) noted, that employees with a proactive personality only achieve potential positive outcomes with engaging in proactive behaviors, when there proactive behaviors are in line with the organizational values and beliefs.

As a result of this ‘iniatitive paradox’ one can argue that employees with a proactive personality will be careful when deciding to engage in proactive behaviors at work. They look whether their behavior is wanted in their organizations and what the risks are for engaging in

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16 proactive behaviors. They thus make a tradeoff looking at the potential rewards and costs associated with engaging in proactive behavior (Bolino et al., 2010). In this study we want to better understand these tradeoffs.

2.1.4. Potential Trade-offs in Behaving Proactively at Work

In the first section of this review, we described proactive behavior as challenging the status quo and creating constructive change within organizations. Furthermore, we argued that organizations are often looking for employees who behave proactively. However we have not yet discussed potential benefits and punishments that employees gain for behaving proactively in an organization. Previous research has already noted that there are often rewards and

punishments associated with being a proactive employee (Grant & Ashford, 2008).

Moreover, recent research has already proposed that certain proactive behaviors are more likely to be rewarded than others and that rewards and punishments for behaving proactively can differ within organizations (see Haworth & Levy,2001; Parker, Williams, & Turner, 2006; Grant & Ashford, 2008; Parker et al., 2010; Bolino et al., 2010). For instance, Grant and Ashford (2008, p. 19) argued in their study that proactive behaviors that are perceived as interpersonally or organizationally beneficial are more likely to be rewarded, and, that proactive behaviors that are perceived as unethical, self-serving or harmful are more likely to be punished. Furthermore, Parker, Williams and Turner (2006) also discuss the role that an employee’s working environment may play in the decision to behave proactively. In later research Parker et al. (2010) also noted the role that individual motivational goal processes may play in behaving proactively. In particular, they argue that when employees have a motivational goal for behaving proactively, such as compensation or promotion, they may actually try to behave proactively more often. Haworth and Levy (2001) also emphasize that perceived instrumentality beliefs of behaving proactively influence actual engagement in proactive behaviors.

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17 Nevertheless, the above researchers mostly did not test their propositions. Although the implication that rewards and punishment can actively influence proactive behaviors there is not an empirical study validating their propositions. As Bolino et al. (2010) noted

investigators should seek to better understand these tradeoffs that employees make in terms of the potential rewards and costs associated with proactive behavior. Of the above, only Haworth and Levy (2001) actually tested their proposition. Their results were promising, showing that instrumentality beliefs actually can influence the frequency of proactive behaviors.

2.1.4 Conclusion

Concluding, we argue that a empirical study is necessary to determinate the role of potential trade-offs involving proactive behavior. In this study we therefore want to contribute to the academic literature by providing more insight in the potential trade-offs that employees make when engaging in proactive behavior at work. In particular, we want to test whether there is a relationship between proactive personality and taking charge behavior and see whether this relationship is moderated by the potential rewards or costs associated with engaging in proactive behavior.

2.2. A Model of Proactive Behavior

After explaining the motivation behind our research topic, this section will help us define the conceptual framework on which this research is based. First, we argue that there is a

relationship between having a proactive personality and engaging in taking charge behaviors at work. Furthermore, we argue that due to rewards and punishments associated with

behaving proactively at work, this relationship is moderated by potential trade-offs that employees make when behaving proactively. We will introduce four potential trade-offs that might influence the above relationship and come up with hypotheses of how these trade-offs influence the tendency for employees to engage in taking charge behaviors at work. An

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18 illustration of how these potential trade-offs influence the association between proactive personality and taking charge behaviors can be found below.

2.2.1. The Influential Role of Proactive Personality in Engaging in Taking Charge Behaviors As noted in the above, we argue that proactive personality stands for having a personal

disposition for behaving proactively and taking charge for behaving proactively due to situational factors. We stated that employees having a proactive personality behave more proactively in life than their fellow peers. In line with this, one could argue that people having a proactively personality also would behave more proactively in a working environment. We therefore think that proactive personality should predict all sort of proactive behaviors at work, including taking charge behavior.

Preliminary research already found evidence for the influential role of proactive personality on taking charge behaviors. In their first article on taking charge behavior, Morrison and Phelps (1999) already noted that individual characteristics may play an important role in taking charge behaviors. They had found evidence that employees with a high level of self-efficacy and a sense of responsibility for bringing about constructive change engaged in taking charge behaviors more often than their peers. Having a high level of self-efficacy and a sense of responsibility for bringing about change have been closely linked to

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19 employees having a proactive personality in academic research (see Crant, 2000; Parker, Williams et al., 2006). Furthermore, Recent research by Parker et al.(2010b) already tested the assumption that proactive personality may influence taking charge behavior at work and found a significant effect of proactive personality on taking charge behaviors. Concluding, we thus hypothesize that:

Hypothesis 1 [H1]: Employee’s proactive personality has a positive association with

engaging in taking charge behaviors at work. Hence, employees with a high proactive personality will engage more in taking charge behaviors at work than employees with a low level of proactive personality.

2.2.2. Potential Trade-offs of Taking Charge Behaviors

Assuming that [H1] is true, we want to look at the potential trade-offs that employees make when engaging in taking charge behaviors. In the current study we will look at four potential trade-offs that employees could make when engaging in taking charge behaviors. First, we argue that the organizational climate can influence the behavioral path for employees to engage in proactive behaviors. Secondly, we argue that employees having certain goal motivations engage in taking charge behaviors more often. Finally we want to look at the potential value that employees place at behaving proactively in their organization, to see whether certain beliefs about potential rewards and costs influence their decision model for engaging in taking charge behaviors.

2.2.3. Voice Climate Safety

To better understand the trade-offs that employees make, it is important that we understand what working environment may encourage employees to engage in taking charge behaviors. Morrison and Phelps (1999) noted that organizational factors, such as openness of a manager for suggestions and improvements, may influence the willingness of employees to behave in taking charge behaviors. In light of this, we argue that organizational climate, which can be

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20 defined as the shared perceptions of employees concerning the practices, procedures and activities that are expected, supported and rewarded within the workplace (Kuenzi &

Schminke, 2009, p. 635), may be an important factor in engaging in taking charge behavior. Morrison and Milliken (2000) noted the importance of having a relatively safe

organizational climate for behaving proactively. Previous research had shown them that shared beliefs within a work group or work unit could have a strong effect on organizational behavior (Kuenzi & Schminke, 2009). They, therefore, argued that the absence of upward information from the employee can be devastating for a organization and organizations should strive to have a relative safe climate for speaking up. They referred to this sort of a climate as voice climate safety, which is having a shared belief about whether speaking up is safe versus dangerous within a organization (Morrison, Wheeler-Smith, & Kandar, 2011, p. 184).

Despite their not being an organizational climate measure for taking charge behavior, we argue that as taking charge and voice both illustrate a construct of speaking up within an organization - whether it is about change-oriented communication or taking concrete actions -, voice climate safety should be roughly similar for the climate safety of taking charge behaviors.

Concluding, we think that the voice climate safety within the different workgroups of an organization may moderate the willingness for employees to engage in taking charge behaviors. As we hypothesized that employees having a proactive personality would likely engage more in taking charge behavior, we think that this relationship is moderated by the perceived voice climate safety of the employee. We thus hypothesize:

Hypothesis 2 [H2]: The perceived voice climate safety of an organization by the

employee positively moderates the relationship between employee’s proactive personality and engaging in taking charge behaviors at work.

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21 2.2.4. The Role of Goal Motivation in Taking Charge Behavior

Besides the role of the organizational climate in taking charge behaviors, we should also look at the goal motivational theory behind proactive behaviors in general. When we see

proactivity as an active-oriented behavior, we assume that the individual employee acts on his or her own volition when behaving proactively. Hence, when the behavior is the result of a direction given by someone else, it does not fit up with our definition of proactive behavior in that it is self-initiated. Consequently, seeing proactive behavior as a self-initiated construct, means there are probably motivations behind engaging in proactive behaviors.

As we initially proposed, we argue that employees having a proactive personality will engage in taking charge behaviors more often than their fellow peers. In this view we see “having a proactive personality” as the main determinant of taking charge behavior. We, however, argue here that this view is too simplistic. Whether having a behavioral tendency to behave proactively in life may be a predictor of organizational proactive behavior in general, it does not explains the ‘why’ of the organizational behavior.

Previous research has also recognized that engaging in proactive behavior probably goes beyond having a proactive personality on his own (Bolino et al., 2010; Parker et al., 2010; Grant & Ashford, 2008; Frese & Fay, 2001). They argue that individual-level proactive behavior is often aimed at future-oriented goals that aim to change and improve the situation or oneself (Parker et al., 2010, p. 829). In their view proactive action is a goal motivated process by the employee. The employee directs their proactive actions towards future impact for himself or the organization (Grant & Ashford, 2008). For example, they might look at outcomes like job satisfaction or promotions for engaging in proactive behaviors. The implication of this is that certain goal motivations may play a moderating role between proactive personality and changed-oriented proactive behaviors (Parker et al., 2010).

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22 On the basis of this, we argue that the relationship between having a proactive

personality and engaging in taking charge behavior will likely be influenced by the personal goals that employees pursue. In the current study we argue that people having a proactive personality and strive high personal goals will more likely engage in taking charge behavior than their fellow peers.

For a definition of the different personal goals the employees may pursue, we adopt the theoretical framework of Button, Mathieu and Zajac (1996). In their view personal organizational goals can be divided in two types of goals: performance goals and learning goals. Individuals having a performance goal strive to demonstrate their competence via task performance or avoid negative judgments to gain favorable judgments by their peers or supervisors. Alternatively, individuals having a learning goal orientation will strive to

understand something new or to increase their level of competence in a given activity (Button et al., 1996, p. 26). We argue that employees having a performance goal will positively moderate the relationship between their proactive personality and engaging in taking charge behaviors. We belief that as organizations are often looking for employees who take initiative and provide judgment, employees with a performance goal orientation will see proactive behaviors as a performance opportunity to show their overall effectiveness (Campbell, 2000). Furthermore, we argue that employees having a learning goal motivation will likely find it less risky to step up to their manager or supervisor, as they see it as development opportunity to improve their work practices (Parker & Collins, 2010). Moreover, employees with a learning goal orientation will consistently set higher goals as their fellow employees, trying to setback their faulty work practices and improve their overall effectiveness. We thus

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Hypothesis 3a [H3a]: Employee’s performance goal positively moderates the

relationship between employee’s proactive personality and engaging in taking charge behaviors at work.

Hypothesis 3b [H3b]: Employee’s learning goal positively moderates the relationship

between employee’s proactive personality and engaging in taking charge behaviors at work.

2.2.5. Instrumentality Beliefs about Taking Charge Behaviors

Provided that employees pursue some personal goals when deciding to engage in taking charge behavior, one could argue that they expect to be rewarded for their behavior by the organization. In line with expectancy theory, they should have a perception of when a certain act will hold a potential reward or cost by the organization and when their behavior is

evaluated as valuable by supervisors or managers (Haworth & Levy, 2001). Furthermore, employees should also have a clear understanding of when certain behavior is worth the effort.

Following this we argue that instrumentality beliefs of the employee, which refers to whether one perceives a relationship between performance of a certain behavior and outcomes such as rewards and punishment (McAllister, Kamdar, Morrison, Turban, 2007), influences the tendency to engage in taking charge behaviors. Support for such a relationship is already provided within the OCB literature (see Haworth & Levy, 2001; McAllister et al., 2007). Haworth and Levy (2001) found evidence that employee’s understanding of the performance appraisal system and their beliefs about fairness related to their performance on certain OCBs. Further support of this notion was provided by McAllister et al. (2007), who found an similar relationship between taking charge behavior and instrumentality beliefs. In line with their views, we therefore argue that instrumentality beliefs about whether taking charge behavior is

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24 actually rewarded within an organization, can influence the tendency for proactive employees to engage in taking charge behaviors. This leads thus to the following hypotheses:

Hypothesis 4a [H4a]: Instrumentality beliefs about the potential rewards associated

with proactive behavior positively moderates the relationship between employee’s proactive personality and their tendency to engage in taking charge behaviors at work.

Hypothesis 4b [H4b]: Instrumentality beliefs about the potential rewards associated

with proactive behavior positively influences the moderation effect that performance goal motivations have on the association between employee’s proactive personality and his or her taking charge behaviors.

3.0 Methodology

In an effort to investigate our hypothesized model, we conducted a survey study. This section will explain the research design and method used to test our hypotheses stated in our literature review. First, we explain the rationale behind our research design and why we decided to conduct a survey study. Following this, we will explain the sample base for our study and the measures used in this survey. After that we follow up with the analysis and operationalization of our proposed model.

3.1. Research Design

To test our hypothesized model we decided to use a dyad questionnaire-based survey design. As noted in our literature review, we wanted to test whether potential trade-offs influence the relationship with having a proactive personality and engaging in taking charge behavior. To answer this question we need a sizeable sample, as we want to generalize our findings to employees in general. A questionnaire-based survey can therefore be seen as best for this research, as it offers a feasible way of reaching a large sample of respondents and offers a way to describe large populations (Saunders et al., 2012). It enables to compare a large

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25 amount of data due to having mostly standardized questions rather than open-ended questions, which are easier to analyse using statistical procedures and methods. Besides this, given the fact that this study was part of a bachelor’s project, there was limited time and means to collect data. Questionnaire-based surveys are a relatively cheap and quick way to collect data (Saunders et al., 2012), which makes them well suited for this study.

Nevertheless, it is important to note that questionnaire-based surveys only outline associations between variables, as the questionnaires are mostly filled in at a given point in time (Saunders et al., 2012). Furthermore, not all respondents are generally willing to fill in a questionnaire, resulting in low response rates or biased samples. In order to counteract this problem we sent multiple reminders to participants to fill in the survey as well as finding new respondents when response rate was considered too low.

In addition to using a questionnaire-based survey, we decided to use a dyad study, where part of the survey needed to be filled in by a colleague of the employee. This was done to counteract common source bias and minimize the social desirability bias of self-reports that might distort our findings (Morrison & Phelps, 1999). Common source bias refers to the bias coming from using the same measurement source to gather the data. It has been shown that individual’s self-assessments of themselves or their organization can consistently differ with other ratings of performance (Meier & O’Toole, 2013). Furthermore, employees may respond to self-administered survey in ways that reflects favourably on themselves. To counteract this problem, we measured taking charge behavior of the employee using a second survey, which needed to be filled in by a colleague.

3.2. Sample and Procedure

As we wanted to focus on organizational behavior of individuals within organizations, we focussed our surveys on the workforce of organizations. In particular, due to time and cost constrains we focussed our research primarily on the Dutch labor force. Furthermore, to draw

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26 a reliable sample size, we strived to reach at least a sample size of 100 dyads. Surveys where constructed using the online platform Qualtrics. Quatltrics is an internet-mediated platform that offers an easy way of making questionnaires and providing them through the internet (Qualtrics, 2015). Respondents were primarily drawn from personal contacts of bachelor’s students. Criteria for participating in the research were that they were Dutch-speaking residents of the Netherlands and were working for at least a year in the same organizational setting. In this way we could be certain that their colleague had a thoughtful understanding of how the employee behaved at the workplace.

Respondents initially received an e-mail, where they were asked whether they wanted to help a group of bachelor’s students graduating by completing a survey and asking a colleague to also complete a second survey. If respondents agreed on participating in the research, they received an email with two web-links to the surveys, one for the employee-survey and one for the colleague-employee-survey. They were asked to forward the web-link of the colleague-survey to one of their close colleagues. Criteria for the colleague, where that they were also Dutch-speaking residents and worked close enough with them to answer certain questions about their organizational behavior. Furthermore, they were asked to agree on a codeword of six letters with their colleague and fill this codeword in at the first page of the survey. This was done to link the data of the employee and their colleague, but also to guarantee anonymity of the respondents and their fellow colleagues. Data was only included in the research when both the employee and supervisor completed the survey and the surveys could be linked to each other using the codeword.

Data was collected through a three week period in the spring of 2015. After two weeks, a reminder was sent to all employees to complete the questionnaires. Furthermore we added codewords in this mail that had not been filled in by the colleague of the employee. We

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27 asked them to validate whether their colleague had filled in the questionnaire and to remind the colleagues to complete the questionnaire.

3.3. Measures

In order to measure our six main variables, we used existing scales from the academic literature. Most of our variables where measured through self-administered questions using the online employee survey. However, to counteract common source bias and social desirability bias, we measured taking charge behavior with a second survey, which had to be filled in by a colleague. Furthermore, as all of the existing scales where in English, we translated them to Dutch paying attention to the suggestions of Usunier (1998) about translating existing scales. For the proactively personality scale, taking charge behavioral scale and voice climate safety scale validated translations where already available and provided by our supervisor. For the other scales we undertook parallel-translation by two students of our bachelor’s group and compared the translation of the scales. After that, we ensured the best match between the source and target questionnaire and included the translation in the survey. This is in line with suggestions done by Usunier (1998), but, however, does not ensure that lexical and idiomatic meaning are similar across the original source and translation. Then again a further analysis of the translation was not available in the given time of writing this thesis. A complete summary of the used measured and the introduction of the survey can be found in appendix B and C.

3.3.1. Taking Charge Behavior

Taking charge was measured with a 10-item questionnaire developed by Morrison and Phelps

(1999) and should be completed by the colleague of the employee. The questionnaire looks at individual differences in behavioral tendencies of employees rather than specific proactive incidents (Crant, 2000). An example item is: ‘This person often makes constructive

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28 (1) Strongly disagree to (5) Strongly agree. Scoring was formed by averaging the responses of the colleague of the ten items. A high score representing a high tendency to engage in taking charge behavior and a low score representing a low tendency to engage in taking charge behavior. Preliminary analysis of the scales showed high internal consistency and reliability (Morrison & Phelps, 1999). Furthermore, the questionnaire and items showed high construct validity with existing scales of other in-role and ex-role behaviors, corresponding with factor loadings on the hypothesized latent constructs (Morrison & Phelps, 1999).

3.3.2 Proactive Personality

Proactive personality was measured with a 6-item questionnaire as an adaption of the

10-scale developed by Bateman and Crant (1993). Responses were indicated on a five-point Likert scale ranging from (1) strongly disagree to (5) strongly agree. Items contained statements like “I excel at identifying opportunities” and “I am constantly on the lookout for

new ways to improve my life”. Scoring was formed by averaging the responses on the items. A

high score representing a high level of proactive personality and a low score representing a low level of proactive personality. Preliminary research by Bateman and Crant (1993) showed high uni-dimensionality and reliability of the scale as well as showing high convergent validity on the relating constructs of other personality questionnaires, such as the NEO-FFI, another personality questionnaire measuring the “Big Five” personality traits (Costa & MaccCrae, 1992).

3.3.3. Voice Climate Safety

Voice climate safety was measured with a 6-item questionnaire derived from the study of

Morrison et al. (2011). Employees were asked the extent to which “members of their team felt

capable of effectively doing each of the following” and then listing the six main voice

behaviors (Morrison et al., 2011, p. 186), such as “develop and make recommendations

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29 ranging from (1) strongly not safe to (5) strongly safe. Scoring was formed by averaging out the responses. A high score represented high voice climate safety within the Organization. A low score representing low voice climate safety within the Organization. Preliminary research on the psychometric properties showed high reliability of the measure as well as high discriminant validity with other measures of safety (Morrison et al., 2011).

3.3.4. Performance Goal Motivation

Performance Goal Motivation was assessed with 8 items and adapted from the study of

Button et al. (1996). Scales ranged from (1) strongly disagree to (5) strongly agree. A high score indicated a strong desire to obtain favorable judgment from their environment. A low score indicating a weak desire to obtain favorable judgment from their environment. Items included statements like “I prefer to do things that I can do well rather than things that I do

poorly” and ´I’m happiest at work when I perform tasks on which I know that I won’t make any errors. Previous research showed reasonable reliability of the items .

3.3.5. Learning Goal

Learning Goal Motivation was also assessed with 8 items and adapted from the study of

Button et al. (1996). Scales ranged from (1) strongly disagree to (5) strongly agree. An example item is: “The opportunity to do challenging work is important to me”. A high agreement with the items indicated a strong desire to perform challenging work and learning new skills. A low agreement suggested little concern for mastering tasks or gaining competency (Button et al., 1996, p. 33). Preliminary research also showed reasonable reliability of the items.

3.3.6 Instrumentality Beliefs

Instrumentality Beliefs were measured with a 4-item scale developed by Haworth and Levy

(2001). Items contained statements like “It is worthwhile to perform –extra-role behaviors

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30

the extra mile” at work”. Responses were measured on a 5-likert scale, ranging from (1)

strongly disagree to (5) strongly agree. Scoring was formed by averaging the responses. A high score represented a high sense of instrumentality of extra-role behavior and a low score represented a low sense of reward for behaving in extra-role behavior. Preliminary psychometric assessment of the scale showed relatively high reliability.

3.3.7 Control Variables

Certain control variables were also taken in account in the research. We controlled our research for the age, gender and level of education of both the employee and the colleague. These control variables where taken in account to see whether our sample was a reliable reflection of the Dutch labor force and to make sure that we could generalize our findings to the general population. In addition to checking for sampling bias, we wanted to check whether certain demographic variables influenced the relationship between taking charge behavior. The reasoning for this is that Morrison and Phelps (1999) already argued that individual characteristics could have an important role in taking charge behavior. We therefore think that drawing a reliable sample was important as individual characteristics could influence the overall findings. We, however, noted that this might not be possible given the limited time and sampling method used in this study.

3.4. Analysis and Predictions

To test our hypothesized model we used a statistical computer program called SPSS. The version used was 20.0. SPSS offers a software package to conduct simple statistical analysis on the computer without having to type confusing commands (Field, 2009).

First, we conducted a reliability analysis on the used measurements to see whether these could be used for regression analysis on the moderation effect. Furthermore, we compared our reliability scores with the scores reported by the constructing of the scales. We also tested for normality using the Shapiro-Wilk test to see whether our data was normally

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31 distributed within the sample (Saunders et al., 2012). In addition to normality test, we also added a correlation matrix to see whether no multicollinearity or singularity existed between our predictors. Finally, we looked at two regression models to test for the moderation effects of our four potential trade-offs, in total we used thirteen regression models using the method proposed by Baron and Kenny (1986). Due to having a small sample and therefore an overall low power, we conducted the moderation analysis for each potential trade-off individually. To see whether certain interactions between performance goal and instrumentality beliefs were present, we tested our model using the Process add-on in SPSS developed by Hayes (2012). We used model 3 of the Process add-on.

In the first regression model we looked at the main effect of the independent variable and moderator variables on the dependent variable. As proposed by our hypotheses we predicted that:

Prediction 1: We predicted to find a significant positive association between the

employee’s Proactive Personality score and his or her Taking Charge score rated by their colleague.

Employee’s Voice Climate Safety Score and his or her Taking Charge score rated by their colleague

Employee’s Performance Goal score and his or her Taking Charge score rated by their colleague

Employee’s Learning Goal score and his or her Taking Charge score rated by their colleague

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32 Prediction 5: We predicted to find a significant positive association between

Employee’s Instrumentality Beliefs and his or her Taking Charge score rated by their colleague.

Using our second regression model, we tested whether there were also moderation effects of our potential trade-offs on the taking charge measure of the employee. To clarify, we wanted to see whether the association between proactive personality and taking charge changed as a function of the potential trade-offs (Baron & Kenny, 1986). As proposed in our conceptual framework we predicted that:

Prediction 6: We predicted to find a significant interaction effect between the

Employee’s Proactive Personality score and Voice Climate score on the Taking Charge score rated by their colleague.

Employee’s Proactive Personality score and Performance Goal score on the Taking Charge score rated by their colleague.

Employee’s Proactive Personality score and Learning Goal score on the Taking Charge score rated by their colleague.

Employee’s Proactive Personality score and his/her Instrumentality beliefs score on the Taking Charge score rated by their colleague.

Finally, as we wanted to see whether instrumentality beliefs influence the moderation effect of performance goal motivation, we looked at the interaction of both moderation variables using the Process add-on of Hayes (2012). We predicted that:

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33 Prediction 10: We predicted to find a significant interaction effect between Employee’s

Instrumentality Beliefs and Performance Goal score, that influences the relationship between Proactive Personality and Taking Charge.

4.0 Results

In this section the results of the different analyses will be presented. First, we will come up with the descriptive characteristics of our final sample, as well as going deeper in which

respondents were included in our research and the normality and homoscedasticityof the data.

Secondly, we will follow up with the reliability analyses of our used questionnaires. In addition, we will compare our reliability assessment with the reliability reported by the developers of the different questionnaires. we will also include an correlation matrix to check whether the assumption of multicollinearity is met in our study. After that we will conclude with our regression analyses to test our proposed hypothesized model. At last we will add our analyses on the interaction effect between instrumentality beliefs and performance goal motivation.

4.1 Participants

Eventually, 121 participants completed the questionnaire of the employee. However, as only 89 colleagues filled in the other questionnaire, we were not able to match all their surveys. Seven colleagues had not fully completed their questionnaire and were therefore excluded from further analysis. 20 participants were excluded from further analysis due to having filled in the same questionnaire. Furthermore, 18 colleagues of the participants had not filled in their questionnaire and we therefore were not able to match their surveys. Finally, we were not able to match two pairs due to them having used the same codeword. As participants were drawn from personal contacts of different bachelor’s students, we could not adequately calculate the response rate of our sample. According to Saunders, Lewis and Thornhill (2012)

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34 a response rate between 30-50% is normal for internet mediated questionnaires. In line with this as well as our own experience with raising respondents, I think this is a reasonable estimation of the overall response rate of this study.

In the end, the overall sample consisted of 73 dyads. Participants worked in different industries, ranging from the hospitality industry to the financial services. Of the employees, 36 employees (49,3%) were male and 37 employees (50,7%) were female. Of the colleagues, 39 participants (53,4%) were male and 34 participants (46,6%) were female. The majority in our sample of employees was 20-30 years old (65,3%), as well as the majority of the sample of colleagues (63,0%) (For a full distribution of the respondents age, see table 1a and table 1b below). One respondent of the employees did not wanted to include his age in his survey. the majority of our sample had a high educational background, as can be seen in table 1c and table 1d. The relative skewness of age to the right and the high educational background of our sample can probably be explained by the used sampling method as we drew participants from personal contacts of university students. Analysis on the skewness of age and

educational background found indeed a skewness to the right for age of 1.23 (SE = 0.28) and a skewness to the left for educational of -1.36 (SE = 0.28), indicating that our sample was non-normally distributed.

Table 1a. Distribution of age - employees (in years)

< 20 20-30 31-40 41-50 51-60 >60 Sample (N=72) 7 (9,7%) 47 (65,3%) 2 (2,8%) 5 (6,9%) 10 (13,9%) 1 (1,4%)

Table1b. Distribution of age - colleagues (in years)

< 20 20-30 31-40 41-50 51-60 >60 Sample (N=73) 7 (9,6%) 46 (63,0%) 7 (9,6%) 4 (5,5%) 9 (12,3%) 0 (0.0%)

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35 4.2 Correlation Matrix and Reliability Analysis

In table 2 means, standard deviations, reliabilities and correlations can be found for all variables. Although both age and educational background were measured as a categorical variable – age at a categorical level of age groups and education at the education level of the Dutch education system - ,we decided to include both variables in the table for the employee to see whether certain demographic variables also influenced the tendency to engage in taking charge behaviors. As both variables were measured using a ordinal approach, we decided for simplicity to see them as numerical variables. We decided to exclude the demographic variables of the colleague as they only rated the taking charge behavior of their colleague and therefore did not affect the other variables significantly. Furthermore, preliminary analysis with the demographic data of the colleague did not reveal any correlations with taking charge behavior.

Table 1c. Distribution of education level - employees

Primary School High School MBO/MAVO HBO University Sample (N=73) 0 (0.0%) 6 (8,2%) 4 (5,5%) 23 (31,5%) 40 (54,8%)

Table 1d. Distribution of education level - colleagues

Primary School High School MBO/MAVO HBO University Sample (N=73) 0 (0.0%) 4 (5,5%) 4 (5,5%) 17 (23,3%) 48 (65,8%)

Table 2 Means, Standard Deviations, Correlations and Scale Reliabilities

Variable Mean s.d. 1 2 3 4 5 6 7 8

1. Taking charge behavior 3.37 0.63 (.88)

2. Proactive personality 3.68 0.47 .140 (.61)

3. Voice climate safety 3.88 0.51 .045 .367** (.82)

4. Performance goal motivation 3.80 0.46 -.093 .138 .056 (.69)

5. Learning goal motivation 4.02 0.42 -.074 .420** .275* .100 (.76) 6. Instrumentality beliefs 4.02 0.53 -.179 .286* _.299* .033 .383** (.75) 7. Agea 2.54 1.27 .071 -.042 .035 -.246* -.112 -.102 8. Educational backgroundb 4.33 0.91 .008 .131 .023 .050 .064 .106 .031 9. Genderc 1.49 0.50 .137 .188 .094 .065 .015 -.111 -.144 .186

Note. N = 72 (one case was excluded due to missing data) a_{Age was measured as a categorical variable using age groups} b

Educational background was measured as a categorical variable, a lower score measuring a lower level of education

c

Coding: 1 = female 2 = male *p < .05

**

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36 4.2.1 Reliability Analysis

To test whether our scales could be used for an regression analysis we used a reliability analysis. We also wanted to see whether the translation of the items influenced the reliability of the used scales. We therefore compared our reliability assessments with the analysis of previous academic research. To test for reliability, we used Cronbach’s alpha as it is the most commonly used measure of reliability (Field, 2009). Furthermore, we used the guidelines of the COTAN for assessing the reliability of our scales (Cotan, 2009). COTAN is an committee which evaluates psychometric instruments issued in the Netherlands and reviews them (Evers et al., 2009). In their guidelines COTAN indicates that a Cronbach alpha’s of at least .70 is required to rate a scale as reasonable to determine individual characteristics. The Cronbach’s Alpha’s of the used scales can be found on the diagonal of table 2.

Most of the scales achieved the requirement set by the COTAN. Cronbach’s alpha’s for taking charge was .88, indicating overall high reliability. Cronbach’s alpha for proactive personality was .61 and did not meet the requirement of the COTAN. Therefore, according to COTAN we can only generalize our findings of having a proactive personality to group level. Cronbach’s alpha for the voice climate safety measure was .82, also indicating overall high reliability. Furthermore, Cronbach’s alpha for the performance goal motivation and learning goal motivation scale were respectively .69 and .70. However, by deleting item eight of the learning goal motivation the alpha was considerably improved to .76. We therefore excluded this item from further analysis. The deleted item measured whether one used different

approaches when having a difficult problem to solve. Lastly, Cronbach’s alpha for the instrumentality beliefs scale was .75, indicating reasonable reliability. No further improvements could be made to the scales by deleting an item.

Comparing our reliability analysis with previous research we only found significant difference between the reported Cronbach’s alpha of the proactive personality scale. Bateman

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37 and Crant (1993) as well as Crant (1995) reported a Cronbach’s alpha between .87 and .93, which is considerably higher than the Cronbach’s alpha of our study (α = .61). Although a reason for the difference could be the different translation of items, we argue that it is more likely that participants nowadays are more likely to behave proactively in life. Furthermore, we argue that due to the need for proactive employees in Organizations employees are more likely to behave proactively at work (Frese & Fay, 2001). Looking at the mean (M = 3.68, SD = .47) of the proactive personality scale we can also see that having a proactive personality is relatively common nowadays. Cronbach’s alpha of taking charge behaviors did not differ much with the Cronbach’s alpha of .92 originally reported by Morrison and Phelps (1999). Secondly, Cronbach’s alpha for voice climate safety did not differ much with the Cronbach’s alpha of .89 reported by Morrison and colleagues (2011). Cronbach’s alpha for performance goal motivation and learning goal motivation also did not differ much with the Cronbach’s alpha of respectively .73 for performance goal and .79 for learning goal reported by Button and colleagues (1996). Finally, instrumentality beliefs also did not differ much with the Cronbach’s alpha reported by previous research (α = .80 compared to α = .75 in this study) (Haworth & Levy, 2001). The implication is that it seems that the overall translation of the items did not influence the reliability of the used scales much. Most of our scales achieved moderate to high reliability and actually measured the underlying construct.

4.2.2 Correlations

A first impression of the table shows that the means of all variables are moderate to high, indicating that the different variables are relatively common with the employee. Furthermore, looking at the correlations between the variables we can see that there were no significant correlations between taking charge and any of the independent variables. We predicted that all independent variables would affect engaging in taking charge behaviors to some extent, however, the results of this study show that none of the variables correlates with

Proactivity in organizations : potential trade-offs for engaging in taking charge behaviors at work