Will performance management systems manage performance?

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Will performance management systems manage performance?

S2355019 Pernette van Eijk

Kloveniersburgwal 121B, 1011 KC Amsterdam 06-20348048 Pernette.vaneijk@gmail.com University of Groningen Author Note

This article was written as part of the course Masterafstudeerwerkstuk Accountancy. The article was written under supervision of Wilmar de Munnik.

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Research Findings: Data of online questionnaires of 67 employees working at a private organization operating in the Netherlands showed several research findings. Firstly, diagnostic and interactive use of performance management systems are both not found to be significant related to performance or to organizational commitment. However, organizational commitment is found to be significant related to performance. Finally, in line with the results above, there was no significant mediation effect of organizational commitment on the relation between the use of PMS and performance found.

Theoretical Implications: The results of this research did not found support for the literature of the goal-setting theory. However, the results do enlist to the earlier found mixed results on the effectiveness of the use of PMS which correspond the contingency theory. Thereby the founded relation between organizational commitment and performance confirms the literature too, especially the literature with regard to the motivational argument.

Practical Implications: The research findings should alert companies on the evaluation of their use of PMS to make sure the systems work as they expect them to. Thereby, the relation between organizational commitment and performance makes organizational commitment an interesting variable to consider in optimizing performance of the employees and the company.

Keywords: Human Resource Management, Goal Setting Theory, Performance Management Systems, use of PMS, Performance, Organizational Commitment

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1. INTRODUCTION

‘It is more or less common knowledge that performance management is not doing well in the Dutch market’ (Krullaars, Visbeen, Lane, Foks & Nigten, 2015). ‘The majority of the organizations perceive performance management as crucial for, or supportive to, a high-performing organization’ (Krulaars et al., 2015). Performance Management Systems (hereafter; PMS) are researched at large companies who find that companies recognize the value of PMS but the systems do not function as they should (Folan & Browne, 2015; Krullaars et al., 2015). The use of PMS plays a key role in the operation of organizations, hence this research will focus on the effectiveness of the use of PMS. Is the use of PMS effective in the Dutch market? And will the effectiveness of the use of PMS be mediated by organizational commitment?

Organizations use PMS for different purposes. One of the advantages of the system is the insights it gains in the performance of employees who are subject to the system. Thereby, it aligns performance of the employee with the strategic goals of the organization (Aguinis, 2013). The system is used to facilitate change and to improve the performance of employees, departments and the organization overall and lead to the achievement of organizational goals and objectives (Amaratunga & Baldry, 2002). Following the goal setting theory, these system advantages will be achieved by the settlement and communication of clear goals because these goals provide focus in the operations of employees (Verbeeten, 2008).

There has been (some) research to the relationship between the use of PMS and performance in the past. Within public organizations in the Netherlands, it is known that the definition of unambiguous and measurable goals, through the use of PMS, is positively linked to performance because it motivates managers to achieve stated goals and it guides their behavior (Verbeeten, 2008). Similar results with regard to the use of PMS and performance are found in private organizations, which have shown most senior financial officers and employees assess their PMS as, at least, sufficiently effective (Tung, Baird & Schoch, 2011; Krullaars et al., 2015). However, the relationship between the use of PMS and performance is found to be influenced by different factors, such as organizational commitment (Spekle & Verbeeten, 2014; Tung et al., 2011). Organizational commitment is assumed to influence almost any employee behavior that could affect the enterprise success, such as attendance, staying at the organization, feeling committed to their

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supervisor and above all, individual performance (Riketta, 2002; Vandenberghe, Bentein, & Stinglhamber, 2004). The influence of organizational commitment on employee behavior and individual performance makes it an important variable to consider because these influences makes it likely that organizational commitment also influences employee performance. Secondly, the use of PMS is expected to influence organizational commitment by the crowding out effect, causing negative emotions, decreasing role ambiguity and increasing feelings of responsibility. When the use of PMS indeed influences organizational commitment and organizational commitment influences employee performance, will organizational commitment, besides being a key factor in, for instance, individual performance, also act as a mediator variable in the relation between the use of PMS and performance?

This paper contributes to the PMS literature for several reasons. Firstly, Spekle & Verbeeten (2014) studied the relationship between the use of PMS and performance, but their sample only included Dutch public organizations. This study will focus on private organizations because such organizations have to perform well to create sufficient profit and to survive, and the use of PMS could contribute to that purposes. Another contribution concerns the performance management systems, because distinction between different uses of performance measures is usually not made in research on performance measurements (Van Veen-Dirks, 2010). The distinction in different uses of PMS does however seem important because there are mixed findings on the effectiveness of PMS and there is evidence of effectiveness differences between uses of PMS. The importance of separating different uses of PMS makes us identify different uses of PMS, whereby PMS will be divided into diagnostic use and interactive use. Finally, the effect of the use of PMS on organizational commitment and the mediating role of organizational commitment in the relation between the use of PMS and individual performance is, to our knowledge, not researched yet. However, to make goal setting work within organizations, commitment of employees to the goals of the organization is necessary. Hence, it is beneficial for organizations to study the role of organizational commitment by employees (Locke, Latham & Erez, 1988). If organizational commitment indeed influence the effectiveness of goal setting, one could expect organizational commitment to mediate the role between the use of PMS and performance. Companies have to ensure that the use of PMS in combination with organizational

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commitment is effective in maximizing performance. Regardless of the fact that this applies to both public and private organizations, this research focuses on private organizations because they have to perform well to achieve a sufficient profit and to survive, and the use of PMS could contribute to these purposes. Thereby they are expected to have more clear and measurable goals.

The following research question will be answered: Will the relation between the use of performance management systems and employee performance be mediated by organizational commitment? To answer this question, different sub questions will be discussed first. These sub questions are ‘What is the goal Setting theory?’, ‘What are performance management systems?’, ‘What is performance?’, ‘What is the relationship between performance management systems and performance?’, ‘What is organizational commitment?’, ‘What is the relationship between performance management systems and organizational commitment?’ and ‘What is the relationship between organizational commitment and performance?’ This article is structured as follows; chapter two reviews the existing literature on the topic, chapter three outlines the methodology used, followed by the data and data analyses and finally a discussion and conclusion on the basis of the results was reached.

2. LITERATURE REVIEW

2.1 Goal Setting Theory

This research will be based on the goal setting theory, wherefore this theory will be outlined first. What is the goal setting theory? The theory was introduced by Edwin Locke in 1966 and is now widely used in organizational context (Miner, 2015). It states that the specification of clear and measurable goals appears to provide focus in operations and will subsequently improve performance (Verbeeten, 2008). According to this theory, the determination and communication of goals makes PMS efficient when it guides attention and behavior and works as a motivator (Erez & Kanfer, 1983; Locke et al., 1981). In a meta-analysis study on the goal setting theory it was found that goal setting is positively related to performance (Latham, 2011). Thereby, we expect that the settlement of specific and measurable goals stimulates diagnostic use of PMS because these goals help set the targets within diagnostic use of PMS. In 90 percent of the reported studies it is found that goal setting has a positive effect on performance when the following two assumptions are

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met (Locket et al., 1981); Firstly, goals should represent an end state towards which a person strives and secondly, goals should serve as immediate regulators of human action, they should mobilize effort, increase persistence and motivate the employee to develop strategies (Erez & Kanfer, 1983; Locke et al., 1981). Thereby, the relation between goals and performance is most likely to be found when goals are specific and challenging, the employee accepts the goals, individuals have the ability to attain their goals and get feedback, and monetary rewards are given (Locke et al., 1981). Latham (2011) found in his meta-analytic study that employees who have measurable and specific goals show superior performance compared with those who are solely encouraged to perform at their best. In this research context, goal setting of private organizations means that goals of (financial) performances are stated to ensure the survival of the organization. These goals are specific and measurable. As outlined in subsequent sections, the use of PMS is expected to be different in a context with such specific and measurable goals in contrast to a context with unclear goals. The characteristics of goals in private organizations, which apply specific and measurable goals, are expected to stimulate diagnostic use of PMS because these goals help to set the targets within diagnostic use of PMS.

As stated in this paragraph, the goal setting theory states that the specification of clear and measurable goals appears to provide focus in operations and will subsequently improve performance when it guides attention and behavior and works as a motivator.

2.2 Performance Management System

As said before, the use of performance management systems (PMS) is central in this research. What is a PMS? PMS will here be defined as ‘a continuous processes of identifying, measuring, and developing the performance of individuals and teams and aligning performance with the strategic goals of the organization’ (Aguinis, 2013). PMS are used by organizations to facilitate change and to improve the performance of employees, departments and the organization overall and to achieve organizational goals and objectives (Amaratunga & Baldry, 2002). Within the existing PMS literature, there are various distinctions within PMS. For instance, Simons (1994) distinct four types of PMS, namely beliefs systems, boundary systems,

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diagnostic control systems and interactive control systems. The first two types of systems constitute the strategic turnaround cluster and diagnostic control systems and interactive control systems together form the strategic evolution cluster. This study intents to examine how the use of PMS can improve performance wherefore, in line with Henri (2006), the focus lies on the strategic evolution cluster. The joint power of the two uses in this cluster lies in the fact that they are in competition but at the same time work complementary (Henri, 2006). The goal of PMS, both diagnostically and interactively used, should be performance enhancement but these systems use a different approach (Lee, 2005). Diagnostic use of PMS is defined as ‘Monitoring activity through deviations from predetermined standards of performance’ (Bedford, Malmi & Sandelin, 2016), these controls are mechanistic (Otley, 1999). The diagnostic use of PMS is used to monitor and reward the achievement of predetermined standards (goals) of performance. These PMS provide motivation and direction towards the achievement of goals (Henri, 2006). The second type of use of PMS, interactive control use, is defined as ‘regular involvement in decision activities of subordinates to encourage debate, learning and opportunity search’ (Bedford et al., 2016). Interactive use of PMS focuses attention on strategic uncertainties and encourages debate throughout the organization by reflecting signals sent by top managers which clarify stated goals (Henri, 2006; Simons, 1990). These reflected signals could, for instance, be goals that should be achieved by the employees. Interactive use takes an organic and learning-oriented control approach (Otley, 1999). Diagnostic use is control and efficiency oriented with a focus on assuring the achievement of predictable goals and prevent innovation and opportunity-seeking. Interactive use of PMS is more strategically oriented and stimulates research and learning, allowing new strategies to emerge (Demartini, 2013). Unless, the two uses got a different orientation and have different purposes, they are complementary to each other and work simultaneously (Henri, 2006). The appearance of one of the two uses is thus correlated to the appearance of the other one. However, the relative appearance of both uses differ in different contexts (Henri 2006). Relatively more diagnostic use of PMS will appear in a context of predictable, measurable goals which exists in a more stable environment. Relatively more interactive use will mostly exist in an innovative context, and will therefore mainly appear in a more flexible environment. The position of an organization on the

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stability/flexibility continuum will thus influence the relative extent of both uses of PMS (Henri, 2006). An overview of the characteristics of both diagnostic use and interactive control use can be find in table 1.

In summary, performance management systems are the continuous processes of identifying, measuring, and developing the performance of individuals and teams and aligning performance with the strategic goals of the organization, which could be used in a diagnostic or interactive way. On one hand, diagnostic use of PMS could positively influence performance because it guides behavior and motivates people to work hard towards the goals (Henri, 2006). On the other hand, interactive use of PMS could positively influence performance because it could clarify stated goals and encourage learning (Henri, 2006; Demartini, 2013). The use of PMS is therefore likely to influence performance.

TABLE 1

Uses of Performance Management Systems

Diagnostic Interactive

Used for Monitoring activity through Reflecting signals sent by deviations from predetermined top managers in decision standards of performance activities of subordinates Controls Mechanistic Organic and learning oriented Goal Motivation and direction to Encourage debate, learning achieve goals and opportunity search Orientation Control and efficiency Strategic

Focus Assuring the achievement of Stimulate search and learning predictable goals and prevent and allowing new strategies

innovation and opportunity- to emerge seeking

Context Predictable, measurable goals Innovative, more within a stable environment flexible environment

2.3 Performance

As mentioned before, earlier research found the use of PMS to be related to performance, but what is performance and what is the relation between the use of PMS and performance? Performance concerns the

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operation of the employee for whom the use of PMS is intended. A study on Australian manufacturing organizations found that senior financial officers assessed the effectiveness of their PMS as moderately effective in measuring and controlling the performance in line with the defined strategy (Tung, Baird & Schoch, 2011). In context of the Netherlands, PWC found that 67% of employees in large, listed, Dutch-based organizations found the overall execution of their PMS either somewhat effective or highly effective (Krullaars et al., 2015). Spekle & Verbeeten (2014) made use of 93 public sector organizations in the Netherlands to investigate the effect of a PMS on qualitative and quantitative performance. They found that the use of PMS influences performance of public organizations by contractibility. Contractibility means that the use of a PMS, with the aid of explicit and measurable goals, should guide employee behavior (Spekle & Verbeeten, 2014). As stated previously, the goal setting process in private organizations is rather explicit, and measurable goals of (financial) performance are set. These goals could indicate contractibility within private organizations because they guide employee behavior, which implies that the results of Spekle & Verbeeten (2014) could be applicable to private organizations too.

The results of Spekle & Verbeeten (2014) are in line with the previously outlined goal setting theory which states that the specification of clear and measurable goals appears to provide focus in operations and will improve performance (Verbeeten, 2008). Also contractibility within the goal setting theory states that the determination and communication of goals makes the PMS efficient because it guides attention and behavior and works as a motivator (Erez & Kanfer, 1983; Locke et al., 1981). As mentioned before, diagnostically used PMS determines and communicates goals which is expected to provide focus in operations. When developing a diagnostically used PMS, departmental goal-setting and long-, short- and medium-term goals (both financial and non-financial) should be considered (Neely, Gregory & Platts, 1995). These considered goals could positively influence performance if they provide focus in operations, in accordance with the previously mentioned contractibility and goal-setting theory. Unless the goal-setting process in diagnostic use is clear, interactive use of PMS is expected to enhance the clearness of goals too (Henri, 2006; Bedford et al., 2016; Simons, 1990). Interactive use of PMS focuses attention on strategic uncertainties which alert employees on possible pitfalls or opportunities and encourages debate throughout

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the organization by reflecting signals sent by top managers (Henri, 2006; Bedford et al., 2016; Simons, 1990). Both processes within interactive use of PMS are expected to enhance clearness of goals and in line with the goal setting theory this appears to provide focus in operations and will improve performance.

In summary, performance concerns the operation of the employee for whom the use of PMS is intended. The use of PMS is therefore expected to influence employee performance. PMS used in a diagnostic way are implemented to monitor and reward the achievement of goals. They confirm the goals that should be achieved, which is, based on the goal setting theory, expected to provide motivation and direction to the goals and so enhances performance. Interactive use of PMS results in regular involvement in decision activities of subordinates to encourage debate, learning and opportunity search (Bedford et al., 2016). This use of PMS focuses attention on strategic uncertainties and encourages debate throughout the organization by reflecting signals sent by top managers which could guide the employee in achieving specific goals and so enhance performance (Henri, 2006; Simons, 1990). In accordance with the stated findings on the efficiency of the use of PMS in the public sector and the findings with regard to contractibility and the goal setting theory, this research will expect the following relations:

Hypothesis 1a: Diagnostic use of Performance Management Systems is positively related to performance.

Hypothesis 1b: Interactive use of Performance Management Systems is positively related to performance.

2.4 Organizational Commitment

Besides the relationship between the use of PMS and individual performance, it is found that organizational commitment is associated with individual performance too (Riketta, 2002; Vandenberghe, Bentein, & Stinglhamber, 2004). Organizational commitment has appeared to be associated with almost any employee behavior that could affect the enterprise success, such as attendance, loyalty to the organization, feeling committed to their supervisor and thus individual performance (Riketta, 2002; Vandenberghe, Bentein, & Stinglhamber, 2004). Therefore, this section discusses organizational commitment and the relationship

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between organizational commitment and employee performance by answering the questions ‘What is organizational commitment?’ and ‘What is the relationship between organizational commitment and performance?’

What is Organizational Commitment? A lot of different definitions of organizational commitment exist in the organizational behavior literature. These definitions differ in antecedents and consequences (Meyer & Allen, 1991; O'Reilly & Chatman, 1986; Mowday et al., 1979). Since the current study focusses on the goal setting process with regard to the use of PMS, organizational commitment will be defined as ‘an individual belief in and acceptance of the organization’s goals and values and his or her willingness to exert considerable effort on behalf of the organization’ (Noor, Scarlat, Kasim & Muhamad, 2010). Besides different definitions of organizational commitment, the organizational behavior literature also recognize different models of organizational commitment. This study will use the three-component model of commitment, which entails three types of organizational commitment, namely affective, continuance and normative commitment (Meyer & Allen, 1991). Affective commitment is a desire to maintain membership in the organization and develops largely as the result of work experiences that create feelings of comfort and personal competence. Continuance commitment is a need to remain and results from recognition of the costs associated with leaving the organization. Normative commitment reflects an obligation to remain resulting from internalization of a loyalty norm and/or the receipt of favors that require repayment (Meyer & Allen, 1991). An overview of the three different types of organizational commitment can be found in table 2. However, because a meta-analyses on the antecedents and consequences of the different types of organizational commitment found that affective organizational commitment has the strongest relation with performance, only this type of organizational commitment will be included in this study (Meyer, Stanley, Herscovitch & Topolnytsky, 2002).

What is the relationship between organizational commitment and performance? Organizational commitment has been found to be one of the predictors of a lot of behaviors of employees in organizations, like absenteeism, turnover, stress and organizational citizenship behaviors (Mercurio, 2015; Somers, 1995;

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changed employee’s attitude as a result of compliance to, identification with and internalization of a company (O’Relly III & Chatman, 1986). A changed attitude as a result of organizational commitment is thus expected to influence employee performance. Besides a changed attitude, the correlations between organizational commitment and employee organizational behaviors are often theoretically justified with the motivational argument (Shaw, Delery & Abdulla, 2003). This argument states that organizational commitment embraces better performance in three different ways. These are, committed employees are more driven to achieve the company goals, are likely to work hard and more consistently in accordance with organizational expectations than those who do not and furthermore that organizational commitment embraces acceptance of the organization’s goals and values (Wood & Wilberger, 2015; Shaw et al., 2003; Noor et al., 2010). Firstly, committed employees are found to be more driven to achieve the company goals. Companies are expected to pursue the best employee performance. Commited employees are thus, through their drive to achieve company goals, expected to get the best out of their selves. Secondly, committed employees are likely to work hard towards organizational expectations. PMS state the organizational expectations with regard to the employee behavior and thus, committed employees could work harder towards goals set by the PMS than less committed employees because committed employees work hard towards organizational expectations. Working hard towards organizational expectations and goals set by the PMS is expected to encourage performance. Thirdly, organizational commitment embraces acceptance of the organization’s goals and values. Goal acceptance is a key issue in the relation of the goal setting theory, which understate a positive relation between goals and performance (Locke, Shaw, Saari & Latham, 1981). Organizational commitment could embrace goal acceptance, which on his turn leads to a more positive relation between goals and performance. Goal acceptance could thus positively influence the performance of an employee. If organizational commitment could indeed make employees more ambitious, work harder and embraces acceptance of the goals of the PMS, these three forces are expected to influence the effectiveness of the system. In line with the previous relations, a study on individual performance of 382 hospital employees and around 100 retail management trainees in the United States found a relation between affective organizational commitment and organizational performance (Mowday et al., 1979). More

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specifically, there is a positive correlation between affective organizational commitment and individual performance in different studies (Mercurio, 2015; Bateman & Strasser, 1984; Angle & Perry, 1981; Allen & Meyers, 2007). For example, a study at a large American multinational corporation observed a positive relationship between affective organizational commitment and job performance (Nouri & Parker, 1998).

In summary, organizational commitment is an individual belief in and acceptance of the organization’s goals and values and an employee’s desire to maintain membership in the organization. The relation between organizational commitment and performance is based on the motivational argument, which states that committed employees are more driven to achieve the company goals and are likely to work hard and more consistently in accordance with organizational expectations than those who don’t, and that organizational commitment embraces acceptance of the organization’s goals and values (Wood & Wilberger, 2015; Shaw et al., 2003; Noor et al., 2010). These effects of organizational commitment on employees are likely to positively impact their performance. In accordance with the motivational argument and the results above, the current research expects the following relation:

Hypothesis 2; Affective organizational commitment is positively related to performance. TABLE 2

Types of Organizational Commitment

Affective Continuance Normative

Definitions A desire to maintain A need to remain, and An obligation to remain membership in the results from recognition resulting from

organization that of the costs associated internalization of a develops largely as with leaving the loyality norm and/or the the result of work organization receipt of favors that experiences that create require repayment feelings of comfort and

personal competence

Used within this Yes No No research?

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2.5 The Mediating Effect of Organizational Commitment

Besides the direct effects of the use of PMS and organizational commitment on performance, the use of PMS is also expected to influence performance by the mediating effect of organizational commitment. Therefore, the question ‘Will the relation between the use of performance management systems and employee performance be mediated by organizational commitment?’ will be under consideration in this section.

To start with, is there a relation between diagnostic use of PMS and organizational commitment? Diagnostic use of PMS is used to monitor and reward the achievement of predetermined standards of performance. Despite that this use of PMS could eventually lead to performance enhancement, it is at the same time expected to negatively influence organizational commitment in two ways. Firstly, by the crowding out effect of intrinsic motivation. This effect states that an external intervention (diagnostic use of PMS) could reduce the individuals’ intrinsic motivation (Frey, 1998). Two psychological processes underlie this crowding-out effect. Firstly, ‘when individuals perceive the external intervention to be controlling in the sense of reducing the extent to which they can determine actions by themselves, intrinsic motivation is substituted by extrinsic control. According to Rotter (1966), the locus of control has shifted from inside to the outside of the person affected. Individuals who are forced to behave in a specific way by outside intervention would feel “overjustified” if they maintained their intrinsic motivation. Then, they behave rationally when reducing the motivational factor under their control, that is, intrinsic motivation’ (Frey, 1998). Diagnostic use of PMS determines and communicates goals which can be expected to be perceives as a reducing of the extent to which employees can determine their actions. Secondly, ‘an intervention from the outside undermines the actor’s intrinsic motivation if it carries the notion that the actor’s intrinsic motivation is not acknowledged. The person affected feels that his or her competence is not appreciated, and that perception leads to an impaired self-esteem, resulting in a reduced effort’ (Frey, 1998). Diagnostic use of PMS could be felt as a undermining of the employee’s intrinsic motivation when there are external motivators included in the system. So, intrinsic motivation is reduced when individuals perceive the external intervention to be controlling and when the use of PMS carries the notion that the

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actor’s intrinsic motivation is not acknowledged. Diagnostic use of PMS is therefore likely to, by the crowding-out effect of intrinsic motivation, decrease organizational commitment. Lower organizational commitment is, according to the motivational argument, linked to lower performance. Besides the crowding-out effect, there is another process which is expected to lower organizational commitment. Diagnostic use of PMS monitors and rewards behavior. This focus is expected to eventually result in an increased orientation on variations between stated goals and realized behavior. Negative emotions resulting from feedback generally diminish employees’ affective organizational commitment (Stepherd, Patzelt & Wolfe, 2011). Thus, when PMS is used in a diagnostic way and experienced by the employee as a negative force which produces negative emotions, employees’ organizational commitment could be diminished. As seen before, organizational commitment will be positively related to performance following the

motivational argument. Decreased organizational commitment by the crowding out effect and negative emotions following relatively much diagnostic use of PMS is likely to be related to lower organizational commitment and hence lower performance. Therefore, organizational commitment is expected to act as a mediator variable in the relation between diagnostic use of PMS and performance.

As mentioned previously, interactive use of PMS provides regular involvement in decision activities of subordinates to encourage debate, learning and opportunity search. Firstly, encoring debate provides a communication tool which could consequently decrease role ambiguity. In a meta-analysis with regard to role ambiguity, it is found that role ambiguity is positively linked to organizational commitment because it could reduce the perceived link between the employee’s role and the attainment of organizational objectives (DeCotiis & Summers, 1987). Therefore, PMS used in an interactive way is, when it decreases role ambiguity, expected to increase organizational commitment. Thereby, encoring debate stimulates contact between people within an organization and keeps individuals so informed. Keeping the individual informed is found to affect the responsibility feelings of an employee and so his organizational commitment (DeCotiis & Summers, 1987). Interactive use of PMS is therefore expected to, by decreasing role ambiguity and increasing responsibility feelings, increase organizational commitment. According to the motivational argument, increased organizational commitment will increase performance. Organizational commitment is

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therefore expected to act as a mediator variable between interactive use of performance management systems and performance.

In summary, diagnostic use of PMS is expected to decrease organizational commitment by the crowding out effect of intrinsic motivation and by negative emotions as a result of feedback. Organizational commitment is on his turn positively linked to performance and therefore expected to act as a mediator variable in the relation between diagnostic use of PMS and performance. Thereby, interactive use of PMS is expected to have a positive relation with organizational commitment by decreasing role ambiguity and increasing responsibility feelings. Increased organizational commitment will, according to the motivational argument, increase performance and is therefore also expected to act as a mediator variable within the relation between interactive use of PMS and performance. Based on the previous, the following relations are expected:

Hypothesis 3a; Diagnostic use of performance management systems is negatively linked to organizational commitment.

Hypothesis 3b; Interactive use of performance management systems is positively linked to organizational commitment.

Hypothesis 4a; Organizational commitment acts as a mediator variable in the relation between diagnostic use of performance management systems and performance.

Hypothesis 4b; Organizational commitment acts as a mediator variable in the relation between interactive use of performance management systems and performance.

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H1A H1B H2 H3A H3B H4A (-*+) = + H4B (+*+) = + The resulting conceptual model is represented below. See table 3 for all effects.

TABLE 3

Effects within Conceptual Model

Effect on organizational Effect on performance

commitment

Diagnostic use of PMS

-

+

Interactive use of PMS

+

Organizational Commitment (OC)

+

Diagnostic use * OC

(-*+) = -

Interactive use * OC (+*+) = +

3. RESEARCH METHODOLOGY

3.1 Design and participants

This research seeks to find evidence to the relations between the use of PMS, performance and organizational commitment in private organizations with clear stated goals. Private organizations are of great interest because these organizations have to perform well to achieve a sufficient profit and to survive and the use of PMS could contribute to these purposes. The Netherlands was under consideration because

Diagnostic use of PMS Interactive use of PMS Performance Organizational Commitment

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contradictory results about the effectiveness of the Dutch systems were found in earlier research (Folan & Browne, 2015; Krullaars et al., 2015; Amaratunga & Baldry, 2002; Verbeeten, 2008). The intended target group were employees at different hierarchical levels within a private organization operating in the IT-industry, ServiceNow. This organization was chosen because it has clear and measurable goals and is based in the Netherlands. Thereby there was great access to data within this organization which could increase reliability of collected data because more data could be collected and data requirements could be better monitored. ServiceNow is listed on the NYSE and established all over the world. It has clear, measurable financial goals and is therefore expected to have more diagnostic use. Within ServiceNow, employees with a certain kind of task complexity were chosen to ensure their use of the PMS. This selection process was twofold. The initial selection of research participants is done by the global HR manager by only including (employees of) certain managers. Managers were included when they are required to use a PMS within executing their management function. The PMS which the managers are required to use included financial targets, employee goal setting and feedback moments with the employees. This requirement was inserted to ensure the employees were subject to the use of a PMS and ensured task complexity because these managers, in general, only managed employees with a certain kind of task complexity. The selection of managers was done by judgment of the global HR manager. After selecting the managers, verification of the resulting employees list of selected managers was done by the global HR director of the company. This list entailed the managers who were required to use a PMS and the employees who they manage. The global HR director judged if selected participants had indeed a certain kind of task complexity to ensure goal setting was of importance in executing their jobs. The requirement of the employees’ managers to use a PMS and the certain kind of task complexity should together ensure that the employees were subject to a PMS. The data used in this research is collected by online surveys, send to the final sample of 340 employees. However, after ten days the response was limited to 42 people. To increase this response, a reminder was sent and employees were approached personally. The online survey was finally completed by 76 research participants, which make the response rate 22.35%. The sample consisted of different aged employees with management and non-management functions working at departments of different sizes.

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This sample was chosen to run out potential personality traits biases, (none) management biases and effects of department size. The survey used consists of validated questionnaires of all included variables. The validation of the resulting questionnaire is done by use of colleague students who filled in the questionnaire and gave a critical review which was incorporated in the questionnaire. The adjusted questionnaire was distributed and can be found in appendix 1.

3.2 Procedure

The data was obtained by online questionnaires in November and December 2017. All questionnaires were digitally issued to the global Human Resource Manager of the company. The global Human Resource Manager thereafter sent the link of the digital questionnaire to selected employees in the Dutch department of the company. A reminder was sent by the manager to the participants 10 days after sending the questionnaire, where after they had one more week to fill in the questionnaire. After the data collection, data was checked and assumptions were tested to construct the final sample. This final sample was used in testing the hypotheses. Descriptive statistics were calculated and correlations were executed first. Thereafter, the hypotheses were tested with a linear multiple regression and a mediation process analysis. These analyses were chosen because all variables have an ordinal measurement level with maximal a seven-point scale and the conceptual model consists of a mediator. The ordinal data was treated as continue data because it had a seven-point scale. Because the conceptual model contains two independent variables, there was forced entry within the linear multiple regression and diagnostic use and interactive use were in turn entered as control variables in the process analysis.

3.3 Measurement of Variables

As stated before, this research focusses on this main question: ‘Will the relation between the use of performance management systems and employee performance be mediated by organizational commitment?’. This study made use of different validated scales to measure the variables. Below, the measurement of all different variables included will be outlined.

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Performance management system. The use of PMS will be measured by the questionnaire and therefore concerns the perception of the employee about the use of the system. This measurement will be done by a validated survey instrument developed by Bedford et al. (2016) which is suitable because it distinguishes PMS in a diagnostic and interactive use and is thereby appropriate for big for-profit organizations in a wide range of industries (Bedford et al, 2016). Diagnostic and interactive use will be measured by two separate parts in the questionnaire. The measurement of diagnostic use of PMS contains five items. The items concern the perception of employees on the extent to which the manager of the employee currently relies on the diagnostic use of a PMS. None of these items are reversed, examples of these items are ‘set targets for critical performance variables’ or ‘review key areas of performance’. The questions about diagnostic control systems were answered on a seven-point Likert scale (1 = very low extent, 7 = very high extent) (

M =4.69, SD=1.29, α =0.95

). Because Cronbach’s alfa is bigger than 0.7, these questions are a reliable measure of the diagnostic use of the performance management system. This Cronbach’s alfa is in line with the Cronbach’s alfa founded in earlier research, which was 0.89 (Bedford et al., 2016). All founded Cronbach’s alfa’s in this research and in earlier research can be found in table 4. A higher score on the dimension of diagnostic use of PMS indicates more perceived use of a diagnostic control system. The interactive control system contains five items, whereof none are revised. The questions concern the perception of the extent to which the manager of the employee currently relies on interactive use of a PMS to for example ‘provide a recurring and frequent agenda for top management activities’ or ‘encourage and facilitate dialogue and information-sharing with subordinates’. The questions about interactive control systems were answered on a seven point Likert scale (1 = strong disagree, 7 = strong agree) (

M =4.39, SD

=1.22, α = 0.93

). Cronbach’s alfa is bigger than 0.7, wherefore these questions are a reliable measure of the interactive use of the performance management system. Thereby this Cronbach’s alfa, is in line with an earlier found Cronbach’s alfa of 0.89 (Bedford et al., 2016). A higher score on this dimension indicates more perceived presence of interactive use of the performance management system.

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Performance

. Performance concerns the operation of the employee who is subject to the PMS. This

performance will be measured with the validated instrument of Van de Ven and Ferry (Verbeeten, 2008). The integral measurement of performance makes this instrument suitable because performance in this research also contains the overall performance of the employee. The instrument of Van de Ven and Ferry includes seven different dimensions of performance, namely (1) productivity, (2) quality or accuracy of work produced, (3) number of innovations, process improvements or new ideas, (4) reputation for work excellence, (5) attainment of production or service level goals, (6) efficiency of operations, and (7) morale of unit personnel. These dimensions of performance are together used as a comprehensive measure of performance. The questions will be answered on a 5 point Likert scale, whereby 1 is far below average performance and 5 is far above average performance. (

M =3.74, SD =0.48, α =0.77

). Despite the Cronbach’s Alfa is smaller than the Cronbach’s Alfa (

α =0.80

) earlier found (Verbeeten, 2008), the questions can be seen as a reliable measure because Cronbach’s alfa is still bigger than 0.7. None of the questions are reversed. A higher score indicates better perceived performance of the employee himself.

Organizational Commitment

.

Organizational commitment will be measured as a feeling of the employee. This will be done with a part of the TCM Employee commitment survey (TCMECS). TCMECS separately measures the three forms of employee commitment of the three component model of commitment. This instrument was used because only affective organizational commitment was under consideration in this research. TCMECS is a standardized validated instrument developed by Allen and Meyer (2004). Affective organizational commitment will be measured with 8 items, whereof four (4, 5, 6 and 8) are reversed. Examples of items are ‘I Enjoy discussing my organization with people outside of it’ and ‘I do not feel “emotionally attached” to this organization’. The items of organizational commitment were answered on a seven-point Likert scale (1 = ‘strongly disagree’, 7 = ‘strongly agree’). Reversed code items were re-encoded before aggregating the items to one affective organizational score (

M =4.84, SD

=0.92, α =0.81

). These questions have a Cronbach’s alfa of 0.807 which confirms the validation of the

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questionnaire, unless it is smaller than earlier measured Cronbach’s alfa of 0.87 (Allen & Meyer, 2004). A higher score on this dimension indicates stronger organizational commitment.

TABLE 4 Cronbach’s alfa

α out of references α in this research

Diagnostic use of PMS .89 .95

Interactive use of PMS .89 .93

Performance .80 .77

Organizational commitment .87 .81

3.4 Control Variables

The interplay between the use of a PMS, employee performance and organizational commitment are measured in this research. To rule out alternative explanations of founded results, reduce error terms and increase statistical power, some control variables are included (Becker, 2005). These control variables are otherwise expected to influence the results. The first control variable is personality, which will be defined as the five-factor model of personality. Personality attains to the personality of the employee subject to the PMS. The five-factor model consists of extraversion, agreeableness, conscientiousness, emotional stability and openness to experience. Earlier research found a link between the five-factor model and job performance wherefore this variable will be included as control variable (Tett, Jackson, Rothstein & Reddon, 1999). Thereby, there is a relation found between personality and organizational commitment (Erdheim, Wang & Zickar, 2006). To measure the personality traits, the BFI-10 (Rammstedt & John, 2006) was used, which contains two items, for each personality trait and thus in total 10 items. The BFI-10 is used because it is a validated measure and proven to be sufficient for research setting with limited time constraints (Rammstedt & John, 2006). Two examples of items are ‘I see myself as someone who is reserved’ and ‘I see myself as someone who tends to be lazy’. The items of personality will be answered on a 5-points Likert scale (1 = ‘strongly disagree’, 5 = ‘strongly agree’) and will involve reversed questions.

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Reversed-coded items will be re-encoded before aggregating the items to one affective organizational score. The measurement of personality could be a sensitive theme and possibly even have negative consequences for employees. Different steps are taken to minimize the chance of these occurrences. Firstly the anonymity of research participants was ensured. Thereby a minimum of questions with regard to personality were asked. As a result of these precautions, the ethics committee was not asked for permission to include the questions with regard to personality. The second control variable is work experience. In a meta-analysis, it was found that work experience is positive related to work performance. To measure work experience, the amount of time spent in a particular job was founded to be a validated tool (Quińones, Ford & Teachout, 1995). Furthermore, Age is related to self-assessment of task performance and thus included as a control variable for his potential effect on performance (Ng & Feldman, 2008). Also, age is found to be positively related to organizational commitment (Mathieu & Zajac, 1990). Women are found to have lower scores on organizational commitment than man (Mathieu & Zajac, 1990), for this reason, gender is included as control variable as well. Gender was transformed into a dummy variable before it was applied in a regression analysis. Finally, Size of Department, (none) management and organizational structure (Jennings & Seaman, 1990) are also included as control variables. (None) Management was transformed into a dummy variable before it was applied it in this study too. Afterwards, a correlation and regression analyses were used to see if all control variables influenced the conceptual model under consideration.

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TABLE 5 Variable Descriptions

Variables Description

Dependent Variable

ZPERFc ZPERFc concerns the self-assessed performance of the employee who is

subject to the PMS. The instrument of Van de Ven and Ferry consists of seven dimension. A higher score indicates better perceived performance of the employee himself.

Independent Variable

ZDIAGNc ZDIAGNc will be measured by the instrument of Bedford et al. and captures the perception of employees on the extent to which the top management team of the employee currently relies on diagnostic use of a PMS.

ZINTERc ZINTERc will be measured by the instrument of Bedford et al. and captures the perception of employees on the extent to which the top management team of the employee currently relies on interactive use of a PMS.

ZORGCOMc Organizational commitment will be measured as a feeling of the employee. A higher score on TCMECS indicates more organizational commitment. Control Variable

Gender Gender of the employee which is 0 if male and 1 if female. Age Age of the employee measured in years.

Education Education captures education levels MAVO/VMBO, HAVO, VWO, MBO, HBO and WO based on the Dutch education system.

Work exp. Work Exp. contains the number of years an employee spend in a particular job.

Dep. Size Dep. Size equals the number of employees working on the department of the regarding employee.

Man. Function Man. Function equals 0 if a person is executing a management function and 1 if the employee is not.

Extra One of the big five personality traits, which is measured by the BFI-10. A higher score indicates more self-assessed extraversion of the employee. Agree One of the big five personality traits, which is measured by the BFI-10. A

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Variables Description

higher score indicates more self-assessed agreeableness of the employee. Consc One of the big five personality traits, which is measured by the BFI-10. A higher score indicates more self-assessed conscientiousness of the employee. Neuro One of the big five personality traits, which is measured by the BFI-10. A higher score indicates more self-assessed neuroticism of the employee. Openness One of the big five personality traits, which is measured by the BFI-10. A higher score indicates more self-assessed openness to experience of the employee.

Form Organizational characteristic as identified by Jennings & Seaman. A higher score indicates a more perceived formalized organizational structure. Strat Organizational characteristic as identified by Jennings & Seaman. A higher score indicates a more perceived stratificated organizational structure. Complex Organizational characteristic as identified by Jennings & Seaman. A higher score indicates a more perceived complex organizational structure. Centra Organizational characteristic as identified by Jennings & Seaman. A higher score indicates a more perceived centralized organizational structure.

4. RESULTS

4.1 Data set

In total, 76 employees completed the questionnaire. Nine of these questionnaires where not completely finished, wherefore these questionnaires were deleted out of the sample. After deletion of these questionnaires the data set was checked on outliers, but this was not a source of concerns wherefore the final sample consisted of 67 questionnaires. Before testing the hypotheses, the four assumptions which are required for a regression analyses were tested. The first assumption is independence of observations, which cannot be tested statistically. However, all resource participants completed the questionnaire independently of one another and there were no repeated measures, wherefore one could expect this assumption to be fulfilled. Secondly, the assumption of normality was tested for which a QQ-plot of the dependent variable, performance, was made (see appendix 2). The QQ-plot showed a normal distribution of performance. Next,

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the assumption of linearity was tested. This assumption was tested with a plot of the standardized expected values on the x-axis and de standardized residue on the y-axis (see appendix 3). Finally, the assumption of homoscedasticity was tested with the same plot that was used in testing the assumption of linearity. The points within the scatterplot were randomly distributed wherefore these assumptions were fulfilled too and all assumptions can be expected to be met. In short, the total sample of 76 employees was reduced to a final sample of 67 research participants after removing research participants with missing data. Outliers and the four assumptions were checked, but found to be no problem.

4.2 Descriptive statistics

Firstly, the descriptive statistics were calculated and can be found in table 6. There were men (65.7%) as well as women (34.3%) included in the sample, varying from 27 years to 66 years old and an average age of 39 years. On average, they worked six years in their function, at different departments. The different departments largely differ in size, varying from three until 591 people, with a mean of 75 people. 21 of the participating people (31.3%) were executing a management function. Most participants completed WO (64.2%) or HBO (19.4%). Finally, personality characteristics of employees were measured. On average, people were scoring high on conscientiousness and low on neuroticism. The company did not have a clear organizational structure, each dimension scored nearly the same and had a comparable standard deviation. With regard to the use of PMS, diagnostic use of PMS was found to be somewhat more experienced by the employee’s then interactive use. This accords the earlier assumption that diagnostic use appears more in a stable environment with predictable and measurable goals, which the researched company has. Thereby, the employees rated their own performance above average (µ = 3.7446) and had on average a high feeling of organizational commitment (µ = 4.8447).

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TABLE 6 Descriptive statistics

Min. Max. Mean Std. dev.

Gender (Dummy) 1 2 1.34 .48

Age 27 66 39 7.88

Work Experience 1 27 6 6.04

Department Size 3 591 75 128.84

Management function (Dummy) 1 2 1.69 .47

Education 3 8 7.31 1.18

Extraversion 1.5 5 3.48 .79

Agreeableness 2 5 3.84 .65

Conscientiousness 3 5 4.04 .63

Neuroticism 1 4 2.34 .78

Openness to Experience 2 5 3.44 .74

Formalized 2 5 3.33 .62

Stratificated 1.5 4.5 3.31 .67

Complex 2 5 3.35 .60

Centralized 2 4.5 3.29 .62

Diagnostic use of PMS 1 7 4.69 1.29

Interactive use of PMS 1 7 4.39 1.22

Performance 2.43 4.86 3.74 .48

Organizational Commitment 2.63 6.88 4.84 .92

4.3 Correlation

Before testing the hypotheses, a correlation matrix was made which can be found in table 7. Education was negatively correlated (r = -.434) to age. This negative correlation could be due the sector wherein the research was done. IT is a relatively new wherefore younger people could have had more opportunities for education within this sector. Some aspects of the big five had correlation with other variables too. Only extraversion was correlated to gender (r = 0.263), which is remarkable because the other four personality

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traits were expected to be correlated to gender too (Schmitt, Realo, Voracek & Allik, 2008). Conscientiousness was negative correlated to management function (r = -.340), which is notable because managers were found to score higher on conscientiousness in earlier research (Barrick & Mount, 1991). Formalization was not correlated to standardization and centralization, while all other correlations between organizational culture dimensions were correlated. Diagnostic use was positively correlated to formalization and complexity. Interactive use was positive correlated to formalization and complexity too, which makes sense because interactive use and diagnostic use are highly positive correlated (r = 0.748). The correlation between the two uses of PMS was expected because they are complementary. Performance is positively correlated to department size and several personality traits, agreeableness, consciousness and neuroticism. However, notably is that performance was not correlated to diagnostic and interactive use of PMS. Organizational commitment was correlated to agreeableness, interactive use of PMS (r = 0.289) and performance (r = 0.377). After analyses of these correlations, department size, personality and organizational structure were included as control variables.

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4.4 Hypothesis testing

To test the hypotheses 1a, 1b and 2, a multiple linear regression with forced entry was conducted. However, before doing so, centralization and standardization was done at all independent and dependent variables. Thereafter, the correlation analysis was done. This analysis showed, as can be found in table 7, that only department size, personality and organizational structure had significant correlations with an independent or dependent variables. As such, only these variables were included as control variables in the analyses of the hypotheses. First a multiple linear regression was conducted, which results can be found in table 8. In conducting the multiple linear regression, a model with only the control variables was made first. Hereafter model 2 was made. This model contained the control variables, both uses of PMS and organizational commitment because a forced entry was conducted. The results of model 2 showed, not in line with Hypothesis 1a, that diagnostic use of PMS does not significantly influence performance, b = 0.221 SEb

=0.161 , t(66)=1.368, p > .05. Because the p-value was larger than the significant level of 0.05, the model is not significant. Next up, Hypothesis 1B was tested. The regression analysis showed no significant relation between interactive use of PMS and performance, b = -0.13, SEb = 0.18, t(66)= -0.684, p > .05. Hypothesis

1B is not significant.

Next up, the multiple linear regression showed the effect of organizational commitment on performance, b = 0.331, SEb = 0.109, t(66) = 3.040, p < .05. The p-value is smaller than 0.05 for which this

relation is significant and there was prove for Hypothesis 2. This is confirmed by the fact that the lower and upper bound do not contain zero.

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TABLE 8

Multiple linear regression

Model 1 Model 2

Step and variables B SE B SE

Intercept -4,25** (1.58) -3.24 (.06) Control Department size .00** (.00) .00** (.00) Extraversion .23 (.14) .23 (.13) Agreeableness .15 (.18) .10 (.18) Conscientiousness .56** (.21) .46 (.20) Neuroticism -.08 (.18) -.11 (.17) Openness to Experience -.06 (.16) .00 (.15) Formalized .24 (.19) .12 (.19) Stratificated -.18 (.17) -.18 (.16) Complex -.14 (.20) -.27 (.20) Centralized .31 (.19) .42 (.18) Main effects Diagnostic use of PMS .22 (.16) Interactive use of PMS -.13 (.18) Organizational Commitment .33** (.11) R Square .41 .52 ∆ R Square .11 F. 3.89 4.38 Sign. 0.00 0.00 **p < .01

After performing the multiple linear regression, the results with regard to the mediator, organizational commitment, are computed. Here fore, a Process Analysis of Hayes is performed. The results with regard to this analysis can be found in table 9. Model 1 of the Process analysis, with organizational commitment as outcome variable, showed no significant relation between diagnostic use of PMS and organizational commitment, b = -.06, SEb = .203, t(66)= -.31, p > .05. Because the p-value was bigger than

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the significant level of 0.05, Hypothesis 3A is not significant. The analyses further showed that interactive use of PMS does not increase organizational commitment either, b = 0.2637, SEb =0.23, t(66)=1.15, p >

.05. Because the p-value was smaller than the significant level of 0.05, Hypothesis 3B is not significant. Finally, the mediating effect was under consideration. However, because the diagnostic use of PMS did not have a significant influence on organizational commitment, there is no partial mediation. In line with this result, there was no mediating role of organizational commitment in the relation between diagnostic use of PMS and performance, b = 0.2205, SEb = 0.16, t(66)= 1.37, p > .05. Thus, no support for

Hypothesis 4A was found. Lastly, interactive use of PMS did also not have a significant influence on organizational commitment, wherefore no partial mediation is found. In line with this lack of support, organizational commitment was not found to act as a mediator variable in the relation between interactive use of PMS and performance, b = -.1260, SEb = 0.18, t(66)= -0.68, p > .05. Thus, no support for Hypothesis

4B was found.

TABLE 9

Process analysis by Hayes

Model 1 Model 2

Step and variables B SE B SE Intercept -2.20 (2.11) -3.24 (1.69) Control Department size -.00 (.00) .00** (.00) Extraversion .06 (.17) .23 (.13) Agreeableness .18 (.18) .10 (.18) Conscientiousness .34 (.25) .46 (.20) Neuroticism .09 (.22) -.11 (.17) Openness to Experience -.23 (.19) .00 (.15) Formalized .20 (.24) .12 (.19) Stratificated .11 (.21) -.18 (.16) Complex .15 (.25) -.27 (.20) Centralized -.28 (.23) .42 (.18)

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Model 1 Model 2 Main effects Diagnostic use of PMS -.06 (2.11) .22 (.16) Interactive use of PMS .26 (.23) -.13 (.18) Organizational Commitment .33** (.11) R Square .23 .52 F. 1.28 4.37 Sign. 0.25 0.00 **p < .01 TABLE 10 Hypotheses’ b, SEb, t, p; Note. N=66; *P<0.05*; **P<0.01

b SEb t p LLCI ULCI

Hypothesis 1A .22 .16 1.37 .18 -.10 .54

Hypothesis 1B -.12 .18 -.68 .50 -.50 .24

Hypothesis 2 .33 .11 3.04 .00** .11 .55

Hypothesis 3A -.06 .21 -.30 .77 -.49 .36

Hypothesis 3B .26 .24 1.08 .28 -.22 .75

Hypothesis 4A .22 .17 1.30 .20 -.12 .56

Hypothesis 4B -.13 .24 -.52 .60 -.61 .36

5 DISCUSSION AND CONCLUSION

This study concentrated on the effect of the use of performance management systems on employee performance and if organizational commitment would act as a mediator in this relation. In explanation of the relation between the use of PMS and performance, the goal setting theory was used. The relation between organizational commitment and performance was based on the motivational argument. This research contributed to the literature in two different ways. To start with, researching the mediating role of organizational commitment on the relation between the use of PMS and individual performance was, to our

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knowledge, not studied before. Thereby, this study is the first research, that we found, focusing completely on the effectiveness of the use of PMS in Dutch private organizations.

5.1 Theoretical Implications

Both uses of PMS are not found to be significantly related to performance. The goal-setting theory however states that the specification of clear and measurable goals appears to provide focus in operations and will subsequently improve performance. The results within this research did therefore not found support for the literature of the goal-setting theory. However, these results, no clear relation between the use of PMS and performance, do enlist to the earlier found mixed results about the effects of PMS. The mixed results on their turn correspond to the contingency theory which state that ‘the link between enhanced organizational performance and usefulness of some aspect of MCS may well depend on the appropriateness of the useful MCS to the context of the organization’ (Chenhall, 2003). Thereby, organizational commitment is found to be significantly positive related to performance. This finding also confirms the literature, especially the motivational argument, about organizational commitment.

5.2 Practical Implications

The results do not show a relation between the use of PMS and performance. This finding could alert companies on the evaluation of their PMS to make sure these systems work as they expect them to do. Thereby there is found that organizational commitment does enhance performance, wherefore organizational commitment of the employees is interesting to consider and, if possible, increase when optimizing performance. The results of the effect of the use of PMS on organizational commitment did not show significant results. Companies should therefore probably not expect organizational commitment to be enhanced by the use of the PMS.

5.3 Strengths and Limitations

There are numerous strong points with regard to this research. Firstly, by use of a field study, the external validity of the results is high. Data is received from a sample from the population we wanted to say something about, which make the results good generalizable. This research was intended for Dutch private

Will performance management systems manage performance?