Master Thesis Organizational & Management Control
Determinants of Perceived Fairness
of Performance Evaluation
Evidence from Dutch Business Units
ABSTRACT
The goal of this research is to examine the relation between accurate performance measurement and perceived fairness of performance evaluations. This is done by looking at the direct effect as well as moderating effects from an agency perspective, namely information asymmetry and managerial power. A literature study was conducted in order to derive the hypotheses and these hypotheses were subsequently tested using data from 100 Dutch business unit managers. The outcomes of the data analysis showed mixed results. Accurate performance measures was shown to cause more perceived fairness of performance evaluations. Similarly, information asymmetry and managerial power proved to do the same, while it was predicted that information asymmetry would have an opposite effect.
Author: Daniël Wiersma – s1694006 Date of submission: 22-06-2015 Supervisor: H. van Elten
2nd assessor: B. Crom
1
I. I
NTRODUCTION
Management accounting and control has been given a lot of attention over the years in academic research (e.g. Van der Stede, 2003; Byrnes & Pierce, 2007; Malmi & Brown, 2008). This does not come as a surprise given the increasing importance of the role of the management accountant. As Byrne & Pierce (2007) noted, the management accountant is shifting its role from the traditional number cruncher towards that of a more process oriented business partner. Similarly, management control (MC) itself has been given a lot of attention in academia over the years. Anthony (1965) described MC as a process through which managers are enabled to ensure effective and efficient use of obtained resources for an organization’s objectives. Additionally, MC and management control systems (MCS) are often regarded as behavior influencing processes (Flamholtz et al., 1985; Langfield-Smith, 1997). Moreover, MC is frequently used to align the behavior and goals of individuals with the organizational goals and strategy (Roberts, 1990; Simons, 1992; Van Elten, 2012). Furthermore, Ouchi & Maguire (1975) and Ouchi (1977) have demonstrated that depending on the purpose that is aimed to be achieved, differing types of control can be used (Otley, 1992). MCS, however, are subject to change when it comes to their definition (Chenhall, 2003). Chenhall (2003) remarked that over the years the definition of MCS has shifted from focusing on financially quantifiable information to a much broader scope of information.
2 inequality cannot lead to metrics that adequately represent performance. Likewise, Otley (1999) stated that a tendency could be observed where mainly financial performance was considered. What is more, according to the author even the behavioral aspects were integrated into an economic approach through agency theory.
While performance measurement is an important and necessary activity for companies, performance evaluation is nearly as important. This becomes clear in the statement of Hsu et al. (2015), who indicated that for sustainable development a model of objective, impartial, and convenient performance evaluation is needed. Furthermore, they pointed out that more robust results from performance evaluation are helpful in understanding operating conditions and identifying whether resources are used effectively. Nevertheless, Kaplan & Norton (1996) described performance measurement systems as being primarily designed to aid in decision making rather than for evaluation objectives. However, it has been mentioned (e.g. Dossi & Patelli, 2008; Ferreira & Otley, 2009; Van Veen-Dirks, 2010) that it is likely for supervisors to use performance information in evaluation processes. Moreover, using the classifications of Demksi & Feltham (1976), Sprinkle (2003) and Van Veen-Dirks (2010) showed that performance measures can play a decision-facilitating as well as a decision-influencing role when it comes to evaluations (among other things).
It is not only important for performance to be measured and evaluated, yet it needs to be evaluated fairly. There have been several studies over the years examining the effects of fair performance evaluations on job satisfaction (e.g. Brownell, 1982; Lau & Sholihin, 2005). These studies have been put to the test by Lau, Wong & Eggleton (2008), who, upon drawing a sample from managerial level employees in the healthcare sector, found that fair evaluation of performance led to increased job satisfaction. Additionally, Lau & Sholihin (2005) have demonstrated, and developed models to cope, that procedural fairness and trust could be used to explain why certain types of performance measures can cause favorable employee behaviors. Moreover, Hartmann & Slapničar (2009) found that the formality of performance evaluations affected interpersonal trust between subordinate and superior managers. They concluded that a higher degree of formality caused the received feedback to be perceived as being of higher quality, which in turn resulted in higher levels of trust.
3 performance measurements and an agency perspective, both within the frame of business unit managers. Agency, operating on the premise that all individuals are motivated by self-interest (Baiman, 1990), has been chosen as it might illuminate whether certain behavior can influence perceived fairness. Moreover, it is not unlikely that the business unit managers often operate in ways their superiors cannot observe. The resulting managerial behavior is often discussed in the field of agency (e.g. Grossman & Hart, 1983; Pepper & Gore, 2015). Furthermore, Pepper and Gore (2015), drawing in part upon previous studies, proposed a new set of theory and terminology regarding behavioral agency. This theory places performance and motivation at the center and, among other things, builds on fairness and inequity aversion. Within that principle this paper will specifically address the constructs information asymmetry and managerial power, which will be explained in the next section. The methodological part of this research will be based on survey data of 100 Dutch business unit managers from various operating sectors.
The research questions I aim to answer with this research are listed below:
1. How does accuracy of performance measurement influence fairness of performance evaluation (FPE)?
2. What role does information asymmetry play when determining FPE? 3. How does managerial power influence FPE?
The remainder of this paper is structured in the as follows. Section two will provide a literature study in order to derive the hypotheses. In sections three and four data will be analyzed and the results presented. In the last section the results will be discussed as well as possible limitations and suggestions for future research.
II. T
HEORY
Definitions
In this subsection the various constructs that will be addressed in this paper are defined in order to adequately frame the research.
Accuracy of performance measurement
4 proficiency perspective. This is in part due to the fact that contextual performance is not part of the job description and as such should be treated with caution (Schmidt, 1993).
The measurement of performance is seldom defined in literature (Neely, Gregory & Platts, 2005). Neely et al. (2005) proposed that this concept is about the quantification of actions, where measurement implies the quantification itself and performance is the result of action. When it comes to measuring performance Otley (1999) recognizes that there is a contingency variable, namely the intended strategy and objectives of the company. Otley and Berry (1980) complement this by stating that objectives and goals are required in order to gauge performance.
Fairness of performance evaluation
The concept of fairness of performance (FPE) evaluation has been researched often throughout the years and has appeared under various names. Dipboye and Pontbriand (1981) addressed it as performance appraisal while other authors (e.g. Greenberg, 1986; Folger & Konovsky, 1989; Lau et al., 2008) speak of justice. According to the latter studies, justice can be divided into two different categories; distributive justice and procedural justice. Distributive justice finds its roots in equity theory (see Adams, 1965) and focuses on the FPE relative to the work employees have done (Greenberg, 1986). Procedural justice, on the other hand, concerns itself more with the procedures of the evaluations themselves (Greenberg, 1986; Folger & Konovsky, 1989) and, for example, the ability of being able to express one’s feelings (Landy, Barnes & Murphy, 1978). In short, the first focuses on the outcomes of the evaluation while the latter is aimed at the way the evaluation is conducted.
Information asymmetry & Managerial power
Both information asymmetry (IA) and managerial power (MP) have been abundantly discussed in academic literature and hardly need any elaboration. For all intents and purposes, a short description will be given to help outline this research.
5 charisma or an expert role (see for example Yulk & Falbe, 1991 and Baker, Gibbons & Murphy, 1999), these sources are beyond the scope of this paper. In this context only the formal source of power will be taken into account.
Literature Review
Throughout the years companies have shifted their performance measurement systems from being finance based to systems that include nonfinancial measures as a response to a changing environment (Malina & Selto, 2001; Ittner, Larcker & Randall, 2003; Van Veen-Dirks, 2010). Research has shown that these types of measures are likely to better reflect company performance (Becker and Huselid, 1998). Moreover, a single performance measure is not capable of capturing all aspects of managerial activity and as such a diverse set of measures is used to evaluate management (Van Veen-Dirks, 2010). Furthermore, it is perceived by firms that financial measures are too past oriented and contain little ability to predict future performance nor do they adequately reflect incorrect behavior or intangible assets such as intellectual capital (Ittner et al., 2003; Fisher, 1995). However, these nonfinancial measures might actually be harder to assess as definitions tend to vary. An example of this is the differing interpretation of flexibility, which Weel Wright (1984) explains as varying production volume while Tunälv (1992) interprets it as the speed at which a company can introduce new products. There are other drawbacks to nonfinancial performance measures as well. Prendergast (2002), and subsequently Moers (2006), make the distinction between aggregate and specific performance measures where the first tries to give insight in all actions and the latter focuses on a subset of actions. It is argued by Moers (2006) that aggregate measures, which are most strongly represented by financial measures such as net income, capture the consequences of all actions taken through the financial statement. In contrast, specific performance measures might not portray the effects of certain actions on the bottom line of a division. Consider, for example, the measure of market share, this could be manipulated by a manager through discounts which hurt the profitability but do increase this specific measure (Moers, 2006). One could, therefore, wonder whether nonfinancial measures should be assessed separately from the overall financial results.
6 The second problem with the “new” performance measures is whether they do what they were intended to do. Despite the fact that there is a consensus in academic literature that measures should be consequential to strategy (e.g. Mintzberg, 1982; Keegan et al., 1989; Kaplan & Norton, 1992), Mills et al. (2000) concluded that the importance of encouragement for strategy supporting behavior is absent in most processes. Furthermore, it often happens that performance measures are not integrated with one another (Lynch & Cross, 1991) and poorly defined causing confusion (Neely, 1999). Very often managers will receive incentives through contracts in order to behave as the principal intends them to behave (Holmstrom, 1979; Moers, 2006). In addition to monetary incentives this could also entail promotions (Ederhof, 2011). Wernerfelt (1994) and Hemmer (1996) have shown that “incentives based on nonfinancial measures can improve contracting” (i.e. stimulate desired behavior) since information that is not normally visible in financial results can be included (Ittner et al., 2003). Given the problems regarding performance measurements stated above, this incentive contracting could change a manager’s perception on how fairly he or she is evaluated. Since the evaluation itself will likely determine the outcome of whether or not the incentive will be issued, the manager might feel a higher need for accurate measurements of performance. This is especially true since it has been suggested that this extrinsic reward may negatively impact intrinsic motivation (Ryan & Deci, 2000). I therefore propose the following hypothesis:
H1: A higher degree of accuracy in performance measurement will result in a higher perceived fairness of performance evaluation.
One of agency theory’s principle contributions is the broadening of the idea of risk sharing between cooperating individuals when there are different goals and division of labor (Jensen & Meckling, 1976; Ross, 1973). This is most often the case where one party delegates work to another (Eisenhardt, 1989). This delegation of work (and authority) is generally due to the agent having better decision relevant information while costs of transferring this information are too high (Jensen & Meckling, 1992). One of the core assumptions within the theory is that actions are based on self-interest (Perrow, 1986; Besanko et al., 2009). Furthermore, it is most likely that an agent (in this case a manager) has more than one task to fulfill, causing incentives to direct an agent’s effort among them (Hölmstrom & Milgrom, 1991). However, the agent also possesses information about, for example, his level of effort, or whether he behaved as he should have, that the principal cannot obtain without cost (Eisenhardt, 1989; Kunz & Pfaff, 2002). This level of information asymmetry increases with higher degrees of environmental uncertainty (Prendergast, 2002).
7 examined situations where, among other information, employees had more knowledge about their own effort or skill level or the state of nature that can enhance firm value. This information can, for example, be used to create what is called budgetary slack, which is a scenario where a difference is created between what is expected and what is actually revealed (Chow, Cooper & Waller, 1988; Sprinkle, 2003). According to several studies, this type of slack can be used by employees to improve their evaluations or hedge against uncertainty (Baiman & Demski, 1980; Merchant, 1998). Moreover, studies have shown that more information asymmetry leads to more slack (Young, 1985; Waller, 1998). If we take a few steps back and think back at the concept of outcome justice described above, we could link this definition to adverse selection in the way that perceived justice should increase as information asymmetry increases. However, as the previous analysis has shown, firms are increasingly using measures other than financial ones to determine performance. Therefore, it is unlikely that employees (or managers in this case) will be evaluated solely on budgetary outcomes. Hence, I would argue that adverse selection mainly affects procedural justice in the sense that given the superior knowledge of the employee, it becomes more important to have an adequate procedure where the employee can voice his or her opinion and knowledge. Additionally, if the manager has knowledge his superior does not, it could also affect the relation between performance measurement and FPE if the manager has no chance to express this knowledge. Given these predictions I propose the following two hypotheses: H2a: A higher degree of information asymmetry will lead to lower perceived FPE.
H2b: A higher degree of information asymmetry will have a negative effect on the relation between APM and FPE.
8 of performance measures and the outcome of performance evaluations. I therefore propose the following set of hypotheses:
H3a: Higher degrees of managerial power will positively influence perceived FPE.
H3b: Higher degrees of managerial power will postively influence the relation between APM and FPE.
III. M
ETHODS
Procedures
The data used in this study is based on the work of Van Elten (2012) and is a sample of the 325 business units originally approached for his work. The data was gathered through means of a questionnaire issued through face-to-face interviews. While these interviews were conducted by students, which benefits interpretation and response due to the ability to explain questions, these students operated under a predetermined protocol. Additionally, through this approach there was better respondent identification. For the purpose of the original research managers were identified who were in charge of an autonomous organizational body and had a superior.
Sample & Participants
The sample of this study consists of 100 business unit managers from various firms located in the Netherlands. Respondents were asked to answer in which sector their business unit and firm were active, there was no nonresponse to this question. The results can be seen in table 1 and 2, though it should be noted that the percentages differ slightly due to rounding and the fact that a small number of business units and firms were indicated to operate in more than one sector. Table 3 shows the average, minimum and maximum size of the business units and the firms as a whole in both FTE’s and revenue. In a few cases (roughly 10%) no revenue data was given, for the calculations these respondents have been left out.
SECTOR PERCENTAGE
PRODUCTION 18,6%
SERVICES 52,9%
FINANCE 16,7%
NONPROFIT 11,8%
Table 1: Business Unit Operating Sector
SECTOR PERCENTAGE
PRODUCTION 22,3%
SERVICES 45,5%
FINANCE 19,6%
NONPROFIT 12,5%
9
LEVEL AVERAGE MINIMUM MAXIMUM
BUSINESS UNIT REVENUE (€) 124.072.178 1.000.000 2.000.000.000
BUSINESS UNIT FTE’S 180 1 1.300
FIRM REVENUE (€) 5.895.866.223 5.600.000 300.000.000.000
FIRM FTE’S 10.590 50 150.000
Table 3: Business Unit and Firm Size
In addition to information about their business units and firms, respondents were also asked to indicate how long they and their superior were active within their organization and position. On average participants had been on their current position for four and a half years while working for the same supervisor for three and a half years. The total amount of years the average participant worked for the same company was 9 years. The superiors were generally indicated to be active in their current function for six and a half years and had a total experience of eleven and a half years in the firm.
Measures
From the questionnaire that was issued to the participants several questions were selected to measure the constructs of the hypotheses. Appendix A gives an overview of the questions relevant for this study, as well as their corresponding background literature. In order to see whether the selected items could be applied to measure each construct an exploratory factor analysis was conducted. The goal of the factor analysis was to obtain single factor loadings for all constructs. In order for the individual items to be accepted into the factor the component loading had to be at least 0,500 in order to have sufficient variance explanation. Values that ended up lower were removed from the factor analysis and the analysis itself would be executed anew. The results of this analysis can be found in tables 4, 5, 6 and 7. The factors have been labeled in accordance with the constructs they intend to represent, i.e. accuracy of performance measurement (APM), information asymmetry (IA), managerial power (MP) and fairness of performance evaluation (FPE).
ACCURACY OF PERFORMANCE MEASUREMENT
Item description Component loadings
Extent to which performance influences performance evaluation ,688 Extent to which performance influences bonus size ,707 Extent to which performance measures match business unit (BU) goals ,766 The total set of performance measures indicates which results the BU should realize ,837 The total set of performance measures is unambiguously linked to organizational
goals
,744
10 INFORMATION ASYMMETRY
Item description Component loadings
Knowledge possession of undertaken activities ,814 Familiarity with the transformation process ,786
Certainty of performance potential ,898
Technical familiarity ,686
Ability to assess impact of internal factors ,742 Ability to assess impact of external factors ,610
Understanding of achievements ,794
Table 5: Factor Results for Information Asymmetry – Q7
MANAGERIAL POWER
Item description Component loadings
Authority on strategic decisions ,789
Authority on investment decisions ,677
Authority on marketing decisions ,788
Authority on internal processes decisions ,724 Table 6: Factor Results for Managerial Power – Q3
FAIRNESS OF PERFORMANCE EVALUATION
Item description Component loadings
Received evaluation is based on a complete picture of performance ,831 Functioning is evaluated in an honest and fair way ,898 Satisfaction with the way of evaluation ,896 Table 7: Factor Results for Fairness of Performance Evaluation – Q6
In order to tell whether the separate questions could be combined into one variable per construct, a reliability test was performed. The resulting Cronbach’s Alphas can be found in table 5.
Construct APM IA MP FPE
Cronbach’s Alpha ,798 ,880 ,727 ,847
Table 8: Reliability Analysis
11
CONSTRUCT N MINIMUM MAXIMUM MEAN STD. DEVIATION
APM 95 -1,83 1,41 -,0033 ,75276
IA 99 -2,32 1,40 ,0017 ,74912
MP 100 -2,21 1,63 ,0000 ,87537
FPE 100 -2,20 1,37 ,0000 ,76212
Table 9: Descriptive Statistics of the Variables
CONSTRUCT SKEWNESS KURTOSIS
Statistic Std. Deviation Statistic Std. Deviation
APM -,383 ,247 -,437 ,490
IA -,710 ,243 1,080 ,481
MP -,540 ,241 -,243 ,478
FPE -,468 ,241 -,018 ,478
Table 10: Skewness & Kurtosis
Variable APM IA MP FPE
APM - - - -
IA ,001 - - -
MP ,001 ,061 - -
FPE ,007 ,101 ,001 -
*Significant correlations at the 0,01 level are indicated in bold Table 11: Correlations between Variables
In order to test the moderating relationships proposed in H2b and H3b, a special method developed by Hayes (2013) was used. In contrast to the testing of the direct relationships, this method requires the new variables to be products of the underlying items for the initial analysis. When the model itself is tested these variables are automatically centered to give the appropriate results. Tables 12 and 13 provide the descriptive statistics and skewness and kurtosis respectively of the new product variables. In order to prevent confusion with the previous tables the product variables have been dubbed APM[PROD], IA[PROD], MP[PROD] and FPE[PROD].
CONSTRUCT N MINIMUM MAXIMUM MEAN STD. DEVIATION
APM[PROD] 99 10,00 270,00 124,8081 59,50385
IA[PROD] 100 384,00 823543,00 176893,4700 196709,70739
MP[PROD] 95 2,00 1764,00 411,3368 403,03032
FPE[PROD] 100 18,00 343,00 147,5400 77,39097
Table 12: Descriptive Statistics of the Product Variables
CONSTRUCT SKEWNESS KURTOSIS
Statistic Std. Deviation Statistic Std. Deviation
APM[PROD] ,401 ,243 ,084 ,481
IA[PROD] 1,879 ,241 3,404 ,478
MP[PROD] 1,158 ,247 ,611 ,490
FPE[PROD] ,321 ,241 -,285 ,478
Table 13: Skewness & Kurtosis
IV. R
ESULTS
12 propose direct relationships between factors and as such have been tested using a linear regression method. In contrast, H2b and H3b propose a moderating relationship and have been analyzed using a technique developed by Hayes (2013). This technique will be elaborated upon further later in this section. B Std. Error Beta t P APM – FPE ,315 ,115 ,268 2,741 ,007 Table 14: Results H1 B Std. Error Beta t P IA – FPE ,189 ,114 ,165 1,655 ,101 MP – FPE ,382 ,115 ,327 3,331 ,001
Table 15: Results H2a & H3a
As becomes clear from table 14, there is a significant relationship between accuracy of performance measurement and fairness of performance evaluation (p<0,01). Additionally, both the B and Beta indicate that this relation is positive. In turn we can state that H1 is accepted. Looking at table 15 we can see that there is a significant relation between managerial power and FPE at the p<0,01 level. However, this is not the case for the relation between information asymmetry and FPE. Nevertheless, it should be noted that in a random sample of 100 this result still shows a strong relation between the two constructs. In both instances the B and Beta yielded positive returns, meaning that there is an increase in the relationship. This means that H2a, predicting that more IA would decrease perceived FPE, is rejected whereas H3a, more MP will result in more perceived FPE, is accepted.
I have mentioned before that H2b and H3b (the relationship between APM and FPE with the moderators AI and MP respectively) will be measured using an alternative method of moderator testing. This method, developed by Hayes (2012; 2013) is argued to be more efficient by the author. In contrast to traditional moderator testing, there are no in between steps and all necessary data is computed at once. This reduces the chance of calculation errors from the researcher. The first step in interpreting the output requires a closer look at whether the moderator accounts significantly more for variance than the model without moderation (i.e. the direct relation). This is done by looking the change in the R2 and see if this is significant, doing so will determine whether there is reason to believe
that a moderating relation exists. The second step is to look at the significance of the proposed moderator model. The third and last step is to plot the interaction in order to see in which direction the moderator is moving the relation between the dependent and independent variable.
13 additional variance explained by the proposed interaction term. The next step in this process is to analyze the model as a whole using model 1 of Hayes’ (2013) technique combined with a 1000 sample bootstrap.
R2 CHANGE F DF1 DF2 P
INTERACTION ,0072 ,7569 1,0000 95,0000 ,3865 Table 16: Explained variance of interaction term IA
Table 17 shows the initial results of the analysis and shows us that the moderating model itself is significant (p<0,05). However, these numbers do not indicate in which direction the moderator operates. In order to see the effect of the moderator on the underlying relation an interaction plot has to be made. This plot is depicted as figure 1 below.
R R2 F df1 df2 P
APM – FPE, IA
,33189 ,1017 3,5841 3,0000 95,0000 ,0166 *Results are significant at the P<0,05 level
Table 17: Significance of the Proposed Moderator IA
Figure 1: Interaction Plot for Proposed Moderator IA
The interaction plot can be interpreted as follows. The mean values are what their name already suggests. The low and high values represent the value of one standard deviation below or above the mean respectively. Analyzing the plot yields the following insight; as information asymmetry increases, so do FPE and APM resulting in a rejection of H2b. It was proposed that IA would weaken the relationship and currently it does the opposite.
100 110 120 130 140 150 160 170 180
Low APM Mean APM High APM
FPE
Interaction Plot Information Asymmetry
14 The previous steps can now be repeated for hypothesis 3b; the moderating effect of managerial power. In table 18 it becomes clear that the variable managerial power almost significantly accounts for more variance. There is reason to believe there is a moderating effect occurring as the r squared change is positive signifying an increase in explained variance due to the introduced interaction term.
R2 CHANGE F DF1 DF2 P
INTERACTION ,0254 2,8003 1,0000 90,0000 ,0977 Table 18:H2b Model Summary
R R2 F df1 df2 P
APM ,44536 ,2057 8,2158 3,0000 90,0000 ,0001 *Results are significant at the P<0,05 level
Table 19: Significance of the Proposed Moderator MP
From table 19 it can be seen that the proposed moderation model of H3b is significant. Nevertheless, we still have to check whether the moderator moves in the right direction. This movement can be seen in figure 2, which shows that with an increase in managerial power there is also an increase in FPE and APM. Therefore, H3b is accepted as it predicted an increase in the relation between APM and FPE.
Figure 2: Interaction Plot for Proposed Moderator MP
V. D
ISCUSSION
Conclusion & Implications
The goal of this research was to investigate several relations, namely the effect of accurate performance measures on perceived fairness of performance evaluations, the role of information asymmetry on perceived FPE, the role of managerial power on FPE and the influences IA and MP exert on the relation between APM and FPE. The methodology section of this paper has shown mixed results in that regard. 80 90 100 110 120 130 140 150 160 170 180
Low APM Mean APM High APM
FPE
Interaction Plot Managerial Power
15 Based on the results from my analyses, the positive relation between APM and FPE proved to be significant. Similarly, the direct, and positive, relation between MP and FPE also showed significant results. In contrast, information asymmetry was hypothesized to decrease the amount of perceived fairness yet it showed an opposite effect. Additionally, when looking at the analysis regarded the proposed moderating effects of IA and MP similar results were found. IA was predicted to have a negative impact on the relation between APM and FPE while in reality the results showed the relation was strengthened by the introduction of the moderator. Managerial power, on the other hand, did increase the relation between APM and FPE as predicted.
One implication of these findings could be the fact that, since managers with sufficient power can indeed influence both the accuracy of performance measurement and their own performance evaluation, stricter use of incentive contracts may be required.
Limitations & Suggestions for Future Research
Several limitations can be discovered when we look at this research. The most important ones in my view will be addressed in this section followed by suggestions for future research.
The first limitation that becomes apparent is the geographical setting of the study. Hofstede (1980) and later Grey (1988) have demonstrated that national culture can be of influence in both accounting systems and other company related aspects. According to the research conducted by Hofstede, The Netherlands shows high individualism, low power distance and low masculinity. This could indicate that there is, for example, less desire for power overall.
Secondly, a measurement limitation could be identified especially in the construct of fairness of performance evaluation. More so than with the other construct, few of the intended questions properly loaded into the factor analysis. This gives cause to believe that there might be a better way to measure this construct.
Thirdly, none of the questions chosen from the original survey enquired about the type of performance measurement used. While the respondent was asked whether the performance measurement system accurately matches the goals of either the BU or the organization, details were neither asked nor given in respect to the type (financial or nonfinancial) of measures.
16 turn could cause cooperation failure. Consistency is mainly an issue since the interviews were not conducted by the same person in every instance. The physical presence bias may be explained by the perceived social distance between the interviewer and the interviewee.
Lastly, this paper assumed and operated on the premise that the agent behaves out of self-interest and does not behave as the principle would like. However, it has been suggested that there could be instances of little to no goal conflict (Demski, 1980). This could be the case in a highly socialized or clan-oriented firm (Ouchi, 1979). When goal conflict is no longer an issue, an agent is assumed to behave exactly as he or she is intended by the superior (Eisenhardt, 1989).
Based on these limitations several suggestions for future research can be derived. First of all, the study could be replicated in countries with opposing cultures to the one examined in this research. It is likely that varying cultural factors will influence the way managers behave.
17
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VII. A
PPENDIX
A:
I
NTERVIEW
Q
UESTIONS
1. Source: Van Elten, 2012
a. To what extent does your performance influence your performance evaluation? b. To what extent does your performance influence the size of your bonus?
c. To what extent does your performance influence your long-term career path?
1 to no extent – 5 very great extent
2. Source: Van Elten, 2012
a. “A significant part of the comparison with reference groups is formalized, and captured in rules.”
b. “When my superior compares me (or my business unit) to a reference group, subjectivity plays a considerable role.”
1 disagree strongly – 5 agree strongly
3. Source: Abernathy et al. 2004
a. Strategic decisions (e.g.: development of new products; enter and develop new markets; your business unit’s strategy)
b. Investment decisions (e.g.: acquiring new plants, property and equipment, development of new information systems)
c. Marketing decisions (e.g.: campaigns, pricing decisions)
d. Decisions regarding your internal processes (e.g.: setting production/sales priorities, resource allocation)
e. Human resource decisions (e.g.: hiring and firing; compensation and setting career paths for the personnel employed within your business unit; reorganizing your business unit; creation of new jobs)
1 my superior has all authority – 7 my business unit has all authority
4. Source: Van Elten, 2012
a. “If I would really want to, I would be able to hide bad performance, so my superior would think that my business unit has performed well”
b. “Probably, my superior would not notice if I’d ‘take it easy’”
c. “If I would really want to, I could window dress my business unit’s figures, and make my business unit’s performance look better than what would be realistic”
1 disagree strongly – 7 agree strongly
5. Source: Farh, Early & Lin, 1996
a. “My superior is familiar with my job performance”
b. “My superior allows me to tell my side of the story in performance evaluation” c. “My superior motivates the outcomes of my performance evaluation”
d. “My superior motivates his/her decisions regarding my pay raise and bonus”
e. “My superior reviews my performance with me and discusses plans or objectives to improve my performance”
f. “When my superior evaluates my performance, subjectivity plays a considerable role"
1 disagree strongly – 7 agree strongly
6. Source: Hartmann, 1997
a. “The evaluation I receive is based on factors over which I have control”
b. “It frequently happens that my superior holds me accountable for certain (negative) results that I cannot help”
c. “When evaluating my functioning my superior emphasizes aspects of my work which I think are irrelevant”
d. “The evaluation I receive is based on a complete picture of my true performance” e. “In general I think that my functioning is evaluated in an honest and fair way” f. “I am satisfied with the way in which I am evaluated”
22 7. Source: Dunk, 1993 & Kruis, 2008
a. Who is in possession of better information regarding the activities undertaken in your business unit?
b. Who is more familiar with the input/output relationships (the transformation process) inherent in the internal operations of your business unit?
c. Who is more certain of the performance potential of your business unit? d. Who is more familiar technically with the work of your business unit?
e. Who is better able to assess the potential impact on your activities of factors internal to your business unit?
f. Who is better able to assess the potential impact on your activities of factors external to your business unit?
g. Who has a better understanding of what your business unit has achieved?
1 your superior – 7 you
8. Source: Van Elten, 2012
To what extent do the performance measures match the goals which your business unit has to realize?
1 to (almost) no extent – 5 very great extent
9. Source: Kruis, 2008
Can the outputs of the business unit be measured objectively and expressed in a number?
1 not at all – 5 very much
10. Source: Kalleberg et al., 1996 (c) & Spekle & Verbeeten, 2008 (a, b)
a. “The total set of performance measures indicates which results my business unit should realize”
b. “The total set of performance measures is unambiguously linked to the goals of my organization”
c. “My business unit performance is substantially influenced by factors beyond my (or my subordinates’) control”
