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3.2. DEVELOPMENT OF THE MODEL 63 3.2.1 Research Hypothesis: RPE use and Noise in the Performance Evaluation The research hypothesis concerns the negative effect of RPE use on the level of noise in the performance evaluation. As discussed in the introductory section of this chapter, RPE use reduces the amount of noise in the performance evaluation. Noise decreases the informativeness of the performance metrics with regard to the agent’s effort level. Because of noise, the measured performance of the business unit manager is not only the result of his effort but also the result of other factors that lie beyond the manager’s control. However, according to RPE theory, noise in the performance evaluation can be reduced by using information about the performance of the manager’s peers. To at least some degree, the agent’s peers are exposed to the same factors that affect the agent’s performance. These ‘common factors’ can for example negatively influence the performance of the agent and his peers in the same period. RPE filters out the noise caused by common factors by comparing the measured performance of the evaluated manager with the performance of the peer group. RPE does not adjust the score on the performance measure itself, but provides information about peer performance that aids the interpretation of the score on the performance measure. In other words, with RPE, the measured performance itself remains noisy, but the performance evaluation is insulated from this noise. Because of this insulation, the performance evaluation provides a more accurate description of the evaluated manager’s effort level. This increased accuracy reduces the risk of the manager not being rewarded for his effort and reduces inefficient risk-sharing between the organization and the manager. The noise-reducing effect of RPE is formalized as follows: H1: RPE use has a negative influence on the amount of noise in the performance evaluation. 3.2.2 Noise-Inducing and Noise-Reducing Factors In addition to the hypothesis of theoretical interest presented above, the model contains additional expectations that address the measurement characteristics of the model’s dependent variable, as explained in the introduction of this section. The additional expectations consist of noise-inducing and noise-reducing factors that constitute the noise that would exist in the performance evaluation, if RPE did not reduce this noise. In the current section, I argue that noise in the performance evaluation is affected by environmental uncertainty, goal ambiguity, measurability of outputs, emphasis on personal-level measures, and emphasis on disaggregated performance measures. The effect of the first of these noise-drivers (environmental uncertainty) is partially mitigated by RPE use. Before discussing the other factors, I first discuss the effects of environmental uncertainty on RPE use and on noise.
64 CHAPTER 3. NOISE REDUCTION EFFECTIVENESS Environmental Uncertainty Environmental uncertainty has two effects in my model. Environmental uncertainty induces noise in the performance evaluation and drives the use of RPE to mitigate its noise-inducing effect. Environmental uncertainty 1 is the primary driver of noise in this study. In the discussion of the research hypothesis, I argue that noise is due to factors that lie beyond the manager’s control. Environmental uncertainty refers to the prevalence of uncertain events that originate from outside the business unit. Almost by definition, these events lie outside the manager’s control 2 . These external events affect the manager’s performance metrics and thereby introduce noise into the performance evaluation. In the previous section, I argued that RPE can reduce noise by partially filtering out these external events. This reduction increases the attractiveness of RPE use in a situation characterised by high environmental uncertainty. If the amount of environmental uncertainty increases, the performance evaluation increasingly benefits from the deployment of RPE. This finding implies that environmental uncertainty drives the use of RPE. This expectation is formalized as follows: environmental uncertainty has a positive effect on RPE use. Although I argue that RPE can reduce the noise-driving effect of environmental uncertainty, this argument only applies to a specific type of environmental uncertainty: environmental uncertainty that is shared with one’s peers. Only shared (or common) environmental uncertainty can be filtered out by comparing the performance with the performance of peers. Other idiosyncratic environmental uncertainties do not affect peer performance and cannot be filtered out from the performance evaluation by using RPE. In summary: although RPE partially filters out the effects of environmental uncertainty from the performance evaluation, a remaining idiosyncratic part of environmental uncertainty can still induce noise. This expectation is explicated as follows: environmental uncertainty has a positive effect on noise in the performance evaluation. Figure 3.1 summarizes the relations among RPE use, environmental uncertainty, and noise in the performance evaluation. 1 Whereas the previous chapter assesses how common uncertainty increases RPE use, the current chapter relies on a broader uncertainty measure that includes both common and idiosyncratic uncertainty. This broader measure is used to improve the noise estimation in the model as both common and idiosyncratic uncertainty induce noise in the performance evaluation. The noise-increasing effect is not limited to common uncertainty per se, although the noise-reducing effect of RPE is. 2 It is possible that a business unit manager can influence his environmental uncertainty to some extent by altering his environment. For example, the manager may be able to choose to operate in a low-risk market, whilst avoiding operating in a more volatile, high-risk market. However, if the manager is part of a larger organization with an overarching company strategy, his influence may be limited. Therefore, this study assumes that the environment (and its uncertainty) is given for the business unit manager.
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Relative Performance Evaluation in
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NYENRODE BUSINESS UNIVERSITEIT Rela
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Table of Contents Preface 1 General
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Preface Why do people make things h
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2 CHAPTER 1. GENERAL INTRODUCTION I
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4 CHAPTER 1. GENERAL INTRODUCTION o
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6 CHAPTER 1. GENERAL INTRODUCTION T
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10 CHAPTER 1. GENERAL INTRODUCTION
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Page 42 and 43: 2.3. SAMPLE AND MEASUREMENT 33 this
Page 44 and 45: 2.3. SAMPLE AND MEASUREMENT 35 Emph
Page 46 and 47: 2.4. ANALYSES 37 2.4 Analyses This
Page 48 and 49: 2.4. ANALYSES 39 Table 2.8: RPE use
Page 50 and 51: 2.4. ANALYSES 41 2.4.2 Correlations
Page 52 and 53: 2.4. ANALYSES 43 Concerning the con
Page 54 and 55: 2.4. ANALYSES 45 Table 2.13: Result
Page 56 and 57: 2.4. ANALYSES 47 Table 2.15: Summar
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Page 70 and 71: 3.1. INTRODUCTION 61 Holmstrom’s
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4.5. CONCLUSIONS AND DISCUSSION 113
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4.5. CONCLUSIONS AND DISCUSSION 115
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Chapter 5 Conclusion 5.1 Summary, C
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5.1. SUMMARY, CONCLUSIONS AND DISCU
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5.2. IMPLICATIONS FOR PRACTICE 125
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5.3. LIMITATIONS AND SUGGESTIONS FO
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Appendix Overview of Questionnaire
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Q5 How often do the following thing
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Q14 When serving your clients, how
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Q23 Please indicate whether you agr
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Noise Q34 NOISE (primary measure) P
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References 1. Abernethy, M.A., Bouw
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26. Diamantopoulos, A. & Siguaw, J.
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52. Himmelberg, C.P. & Hubbard R.G.
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83. Towry, K. 2003. ‘Control in a
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148 beïnvloeden, veroorzaken ruis
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Biography Hilco van Elten (1979) ho
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