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3.3. SAMPLE AND MEASUREMENT 69 3.3.3 Measurement This section describes the measurement of the variables used for this study. I discuss the variables related to the research hypothesis (i.e., noise in the performance evaluation, and RPE-Use), as well as the noise drivers (i.e., environmental uncertainty, goal ambiguity, measurability of outputs, emphasis on personal-level measures, and emphasis on disaggregated measures). Additionally, this section motivates and describes the control variables for size and sector. When references are made to the questionnaire items, please see the appendix at the end of the thesis for the exact phrasing, response categories, and, if applicable, sources. Noise in the Performance Evaluation The dependent variable noise in the performance evaluation is based on a single question that asks the respondent to indicate the extent to which the performance evaluation that he receives is based on factors over which he has control (Q34). Throughout this chapter, this proxy is referred to as ‘NOISE’. NOISE is measured by taking the reverse of the respondents’ answers. In other words, NOISE measures the extent to which the performance evaluation is influenced by factors that lie beyond the business unit manager’s control. I acknowledge that relying on a single indicator construct is less than ideal, especially when measuring the dependent variable in the model. Therefore, I seek additional validation for NOISE. The questionnaire provides additional items that support this metric. Specifically, the questionnaire provides two items that are associated with the variable of interest, though they do not measure noise in the performance evaluation per se. For one, I asked the respondents to indicate the extent to which the business unit’s performance is substantially influenced by factors beyond his control (labelled: exogenous-performance-effects, Q35). Similar to NOISE, this question refers to the impact of exogenous factors. However, this time on the difficulty of the business unit performance instead of on the performance evaluation. Several reasons exist why NOISE and exogenous-performance-effects are not perfectly correlated. Firstly, the performance evaluation can be informed by things other than the business unit’s performance (e.g., contributions to firm performance, or personal development of skills). If so, the exogenous events that impact the business unit’s performance, impact the performance evaluation only to a certain degree. Second, the performance evaluation can be insulated from exogenous events that influence business unit’s performance through, for example, RPE. As argued before, RPE filters noise out of the performance evaluation. However, RPE does not remove the impact of exogenous events on the BU performance itself. Therefore, I expect NOISE and exogenous-performance-effects to correlate positively with one another, though not to a great extent. The second questionnaire item to validate NOISE captures more broadly and informally whether the respondent is held accountable for uncontrollable factors, instead of whether
70 CHAPTER 3. NOISE REDUCTION EFFECTIVENESS such factors specifically affect his (formal) performance evaluation. This item is labelled held-accountable (Q36). Specifically, held-accountable asks whether the respondent is frequently held accountable for certain (negative) results beyond his control. Because of its phrasing, this item focuses on the negative impact of external factors, whereas the primary measure NOISE measures both positive and negative noise. Although these two additional questionnaire items (exogenous-performance-effects and held-accountable) do not proxy noise in the performance evaluation per se, they can inform us about the quality of the NOISE measure. The correlations between NOISE and the two associated items are positive and significant (p < 0.01), but not high, as shown in table 3.2. The convergent validity of the NOISE measure is also analysed through a factor analysis of the three measures. Although the scale reliability does not suggest constructing a multi-item scale to proxy for noise in the performance evaluation (Cronbach’s alpha < 0.6), factor analysis shows that the three measures can be combined into one measure by yielding a one-component solution (component loadings > 0.5). Both the correlations and factor analysis provide validation for the NOISE measure. Table 3.2: Correlations between Noise-Measures 1. 2. 1. NOISE 2. Exogenous-Performance-Effects .154*** 3. Held-Accountable .334*** .165*** *** Correlation is significant at the 0.01 level (2-tailed). Listwise N=325 RPE use The RPE use measure (labelled ‘RPE-Use’) asks about the extent to which peer performance functions as a point of reference for evaluating the quality of the agent’s performance (Q1). The underlying questionnaire items focus on the ex-post nature of performance evaluation. This measure comprises both explicit coupling of the performance target to peer performance and more implicit applications of RPE. Implicit applications of RPE do not require that peer performance affects the performance target explicitly, but they can, for example, play a role in establishing an implicit performance standard or norm for the performance evaluation. This measure asks to what extent the respondent perceives that the performance of his peers is a point of reference for his superior when evaluating the respondent’s performance. Additionally, the question differentiates between situations where the evaluated business unit performs substantially better versus substantially worse than its peers. This dinstinction controls for potential asymmetries in peer comparison. Throughout the sample, the asymmetries do not seem to be of great influence; the three settings (neutral/better/worse) lead to an internally consistent scale, as presented in table 3.3.
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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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8 CHAPTER 1. GENERAL INTRODUCTION F
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10 CHAPTER 1. GENERAL INTRODUCTION
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Chapter 2 The Use of Relative Perfo
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2.1. INTRODUCTION 15 is not a promi
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2.2. THEORETICAL BACKGROUND 17 The
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Page 40 and 41: 2.3. SAMPLE AND MEASUREMENT 31 Comp
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 68 and 69: Chapter 3 Does Relative Performance
Page 70 and 71: 3.1. INTRODUCTION 61 Holmstrom’s
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Page 86 and 87: 3.4. ANALYSES 77 Table 3.9: Pearson
Page 92 and 93: 3.4. ANALYSES 83 Larcker & Rusticus
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Page 112 and 113: 4.4. ANALYSES 103 Table 4.8: Items
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Page 118 and 119: 4.4. ANALYSES 109 RPE and RFMO. Mor
Page 120 and 121: 4.4. ANALYSES 111 room for manageri
Page 126 and 127: 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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