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2.3. SAMPLE AND MEASUREMENT 27 2.3.2 The Questionnaire The survey instrument was specifically designed for this research, following the Tailored Design Method (Dillman 2000), where applicable to the specific research setting 11 . The survey instrument relies heavily on previously used and validated questions. Some of those measures are well established (e.g., the measure for information asymmetry is largely based on Dunk (1993)). Other questions were specifically constructed for this survey. For example, the measures for the dependent variable that measures the use of RPE are purposedeveloped. To increase the reliability of the instrument, the survey instrument was thoroughly pretested using Hak’s Three-Step Test Interview method (abbreviated: TSTI) (Hak et al. 2008). This method is an observational instrument for pretesting self-completion questionnaires 12 . TSTI works through observing actual instances of interaction between respondents and the instrument. Because this process mainly consists of cognitive processing and is therefore hidden from the observer, ‘thinking aloud’ is used as a technique for making the thought process observable (Hak et al. 2008). Through this process, TSTI helps to identify problems in questionnaires, often leading to modification of the instrument. Three rounds of pre-tests with twelve managers 13 ensured a thorough and correct understanding of the questions and response categories. 2.3.3 Measurement This section describes the measurement of the variables used for this study. Where references are made to questionnaire items, please see the appendix at the end of the thesis for the exact phrasing, response categories, and sources (where applicable). 11 The Tailored Design Method is specifically designed for mail and internet surveys. Many of the guidelines provided by Dillman (2000) are applicable to the survey design, but others specifically apply to mail surveys instead of face-to-face survey interviews. 12 Although the survey was not a self-completion questionnaire in the sense that the respondents did not fill out the survey by themselves, but together with the interviewing student, I still value the contribution of TSTI. Filling out the survey was outside of the direct sphere of influence of the researcher, but was carried out by -carefully briefed- students. 13 The pre-test participants’ organizations show great diversity, ranging from production to consulting, educational and financial services, and from very large to smaller business units, including both for-profit and not-for-profit organizations.
28 CHAPTER 2. RPE AT THE BUSINESS UNIT MANAGER LEVEL 2.3.3.1 Dependent Variable: the Use of RPE RPE use is measured in two different ways to capture different applications of RPE. The first measure (labelled ‘RPE-Use’) is broad and unspecific. RPE-Use measures the extent to which peer performance functions as a point of reference for evaluating the quality of the agent’s performance. 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 distinction controls for potential asymmetries in peer comparison, as suggested by Garvey & Milbourn (2006). Throughout the sample, asymmetries do not seem to be of great influence; the three settings (neutral/better/worse) lead to a highly internally consistent scale, as presented in table 2.2 14 . Table 2.2: Items for RPE-Use (Q1) Item description Component loadings a. Peer performance point of reference 0.868 b. Substantially better 0.923 c. Substantially worse 0.902 Percentage variance explained 80.6% Cronbach’s alpha 0.879 The second proxy for RPE measures specifically the explicit use of RPE for target-setting purposes; i.e., how peer performance influences the difficulty of the performance standards against which the manager’s performance is evaluated. This measure is labelled ‘RPEbased-Targets’. I measure RPE-based-Targets as the impact of peer performance on the performance target. I ask to what extent peer performance influences the difficulty of the target and/or budget for a variety of performance measures (Q2). To interpret the impact of peers on the evaluation as a whole, the various performance metrics are weighted (Q3). I weigh the impact of peers on each of the metrics, by multiplying the scores by their individual importance for the performance evaluation. RPE-based-Targets does not measure solely ex-post peer comparison. The influence of peer performance on the agent’s target 14 The presented component loadings result from principal component analysis.
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Page 6 and 7: Table of Contents Preface 1 General
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3.4. ANALYSES 77 Table 3.9: Pearson
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3.4. ANALYSES 79 Table 3.10: Result
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3.4. ANALYSES 81 Table 3.11: Result
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3.4. ANALYSES 83 Larcker & Rusticus
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3.5. CONCLUSIONS AND DISCUSSION 85
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Chapter 4 Does Relative Performance
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4.1. INTRODUCTION 89 Moreover, chap
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4.3. SAMPLE AND MEASUREMENT 95 4.3
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4.3. SAMPLE AND MEASUREMENT 97 To i
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4.3. SAMPLE AND MEASUREMENT 101 Tab
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4.4. ANALYSES 103 Table 4.8: Items
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4.4. ANALYSES 105 RPE use ✻ Posit
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4.4. ANALYSES 107 The model does sh
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4.4. ANALYSES 109 RPE and RFMO. Mor
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4.4. ANALYSES 111 room for manageri
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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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