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4.3. SAMPLE AND MEASUREMENT 95 4.3 Sample and Measurement The current section contains parts that are largely similar to parts of chapters 2 and 3. This section is similar because it uses the same survey instrument and, in part, the same measures. Subsections 4.3.1 and 4.3.2 and parts of subsection 4.3.3 are marked with an asterisk to indicate this repetition. The reader may wish to skip these parts. RPE use Information Asymmetry - Goal Ambiguity - Measurability of Outputs - Decentralization 4.3.1 Sample(*) ✻ Positive Figure 4.2: Causal Model Negative (H1) Positive Room for Managerial Opportunism This study uses primary data collected from 325 business units with an extensive survey instrument. The questionnaire was filled out by business unit managers contacted through students’ professional networks. This approach has several benefits. The first is respondent identification. The students were instructed to identify managers who are responsible for an autonomous organizational body engaged in multiple activities (e.g., purchasing, production, and sales). Furthermore, the respondent should have a superior within the organization (in other words, the respondent should not be the CEO). The second benefit is the possibility to conduct face-to-face interviews, which improves the respondent’s valid interpretation of and careful responding to the questions. During these interviews, the student can explain the survey questions (using a strict protocol provided by the researcher) ✻ ❄ ✻
96 CHAPTER 4. OPPORTUNISM MITIGATION EFFECTIVENESS to the business unit manager who answers the questions in the survey and fills out the questionnaire. The observations include data from production business units (17%), service BUs (56%), financial services (16%), and BUs operating in the not-for-profit sector (18%) 5 . Similarly diverse responses to the variance of sectors at the BU level were provided on the question about the respondents firm’s sector. Table 4.1 summarizes the background information on the respondents’ business units and the firm to which each business unit belongs. BU size Firm size Table 4.1: Summary Statistics on Sample Panel A - size N Mean Std. dev. of mean Min. Max. FTE 325 220 439 10 5.000 Revenue (mio EURO) 292 196 840 1 1.000 FTE 321 14.730 41.771 31 470.123 Revenue (mio EURO) 301 7.775 43.240 4 600.000 Panel B - sector BU sector Production 54 Firm sector Production 71 Services 181 Services 170 Financial 52 Financial 62 Not-for-profit 57 Not-for-profit 64 4.3.2 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 6 . 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. 5 These percentages sum to 107% because some business units operate in more than one sector. Multiple answers to the related question are considered valid. 6 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 mailed surveys instead of face-to-face survey interviews.
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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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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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2.2. THEORETICAL BACKGROUND 19 Sinc
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2.2. THEORETICAL BACKGROUND 23 suff
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2.3. SAMPLE AND MEASUREMENT 25 2.2.
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2.3. SAMPLE AND MEASUREMENT 27 2.3.
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2.3. SAMPLE AND MEASUREMENT 33 this
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2.3. SAMPLE AND MEASUREMENT 35 Emph
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2.4. ANALYSES 37 2.4 Analyses This
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2.4. ANALYSES 39 Table 2.8: RPE use
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2.4. ANALYSES 41 2.4.2 Correlations
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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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Page 74 and 75: 3.2. DEVELOPMENT OF THE MODEL 65 RP
Page 76 and 77: 3.3. SAMPLE AND MEASUREMENT 67 3.3
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Page 80 and 81: 3.3. SAMPLE AND MEASUREMENT 71 Tabl
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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 110 and 111: 4.3. SAMPLE AND MEASUREMENT 101 Tab
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Page 120 and 121: 4.4. ANALYSES 111 room for manageri
Page 126 and 127: Chapter 5 Conclusion 5.1 Summary, C
Page 128 and 129: 5.1. SUMMARY, CONCLUSIONS AND DISCU
Page 134 and 135: 5.2. IMPLICATIONS FOR PRACTICE 125
Page 136 and 137: 5.3. LIMITATIONS AND SUGGESTIONS FO
Page 138 and 139: Appendix Overview of Questionnaire
Page 140 and 141: Q5 How often do the following thing
Page 142 and 143: Q14 When serving your clients, how
Page 144 and 145: Q23 Please indicate whether you agr
Page 146 and 147: Noise Q34 NOISE (primary measure) P
Page 148 and 149: References 1. Abernethy, M.A., Bouw
Page 150 and 151: 26. Diamantopoulos, A. & Siguaw, J.
Page 152 and 153: 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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