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5.3. LIMITATIONS AND SUGGESTIONS FOR FURTHER RESEARCH 127 5.3.2 Causality The second limitation arises from the fact that I use cross-sectional data for my analyses, which measure the independent and dependent variables at one point in time. Although this type of quantitative research has several benefits (e.g., relatively large-scale datasets, which increases the generalizability of the results), the method has drawbacks as well. With this method, I cannot fully test the causal character of the relations. A common trap in interpreting statistical results is to claim causation when the empirical methodology supports correlation (Echambadi et al. 2006:1811). I stress here that I theorize causation but primarily test associations. Research methods that incorporate longitudinal data (e.g., longitudinal case studies) are better equipped to determine causality. Nonetheless, I take steps to detect potential problems with causality. In chapters 3 and 4, I test for the endogeneity of the independent variables. Endogeneity occurs if the independent variable included in the model is correlated with the error terms of the estimated model. Sources of endogeneity include reverse causality, simultaneous causality, and omitted variables. Ignoring endogeneity may lead to biased and inconsistent estimates (Echambadi et al. 2006:1805). Hausman test results indicate that endogeneity is not a major concern in my models and that the results from my analyses are not biased by endogeneity. However, the endogeneity analysis cannot positively rule out reverse causality. Future research may wish to rely on panel data or design experiments to fully rule out reverse causality (Echambadi et al. 2006:1805). 5.3.3 Measurement The final limitation that I discuss here refers to the measurement of my variables. This thesis relies on an extensive questionnaire. I invested considerable time and effort into the survey instrument. For example, I conducted several rounds of pretesting among the potential respondents. Doing so certainly improved the quality of the data that were obtained for this study. However, with the benefit of hindsight, several measures leave room for improvement. Most importantly, the RPE proxies that are used in this study can be improved. I use two different RPE measures that have specific strengths and weaknesses. Looking back, I should have developed an overall measure to function as a safety net under the measures that investigate specific manifestations of RPE. If I had developed this overall RPE measure, I would have invested in the other specific RPE measures such that they would show less overlap with each other and only overlap with the overall measure. In addition to the RPE measures, other measures can be improved as well. For example, the measure for noise in the performance evaluation (i.e., the dependent variable in chapter 3) is less than perfect. I established the noise measure by using a single-item construct.
128 CHAPTER 5. CONCLUSION Despite efforts to buttress the validity of the construct, the noise measure would have benefited from a broader operationalization. Another important limitation in the measurement arises from the fact that my study cannot adequately distinguish between the extent to which peer comparison relies on internal versus external peer groups. The questionnaire provides some information on whether RPE adopters use internal peers, external peers, or both. However, these data are not sufficiently refined to allow for more sophisticated analyses of the opportunism-mitigating explanation of RPE use. Despite these limitations, I believe that the models and the findings of this study contribute to our understanding of RPE. Citing the original research proposal for my PhD project: “This study sets out to build on and extend the literature on RPE. Its aim is to document and explain the use of RPE in performance evaluation and compensation plan design at the business unit management level, adding to our understanding of the incentive structure within the firm as one of the key components of the Management Control System.” Whether I succeeded in this task, I leave to the reader to answer.
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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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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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2.2. THEORETICAL BACKGROUND 19 Sinc
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2.2. THEORETICAL BACKGROUND 21 who
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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 29 can
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2.3. SAMPLE AND MEASUREMENT 31 Comp
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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
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2.4. ANALYSES 45 Table 2.13: Result
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2.4. ANALYSES 47 Table 2.15: Summar
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2.5. CONCLUSIONS AND DISCUSSION 49
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2.5. CONCLUSIONS AND DISCUSSION 51
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2.6. CONTRACTIBILITY MIMIC MODEL (A
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2.6. CONTRACTIBILITY MIMIC MODEL (A
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2.7. ANALYSES FOR FOR-PROFIT BUS (A
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Chapter 3 Does Relative Performance
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3.1. INTRODUCTION 61 Holmstrom’s
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3.2. DEVELOPMENT OF THE MODEL 63 3.
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3.2. DEVELOPMENT OF THE MODEL 65 RP
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3.3. SAMPLE AND MEASUREMENT 67 3.3
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3.3. SAMPLE AND MEASUREMENT 71 Tabl
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3.3. SAMPLE AND MEASUREMENT 73 Tabl
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3.4. ANALYSES 75 3.4 Analyses This
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Page 92 and 93: 3.4. ANALYSES 83 Larcker & Rusticus
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Page 138 and 139: Appendix Overview of Questionnaire
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Page 148 and 149: References 1. Abernethy, M.A., Bouw
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Page 154: 83. Towry, K. 2003. ‘Control in a
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Page 160 and 161: Biography Hilco van Elten (1979) ho
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