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2.4. ANALYSES 43 Concerning the control variables, I find a negative and significant influence of the unhypothesized main effect of comparability and the use of firm-level measures on RPE use. This former finding is counterintuitive. Although this study does not formulate explicit expectations concerning the direct effect of comparability on RPE use, it is plausible that a potential significant relation is positive. This is because comparability is a necessary condition for peer comparisons. Bivariately, the two variables are not significantly correlated (r = -0.08, p = 0.19). Furthermore, the results show a positive significant effect of contractibility. Other control variables (business unit and firm size and the sector dummies) do not yield significant results. Neither does the information asymmetry variable, which was included to rule out the possibility that the significant coefficient of the interaction effect between information asymmetry and uniqueness is caused by a lower-order effect (i.e., a main effect of comparability on RPE-Use) (conform: Hartmann & Moers 1999, Echambadi et al. 2006). However, the data are censored. A group of 21 respondents does not use RPE. To better suit the left-censoring characteristic of the dependent variable RPE-Use, I estimate a Tobit model, which is a regression technique especially suited to analysing limited (censored) dependent variables. The Tobit model yields results similar to those of the OLS analysis. This model supports the hypotheses regarding the effects of common uncertainty (H1) and the interaction effect between information asymmetry and comparability (H2). To facilitate the comparison with the results of the OLS model, I report the McKelvey-Zavoina statistic. This statistic is a pseudo-R 2 measure that comes closest to the familiar R 2 from the OLS regression (Veall & Zimmermann 1994). According to the McKelvey-Zavoina statistic, the Tobit analysis explains 7.9% of the variance in RPE-Use. The results of the Tobit analysis are qualitatively similar to those of the OLS analysis, as is shown in table 2.12. 2.4.3.2 Analyses with RPE-based-Targets Measure I also test the model with the RPE-based-Targets measure. RPE-based-Targets relates to the explicit impact of peer performance on the performance target difficulty. This model yields better test-statistics. As presented in table 2.13, I find a significant model that fits the data. The ANOVA F-statistic is higher than the RPE-Use model (p < 0.01), and the reported R 2 is higher at 12.2%. The qualitative results differ partially from those of the analyses with explicit RPE use. Similar to the previous model, I find a significant positive effect of common uncertainty (hypothesis H1), but the hypothesized interaction of information asymmetry and comparability (hypothesis H2) does not hold in this model. Instead, this model supports the interaction between common uncertainty and information asymmetry (hypothesis H3). The results are shown in table 2.13.
44 CHAPTER 2. RPE AT THE BUSINESS UNIT MANAGER LEVEL Table 2.12: Results of Tobit Regression Analysis (RPE-Use) Coefficient Std. Error t-Stat. Prob. Constant 3.315 0.634 5.226 0.00 Common uncertainty (H1) 0.373 0.283 1.316 0.09a Interaction information asymmetry * comparability (H2) 0.134 0.102 1.306 0.10a Interaction uncertainty * information -0.130 0.116 -1.116 0.13a asymmetry (H3) Information asymmetry 0.080 0.075 1.072 0.28 Comparability -1.835 1.010 -1.818 0.07 Contractibility 0.049 0.023 2.130 0.03 Firm-Level Measures -0.997 0.370 -2.690 0.01 Size of BU 0.031 0.034 0.919 0.36 Size of firm -0.009 0.031 -0.294 0.83 Dummy production BU 0.058 0.177 0.332 0.77 Dummy financial services BU 0.006 0.173 -0.034 0.97 Dummy not-for-profit BU 0.049 0.183 0.270 0.79 McKelvey-Zavoina statistic = 0.079 Left censored observations: 21 Right censored observations: 0 Uncensored observations: 246 Total observations: 267 ‘a’ : variable based on directional hypothesis significance calculated as one-tailed p-value Similar to the analyses with RPE-Use, the current model is also analysed with a subsample consisting of for-profit business units only. The results are presented in appendix B at the end of this chapter on page 57. Although the results explain less variance in the dependent variable RPE-based-Targets than the full sample analysis, the model is significant (N = 200, ANOVA F-statistic is 1.884, p = 0.044). The reduced explanatory power (R 2 = 9.9%) is probably the result of the limited size of the for-profit subsample. The subsample analysis supports the qualitative findings of the full sample analysis of the RPE-based-Targets model. Again, I find that the unhypothesized main effects of comparability (negative) and of contractibility (positive) significantly influence RPE use. This repeated finding renders these unhypothesized effects more robust against the different operationalizations of RPE use. The other results from the control variables are not significant, consistent with the RPE-Use model. The Tobit model, which corrects for the effects of the 19 observations of non-adopters of RPE-based-Targets, yields similar qualitative results. The corresponding McKelvey-Zavoina pseudo R 2 is 13.5%. The Tobit model shows qualitative similar results as the base model. The Tobit model is tabulated in table 2.14 on page 46.
Page 2 and 3: Relative Performance Evaluation in
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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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4.5. CONCLUSIONS AND DISCUSSION 113
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Chapter 5 Conclusion 5.1 Summary, C
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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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