pdf - Nyenrode Business Universiteit
pdf - Nyenrode Business Universiteit pdf - Nyenrode Business Universiteit
2.3. SAMPLE AND MEASUREMENT 35 Emphasis on Firm-Level Measures The emphasis on firm-level measures construct captures the reliance on performance measures that surpass the boundaries of the business unit. Firm-level performance measures also capture the performance of other organizational parts (e.g., other business units over which the business unit manager has no control). Measures that include more than the organizational parts over which the business unit manager has control, introduce noise into the performance evaluation. I include the use of firm-level measures to control for this noise-increasing effect. ‘Emphasis on firmlevel measures’ is measured as the summed weights of firm stock, firm value and firm profit measures in the performance measurement system (Q30). Size (BU and Firm) The control variables business unit size (Q31) and firm size (Q32) are both based on the number of FTE and revenues. For both control variables, the natural logs of FTE and revenue were calculated. With business unit size measured as FTE and revenue, the Cronbach’s alpha is rather low at a value of 0.634. However, the two items correlate positively (r = 0.50, p < 0.01). Additionally, the two factors load onto one component in the factor analysis (component loading = 0.866). Despite the low Cronbach’s alpha, both items are combined into the measure business unit size. Although business unit size and firm size are significantly correlated with one another (Pearson correlation 0.479), they do not yield collinearity-issues in the multivariate analyses (as described in paragraph 2.4.3). Table 2.6 summarizes the questionnaire items and statistics on the size variables. Table 2.6: Items for Business Unit Size & Firm Size (Q31-32) Item description Component loadings a. Business unit FTE (Ln) 0.866 b. Business unit revenue (Ln) 0.866 Percentage variance explained 75.0% Cronbach’s alpha 0.634 c. Firm FTE (Ln) 0.952 d. Firm revenue (Ln) 0.952 Percentage variance explained 90.6% Cronbach’s alpha 0.892 Sector Dummy Variables Murphy’s (2001) findings indicate differences in RPE use at the executive level across industries. To filter out these effects from the analyses, I include dummy variables that distinguish between business unit sectors (Q33). The model contains dummies for production, financial services, and not-for-profit business units. The base model consists of service organizations, which represent the largest sector in the sample.
36 CHAPTER 2. RPE AT THE BUSINESS UNIT MANAGER LEVEL 2.3.4 Descriptive Statistics The descriptive statistics of the variables that are described above, are presented in table 2.7. The distribution analysis does not indicate normality issues for any of the variables. Kline (2005) and Widener (2007) suggest that skewness greater than three and kurtosis greater than ten may suggest a problem with the data. Kurtosis and skewness indicate that the data are within tolerable levels of univariate normality. However, although the distribution of the RPE measures lies well within the boundaries of normality for the OLS regression (the skewness and kurtosis values are presented in table 2.7), the measures are actually left-censored. At the left end of the scale, a group of 21 (RPE-Use) or 19 (RPE-based-Targets) respondents do not use RPE at all. The rest of the responses are normally distributed and range from small use to extensive use of RPE. To address the censored nature of the dependent variables, I use Tobit regression as an additional analysis. Table 2.7: Descriptive Statistics Mean Min Max Std. Dev. SkewnessKurtosis RPE-Use 3.37 1.00 5.00 1.00 -0.85 0.31 RPE-based-Targets 3.49 1.00 5.00 1.04 -0.95 0.48 Common uncertainty 9.01 3.11 18.65 2.65 0.64 0.63 Interaction information asymmetry * comparability -0.03 -2.69 2.95 0.86 0.23 1.96 Interaction uncertainty * information -0.01 -2.78 2.69 0.77 0.02 2.02 asymmetry Information asymmetry 5.29 2.00 7.00 0.91 -0.61 0.57 Comparability 2.85 1.00 4.55 0.71 0.08 -0.31 Contractibility -3.78 -14.76 3.30 3.06 -0.55 0.41 Emphasis on firm-level measures 0.16 0.00 1.00 0.21 1.83 3.46 Business unit size 10.27 2.30 14.97 2.26 -1.56 2.70 Firm size 13.41 3.69 19.41 2.43 -0.44 1.34
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2.3. SAMPLE AND MEASUREMENT 35<br />
Emphasis on Firm-Level Measures The emphasis on firm-level measures construct<br />
captures the reliance on performance measures that surpass the boundaries of the business<br />
unit. Firm-level performance measures also capture the performance of other organizational<br />
parts (e.g., other business units over which the business unit manager has no control).<br />
Measures that include more than the organizational parts over which the business<br />
unit manager has control, introduce noise into the performance evaluation. I include the<br />
use of firm-level measures to control for this noise-increasing effect. ‘Emphasis on firmlevel<br />
measures’ is measured as the summed weights of firm stock, firm value and firm profit<br />
measures in the performance measurement system (Q30).<br />
Size (BU and Firm) The control variables business unit size (Q31) and firm size (Q32)<br />
are both based on the number of FTE and revenues. For both control variables, the<br />
natural logs of FTE and revenue were calculated. With business unit size measured as<br />
FTE and revenue, the Cronbach’s alpha is rather low at a value of 0.634. However, the two<br />
items correlate positively (r = 0.50, p < 0.01). Additionally, the two factors load onto one<br />
component in the factor analysis (component loading = 0.866). Despite the low Cronbach’s<br />
alpha, both items are combined into the measure business unit size. Although business<br />
unit size and firm size are significantly correlated with one another (Pearson correlation<br />
0.479), they do not yield collinearity-issues in the multivariate analyses (as described in<br />
paragraph 2.4.3). Table 2.6 summarizes the questionnaire items and statistics on the size<br />
variables.<br />
Table 2.6: Items for <strong>Business</strong> Unit Size & Firm Size (Q31-32)<br />
Item description<br />
Component<br />
loadings<br />
a. <strong>Business</strong> unit FTE (Ln) 0.866<br />
b. <strong>Business</strong> unit revenue (Ln) 0.866<br />
Percentage variance explained 75.0%<br />
Cronbach’s alpha 0.634<br />
c. Firm FTE (Ln) 0.952<br />
d. Firm revenue (Ln) 0.952<br />
Percentage variance explained 90.6%<br />
Cronbach’s alpha 0.892<br />
Sector Dummy Variables Murphy’s (2001) findings indicate differences in RPE use<br />
at the executive level across industries. To filter out these effects from the analyses, I<br />
include dummy variables that distinguish between business unit sectors (Q33). The model<br />
contains dummies for production, financial services, and not-for-profit business units. The<br />
base model consists of service organizations, which represent the largest sector in the<br />
sample.
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