pdf - Nyenrode Business Universiteit
pdf - Nyenrode Business Universiteit pdf - Nyenrode Business Universiteit
3.3. SAMPLE AND MEASUREMENT 73 Table 3.6: Items for Measurability of Outputs (Q21-23) Item description Component loadings a. Match between performance measures and business unit goals 0.731 b. Objective measurability of goals 0.724 c. Match between performance measures system and results 0.809 d. Goals consistency performance measurement system 0.760 Percentage variance explained 57.3% Cronbach’s alpha 0.744 Emphasis on Disaggregated Performance Measures Similar to the measurement of the emphasis on personal-level performance measures, I measure the emphasis on disaggregated measures as their relative weights within the total set of performance measures (Q38). The importance of the individual disaggregated measures are measured at the business unit and the within-business-unit levels of the organization, and consist of costs, revenues, cash flow and non-financial disaggregated measures including market share, customer satisfaction, and quality measures. The weights of these measures are summated and jointly form the measure emphasis on disaggregated measures. Control Variables This study controls for business unit and firm size, as well as for sector effects. This paragraph presents the measures for these control variables. Size (BU and Firm) Size is often regarded as a potentially important determinant of performance measurement practices (Speklé & Verbeeten 2008). For example, larger organizations might be more effective in the use and implementation of sophisticated performance measures that are less vulnerable to noise. 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. 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. Table 3.7 summarizes the questionnaire items and statistics on the size variables.
74 CHAPTER 3. NOISE REDUCTION EFFECTIVENESS Table 3.7: 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 To control for potential industry effects, dummy variables were included 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, representing the largest sector in the sample. 3.3.4 Descriptive Statistics Table 3.8 presents the descriptive statistics for all of the metrics variables described in the preceding section. According to the skewness and kurtosis indicators, all of the variables follow a normal distribution. Table 3.8: Descriptive Statistics Mean Min Max Std. Dev. SkewnessKurtosis NOISE 3.24 1.00 6.00 1.16 0.33 -0.31 RPE-Use 3.37 1.00 5.00 1.00 -0.85 0.31 Environmental Uncertainty 3.19 1.57 4.76 0. 60 -0.38 0.07 Goal Ambiguity 2.34 1.00 5.00 0.57 0.43 1.19 Measurability 4.48 2.00 6.00 0.69 -0.45 0.38 Emphasis on Personal-Level Measures 0.30 0.00 1.00 0.22 0.79 0.47 Emphasis on Disaggregated Measures 0.31 0.00 0.90 0.18 0.50 0.13 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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3.3. SAMPLE AND MEASUREMENT 73<br />
Table 3.6: Items for Measurability of Outputs (Q21-23)<br />
Item description<br />
Component<br />
loadings<br />
a. Match between performance measures<br />
and business unit goals<br />
0.731<br />
b. Objective measurability of goals 0.724<br />
c. Match between performance measures<br />
system and results<br />
0.809<br />
d. Goals consistency performance measurement<br />
system<br />
0.760<br />
Percentage variance explained 57.3%<br />
Cronbach’s alpha 0.744<br />
Emphasis on Disaggregated Performance Measures Similar to the measurement<br />
of the emphasis on personal-level performance measures, I measure the emphasis on disaggregated<br />
measures as their relative weights within the total set of performance measures<br />
(Q38). The importance of the individual disaggregated measures are measured at the<br />
business unit and the within-business-unit levels of the organization, and consist of costs,<br />
revenues, cash flow and non-financial disaggregated measures including market share, customer<br />
satisfaction, and quality measures. The weights of these measures are summated<br />
and jointly form the measure emphasis on disaggregated measures.<br />
Control Variables This study controls for business unit and firm size, as well as for<br />
sector effects. This paragraph presents the measures for these control variables.<br />
Size (BU and Firm) Size is often regarded as a potentially important determinant<br />
of performance measurement practices (Speklé & Verbeeten 2008). For example, larger<br />
organizations might be more effective in the use and implementation of sophisticated performance<br />
measures that are less vulnerable to noise. Control variables business unit size<br />
(Q31) and firm size (Q32) are both based on the number of FTE and revenues. For both<br />
control variables, the natural logs of FTE and revenue were calculated. With business<br />
unit size measured as FTE and revenue, the Cronbach’s alpha is rather low. However,<br />
the two items correlate positively (r = 0.50, p < 0.01). Additionally, the two factors load<br />
onto one component in the factor analysis (component loading = 0.866). Despite the low<br />
Cronbach’s alpha, both items are combined into the measure business unit size. Although<br />
business 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. Table 3.7<br />
summarizes the questionnaire items and statistics on the size variables.
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