## 4 Empirical Investigation on the Impact of Competencies on Job Performance and Job Satisfaction
Most of the selected indicators were used in previous studies within a similar context, which further contributes to the enhancement of content validity. Furthermore, the \begin{table}
\begin{tabular}{c c} \hline \hline
**Indicator** & **Measurement** \\ \hline Competence & Test Groups: Apprenticeship certificate, high school education, university education, and other supply management-oriented education \\ JP1 & Job Performance: Development of total costs since the beginning of the SSP \\ JP2 & Price stability since the beginning of the SSP \\ JP3 & Comparison of actual costs to costs at the beginning of the SSP \\ JP4 & Adherence to quality standards \\ JP5 & Frequency of quality complaints \\ JP6 & On-time delivery performance \\ JP7 & Reliability in terms of complete deliveries \\ JP8 & Reliability in terms of on-time deliveries \\ Job Performance & Mean (JP1 \(\ldots\) JP8) \\ JS1 & How satisfied are you with the supplier selection decision \\ JS2 & How do you commit to the selected supplier \\ JS3 & How satisfied are you with the process of supplier selection \\ Job Satisfaction & Mean (JS1 \(\ldots\) JS3) \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Operationalization (variables and indicators). authors tested for the non-response bias as suggested by [PERSON] and [PERSON], which evaluates the representability based on significant differences in earlier and later responses. The conducted non-parametric Kruskal-Wallis test showed no significant differences in all indicator values between \"earlier\", \"average\", and \"later\" received survey responses. This can be seen as another indication of the representability and the external validity of the research results [57; 58]. The final sample includes 206 fully completed questionnaires leading to a response rate of 5.2% for the subsequent statistical analyses. The 206 participating manufacturing enterprises pertain to the following branches: 6.3% \"Chemicals/Pharma\", 6.8% \"Wood/Paper\", 6.8%, \"Automotive\", 4.9% \"Plastics/Glass\", 20.9% \"Mechanical Engineering\", 17.0% \"Metal\", 2.9% \"Food/Clothing\", 13.1% \"Optics/Electronics\"; the remaining 21.4% are assigned to other product-manufacturing branches. Most of the responders (66.1%) had more than 10 years of experience in supply management-related tasks [57; 58]. Table 2 shows the descriptive results of the field study. For the evaluation of the aggregated variables, the authors computed [PERSON]'s alpha (CBA) values, resulting in 0.920 for job performance and 0.854 for job satisfaction. Both are above the recommended values of 0.600 and 0.700, respectively, and thus ensure internal consistency reliability [66; 67]. To test the proposed hypotheses, an ANOVA was computed to investigate potential differences in the variables job performance (H1) and job satisfaction (H2) between the test groups of competence. The results of the ANOVA analysis are displayed in Tables 3 and 4. \begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline  & & **Num of Squares** & **Df** & **Mean Square** & **F** & **Sig.** \\ \hline \multirow{3}{*}{**Job Performance**} & Between Groups & 1.99 & 2.00 & 1.00 & 1.63 & 0.20 \\  & Within Groups & 103.46 & 169.00 & 0.61 & & & \\  & Total & 105.45 & 171.00 & & & & \\ \hline \multirow{3}{*}{**Job Satisfaction**} & Between Groups & 2.16 & 2.00 & 1.08 & 1.89 & 0.15 \\  & Within Groups & 96.39 & 169.00 & 0.57 & & & \\ \cline{1-1}  & Total & 98.55 & 171.00 & & & & \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Detail results of the ANOVA analysis. \begin{table}
\begin{tabular}{c c c c} \hline \hline  & **Competence** & **Job Performance** & **Job Satisfaction** \\ \hline N (valid) & 206 & 206 & 206 \\ N (missing) & 0 & 0 & 0 \\ Mean & 1.75 & 4.12 & 4.34 \\ Std. Deviation & 0.85 & 0.81 & 0.75 \\ Minimum & 0 & 1 & 1 \\ Maximum & 3 & 5 & 5 & 5 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Descriptive results. \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline  & **N** & **Mean** & **Std. Dev. ** & **Std.