Abstract
This chapter describes the analysis of the collected survey data and testing of the five hypotheses in the research model. Section 5.1 outlines the study sample providing an overview of studied population. In Sect. 5.2, the newly developed team performance measurement instrument and the gathered performance data is discussed. Testing of the research propositions are described in Sect. 5.3 and the final integration into a performance prediction model is summarized in Sect. 5.4.
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Notes
- 1.
The company does not allow to disclose the overall number of teams working in Germany.
- 2.
Details on this analysis technique are described in Sect. 4.4.2
- 3.
See item PERF2: “I consider this team a high performance team”.
- 4.
See item PP1: “How much of your code do you develop with a programming partner?”
- 5.
See item SMM1: “The two of us, we agree how well-crafted code looks like.”
- 6.
\(AV E =\sum \lambda _{i}^{2}/\big(\sum \lambda _{i}^{2} +\sum _{i}var(\varepsilon _{i})\big)\).
- 7.
\(CR =\big (\sum \lambda _{i}\big)^{2}/\big((\sum \lambda _{i})^{2} +\sum _{i}var(\varepsilon _{i})\big)\).
- 8.
Cronbach’s \(\alpha = N/(N - 1) {\ast}\big (1 -\sum _{i}\sigma _{i}^{2}/\sigma _{t}^{2}\big)\) where N is the number of items, \(\sigma _{i}\) is the variance of item i, and \(\sigma _{t}\) is the variance of the variable score.
- 9.
\(f^{2} =\big (R_{incl}^{2} - R_{excl}^{2}\big)/\big(1 - R_{incl}^{2}\big)\).
- 10.
\(Q^{2} = 1 -\big (\sum E_{\omega }/\sum O_{\omega }\big)\) where E ω are the squared errors of the predicted values and O ω the squared error using the mean as prediction value.
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Schmidt, C. (2016). Empirical Validation. In: Agile Software Development Teams. Progress in IS. Springer, Cham. https://doi.org/10.1007/978-3-319-26057-0_5
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