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Making Software Teams Effective

How Agile Practices Lead to Project Success Through Teamwork Mechanisms

Chaehan So

How does good teamwork emerge?
Can we control mechanisms of teamwork?
The author has analyzed these questions in a study involving 227 participants of 55 software development teams. First, he empirically confirmed his teamwork model based on innovation research, goal setting and control theory. Second, he measured the impact of a wide selection of agile practices on these teamwork mechanisms. Third, he explained these impacts based on a thorough review of current psychological research.
This book is intended for people working in agile contexts as they will gain insight into the complexity of how «good teamwork» emerges. This insight on team dynamics may also prove valuable for upper management for calibrating agile practices and «soft factors», thus increasing the effectiveness of software teams.


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4 Results 95


Chapter 4 Results This chapter presents the results of the statistical analysis methods applied for (a) scale validation by means of reliability analysis and explorative factor analysis, and (b) hypothesis testing by structural equation modeling. Furthermore, descrip- tive statistics on sample data are given, as well as various tests on normal distri- bution of latent variables in the tested causal model. The SEM results are presented first for the total aggregation model using in- dex scores as composites, and then for the partial disaggregation model using item parcels as composites. The finalizing SEM analysis consists of a comparison of the total aggregation model with the same parameter specifications of the final partial disaggregation model. Consistent with APA style guidelines, names of variables used in the statisti- cal analysis of this study are capitalized (e.g. the scale or latent variable score of Iterative Development) unless the semantic intent is on the underlying construct (e.g. the agile practice iterative development). 4.1 Scales Analysis 4.1.1 Reliability Analysis First, this study analyzed internal consistency coefficients on the individual level. In order to improve the level of confidence, this study tested internal consistency additionally on the group level by using aggregated individual item scores for the calculation of alpha coefficients. The obvious exception was the Customer Satisfaction scale which was intended for individual responses. The reliability analysis (Table 4.1) yielded Cronbach α coefficients for all scales ranging between .79 and .93 on the individual level. The only exception was the Continuous Integration scale with a low...

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