Schürholz, V. (2025). A Descriptive Evaluation of the Value Chain Model for Team Performance [Diploma Thesis, Technische Universität Wien]. reposiTUm. https://doi.org/10.34726/hss.2025.122702
In today’s complex and fast-paced organizational environments, leaders face the challenge of managing numerous inter related factors that influence team performance, ranging from setting clear and accepted goals to establishing defined roles and fostering trust and psychological safety. Given the difficulty of maintaining oversight of all these factors, there is a growing need for comprehensive models that offer cognitive guidance and enable performance measurement. This thesis examines whether the Value Chain Model addresses this need and how it compares to existing models, with a particular focus onits performance dimensions. The analysis explores the model’s fit with its intended purpose (user purpose–model fit) and alignment with performance goals (target system–model fit), based on theoretical considerations and quantitative descriptive methods.The investigation into the user purpose–model fit reveals that, compared to older models, the Value Chain Model holds strong potential as a leadership tool for analyzing and improving team performance. This is primarily due to its inclusion of a broad range of performance factors and its explicit integration of leadership aspects, which are often neglected in other frameworks. Moreover,by foregoing a rigid, sequential phase model, it offers greater practical flexibility, reflecting the real-world challenge of addressing multiple performancefactors simultaneously. At the same time, it neglects complex interrelation-ships in favor of improved cognitive accessibility and practical usability.With regard to the target system–model fit, the results were mixed. While some data strongly supported the hypotheses, issues with data quality and contextual limitations introduced contradictions that ultimately led to a more cautious interpretation. Overall, the three hypotheses remain inconclusive,though some findings indicate partial support. This highlights the model’s potential and the need for further empirical testing under more controlled conditions
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