Abstract
Industry-scale projects often require large multi-functional teams to deliver complex inter-related tasks. However, to put together an organization structure to meet a project’s targets most effectively is challenging. In this paper, we introduce a novel agent-based simulation system that models team member behaviour by combining socio-technical attributes to estimate time and cost outputs. It defines team-level performance as a function of individual attributes including new skill learning by exchanging help requests. It provides a framework for simulating arbitrary team configurations against given project task workflow and hence, evaluating the performances of different organization structures. Different modeling granularity levels (tasks, individuals, and teams), together with the flexibility with which the system allows rapid modeling and evaluation of organizational scenarios represent a step change from existing organizational and project analysis tools. It provides the foundation for resource managers to design optimized project teams in future.
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Dutta, P., Pepe, C., Xi, H. (2015). Analyzing Organization Structures and Performance through Agent-Based Socio-technical Modeling. In: Handa, H., Ishibuchi, H., Ong, YS., Tan, KC. (eds) Proceedings of the 18th Asia Pacific Symposium on Intelligent and Evolutionary Systems - Volume 2. Proceedings in Adaptation, Learning and Optimization, vol 2. Springer, Cham. https://doi.org/10.1007/978-3-319-13356-0_4
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DOI: https://doi.org/10.1007/978-3-319-13356-0_4
Publisher Name: Springer, Cham
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