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Art der Publikation: Beitrag in Zeitschrift
Selecting appropriate process models for IT projects: Towards a tool-supported decision approach
- Autor(en):
- Harr, Michael; Seufert, Sarah
- Titel der Zeitschrift:
- Wirtschaftsinformatik (WI) 2023 Proceedings
- Veröffentlichung:
- 2023
- Sprache:
- EN
- Schlagworte:
- IT Project Management, Process Models, Decision Model, Self-Enforcing Network, Contingency Theory.
- Volltext:
- Selecting appropriate process models for IT projects: Towards a tool-supported decision approach (868 KB)
- Link zum Volltext:
- https://aisel.aisnet.org/cgi/viewcontent.cgi?article=1100&context=wi2023
- Vortrag zu dieser Publikation:
- Wirtschaftsinformatik Conference (2023)
- Zitation:
- Download BibTeX
Kurzfassung
The appropriate selection of suitable process models plays an important role for IT project success. To aid in decision-making, IT project management literature offers a plethora of decision models for selecting suitable process models, however, hybrid process models are often neglected and adoption in practice is low or non-existent. To address this challenge, we draw on contingency theory to develop and implement a tool-supported decision model for the selection and evaluation of appropriate process models for IT projects, thereby leveraging artificial intelligence and machine learning in the context of a self-enforcing network. Our model provides an objective tool to assess process model suitability. Results from a conducted online survey with project management experts indicate high validity. Therefore, we contribute to the field of IT project management by expanding AI-based decision models for selecting and evaluating process models through extending the range of covered models and implementing inherent weighting of criteria.