Selecting Appropriate Process Models for IT Projects: Towards a Tool-Supported Decision Approach

Michael Dominic Harr () and Sarah Seufert ()
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Michael Dominic Harr: University of Duisburg-Essen
Sarah Seufert: University of Duisburg-Essen

A chapter in Conceptualizing Digital Responsibility for the Information Age, 2025, pp 447-464 from Springer

Abstract: Abstract 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.

Keywords: IT project management; Process models; Decision model; Self-enforcing network; Contingency theory (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:spr:lnichp:978-3-031-80119-8_28

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DOI: 10.1007/978-3-031-80119-8_28

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