Type of Publication: Article in Journal

Selecting appropriate process models for IT projects: Towards a tool-supported decision approach

Author(s):

Harr, Michael; Seufert, Sarah

Title of Journal:

Wirtschaftsinformatik (WI) 2023 Proceedings

Publication Date:

2023

Language:

EN

Keywords:

IT Project Management, Process Models, Decision Model, Self-Enforcing Network, Contingency Theory.

Fulltext:

Selecting appropriate process models for IT projects: Towards a tool-supported decision approach (868 KB)

Link to complete version:

https://aisel.aisnet.org/cgi/viewcontent.cgi?article=1100&context=wi2023

Talk associated with this publication:

Wirtschaftsinformatik Conference (2023)

Citation:

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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.