Measuring Information Systems Project Complexity: A Structural Equation Modelling Approach
Author(s) -
Nazeer Joseph,
Carl Marnewick
Publication year - 2021
Publication title -
complexity
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.447
H-Index - 61
eISSN - 1099-0526
pISSN - 1076-2787
DOI - 10.1155/2021/5907971
Subject(s) - structural equation modeling , computer science , structural complexity , management science , artificial intelligence , machine learning , engineering
Complexity has emerged as the new norm in the 21st century, and IS projects play a significant role in organisations to address various socio-political concerns. The purpose of this paper is to understand what are the relevant constructs for measuring IS project complexity. A model for measuring IS project complexity is developed using PLS-SEM. The model reveals that organisational complexity, technical complexity, and uncertainty underpin IS project complexity. Organisational complexity in terms of project team, stakeholder management, and strategic drive should be managed by the project manager. Technical complexity was established in terms of project goals, requirements management, technology management, and norms and standards. Uncertainty in IS projects exists in terms of skills management, the triple constraint, and activity management. Suggestions were provided to guide IS project managers on how to manage each construct and alleviate the level of project complexity. This paper presents an updated and different perspective on measuring and managing IS project complexity. The findings would serve as additional building blocks to further elucidate IS project complexity understanding and assist with improving the value of these projects. Furthermore, the suggestions for IS project managers can lead discussions around how IS projects should be managed to ensure complexity is under control.
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