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Investigating Relationship Conflict within the Social Network of Large IS Projects using a SIR Model

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paperpeer-review

Published
Publication date28/08/2023
Host publication2022 IEEE International Symposium on Technology and Society (ISTAS)
PublisherIEEE
ISBN (electronic)9781665484107
ISBN (print)9781665484114
<mark>Original language</mark>English
EventIEEE International Symposium on Technology and Society 2022 - Hong Kong, Hong Kong
Duration: 10/11/202212/11/2022
https://www.istas22.org

Conference

ConferenceIEEE International Symposium on Technology and Society 2022
Abbreviated titleIEEE ISTAS 2022
Country/TerritoryHong Kong
Period10/11/2212/11/22
Internet address

Conference

ConferenceIEEE International Symposium on Technology and Society 2022
Abbreviated titleIEEE ISTAS 2022
Country/TerritoryHong Kong
Period10/11/2212/11/22
Internet address

Abstract

In large corporate organisations, significant business transformation initiatives are often implemented using large IS and IT projects that involve multiple third-party providers. These are often structured around multi-partner project teams that align to the various functional and technical aspects of the new system, incorporating a diversity of members within each project team, which frequently results in conflicts that spread across the social network of the implementation programme. While several studies on conflict in project teams have been published, to the best of our knowledge, there are no visual simulations that allow observers to examine the underlying social relationships and system dynamics. As a result, we believe exploring the process of conflict propagation through computa- tional modelling will become a critical component of the study of conflict management. A common approach for modelling complex systems is agent-based modelling and simulation, which enables complex emergent behaviours to emerge at the system- level through simple rule-based interactions at the individual agent-level. We developed an agent-based model of conflict that incorporporated the Susceptible-Infectious-Removed model from epidemiology, in order investigate the propagation of conflict in a large IS implementation. Conflict is viewed as an infection, and the process of post-conflict management as patient recovery. We illustrate the model’s validity in reality and the results demonstrate that regardless of the magnitude of the conflict, if it is not adequately handled at the start, it may rapidly spread throughout the network.