Collaboration Process Pattern & Teamwork Performance: A Graph Mining-Based Methodology
By Dr. LI Xin
Department of Information Systems
City University of Hong Kong
It is well documented in management literature that characteristics of collaboration processes strongly influence team performance in a business environment. However, little work has been done on how specific collaboration process patterns affect teamwork performance, leading to an open issue in collaboration management. To address this research gap, we develop a Collaboration Process Pattern (CPP) approach that analyzes teamwork performance by mining collaboration system logs from open source software development. Our empirical study identifies collaboration patterns that can lead to more efficient teamwork. It also shows that the effects of collaboration patterns vary depending on the types of tasks. These findings are of significant business value since they suggest that managers should carefully prioritize their limited attention on certain types of tasks for intervention.
Xin is an Associate Professor in the Department of Information Systems at City University of Hong Kong. He has published 90 publications, including about 50 journal papers. His work has appeared in MISQ, JMIS, INFORMS JOC, DSS, I&M, IJEC, JASIST, IEEE/ACM Transactions, Nature Nanotechnology, Bioinformatics, among others. He has received about 20 external and internal grants as PI and Co-I. He is a senior member of IEEE, and ACM, and a member of AIS and INFORMS.
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