Team Knowledge Networks, Task Dependencies and Coordination Preliminary Findings from Software Teams

Alberto Espinosa, Mark Clark, Emma Nordbäck

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Abstract

Today’s work increasingly involves teams with fluid boundaries, and members working on multiple projects at a time. To understand how work is effectively coordinated in such complex organizations, we focus on the role of a company’s task dependency network. We integrate three research streams – coordination, team knowledge and social networks to conceptualize multiteam work as a large collaboration with members in multiple functional roles and areas of expertise, with complex task dependency relationships, operating as a coherent and well-coordinated knowledge network. Through this integration and empirical test of associated hypotheses with data from a European software company, our study illustrates how to represent multiple relationships in one complex multiplex network. This extends our understanding of how the various knowledge relationships and individual attribute differences influence the effective coordination in collaborative software development work. We address the concepts of awareness and shared familiarity and how they affect coordination, while keeping our focus on illustrating the power of network analytics to gain nuanced insights into the drivers of effective coordination.
Original languageEnglish
Title of host publicationProceedings of the 55th Hawaii International Conference on System Sciences
Number of pages10
Publication date04.01.2022
Pages614-623
ISBN (Electronic)978-0-9981331-5-7
Publication statusPublished - 04.01.2022
MoE publication typeA4 Article in conference proceedings
EventHawaii International Conference on System Sciences - Virtual event, Honolulu, United States
Duration: 05.01.202207.01.2022
Conference number: 55

Publication series

NameProceedings of the annual Hawaii international conference on system sciences
Number2022
ISSN (Electronic)2572-6862

Keywords

  • 512 Business and Management

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