https://orcid.org/0000-0003-0401-287X
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ABSTRACT
While IT workforce research often examines job- and organizational-related reasons for turnover, studies rarely connect the immediate social context of IT work to IT professionals’ workplace behavior. To understand the influence of the immediate social context, we develop a social comparison model that connects the social influence of co-worker who have left an organization to turnover among IT professionals who remain. We test our model using a social network of 4,011 IT professionals employed in a large IT firm over four years. We complement our analysis of this data with a multiple-case study with five software development teams. Across the two studies, our results suggest that the departure of an IT professional increases the probability of turnover among remaining coworkers; further, we found that turnover is even more likely when the remaining IT professionals are similar in technical abilities and demographic attributes to the co-worker who left. Our results direct attention to the immediate social context as an influence on the turnover behavior of IT professionals and explain how similarity in domain-specific attributes shapes this turnover behavior. Practitioners should know that a single departure may cause a chain reaction in IT work teams and organizations and find suggestions for assigning new employees.
Acknowledgements
We thank the associate editor and reviewers for their developmental feedback and guidance throughout the review process. We thank Markus Schichtl, Leonard Przybilla, Mai Nguyen, and Katharina Wahl for their data collection and analysis support. We greatly appreciate the helpful comments on earlier versions of this paper from Damien Joseph, Sven Laumer, and the brown bag seminars at the University of Mannheim and ESSEC Business School, Paris.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Notes
1. A pseudonym to ensure the company’s anonymity.
2. In order to test all possible empirical configurations of the age, we ran additional analyses to understand whether age brackets or dilution of effect size might exist that affect our analysis. We did not find any significant effects. These additional analyses are available upon request.
3. For the social comparison measure, we ran a face validity check by surveying a smaller set of IT professions about their social comparison behavior to close and distant colleagues. This analysis is available up-on request.
Additional information
Funding
Notes on contributors
Manuel Wiesche
Manuel Wiesche is a Full Professor and Chair of Digital Transformation at TU Dortmund University, Germany. He holds a doctoral degree and a habilitation degree from TUM School of Management, Technical University of Munich, Germany. Dr. Wiesche’s research interests include IT workforce, IT project management, digital platform ecosystems, and IT service innovation. His research has been published in MIS Quarterly, Journal of Information Technology, Journal of the AIS, and many other journals.
Christoph Pflügler
Christoph Pflügler holds a Ph.D. from the Technical University (TUM) of Munich. He graduated in Finance and Information Management from TUM and Universität Augsburg, Germany. His main research interests include IT turnover, retention strategies, IT team composition, and governance of IT outsourcing projects.
Jason Bennett Thatcher
Jason B. Thatcher is the Tandean Rustandy Esteemed Endowed Chair in the Leeds School of Business at the University of Colorado Boulder. He is also a professor of Information Systems and Digital Transformation at the University of Manchester, UK. Dr. Thatcher received degrees from the University of Utah and Florida State University. His work appears in Information Systems Research and MIS Quarterly. He serves as Senior Editor at Information Systems Research. He has been honored by the Technical University of Munich, an Honorary Professor by the University of Nottingham-Ningbo, and as a member of the Circle of Compadres by the KPMG Ph.D. Project.