Ching, Kenny;
Forti, Enrico;
Rawley, Evan;
(2024)
Competitive Familiarity: Learning to Coordinate by Competing.
Organization Science
10.1287/orsc.2022.17068.
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Abstract
This paper develops and tests a theory of organizational learning, proposing that prior competitive interaction improves coordination among teammates. We test the theory using millions of experiments in the formation of eSports teams. The results show that exogenously assigned teams of former competitors are highly effective—The marginal returns to prior competitive interaction are even larger than the returns to prior collaborative interaction. The evidence suggests that teammates learn to coordinate by competing, a finding with implications for organizational design and the management of human capital. Funding: The authors are grateful to UCL School of Management and Worcester Polytechnic Institute for financial and technical support.
| Type: | Article |
|---|---|
| Title: | Competitive Familiarity: Learning to Coordinate by Competing |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1287/orsc.2022.17068 |
| Publisher version: | http://doi.org/10.1287/orsc.2022.17068 |
| Language: | English |
| Additional information: | This work is licensed under a Creative Commons Attribution-NonCommercialNoDerivatives 4.0 International License. You are free to download this work and share with others, but cannot change in any way or use commercially without permission, and you must attribute this work as “Organization Science. Copyright © 2024 The Author(s). https://doi.org/10.1287/orsc.2022. 17068, used under a Creative Commons Attribution License: https://creativecommons.org/licenses/ by-nc-nd/4.0/.” |
| Keywords: | Competition, collaboration, organization design, team performance, strategic human capital |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > UCL School of Management |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10187780 |
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