Do Social Dominance-Based Faultlines Help or Hurt Team Performance in Crowdsourcing Tournaments?

ABSTRACT

Firms organize tournaments on online crowdsourcing platforms to outsource complex business problems to external solvers. Participants on these platforms often self-organize into ad-hoc virtual teams to compete in such tournaments. Social dominance-based faultlines, which originate from the alignment of members based on IT-enabled social dominance attributes (e.g., rank and tier), have emerged as a novel type of faultline in crowdsourcing teams. Building on the Categorization-Elaboration Model (CEM), we investigate the contingent effects of team ability and team effort on the relationship between social dominance-based faultlines and team performance in crowdsourcing tournaments. We collected data of 265 virtual teams from Kaggle.com. We discovered that IT-enabled social dominance-based faultlines positively influence the performance of teams with low ability and high effort, whereas the effect becomes negative for teams with high ability and low effort. Our study yields theoretical implications by advancing a novel type of social dominance-based faultline and extending the CEM with two contingent factors (i.e., team effort and team ability) pertinent to team performance on crowdsourcing tournaments. We also offer practical guidelines for team formation in crowdsourcing tournaments and for the design of crowdsourcing platforms.

KEYWORDS:

• Crowdsourcing tournament
• social dominance-based faultline
• team ability
• team effort
• categorization-elaboration model
• virtual teams
• crowdsourcing

Acknowledgements

A shorter version of this manuscript was published in the Proceedings of the Seventy-Eighth Annual Meeting of the Academy of Management (2018), Chicago. The authors are grateful to three anonymous reviewers for their invaluable feedback on the earlier versions of the manuscript.

Supplementary information

Supplemental data for this article can be accessed on the publisher’s website

Disclosure Statement

No potential conflict of interest was reported by the authors.

Notes

1. Hereafter, whenever we mention crowdsourcing platforms, we refer to those that are competitive in nature. Likewise, we refer to spontaneous virtual teams that compete on these crowdsourcing platforms as crowdsourcing teams.

2. Spontaneous virtual teams in our context differ from collectives whose primary communal activity revolves around interactions among members with no explicit goal to be attained (e.g., online communities). Compared to crowdsourcing teams, membership in these collectives is relatively fluid in that members can join and leave at any time. In turn, the commune-ludic nature of such collectives imply that SD-based faultlines are unlikely to manifest because members will probably not view one another in terms of their relative superiority. In contrast, the competitive nature of crowdsourcing tournaments is likely to give rise to SD-based faultlines in crowdsourcing teams because it will lend prominence to SD attributes that is further fueled by the IT-enabled visualization of these attributes.

3. We checked the following topics from the online discussion forums of tournaments on Kaggle.com:

• (a) https://www.kaggle.com/c/siim-isic-melanoma-classification/discussion/154290

• (b) https://www.kaggle.com/c/prostate-cancer-grade-assessment/discussion/145023

• (c) https://www.kaggle.com/c/alaska2-image-steganalysis/discussion/146595

• (d) https://www.kaggle.com/c/birdsong-recognition/discussion/158876

(a) https://www.kaggle.com/c/siim-isic-melanoma-classification/discussion/154290

(b) https://www.kaggle.com/c/prostate-cancer-grade-assessment/discussion/145023

(c) https://www.kaggle.com/c/alaska2-image-steganalysis/discussion/146595

(d) https://www.kaggle.com/c/birdsong-recognition/discussion/158876

(e) https://www.kaggle.com/c/landmark-retrieval-2020/discussion/163037

4. https://medium.com/kaggle-blog/the-3-ingredients-to-our-success-winners-dish-on-their-solution-to-googles-quest-q-a-labeling-c1a63014b88.

Additional information

Funding

The work described in the paper was partially supported by grants from the Research Grants Council of Hong Kong S.A.R. (Project no. CityU 11501721) and the National Natural Science Foundation of China (NSFC) (Projects no. 72071172 and no. 71572140).

Notes on contributors

Fang Cao

Fang Cao ([email protected]) is a Ph.D. candidate in the School of Management at Xi’an Jiaotong University, China, and Department of Information Systems at City University of Hong Kong. Her research interests include crowdsourcing, open innovation, team composition, and creativity. Her research has been published in Academy of Management Proceedings.

Weiquan Wang

Weiquan Wang ([email protected]; corresponding author) is a professor in the Department of Information Systems at City University of Hong Kong. He received his Ph.D. in Management Information Systems from the University of British Columbia. His research interests include human-AI/Algorithm interaction, social media, online platforms, and information privacy. Dr. Wang’s papers have been published on Information Systems Research, Journal of Management Information Systems, MIS Quarterly, Management Science, and Journal of the Association for Information Systems, among others. He served as an Associate Editor of MIS Quarterly.

Eric Lim

Eric T.K. Lim ([email protected]) is a tenured senior lecturer in the School of Information Systems & Technology Management at UNSW Business School, UNSW Sydney. He investigates how technologically enabled open innovations in crowd platforms and social media can be harnessed to benefit society. Dr. Lim’s research has been published in Information Systems Research, Journal of Management Information Systems, Journal of the Association for Information Systems, Journal of the American Society for Information Science and Technology, and European Journal of Information Systems, among others. He serves as Associate Editor for Internet Research.

Xinmei Liu

Xinmei Liu ([email protected]) is a professor in the School of Management at Xi’an Jiaotong University, China. Her research interests include service innovation and management, technological innovation and creativity. Her research has been published in Journal of Knowledge Management, Management Decision, Small Group Research, Leadership& Organization Development Journal, and Journal of the Association for Information Science and Technology, among others. Dr. Liu’s research has also been presented several times on Academy of Management (AOM) Annual Meetings.

Chee-Wee Tan

Chee-Wee Tan ([email protected]) is a professor in the Department of Digitalization at Copenhagen Business School. His research interests center on design and innovation related to the delivery of digital services in various contexts such as e-commerce, e-government, e-health, and m-commerce. His work has been published in Information Systems Research, Journal of Management Information Systems, MIS Quarterly, Journal of the Association for Information Systems, and European Journal of Information Systems, among others. Dr. Tan serves as Senior Editor for MIS Quarterly, AIS Transactions on Human-Computer Interaction, and Industrial Management and Data Systems and on the editorial boards of several other journals.