Teams vs. Crowds: A Field Test of the Relative Contribution of Incentives, Member Ability, and Emergent Collaboration to Crowd-Based Problem Solving Performance

Academy of Management Discoveries, 3(4), 382-403

58 Pages Posted: 24 Jan 2014 Last revised: 6 Apr 2018

See all articles by Christoph Riedl

Christoph Riedl

Northeastern University - D’Amore-McKim School of Business

Anita Williams Woolley

Carnegie Mellon University

Date Written: December 8, 2016

Abstract

Organizations are increasingly turning to crowdsourcing to solve difficult problems. This is often driven by the desire to find the best subject matter experts, strongly incentivize them, and engage them with as little coordination cost as possible. A growing number of authors, however, are calling for increased collaboration in crowdsourcing settings, hoping to draw upon the advantages of teamwork observed in traditional settings. The question is how to effectively incorporate team-based collaboration in a setting that has traditionally been individual-based. We report on a large field experiment of team collaboration on an online platform, in which incentives and team membership were randomly assigned, to evaluate the influence of exogenous inputs (member skills and incentives) and emergent collaboration processes on performance of crowd-based teams. Building on advances in machine learning and complex systems theory, we leverage new measurement techniques to examine the content and timing of team collaboration. We find that temporal “burstiness” of team activity and the diversity of information exchanged among team members are strong predictors of performance, even when inputs such as incentives and member skills are controlled. We discuss implications for research on crowdsourcing and team collaboration.

Keywords: Collaboration, crowdsourcing, emergence, team communication, team performance

Suggested Citation

Riedl, Christoph and Woolley, Anita Williams, Teams vs. Crowds: A Field Test of the Relative Contribution of Incentives, Member Ability, and Emergent Collaboration to Crowd-Based Problem Solving Performance (December 8, 2016). Academy of Management Discoveries, 3(4), 382-403, Available at SSRN: https://ssrn.com/abstract=2384068 or http://dx.doi.org/10.2139/ssrn.2384068

Christoph Riedl (Contact Author)

Northeastern University - D’Amore-McKim School of Business ( email )

360 Huntington Ave.
Boston, MA 02115
United States

HOME PAGE: http://www.christophriedl.net

Anita Williams Woolley

Carnegie Mellon University ( email )

Pittsburgh, PA 15213-3890
United States

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