Seeker Exemplars and Quantitative Ideation Outcomes in Crowdsourcing Contests

Information Systems Research (Forthcoming)

48 Pages Posted: 2 Aug 2021 Last revised: 5 Aug 2021

See all articles by Tat Koon Koh

Tat Koon Koh

Hong Kong University of Science & Technology (HKUST) - Department of Information Systems, Business Statistics and Operations Management

Muller Y.M. Cheung

Hong Kong University of Science & Technology (HKUST) - Department of Information Systems, Business Statistics and Operations Management

Date Written: August 5, 2021

Abstract

Idea seekers in crowdsourcing ideation contests often provide solution exemplars to guide solvers in developing ideas. Solvers can also use these exemplars to infer seekers’ preferences when generating ideas. In this study, we delve into solvers’ ideation process and examine how seeker exemplars affect the quantitative outcomes in solvers’ scanning, shortlisting, and selection of ideas; these ideation activities relate to the Search and Evaluate stage of the Knowledge Reuse for Innovation model. We theorize that solvers’ use of local (problem-related) and/or distant (problem-unrelated) seeker exemplars in the respective search and evaluation activities is affected by their belief and emphasis in contests as well as the influences of processing fluency and confirmation bias during idea generation. Consequently, local and distant seeker exemplars have different effects in different ideation activities. Consistent with our theorizing, the results from an ideation contest experiment show that, compared to not showing any seeker exemplars, providing these exemplars either does not affect or could even hurt the quantitative outcomes in the respective ideation activities. We find that solvers generally search for, shortlist, and/or submit fewer ideas when shown certain seeker exemplars. Moreover, solvers who submit fewer ideas tend to submit lower quality ideas on average. Thus, showing seeker exemplars, which contest platforms encourage and seekers often do, could negatively affect quantitative ideation outcomes and thereby impair idea quality. We discuss the theoretical and practical implications of this research.

Keywords: Crowdsourcing, Ideation contests, Confirmation bias, Online experiment, Knowledge reuse for innovation, Processing fluency

Suggested Citation

Koh, Tat Koon and Cheung, Muller Y.M., Seeker Exemplars and Quantitative Ideation Outcomes in Crowdsourcing Contests (August 5, 2021). Information Systems Research (Forthcoming), Available at SSRN: https://ssrn.com/abstract=3859023 or http://dx.doi.org/10.2139/ssrn.3859023

Tat Koon Koh (Contact Author)

Hong Kong University of Science & Technology (HKUST) - Department of Information Systems, Business Statistics and Operations Management ( email )

Clear Water Bay
Kowloon
Hong Kong

Muller Y.M. Cheung

Hong Kong University of Science & Technology (HKUST) - Department of Information Systems, Business Statistics and Operations Management ( email )

Clear Water Bay
Kowloon
Hong Kong

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