Adopting Seekers’ Solution Exemplars in Crowdsourcing Ideation Contests: Antecedents and Consequences

Information Systems Research, 2019, 30(2), pp. 486-506

43 Pages Posted: 12 Sep 2017 Last revised: 25 Jul 2019

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

Date Written: July 26, 2018

Abstract

To benefit from the wisdom of the crowd in ideation contests, seekers should understand how their involvement affects solvers’ ideation and the ensuing ideas. This present study addresses this need by examining the antecedents and consequences of solvers’ exemplar adoption (i.e., use of solution exemplars that the seekers provide) in such contests. We theorize how the characteristics of seekers’ exemplars (specifically, quantity and variability) and prizes jointly influence exemplar adoption. We also consider how exemplar adoption affects the effectiveness of the resulting ideas, conditional on solvers’ experience with the problem domain of the contests. The results from a company naming contest and an ad design contest show that exemplar quantity and exemplar variability both positively affect exemplar adoption, but the effects are strengthened and attenuated, respectively, by prize attractiveness. The outcomes of a campaign using the ads from the design contest further show that greater exemplar adoption improves ad effectiveness (in terms of click-through performance), although this is negatively moderated by solvers’ domain experience. We discuss the theoretical and practical contributions of this research to ideation contests.

Keywords: ideation contests, crowdsourcing, exemplars, prizes, contest winning, effort economization, payoff attractiveness, domain experience, banner ads, click-through

Suggested Citation

Koh, Tat Koon, Adopting Seekers’ Solution Exemplars in Crowdsourcing Ideation Contests: Antecedents and Consequences (July 26, 2018). Information Systems Research, 2019, 30(2), pp. 486-506 . Available at SSRN: https://ssrn.com/abstract=3034630 or http://dx.doi.org/10.2139/ssrn.3034630

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

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