Effect of Knowledge-Sharing Trajectories on Innovative Outcomes in Temporary Online Crowds

Ann Majchrzak () and Arvind Malhotra ()
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Ann Majchrzak: Marshall School of Business, University of Southern California, Los Angeles, California 90089; and ESADE Business School, 08034 Barcelona, Spain
Arvind Malhotra: Kenan–Flagler Business School, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599

Information Systems Research, 2016, vol. 27, issue 4, 685-703

Abstract: There is substantial research on the effects of formal control structures (i.e., incentives, identities, organization, norms) on knowledge sharing leading to innovative outcomes in online communities. However, there is little research on how knowledge-sharing trajectories in temporary online crowds create innovative outcomes without these structures. Such research is particularly of interest in the context of temporary online crowds solicited with crowdsourcing in which there is only minimal structure for knowledge sharing. We identify eight types of crowdsourcing with different knowledge-sharing patterns. The focus of this study is on the one type of crowdsourcing—collaborative innovation challenges—in which there is the least restriction on knowledge sharing in the crowd. A content analysis was conducted of all time-stamped posts made in five different collaborative innovation challenges to identify different knowledge-sharing trajectories used. We found that a paradox-framed trajectory was more likely to be followed by innovative outcomes compared to three other knowledge-sharing trajectories. A paradox-framed trajectory is one in which a novel solution emerges when different participants post in the following sequence: (1) contributing a paradox associated with the problem objective, (2) sharing assumptions to validate the paradox, and (3) sharing initial ideas for resolving the paradox in a manner that meets the problem statement. Based on the findings, a theory of paradox-framed trajectories in temporary online crowds is presented along with implications for knowledge creation theories in general and online knowledge-creating communities in particular.

Keywords: innovation; sequences; crowdsourcing; knowledge; online communities (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (15)

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Persistent link: https://EconPapers.repec.org/RePEc:inm:orisre:v:27:y:2016:i:4:p:685-703

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