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

成果类型:
Article
署名作者:
Majchrzak, Ann; Malhotra, Arvind
署名单位:
University of Southern California; Universitat Ramon Llull; Escuela Superior de Administracion y Direccion de Empresas (ESADE); University of North Carolina; University of North Carolina Chapel Hill
刊物名称:
INFORMATION SYSTEMS RESEARCH
ISSN/ISSBN:
1047-7047
DOI:
10.1287/isre.2016.0669
发表日期:
2016
页码:
685-703
关键词:
OPEN SOURCE SOFTWARE USER COMMUNITIES MODEL INFORMATION creativity contests PARADOX DESIGN firm PARTICIPATION
摘要:
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.
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