What kind of user-generated ideas are more likely to be implemented? Evidence from an open innovation community

Qian Liu, Yili Hong, Qianzhou Du, Weiguo Fan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Collaborative crowdsourcing communities help firms effectively obtain knowledge, skills, and resources distributed by the public at a lower cost in order to promote the effective integration of internal and external resources of firms and thus achieve open innovation of new product development. Despite the popularity and success of these open innovation communities, little is known about the determinants of users' idea implementation, particularly idea content characteristics. Using an elaboration likelihood model, we integrate a central route and a peripheral route of the process of firm experts' decisions regarding idea implementation-that is, idea content characteristics and idea popularity. The empirical results (90,043 ideas submitted by 53,836 users in the MIUI new function discussion forum hosted by Xiaomi) suggest that original, topic dispersion-focused or concrete ideas are more likely to be adopted and implemented by the firm's experts. Firms' experts are more inclined to adopt those ideas that are most popular in the community. Furthermore, originality and topic dispersion as content factors interact with comments and ratings as popular indicators to affect the experts' decision-making process regarding idea implementation. The implications for both theory and practice are discussed.

Original languageEnglish (US)
Title of host publicationInternational Conference on Information Systems 2018, ICIS 2018
PublisherAssociation for Information Systems
ISBN (Electronic)9780996683173
StatePublished - Jan 1 2018
Event39th International Conference on Information Systems, ICIS 2018 - San Francisco, United States
Duration: Dec 13 2018Dec 16 2018

Publication series

NameInternational Conference on Information Systems 2018, ICIS 2018

Conference

Conference39th International Conference on Information Systems, ICIS 2018
CountryUnited States
CitySan Francisco
Period12/13/1812/16/18

Keywords

  • Abstractness
  • Crowdsourcing
  • Idea implementation likelihood
  • Originality
  • Topic dispersion

ASJC Scopus subject areas

  • Computer Science Applications
  • Statistics, Probability and Uncertainty
  • Library and Information Sciences
  • Applied Mathematics

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  • Cite this

    Liu, Q., Hong, Y., Du, Q., & Fan, W. (2018). What kind of user-generated ideas are more likely to be implemented? Evidence from an open innovation community. In International Conference on Information Systems 2018, ICIS 2018 (International Conference on Information Systems 2018, ICIS 2018). Association for Information Systems.