TY - GEN
T1 - What kind of user-generated ideas are more likely to be implemented? Evidence from an open innovation community
AU - Liu, Qian
AU - Hong, Yili
AU - Du, Qianzhou
AU - Fan, Weiguo
N1 - Funding Information:
The authors are grateful for the financial support from the National Natural Science Foundation of China (71702206; 71872149) and National Key Research & Development Plan of China (2017YFB1400100).
Publisher Copyright:
© International Conference on Information Systems 2018, ICIS 2018.All rights reserved.
PY - 2018
Y1 - 2018
N2 - 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.
AB - 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.
KW - Abstractness
KW - Crowdsourcing
KW - Idea implementation likelihood
KW - Originality
KW - Topic dispersion
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M3 - Conference contribution
AN - SCOPUS:85062542827
T3 - International Conference on Information Systems 2018, ICIS 2018
BT - International Conference on Information Systems 2018, ICIS 2018
PB - Association for Information Systems
T2 - 39th International Conference on Information Systems, ICIS 2018
Y2 - 13 December 2018 through 16 December 2018
ER -