Which ideas are more likely to be implemented in online user innovation communities? An empirical analysis

Decision Support Systems

Volumn 84, Issue , 2016, Pages 28-40

  Li, Mingguo ^a   Kankanhalli, Atreyi ^b   Kim, Seung Hyun ^c  

^a CARNEGIE MELLON UNIVERSITY   (United States)

^b NATIONAL UNIVERSITY OF SINGAPORE   (Singapore)

^c Yonsei University   (South Korea)

Author keywords

Cognitive overload; Message persuasion; User ideas; User innovation community

Indexed keywords

LARGE DATASET;

COGNITIVE OVERLOAD; CONCEPTUAL MODEL; EMPIRICAL ANALYSIS; INNOVATION IDEAS; MESSAGE PERSUASION; ONLINE USERS; USER IDEAS; USER INNOVATION;

LOGISTIC REGRESSION;

EID: 84980053076     PISSN: 01679236     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.dss.2016.01.004     Document Type: Article

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