Why Do Participants Continue to Contribute? Evaluation of Usefulness Voting and Commenting Motivational Affordances within an Online Knowledge Community


Participants are increasingly using online knowledge communities to access and share information and to collaboratively solve problems. However, in online communities that address technical questions (i.e., utilitarian, rather than hedonic or supportive, in nature), a key problem is encouraging sufficient, ongoing knowledge contribution. While many may use the community to post and obtain information periodically, fewer take the time to consistently contribute knowledge to the community. Interestingly, research has yet to comprehensively consider the impact of motivational affordances, in the forms of voting and commenting features, to address this challenge of under-contribution in online knowledge communities. To fill this research gap, this study proposes a research framework that integrates consideration of usefulness voting and the collaboration tool of commenting to explain variation in individuals' online knowledge contribution behaviors. The research model is estimated with a fixed-effects Poisson regression applied to a longitudinal panel dataset collected from a technical online question and answer community. We find that positive votes motivate participants' knowledge contributions, while received negative votes significantly decrease their knowledge contributions. Thus, while maintaining content quality is important, negative motivational affordances (i.e., down voting) can reduce sustained contributions. We also find commenting to be an important motivator for online knowledge contribution and, interestingly, find that comments moderate the relationships between voting and knowledge contribution. Overall, this research not only extends our current understandings of knowledge contribution in online communities, but also sheds light on improving online community knowledge exchange.


Business and Information Technology

Keywords and Phrases

Commenting; Knowledge contribution; Online knowledge communities; Usefulness voting

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Document Type

Article - Journal

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© 2019 Elsevier B.V., All rights reserved.

Publication Date

01 Mar 2019