Journal article
What drives users' knowledge payment behaviour? The moderating role of knowledge expertise and social identity
Behaviour & information technology, Vol.44(3), pp.407-427
02/07/2025
DOI: 10.1080/0144929X.2024.2320213
Abstract
Previous research on user payment behaviour in online community has predominantly focused on the pre-paid mode, with limited understanding of the antecedents influencing user payment behaviour in the post-paid mode. Drawing upon the dual-process theory and social identity theory, this study uses the text mining method based on the attention mechanism and the social network method to explore the influence of the quality of knowledge products and the credibility of contributors, focusing on the role of knowledge expertise and social identity. Using 247,013 replies to 32,373 questions from 3,631 seekers on Xueqiu.com (one of the most popular post-paid online Q&A communities in China), our empirical results found that informativeness, relevance of knowledge products, contributor honour, and experience significantly positively influence user payment behaviour, while timeliness of knowledge products exhibits a significant negative impact on user payment behaviour. Furthermore, contributor social interaction has a significant negative impact on user payment behaviour, contrary to the direction observed in the pre-paid mode. Moreover, the findings show that knowledge expertise and social identity have significant moderating effects in this process. This study provides assistance in developing diverse payment modes for knowledge platforms, and suggests insights for users to contribute knowledge more effectively.
Details
- Title: Subtitle
- What drives users' knowledge payment behaviour? The moderating role of knowledge expertise and social identity
- Creators
- Jinpeng Liu - Shanghai University of Finance and EconomicsWeiguo Fan - University of IowaXinmiao Li - Shanghai University of Finance and EconomicsXipeng Liu - Shanghai University of Finance and Economics
- Resource Type
- Journal article
- Publication Details
- Behaviour & information technology, Vol.44(3), pp.407-427
- DOI
- 10.1080/0144929X.2024.2320213
- ISSN
- 0144-929X
- eISSN
- 1362-3001
- Publisher
- Taylor & Francis
- Number of pages
- 21
- Grant note
- National Natural Science Foundation of China; National Natural Science Foundation of China (NSFC)
- Language
- English
- Electronic publication date
- 02/27/2024
- Date published
- 02/07/2025
- Academic Unit
- Business Analytics
- Record Identifier
- 9984577124402771
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