Journal article
What factors influence grassroots knowledge supplier performance in online knowledge platforms? Evidence from a paid Q&A service
Electronic markets, Vol.32(4), pp.2507-2523
12/01/2022
DOI: 10.1007/s12525-022-00588-2
Abstract
The popularity of online paid knowledge platforms offers opportunities for massive grassroots knowledge suppliers to participate in knowledge sharing services and get financial rewards, but little is known about the determinants influencing users' payment decisions in the particular knowledge transaction such as paid Q&A. This study examines the factors that influence the performance of grassroots knowledge supplier in paid Q&A platforms. We develop a research model integrating reputation, experience, and authority signal to explain the knowledge payment behavior based on signaling theory. Using a panel data analysis of 12,419 records from Zhihu, the largest online Q&A platform in China, our empirical study reveals that user payment behavior is significantly influenced by reputation signal and experience signal of a knowledge supplier. Interestingly, different from previous conclusions on professional knowledge payment platforms, authority signal of grassroots knowledge supplier has no significant impact on the payment behavior of online Q&A platform users.
Details
- Title: Subtitle
- What factors influence grassroots knowledge supplier performance in online knowledge platforms? Evidence from a paid Q&A service
- Creators
- Qingfeng Zeng - Shanghai University of Finance and EconomicsWei Zhuang - Shanghai Univ Finance & Econ, 777 Guoding Rd, Shanghai 200433, Peoples R ChinaQian Guo - Shanghai Univ Finance & Econ, 777 Guoding Rd, Shanghai 200433, Peoples R ChinaWeiguo Fan - University of Iowa
- Resource Type
- Journal article
- Publication Details
- Electronic markets, Vol.32(4), pp.2507-2523
- Publisher
- Springer Nature
- DOI
- 10.1007/s12525-022-00588-2
- ISSN
- 1019-6781
- eISSN
- 1422-8890
- Number of pages
- 17
- Language
- English
- Date published
- 12/01/2022
- Academic Unit
- Business Analytics
- Record Identifier
- 9984380446302771
Metrics
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