What factors influence grassroots knowledge supplier performance in online knowledge platforms? Evidence from a paid Q&A service

Qingfeng Zeng, Wei Zhuang (), Qian Guo and Weiguo Fan
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Qingfeng Zeng: Shanghai University of Finance and Economics
Wei Zhuang: Shanghai University of Finance and Economics
Qian Guo: Shanghai University of Finance and Economics
Weiguo Fan: University of Iowa

Electronic Markets, 2022, vol. 32, issue 4, No 35, 2507-2523

Abstract: 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.

Keywords: Paid Q&A platform; Grassroots knowledge supplier; Knowledge payment; Signaling theory (search for similar items in EconPapers)
JEL-codes: D83 (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (3)

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DOI: 10.1007/s12525-022-00588-2

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