Abstract

With the increase of peoples’ eagerness for higher quality knowledge, paid Q&A is becoming a new tendency. However, what factors are helpful to drive potential users’ payment decisions remains unknown. In this paper, we investigated the effects of expert attributes and reputation on users’ payment decisions made on an online Q&A platform in China. We developed auto-parsing crawlers to collect online observational data and used the negative binomial panel regression method to estimate the effects of expert attributes and reputation on users’ payment decision. The results show that expert attributes such as the number of paid questions, the number of times that answers are approved, whether the expert has a personal home page, whether the expert mentions his/her area of expertise, the number of followers, score of expert answers have significant effects, whereas the times that the expert shared knowledge free and whether the expert has a real name certification do not influence users’ willingness to pay for an answer. The results help experts on paid Q&A platforms to improve their performance, perfect their personal information, and enhance users’ trust, so as to promote the development of knowledge sharing economy.

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