The Goldilocks question: How optimal length and answerer match boost reader payments on paid Q&A platforms

Abstract

Paid Question & Answer platforms make profits by charging readers a small fee for each answer they read. Because readers decide whether to pay for reading the answer only after reading the question, it is imperative to understand how question traits affect readers’ paying behavior. Drawing upon signaling theory and the Elaboration Likelihood Model, we examine how question length and the answerer-question match affect the number of paying readers. Based on 17,351 observations from Weibo, a large Chinese Q&A platform, we find that the inverted U-shaped impact of the question length on the sales of questions is moderated by the answerer-question match. By showing this conditional curvilinear relationship, this paper illustrates theoretical nuances behind the effects of question length and answerer-question match and offers practical implications regarding how to foster users’ willingness to pay for answers and make Q&A platforms sustainable.