Content Characteristics, Source Characteristics, and Information Helpfulness: Evidence From a User-Generated Content Community

Description

While help and advice were traditionally sought from experts and professionals, an increasing number of people have begun taking advantage of question-and-answer (Q&A) websites where they can ask questions and others can answer them (Harper et al. 2009). According to a survey commissioned by Yahoo! (2006), one third of online adults have used a Q&A website, and over half of these individuals state that information from a Q&A website has affected a decision that they have made. A more recent report revealed that adults seeking legal advice consider Q&A websites as the most useful online tool (American Bar Association 2011).Q&A websites can facilitate knowledge discovery and delivery if the answers help readers to address people's problems. Despite the growing body of literature that has examined the helpfulness of online consumer reviews, relatively little is known about what makes a helpful answer on Q&A websites. We identify two types of source expertise – professional expertise and experience-based expertise – and argue that they are positively associated with answer helpfulness. In addition to source expertise, we hypothesize an inverted U-shaped relationship between the amount of information in an answer and its helpfulness. Drawing on the heuristic-systematic model, we further predict that both types of source expertise moderate the nonlinear impact of information amount. To test these hypotheses, we will collect a unique data set from one of the leading Q&A websites, WebMD Answers. This paper will contribute to the studies on information amount and source characteristics, and our findings may provide significant practical implication for managers of knowledge sharing platforms.