Analysis of Herding on the Internet - An Empirical Investigation of Online Software Download
From Virtual Communities
Wenjing Duan, University of Texas at Austin, Bin Gu, University of Texas at Austin
Online shopping often requires consumers to choose among multiple products without detailed information about the quality. Herding is common in situations where consumers infer product quality from other consumers´ choices and incorporate that information into their own decision-making process. The Internet affects the herding phenomenon in two ways. On the one hand, it provides more information about other consumers´ choices, therefore making herding more feasible. On the other hand, it provides more details about product quality, thus making herding less desirable. This paper empirically examines those two effects in the context of online software downloading. We find significant herd behavior in our analysis, and, surprisingly, the provision of professional product reviews or user reviews does not significantly influence the herding phenomenon. This study contributes to the E-Commerce and the Internet marketing research by investigating online consumer behavior. This paper also contributes to the emerging literature of studying the impact of virtual communities.
E-Commerce, herding, informational cascades, software download, virtual community, online user review