Online User Reviews, Product Variety, and the Long Tail: An Empirical Investigation on Online Software Downloads

Abstract

Our study examines the impact of both a demand side factor (online user reviews) and a supply side factor (product variety) on the long tail and superstar phenomena in the context of online software downloading. The descriptive analysis suggests a significant superstar download pattern and also the emergence of the long tail. Using the quantile regression technique, we find the significant interaction effect between online user reviews and product variety on software download. We find that the impacts of both positive and negative user reviews are weakened as product variety goes up. In addition, the increase in product variety reduces the impact of user reviews on popular products more than it does on niche products. After taking the interaction effect into account, we find that the overall impact of the increased product variety helps niche products to get more downloads. These results highlight the importance of considering the intricate interplay between demand side and supply side factors in the long tail and online word-of-mouth research.

Keywords: Long tail, Superstar, Online user reviews, Product variety, Word-of-mouth, Software download, Quantile regression

JEL Classification: L86, M31