Given the increasing importance of mobile applications in people's daily life and the unique characteristics of the mobile environment, surprisingly little research has been conducted to investigate consumers' downloading behavior in mobile application stores. In this study, by combining predictors of product performance with customer value framework, we consider both text and non-text information in examining the effect of in-store information on application downloads. We apply latent semantic analysis technique to find out the meaningful, valuable information embedded in customer review and product description for five types of applications. We also find that for different types of applications, customers weight information at various levels when they make downloading decisions. This study makes contributions by revealing the role of in-store information in mobile application downloads and providing application developers with useful guidance to improve in-store information management.
