A Decision Tree Based Method for Extracting Important Elements of In-Applications Purchase

Abstract

With rapid development of mobile communications services and handheld devices, it led to explosive growth in mobile applications (App). Related works also indicated that game Apps have become the biggest source of revenue compared to other kinds of Apps. Recent surveys have found that the mobile games industry will account for ever increasing contributions, with a market share approaching 35% by 2020. Therefore, the game App providers need to know how to design products to satisfy consumer's needs and how to increase revenue from Apps. In particular, in-App purchase is the major revenue models for game Apps. Consequently, this study attempts to define the potential factors of influencing in-App purchase behaviors of game users. Then, we use decision trees (DT) to identify important factors. The findings can be used as a reference when designing game Apps for game developers and researchers to increase profit of game Apps.