||The App Store's success has not only changed the business model of mobile software, but also expedited the development of ICT and newly developed industries. Eletronic word of mouth (e-WOM) has become an influential power in consumer decision making. However, not much previous research has examined the effect of eWOM on sales performance of mobile App. |
This research is an empirical research that is focused on the issue of how eWOM affect the sales performance of mobile App. I used text mining and heuristic rules to classify and analyze the mood of the eWOMs and empirical examined their effects. The eWOM and sales ranking of the top ten Apple’s App’s in Taiwan in 2011 were retrieved for this research. Each eWOM was classified into system and service-related comments (based on the information system success model). These comments were then classified into their emotional scale. The top ten App’s were classified into utilization and hedonic Apps’. The data were then combined with price and the average ranking to examine their effects on the sales ranking. Major findings include the following:
1. Overall, our proposed method for analyzing eWOM can effectively predict the sales ranking of an App. The eWOM score of system quality had significant effect on the sales ranking of the top ten App in the Apple’s App Store in 2011.
2. When the top ten App’s were divided into utilization and hedonic groups, we found that the score of system quality and price had significant effect on the sales ranking.
3. For hedonic App’s, all four factors (system quality score, service quality score, average rating, and price) had significant effect on the sales ranking.
Keywords: App Store, mobile software, eWOMs, text mining, heuristic rules