Abstract
The patterns of technology usages are the actual reflection of user preference and value assessment over the technology. In the context of mobile app downloads and usages, we show that users’ early-time app usage patterns are important predictors for their continued usages and usage intensity of the app. Using the large-scale mobile app download and usage data, we develop and empirically validate prediction models for continued usages and usage intensity of apps with early-time usage patterns right after the download of an app such as first-usage time, secondusage time, revisit time, and in-app activities. We also consider possible heterogeneity among user groups and app characteristics in our model and discuss the interplay between user and technology for explaining post-adoption user behaviors.
Recommended Citation
Bang, Youngsok; Lee, Dong-Joo; and Kim, Keehyung, "Predicting Post-adoption Usage of Information Technology: A Large-scale Data Analysis of Mobile App Download and Usage Behavior" (2017). PACIS 2017 Proceedings. 160.
https://aisel.aisnet.org/pacis2017/160