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, second-usage 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.
|Publication status||Published - 2017|
|Event||21st Pacific Asia Conference on Information Systems: Societal Transformation Through IS/IT, PACIS 2017 - Langkawi, Malaysia|
Duration: 2017 Jul 16 → 2017 Jul 20
|Conference||21st Pacific Asia Conference on Information Systems: Societal Transformation Through IS/IT, PACIS 2017|
|Period||17/7/16 → 17/7/20|
Bibliographical noteFunding Information:
The work described in this paper was fully supported by a grant from the Research Grants Council of the Hong Kong Special Administrative Region, China (Project No. CUHK 24504416) for Youngsok Bang and by Hansung University for Dong-Joo Lee.
All Science Journal Classification (ASJC) codes
- Information Systems