Segmenting utilitarian-based mobile app users: an empirical study using SEM and clustering techniques

Abstract

This study endeavours to facilitate the app developers and marketers in segmenting the market using antecedents - interactivity, information quality and system quality, and mediating variable - perceived ease of use, of the users' intention to continuously use the informational app. The study commences with the verification of input variables using structural equation modelling. This was followed by segmentation of the market using two clustering techniques - self-organising maps and k-means. Analysis of data collected from 274 respondents showed that system quality and information quality have a very strong influence on the mediating variable - perceived ease of use, which further has a great impact on informational app users' intention to use the app continuously. Based upon these antecedents, six clusters were identified - four and two using SOM and k-means clustering techniques respectively. The study closes with managerial and research implications.