Impact of values on the continual intention of mobile health apps: a text mining perspective

Abstract

Purpose This study aims to examine values derived from apps and their relationship with continual intention using reviews from the Google Play Store. Design/methodology/approach This paper delves deep into the determinants of mobile health apps’ (MHAs) value offering (functional, social, epistemic, conditional and hedonic value) using automatic content analysis and text mining of user reviews. This paper obtained data from a sample of 45,019 MHA users who have posted reviews on the Google Play Store. This paper analyzed the data using text mining, ACA and regression techniques. Findings The findings show that values moderate the relationship between review length and ratings. This paper found that the higher the length, the lower the ratings and vice versa. This paper also demonstrated that the novelty and perceived reliability of the app are the two most essential constructs that drive user ratings of MHAs. Originality/value This is one of the first studies, to the best of the authors’ knowledge, that derives values (functional, social, epistemic, conditional and hedonic value) using text mining and explores the relationship with user ratings.