Mobile application adoption predictors: Systematic review of UTAUT2 studies using weight analysis

16Citations
Citations of this article
71Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

Mobile phone subscriptions are the largest form of consumer technology adopted across the world. Despite their potential, the research is very scant in understanding various predictors of consumer adoption towards mobiles technologies in particular mobile applications. This study intend to fulfil this purpose through weight analysis on mobile application adoption based studies that utilized UTAUT2 model. Studies needed for weight analysis were located through cited reference search method in Scopus and Web of Science bibliographic databases. The results of weight analysis revealed performance expectancy/perceived usefulness, trust and habit as best predictors of consumer behavioural intention to mobile applications adoption whereas behavioural intention was the best predictor of use behaviour. There were also two promising predictors with perfect weight of one such as perceived risk on behavioural intention and habit on use behaviour. Further steps of this research involves meta-analysis to develop comprehensive conceptual model concurrent with weight analysis results for empirical evaluation on various mobile applications.

Cite

CITATION STYLE

APA

Tamilmani, K., Rana, N. P., & Dwivedi, Y. K. (2018). Mobile application adoption predictors: Systematic review of UTAUT2 studies using weight analysis. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11195 LNCS, pp. 1–12). Springer Verlag. https://doi.org/10.1007/978-3-030-02131-3_1

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free