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Mobile Application Adoption Predictors: Systematic Review of UTAUT2 Studies Using Weight Analysis

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.
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Kuttimani Tamilmani, Nripendra Rana, Yogesh Dwivedi. Mobile Application Adoption Predictors: Systematic Review of UTAUT2 Studies Using Weight Analysis. 17th Conference on e-Business, e-Services and e-Society (I3E), Oct 2018, Kuwait City, Kuwait. pp.1-12, ⟨10.1007/978-3-030-02131-3_1⟩. ⟨hal-02274184⟩

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