Drivers of mobile payment acceptance: The impact of network externalities

Qasim, Ajao; Abu-Shanab, Emad · 2015 · Crossref

DOI: 10.1007/s10796-015-9598-6

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Summary

This study investigates the drivers of mobile banking (MBanking) adoption within the Portuguese context, addressing the research question of what factors influence a client’s decision to adopt this technology. The motivation stems from Portugal’s high mobile phone penetration and broadband connectivity, which position the country as a likely leader in early mobile technology adoption, despite currently low MBanking usage rates compared to the European average. The paper aims to provide banks with a comprehensive overview of adoption drivers to optimize implementation strategies. To answer this question, the author developed a novel conceptual model that integrates three distinct theoretical frameworks: the Task Technology Fit (TTF) model, representing rational knowledge; the Unified Theory of Acceptance and Use of Technology (UTAUT), representing empirical knowledge; and an Initial Trust model, representing individual first impressions. This integrated approach allows for the examination of the relationship between rational assessment, empirical experience, and initial beliefs regarding MBanking. The study employed an empirical test involving a survey of potential and actual users in Portugal. Data were analyzed to determine the significance of various constructs on behavioral intention and actual adoption, utilizing Partial Least Squares (PLS) analysis as indicated by the methodology section. The results demonstrate that facilitating conditions, behavioral intention, task technology fit, technology characteristics, performance expectancy, and initial trust have significant effects on MBanking adoption. Crucially, the study found that the combined effect of task technology fit, technology characteristics, performance expectancy, and initial trust on behavioral intention overpowers the effects of effort expectancy and social influence. This finding suggests that rational fit and initial trust are more critical determinants than ease of use or social pressure in this context. The integrated model proved highly effective, explaining 66.7% of the variance in MBanking adoption. The significance of this research lies in its validation of an integrated theoretical framework for understanding technology adoption. By proving that the combination of TTF, UTAUT, and initial trust provides a more robust explanation than individual models, the study offers valuable theoretical implications for information systems research. Practically, the findings provide managerial insights for banking technology and marketing departments, highlighting that optimizing the fit between technology and user tasks, ensuring strong performance expectations, and building initial trust are the most effective strategies for driving MBanking adoption in markets with high mobile infrastructure but low current usage.

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• acceptance adoption