Predicting the Determinants of Mobile Payment Acceptance

Author:

Akgül Yakup1ORCID

Affiliation:

1. Alanya Alaaddin Keykubat University, Turkey

Abstract

This chapter aims to determine the main factors of mobile payment adoption and the intention to recommend this technology. An innovative research model has been proposed with the advancement of the body of knowledge on this subject that combines the strengths of two well-known theories: the extended unified theory of acceptance and use of technology (UTAUT2) with the innovation characteristics of the diffusion of innovations (DOI) with perceived security and intention to recommend the technology constructs. The research model was empirically tested using 259 responses from an online survey conducted in Turkey. Two techniques were used: first, structural equation modeling (SEM) was used to determine which variables had significant influence on mobile payment adoption; in a second phase, the neural network model was used to rank the relative influence of significant predictors obtained by SEM. This study found that the most significant variables impacting the intention to use were perceived technology security and innovativeness variables.

Publisher

IGI Global

Reference160 articles.

1. Akgül, Y. (2017a). Integrating e-trust antecedents into TAM to explain mobile banking behavioral intention: A SEM-neural network modeling. 4th International Conference on Business and Economics Studies (Özet Bildiri/Sözlü Sunum). (Yayın No:4406728)

2. An Analysis of Customers' Acceptance of Internet Banking

3. A SEM-Neural Network Approach for Predicting Antecedents of Factors Influencing Consumers' Intent to Install Mobile Applications

4. Akgül, Y. (2018c). Predicting determinants of Mobile banking adoption: A two-staged regression-neural network approach. 8th International Conference of Strategic Research on Scientific Studies and Education (ICoSReSSE) 2018 (Özet Bildiri/Sözlü Sunum). (Yayın No:4405980)

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