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Factors Determining Consumer Acceptance of NFC Mobile Payment: An Extended Mobile Technology Acceptance Model

Author

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  • Qingyu Zhang

    (Research Institute of Business Analytics and Supply Chain Management, College of Management, Shenzhen University, Shenzhen 518060, China)

  • Salman Khan

    (Research Institute of Business Analytics and Supply Chain Management, College of Management, Shenzhen University, Shenzhen 518060, China)

  • Mei Cao

    (School of Business & Economics, University of Wisconsin-Superior, Superior, WI 54880, USA)

  • Safeer Ullah Khan

    (Department of Business Administration, Gomal University, Dera Ismail Khan 29050, Pakistan)

Abstract

The demand for mobile payments using smartphones to substitute the need for cash, credit cards, or checks is swiftly increasing in Pakistan. This study investigates the factors determining consumers’ behavioral intention to adopt near-field communication mobile payment from a developing country’s viewpoint. A conceptual framework was adopted based on the mobile technology acceptance model (MTAM), integrating self-efficacy theory, critical mass theory, flow theory, and system and service quality to elucidate the behavioral intention. Data were collected through a self-administered questionnaire applied to 310 nonusers of near-field communication mobile payment in Pakistan. The analysis was performed using SmartPLS3.0. The results demonstrated that other independent variables are the main predictors of the intention to adopt mobile payment besides technology self-efficacy, perceived critical mass, and mobile ease of use. The study concludes with key implications and future work directions concerning the limitation of this study.

Suggested Citation

  • Qingyu Zhang & Salman Khan & Mei Cao & Safeer Ullah Khan, 2023. "Factors Determining Consumer Acceptance of NFC Mobile Payment: An Extended Mobile Technology Acceptance Model," Sustainability, MDPI, vol. 15(4), pages 1-18, February.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:4:p:3664-:d:1070941
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    References listed on IDEAS

    as
    1. Francisco Liébana-Cabanillas & Nidhi Singh & Zoran Kalinic & Elena Carvajal-Trujillo, 2021. "Examining the determinants of continuance intention to use and the moderating effect of the gender and age of users of NFC mobile payments: a multi-analytical approach," Information Technology and Management, Springer, vol. 22(2), pages 133-161, June.
    2. Rishi Manrai & Kriti Priya Gupta, 2022. "A study on factors influencing mobile payment adoption using theory of diffusion of innovation," International Journal of Business Information Systems, Inderscience Enterprises Ltd, vol. 39(2), pages 219-240.
    3. Mahler, Alwin & Rogers, Everett M., 1999. "The diffusion of interactive communication innovations and the critical mass: the adoption of telecommunications services by German banks," Telecommunications Policy, Elsevier, vol. 23(10-11), pages 719-740, November.
    4. Gudergan, Siegfried P. & Ringle, Christian M. & Wende, Sven & Will, Alexander, 2008. "Confirmatory tetrad analysis in PLS path modeling," Journal of Business Research, Elsevier, vol. 61(12), pages 1238-1249, December.
    5. Rana Saeed Al-Maroof & Khadija Alhumaid & Iman Akour & Said Salloum, 2021. "Factors That Affect E-Learning Platforms after the Spread of COVID-19: Post Acceptance Study," Data, MDPI, vol. 6(5), pages 1-20, May.
    6. Hong-Lei Mu & Young-Chan Lee, 2021. "How Inclusive Digital Financial Services Impact User Behavior: A Case of Proximity Mobile Payment in Korea," Sustainability, MDPI, vol. 13(17), pages 1-23, August.
    7. Dmaithan Almajali & Manaf Al-Okaily & Khaleel Al-Daoud & Sulaiman Weshah & Aijaz A. Shaikh, 2022. "Go Cashless! Mobile Payment Apps Acceptance in Developing Countries: The Jordanian Context Perspective," Sustainability, MDPI, vol. 14(20), pages 1-15, October.
    8. Wynne W. Chin & Barbara L. Marcolin & Peter R. Newsted, 2003. "A Partial Least Squares Latent Variable Modeling Approach for Measuring Interaction Effects: Results from a Monte Carlo Simulation Study and an Electronic-Mail Emotion/Adoption Study," Information Systems Research, INFORMS, vol. 14(2), pages 189-217, June.
    9. Lai-Wan Wong & Garry Wei-Han Tan & Jun-Jie Hew & Keng-Boon Ooi & Lai-Ying Leong, 2022. "Mobile social media marketing: a new marketing channel among digital natives in higher education?," Journal of Marketing for Higher Education, Taylor & Francis Journals, vol. 32(1), pages 113-137, January.
    10. Chen, Yi-Mu & Hsu, Tsuen-Ho & Lu, Yu-Jou, 2018. "Impact of flow on mobile shopping intention," Journal of Retailing and Consumer Services, Elsevier, vol. 41(C), pages 281-287.
    11. Ozturk, Ahmet Bulent & Bilgihan, Anil & Nusair, Khaldoon & Okumus, Fevzi, 2016. "What keeps the mobile hotel booking users loyal? Investigating the roles of self-efficacy, compatibility, perceived ease of use, and perceived convenience," International Journal of Information Management, Elsevier, vol. 36(6), pages 1350-1359.
    12. Viswanath Venkatesh & Fred D. Davis, 2000. "A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies," Management Science, INFORMS, vol. 46(2), pages 186-204, February.
    13. H. Leibenstein, 1950. "Bandwagon, Snob, and Veblen Effects in the Theory of Consumers' Demand," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 64(2), pages 183-207.
    14. Michael R Mullen, 1995. "Diagnosing Measurement Equivalence in Cross-National Research," Journal of International Business Studies, Palgrave Macmillan;Academy of International Business, vol. 26(3), pages 573-596, September.
    15. Nan, Dongyan & Lee, Haein & Kim, Yerin & Kim, Jang Hyun, 2022. "My video game console is so cool! A coolness theory-based model for intention to use video game consoles," Technological Forecasting and Social Change, Elsevier, vol. 176(C).
    16. Baabdullah, Abdullah Mohammed, 2018. "Consumer adoption of Mobile Social Network Games (M-SNGs) in Saudi Arabia: The role of social influence, hedonic motivation and trust," Technology in Society, Elsevier, vol. 53(C), pages 91-102.
    17. Lew, Susan & Tan, Garry Wei-Han & Loh, Xiu-Ming & Hew, Jun-Jie & Ooi, Keng-Boon, 2020. "The disruptive mobile wallet in the hospitality industry: An extended mobile technology acceptance model," Technology in Society, Elsevier, vol. 63(C).
    18. de Luna, Iviane Ramos & Liébana-Cabanillas, Francisco & Sánchez-Fernández, Juan & Muñoz-Leiva, Francisco, 2019. "Mobile payment is not all the same: The adoption of mobile payment systems depending on the technology applied," Technological Forecasting and Social Change, Elsevier, vol. 146(C), pages 931-944.
    19. Marios Koufaris, 2002. "Applying the Technology Acceptance Model and Flow Theory to Online Consumer Behavior," Information Systems Research, INFORMS, vol. 13(2), pages 205-223, June.
    20. Ng, Felicity Zi-Xuan & Yap, Hui-Yee & Tan, Garry Wei-Han & Lo, Pei-San & Ooi, Keng-Boon, 2022. "Fashion shopping on the go: A Dual-stage predictive-analytics SEM-ANN analysis on usage behaviour, experience response and cross-category usage," Journal of Retailing and Consumer Services, Elsevier, vol. 65(C).
    21. Nicole Koenig-Lewis & Morgan Marquet & Adrian Palmer & Anita Lifen Zhao, 2015. "Enjoyment and social influence: predicting mobile payment adoption," The Service Industries Journal, Taylor & Francis Journals, vol. 35(10), pages 537-554, July.
    22. Hooks, D. & Davis, Z. & Agrawal, V. & Li, Z., 2022. "Exploring factors influencing technology adoption rate at the macro level: A predictive model," Technology in Society, Elsevier, vol. 68(C).
    23. Türker, Cansu & Altay, Burak Can & Okumuş, Abdullah, 2022. "Understanding user acceptance of QR code mobile payment systems in Turkey: An extended TAM," Technological Forecasting and Social Change, Elsevier, vol. 184(C).
    24. Masuda, Hisashi & Han, Spring H. & Lee, Jungwoo, 2022. "Impacts of influencer attributes on purchase intentions in social media influencer marketing: Mediating roles of characterizations," Technological Forecasting and Social Change, Elsevier, vol. 174(C).
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    2. Amy H. I. Lee & He-Yau Kang, 2024. "A Model for Developing a Mobile Payment Service Framework," Mathematics, MDPI, vol. 12(13), pages 1-25, June.

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