The Influence of Mobile Banking Attributes on Cashless Society Through Anthropomorphism Adaptation and Task-Fit Technology
Keywords:
UTAUT Model, cashless society, adaptive anthropomorphism, Task-fit technologyAbstract
This study aimed to analyze the adaptive anthropomorphism and task-fit technology as mediator variables that mediate the relationship between performance expectancy, effort expectancy, perceived security, and cashless society in traditional market traders. The urgency of this study was to identify factors that could facilitate aspects of mobile banking service attributes in encouraging cashless society activities among traditional market traders. The empirical research was quantitative by design, The data respondents consisted of 279 traditional market who had used mobile banking services. The study analysis was to measure the structural relationship integrated with PLS-SEM and This research capproach used tools Smart-PLS 3, which had two stages in analyzing research data, which could provide information related to the influence of mediators and their levels. The results of this study provide information about the benefits of using Mobile Banking integrated with UTAUT and TTF so that it can provide scientific explanations, evidence, and sources from customers who use Mobile Banking in financial transactions. Theoretically, adaptive anthropomorphism is positioned as a mediator that bridges the relationship between facilitating conditions, perceived security, perceived trust, and cashless society, whereas task-fit technology can mediate this linkage between effort expectancy, perceived security, perceived trust, and cashless society in the context of mobile banking service. Practically, our findings could be useful for banking management because facilitating conditions positively encourages the use of non-cash payments in the market between merchants and consumers where proof of payment is represented through human-like voice interaction in mobile banking services.
References
Afeti, E. Y., & Owusu, A. (2022). Impact of Mobile Payments on Micro-Business Activities: A Developing Country Experience: Impact of Mobile Payments. Digital Innovations, Business and Society in Africa: New Frontiers and a Shared Strategic Vision, 75–95.
Alalwan, A. A., Dwivedi, Y. K., Rana, N. P., & Algharabat, R. (2018). Examining factors influencing Jordanian customers’ intentions and adoption of internet banking: Extending UTAUT2 with risk. Journal of Retailing and Consumer Services, 40, 125–138.
Almaiah, M. A., Al-Otaibi, S., Shishakly, R., Hassan, L., Lutfi, A., Alrawad, M., Qatawneh, M., & Alghanam, O. A. (2023). Investigating the Role of Perceived Risk, Perceived Security and Perceived Trust on Smart m-Banking Application Using SEM. Sustainability (Switzerland), 15(13), 1–17. https://doi.org/10.3390/su15139908
Aman, I., Yuvita, Y., & Hafd, A. (2023). Efektivitas Penggunaan Quick Response Indonesia Standard (QRIS) di Pasar Tradisional Pabaeng-Baeng Kota Makassar. eCo-Buss, 6(2), 870–881. https://doi.org/10.32877/eb.v6i2.105
Arcand, M., PromTep, S., Brun, I., & Rajaobelina, L. (2017). Mobile banking service quality and customer relationships. International Journal of Bank Marketing, 35(7), 1068–1089.
Azis, I. J. (2024). Financing Gap and Digitalization. In Listen and Design: On Micro, Small and Medium Enterprises (pp. 77–99). Springer.
Baabdullah, A. M., Alalwan, A. A., Rana, N. P., Kizgin, H., & Patil, P. (2019). Consumer use of mobile banking (M-Banking) in Saudi Arabia: Towards an integrated model. International Journal of Information Management, 44, 38–52.
Baptista, G., & Oliveira, T. (2015). Understanding mobile banking: The unified theory of acceptance and use of technology combined with cultural moderators. Computers in Human Behavior, 50, 418–430.
Changchun, G., Haider, M. J., & Akram, T. (2017). Investigation of the Effects of Task Technology Fit, Attitude and Trust on Intention to Adopt Mobile Banking: Placing the Mediating Role of Trialability. International Business Research, 10(4), 77. https://doi.org/10.5539/ibr.v10n4p77
Che, M., Say, S. Y. A., Yu, H., Zhou, Q., Shu, J., Sun, W., Luo, X., & Xu, H. (2023). Investigating customers’ continuous trust towards mobile banking apps. Humanities and Social Sciences Communications. https://doi.org/10.1057/s41599-023-02483-3
Chi, O. H., Jia, S., Li, Y., & Gursoy, D. (2021). Developing a formative scale to measure consumers’ trust toward interaction with artificially intelligent (AI) social robots in service delivery. Computers in Human Behavior, 118(May 2020), 106700. https://doi.org/10.1016/j.chb.2021.106700
Chin, W. W. (1998). Commentary: Issues and Opinion on Structural Equation Modeling. MIS Quarterly, 22(1), vii–xvi.
Dahlberg, T., Guo, J., & Ondrus, J. (2015). A critical review of mobile payment research. Electronic Commerce Research and Applications, 14(5), 265–284.
de Andrés-Sánchez, J., & Gené-Albesa, J. (2023). Assessing attitude and behavioral intention toward chatbots in an insurance setting: A mixed method approach. International Journal of Human–Computer Interaction, 1–16.
de Kloet, M., & Yang, S. (2022). The effects of anthropomorphism and multimodal biometric authentication on the user experience of voice intelligence. Frontiers in Artificial Intelligence, 5. https://doi.org/10.3389/frai.2022.831046
Eneizan, B., Mohammed, A. G., Alnoor, A., Alabboodi, A. S., & Enaizan, O. (2019). Customer acceptance of mobile marketing in Jordan: An extended UTAUT2 model with trust and risk factors. International Journal of Engineering Business Management, 11, 1847979019889484.
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50.
Geebren, A., Jabbar, A., & Luo, M. (2021). Examining the role of consumer satisfaction within mobile eco-systems: Evidence from mobile banking services. Computers in Human Behavior, 114(September 2020), 106584. https://doi.org/10.1016/j.chb.2020.106584
Guo, J., & Bouwman, H. (2016). An analytical framework for an m-payment ecosystem: A merchants׳ perspective. Telecommunications Policy, 40(2–3), 147–167.
Gupta, S., & Dhingra, S. (2022). Modeling the key factors influencing the adoption of mobile financial services: An interpretive structural modeling approach. Journal of Financial Services Marketing, 27(2), 96–110.
Hair Jr, J. F., Hult, G. T. M., Ringle, C. M., Sarstedt, M., Danks, N. P., Ray, S., Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2021). Evaluation of formative measurement models. Partial Least Squares Structural Equation Modeling (PLS-SEM) Using R: A Workbook, 91–113.
Hair Jr, J. F., Matthews, L. M., Matthews, R. L., & Sarstedt, M. (2017). PLS-SEM or CB-SEM: updated guidelines on which method to use. International Journal of Multivariate Data Analysis, 1(2), 107–123.
Jamshidi, D., Keshavarz, Y., Kazemi, F., & Mohammadian, M. (2018). Mobile banking behavior and flow experience: An integration of utilitarian features, hedonic features and trust. International Journal of Social Economics, 45(1), 57–81.
Kaur, S., & Arora, S. (2021). Role of perceived risk in online banking and its impact on behavioral intention: Trust as a moderator. Journal of Asia Business Studies, 15(1), 1–30. https://doi.org/10.1108/JABS-08-2019-0252
Komulainen, H., & Saraniemi, S. (2019). Customer centricity in mobile banking: A customer experience perspective. International Journal of Bank Marketing, 37(5), 1082–1102.
Kosim, K. P., & Legowo, N. (2021). Factors affecting consumer intention on QR payment of mobile banking: A case study in Indonesia. The Journal of Asian Finance, Economics and Business, 8(5), 391–401.
Kusuma, M. W. (2023). Pedagang di Pasar Anyar Singaraja Kuasai 3-12 Kios. detikNews. https://www.detik.com/bali/berita/d-6554801/pedagang-di-pasar-anyar-singaraja-kuasai-3-12-kios.
Laukkanen, T. (2016). Consumer adoption versus rejection decisions in seemingly similar service innovations: The case of the Internet and mobile banking. Journal of Business Research, 69(7), 2432–2439.
Lee, J.-C., & Chen, X. (2022). Exploring users’ adoption intentions in the evolution of artificial intelligence mobile banking applications: The intelligent and anthropomorphic perspectives. International Journal of Bank Marketing, 40(4), 631–658.
Lestari, D., Darma, D., & Muliadi, M. (2020). Fintech and micro, small and medium enterprises development: Special reference to Indonesia. Entrepreneurship Review, 1(1), 1–9.
Lyu, V. C., Chin, W., Zhang, H., & Liu, V. (2022). Value added or overload? A study of the countervailing effects of non‐core features on mobile banking apps. Journal of Consumer Behaviour, 21(3), 602–613.
Mahfuz, M. A., Khanam, L., & Wang, H. (2017). The influence of culture on m-banking technology adoption: An integrative approaches of UTAUT2 and ITM. PICMET 2016 - Portland International Conference on Management of Engineering and Technology: Technology Management for Social Innovation, Proceedings, 824–835. https://doi.org/10.1109/PICMET.2016.7806814
Manser Payne, E. H., Peltier, J., & Barger, V. A. (2021). Enhancing the value co-creation process: Artificial intelligence and mobile banking service platforms. Journal of Research in Interactive Marketing, 15(1), 68–85.
Maurida, I., Hanna, S. R., & Yuwana, S. I. P. (2024). Optimalisasi Pasar Tradisional Dalam Meningkatkan Minat Pengunjung Di Pasar Tanjung Kabupaten Jember. Khidmah: Jurnal Pengabdian Masyarakat, 2(1), 13–25.
McLean, G., Osei-Frimpong, K., Al-Nabhani, K., & Marriott, H. (2020). Examining consumer attitudes towards retailers’m-commerce mobile applications–An initial adoption vs. Continuous use perspective. Journal of Business Research, 106, 139–157.
Moghavvemi, S., Mei, T. X., Phoong, S. W., & Phoong, S. Y. (2021). Drivers and barriers of mobile payment adoption: Malaysian merchants’ perspective. Journal of Retailing and Consumer Services, 59, 102364.
Molina-Collado, A., Salgado-Sequeiros, J., Gómez-Rico, M., Aranda García, E., & De Maeyer, P. (2021). Key themes in consumer financial services research from 2000 to 2020: A bibliometric and science mapping analysis. International Journal of Bank Marketing, 39(7), 1446–1478.
Moriuchi, E. (2021). An empirical study on anthropomorphism and engagement with disembodied AIs and consumers’ re-use behavior. Psychology and Marketing, 38(1), 21–42. https://doi.org/10.1002/mar.21407
Njenga, A. K., Litondo, K., & Omwansa, T. (2016). A theoretical review of mobile commerce success determinants. Journal of Information Engineering and Applications, 6(5), 13–23.
Nubatonis, J. P. S., Ballo, F. W., & Kiak, N. T. (2024). Implementasi Quick Response Code Indonesian Standard (QRIS) Untuk Pelaku Usaha Di Pasar Tradisional: Studi Kasus Pada Pasar Tradisional Di Kota Kupang. Jurnal Ekonomi Dan Pembangunan Indonesia, 2(2), 1–8.
Ochs, M., Pelachaud, C., & Mckeown, G. (2017). A User Perception—Based Approach to Create Smiling Embodied Conversational Agents. ACM Transactions on Interactive Intelligent Systems (TiiS), 7(1), 1–33.
Oliveira, T., & Tam, C. (2016). Performance impact of mobile banking: Using the task-technology fit (TTF) approach. International Journal of Bank Marketing, 34(4).
Oruganti, S. C. (2020). Virtual bank assistance: An AI based voice bot for better banking. International Journal of Research, 9(1), 177–183.
Pelau, C., Dabija, D.-C., & Ene, I. (2021). What makes an AI device human-like? The role of interaction quality, empathy and perceived psychological anthropomorphic characteristics in the acceptance of artificial intelligence in the service industry. Computers in Human Behavior, 122, 106855.
Prasetia, P. B. W., & Lestari, N. P. N. E. (2023). Cashless Society: Tantangan Dan Kesiapan Pedagang Pasar Tradisional Di Kota Denpasar. Buletin Studi Ekonomi, 28(01), 83. https://doi.org/10.24843/bse.2023.v28.i01.p08
Priananda, I., Stevani, M., Sutanto, T. I., & Mariani, M. (2020). Grassroots economy towards cashless society: An empirical analysis of micro-merchant’s readiness in continuing the usage of cashless payment system. International Journal of Scientific & Technology Research, 9(3), 929–928.
Priya, B., & Sharma, V. (2023). Exploring users’ adoption intentions of intelligent virtual assistants in financial services: An anthropomorphic perspectives and socio-psychological perspectives. Computers in Human Behavior, 148, 107912.
Rachapaettayakom, P., Wiriyapinit, M., Cooharojananone, N., Tanthanongsakkun, S., & Charoenruk, N. (2020). The need for financial knowledge acquisition tools and technology by small business entrepreneurs. Journal of Innovation and Entrepreneurship, 9, 1–28.
Raharjo, M. (2023). ‘QRIS Cross Border’as Digital Financial Inclusion Acceleration in Southeast Asia. Global Local Interactions: Journal of International Relations, 3(1), 151–161.
Rahi, S., & Abd. Ghani, M. (2019). Investigating the role of UTAUT and e-service quality in internet banking adoption setting. The TQM Journal, 31(3), 491–506.
Ratna, S., Nayati Utami, H., Siti Astuti, E., & Muflih, M. (2020). The technology tasks fit, its impact on the use of information system, performance and users’ satisfaction. VINE Journal of Information and Knowledge Management Systems, 50(3), 369–386.
Shahid, S., Islam, J. U., Malik, S., & Hasan, U. (2022). Examining consumer experience in using m-banking apps: A study of its antecedents and outcomes. Journal of Retailing and Consumer Services, 65, 102870.
Tran, H. T. T., & Corner, J. (2016). The impact of communication channels on mobile banking adoption. International Journal of Bank Marketing, 34(1), 78–109.
Wang, C., Wang, Y., Chen, Y., Liu, H., & Liu, J. (2020). User authentication on mobile devices: Approaches, threats and trends. Computer Networks, 170, 107118.
Xia, H., Gao, Y., & Zhang, J. Z. (2023). Understanding the adoption context of China’s digital currency electronic payment. Financial Innovation, 9(1), 63.
Zhou, T., Lu, Y., & Wang, B. (2010). Integrating TTF and UTAUT to explain mobile banking user adoption. Computers in Human Behavior, 26(4), 760–767. https://doi.org/10.1016/j.chb.2010.01
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