PERILAKU NASABAH DALAM PENGGUNAAN TECHNOLOGY ACCEPTANCE MODEL (TAM) KOMPETITIF PADA MOBILE BANKING DI WILAYAH KARESIDENAN KEDIRI (STUDI KASUS: BANK SYARIAH INDONESIA DI JAWA TIMUR)
DOI:
https://doi.org/10.31539/costing.v6i2.13177Keywords:
Attitude Towards Use, Behavioral Intention To Use, Actual Use, Perceived Ease Of Use, Perceived Enjoyment, Perceived Usefulness, Technology Acceptance Model, Mobile Banking, Bank Syariah Indonesia, Jawa Timur.Abstract
Penelitian ini bertujuan untuk menganalisis faktor-faktor yang mempengaruhi perilaku nasabah dalam menggunakan layanan mobile banking di Bank Syariah Indonesia di wilayah Jawa Timur menggunakan Technology Acceptance Model (TAM) kompetitif. Data diperoleh dari pengisian kuesioner oleh nasabah Bank Syariah Indonesia di wilayah Jawa Timur yang menggunakan layanan mobile banking. Data kemudian dianalisis menggunakan Structural Equation Modeling (SEM) dengan menggunakan software SmartPLS. Hasil penelitian menunjukkan bahwa faktor-faktor seperti perceived usefulness (PU), perceived ease of use (PEU), attitude towards use (AU), behavioral intention to use (BIU), actual use (ATU), dan perceived enjoyment (PUF) mempengaruhi perilaku nasabah dalam menggunakan layanan mobile banking. Bank perlu memperhatikan faktor-faktor tersebut untuk meningkatkan penggunaan mobile banking oleh nasabah dan meningkatkan kepuasan nasabah terhadap layanan yang disediakan. Penelitian ini merekomendasikan beberapa saran untuk Bank Terpilih di Jawa Timur dalam meningkatkan penggunaan mobile banking oleh nasabah di wilayah Karesidenan Kediri, antara lain meningkatkan kualitas layanan, memperluas jangkauan layanan, meningkatkan promosi dan edukasi, dan meningkatkan keamanan layanan.
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Alyahya, M., Agag, G., Aliedan, M., & Abdelmoety, Z. H. (2023). Understanding the factors affecting consumers’ behaviour when purchasing refurbished products: A chaordic perspective. Journal of Retailing and Consumer Services, 75(April), 103492. https://doi.org/10.1016/j.jretconser.2023.103492
Ariff, M. S. M., Yeow, S. M., Zakuan, N., Jusoh, A., & Bahari, A. Z. (2012). The Effects of Computer Self-Efficacy and Technology Acceptance Model on Behavioral Intention in Internet Banking Systems. Procedia - Social and Behavioral Sciences, 57, 448–452. https://doi.org/10.1016/j.sbspro.2012.09.1210
Bandinelli, R., Scozzafava, G., Bindi, B., & Fani, V. (2023). Blockchain and consumer behaviour: Results of a Technology Acceptance Model in the ancient wheat sector. Cleaner Logistics and Supply Chain, 8(July), 100117. https://doi.org/10.1016/j.clscn.2023.100117
Berlin, P., Seifart, C., & von Blanckenburg, P. (2022). Validation of the Readiness for End-of-Life Conversations (REOLC) scale in a German hospital setting. PEC Innovation, 1(November 2021), 100045. https://doi.org/10.1016/j.pecinn.2022.100045
Chen, Y., Khalid Khan, S., Shiwakoti, N., Stasinopoulos, P., & Aghabayk, K. (2023). Analysis of Australian public acceptance of fully automated vehicles by extending technology acceptance model. Case Studies on Transport Policy, 14(August), 101072. https://doi.org/10.1016/j.cstp.2023.101072
Chmielewska, M., Stokwiszewski, J., Filip, J., & Hermanowski, T. (2020). Motivation factors affecting the job attitude of medical doctors and the organizational performance of public hospitals in Warsaw, Poland. BMC Health Services Research, 20(1), 1–12. https://doi.org/10.1186/s12913-020-05573-z
Davis, F. D. (1993). User acceptance of information technology: system characteristics, user perceptions and behavioral impacts. International Journal of Man-Machine Studies, 38(3), 475–487. https://doi.org/10.1006/IMMS.1993.1022
German Ruiz-Herrera, L., Valencia-Arias, A., Gallegos, A., Benjumea-Arias, M., & Flores-Siapo, E. (2023). Technology acceptance factors of e-commerce among young people: An integration of the technology acceptance model and theory of planned behavior. Heliyon, 9(6), e16418. https://doi.org/10.1016/j.heliyon.2023.e16418
Herdhayinta, H., & Supriyono, R. A. (2019). Determinants of Bank Profitability: the Case of the Regional Development Bank (Bpd Bank) in Indonesia. Journal of Indonesian Economy and Business, 34(1), 1. https://doi.org/10.22146/jieb.17331
Huang, Y. C., Li, L. N., Lee, H. Y., Browning, M. H. E. M., & Yu, C. P. (2023). Surfing in virtual reality: An application of extended technology acceptance model with flow theory. Computers in Human Behavior Reports, 9(1), 100252. https://doi.org/10.1016/j.chbr.2022.100252
Kurniawati, H. A., Arif, A., & Winarno, W. A. (2017). Analisis Minat Penggunaan Mobile Banking Dengan Pendekatan Technology Acceptance Model (TAM) Yang Telah Dimodifikasi. E-Journal Ekonomi Bisnis Dan Akuntansi, 4(1), 24. https://doi.org/10.19184/ejeba.v4i1.4563
Ly, B., & Ly, R. (2022a). Internet banking adoption under Technology Acceptance Model—Evidence from Cambodian users. Computers in Human Behavior Reports, 7(July), 100224. https://doi.org/10.1016/j.chbr.2022.100224
Ly, B., & Ly, R. (2022b). Internet banking adoption under Technology Acceptance Model—Evidence from Cambodian users. Computers in Human Behavior Reports, 7(May), 100224. https://doi.org/10.1016/j.chbr.2022.100224
Ma, Q., & Liu, L. (2011). The Technology Acceptance Model. Advanced Topics in End User Computing, Volume 4, October 2017. https://doi.org/10.4018/9781591404743.ch006.ch000
Omar Ali, S. R., Wan Marzuki, W. N. K., Mohd Said, N. S., Abdul Manaf, S. M., & Adenan, N. D. (2020). Perceived Ease of Use and Trust Towards Intention to Use Online Banking in Malaysia. Jurnal Intelek, 15(1), 107–114. https://doi.org/10.24191/ji.v15i1.273
Petcharat, T., & Leelasantitham, A. (2021). A retentive consumer behavior assessment model of the online purchase decision-making process. Heliyon, 7(10), e08169. https://doi.org/10.1016/j.heliyon.2021.e08169
Purnamadewi, D. P., & Suresh, K. (2020). Understanding customer loyalty in the coffee shop industry (A survey in Jakarta, Indonesia). British Food Journal, 122(7), 2253–2271. https://doi.org/10.1108/BFJ-10-2019-0763
Putri, G. A., Widagdo, A. K., & Setiawan, D. (2023). Analysis of financial technology acceptance of peer to peer lending (P2P lending) using extended technology acceptance model (TAM). Journal of Open Innovation: Technology, Market, and Complexity, 9(1), 100027. https://doi.org/10.1016/j.joitmc.2023.100027
Reina Paz, M. D., & Rodríguez Vargas, J. C. (2023). Main theoretical consumer behavioural models. A review from 1935 to 2021. Heliyon, 9(3), e13895. https://doi.org/10.1016/j.heliyon.2023.e13895
Richter, N. F., Hauff, S., Kolev, A. E., & Schubring, S. (2023). Dataset on an extended technology acceptance model: A combined application of PLS-SEM and NCA. Data in Brief, 48, 109190. https://doi.org/10.1016/j.dib.2023.109190
Riegger, A. S., Merfeld, K., Klein, J. F., & Henkel, S. (2022). Technology-enabled personalization: Impact of smart technology choice on consumer shopping behavior. Technological Forecasting and Social Change, 181(March 2021), 121752. https://doi.org/10.1016/j.techfore.2022.121752
Rolik, Y. (2017). Risk Management in Implementing Wind Energy Project. Procedia Engineering, 178, 278–288. https://doi.org/10.1016/j.proeng.2017.01.115
SiaranPers. (2023). Siaran Pers: Operasional Bank Syariah Indonesia Kembali Normal Masyarakat Diminta Tenang. Otoritas Jasa Keuangan. https://ojk.go.id/id/berita-dan-kegiatan/siaran-pers/Pages/Operasional-Bank-Syariah-Indonesia-Kembali-Normal-Masyarakat-Diminta-Tenang.aspx
Sugiyono. (2011). Metode Penelitian Kuantitatif, Kualitatif dan R&D. Teknik Industri, 1.
Wang, C., Ahmad, S. F., Bani Ahmad Ayassrah, A. Y. A., Awwad, E. M., Irshad, M., Ali, Y. A., Al-Razgan, M., Khan, Y., & Han, H. (2023). An empirical evaluation of technology acceptance model for Artificial Intelligence in E-commerce. Heliyon, 9(8), e18349. https://doi.org/10.1016/j.heliyon.2023.e18349
Zaineldeen, S., Hongbo, L., Koffi, A. L., & Hassan, B. M. A. (2020). Technology acceptance model’ concepts, contribution, limitation, and adoption in education. Universal Journal of Educational Research, 8(11), 5061–5071. https://doi.org/10.13189/ujer.2020.081106
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2024-11-15
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