Peran Kesiapan Teknologi Dalam Minat Menggunakan Aplikasi Pembayaran Seluler Di Masa Pandemi Covid-19

Main Article Content

Widi Senalasari
Wahyu Rafdinal
Agri Qisthi

Abstract

Penelitian ini bertujuan untuk menganalisis minat penggunaan aplikasi pembayaran seluler dalam masa pandemi Covid-19 dengan menggunakan model TRI dan TPB. Data dikumpulkan dari 200 pengguna aplikasi pembayaran seluler di Indonesia. Teknik analisis data yang digunakan yaitu SEM-PLS. Hasil penelitian membuktikan bahwa semua konstruk TPB yaitu sikap, norma subjektif, dan kontrol prilaku yang dirasakan berpengaruh signifikan terhadap minat penggunaan aplikasi pembayaran seluler. TRI berpengaruh terhadap sikap. TRI tidak berpengaruh secara langsung terhadap minat penggunaan aplikasi pembayaran seluler, tetapi berpengaruh melalui sikap. Hasil dari penelitian ini akan membantu penyedia layanan aplikasi pembayaran seluler dan pembuat kebijakan dalam merencanakan layanan dan meningkatkan niat penggunaan aplikasi pembayaran seluler pada masa pandemi Covid-19. Penelitian ini adalah yang pertama secara empiris mengguji model TPB dan TRI untuk menjelaskan adopsi dan minat menggunakan aplikasi pembayaran seluler pada masa pandemi Covid-19. Hasil penelitian akan menambah pengetahuan yang ada tentang literatur aplikasi pembayaran seluler pada masa pandemi.

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How to Cite
Senalasari, W., Rafdinal, W., & Qisthi, A. (2021). Peran Kesiapan Teknologi Dalam Minat Menggunakan Aplikasi Pembayaran Seluler Di Masa Pandemi Covid-19. Jurnal Riset Bisnis Dan Investasi, 7(1), 22-32. https://doi.org/10.35313/jrbi.v7i1.2266
Section
Regular Article

References

Agusta, J. (2018, March 6). Mobile Payments in Indonesia: Race to Big Data Domination. Forbes Indonesia. https://medium.com/@joshuaagusta/mobile-payments-in-indonesia-race-to-big-data-domination-e1fb23211fc4
Ajzen, I. (1985). From intentions to actions: A theory of planned behavior. Action Control, 11–39. https://doi.org/10.1007/978-3-642-69746-3_2
Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50, 179–211. https://doi.org/10.4135/9781446249215.n22
BPS. (2020). Laporan bulanan data sosial ekonomi April 2020. Badan Pusat Statistik.
Bradley, J. (2012). If We Build It They Will Come? The Technology Acceptance Model. In Information Systems Theory: Explaining and Predicting Our Digital Society (Vol. 1, pp. 19–34). Springer Science+Business Media. https://doi/10.1007/978-1-4419-6108-2
Cao, X., Yu, L., Liu, Z., Gong, M., & Adeel, L. (2018). Understanding mobile payment users’ continuance intention: A trust transfer perspective. Internet Research, 28(2), 456–476. https://doi.org/10.1108/IntR-11-2016-0359
Chin, W. W., Peterson, R. A., & Brown, S. P. (2008). Structural equation modeling in marketing: Some practical reminders. Journal of Marketing Theory and Practice, 16(4), 287–298.
Fan, J., Shao, M., Li, Y., & Huang, X. (2018). Understanding users’ attitude toward mobile payment use: A comparative study between China and the USA. Industrial Management & Data Systems, 118(3), 524–540. https://doi.org/10.1108/IMDS-06-2017-0268
Fishbein, M., & Ajzen, I. (1975). Belief, Attitude, Intention, and Behavior: An Introduction to Theory and Research. Addison-Wesley.
Hair, J. E., Hult, G. T., Ringle, C. M., & Sarstedt, M. (2017). A primer on partial least squares structural equation modeling (PLS-SEM) (2nd ed.). Sage.
Hair, J. F., Anderson, R. E., Babin, B. J., & Black, W. C. (2010). Multivariate data analysis: A global perspective (Vol. 7). Upper Saddle River, NJ: Pearson.
Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115–135. https://doi.org/10.1007/s11747-014-0403-8
Humbani, M., & Wiese, M. (2019a). An integrated framework for the adoption and continuance intention to use mobile payment apps. International Journal of Bank Marketing. https://doi.org/10.1108/IJBM-03-2018-0072
Humbani, M., & Wiese, M. (2019b). An integrated framework for the adoption and continuance intention to use mobile payment apps. International Journal of Bank Marketing, 37(2), 646–664. https://doi.org/10.1108/IJBM-03-2018-0072
Kalinić, Z., Liébana-Cabanillas, F. J., Muñoz-Leiva, F., & Marinković, V. (2019). The moderating impact of gender on the acceptance of peer-to-peer mobile payment systems. International Journal of Bank Marketing, 38(1), 138–158. https://doi.org/10.1108/IJBM-01-2019-0012
Kim, C., Mirusmonov, M., & Lee, I. (2010). An empirical examination of factors influencing the intention to use mobile payment. Computers in Human Behavior, 26(3), 310–322. https://doi.org/10.1016/j.chb.2009.10.013
Kim, & Kankanhalli. (2009). Investigating User Resistance to Information Systems Implementation: A Status Quo Bias Perspective. MIS Quarterly, 33(3), 567. https://doi.org/10.2307/20650309
Liébana-Cabanillas, F., Sánchez-Fernández, J., & Muñoz-Leiva, F. (2014). Antecedents of the adoption of the new mobile payment systems: The moderating effect of age. Computers in Human Behavior, 35, 464–478. https://doi.org/10.1016/j.chb.2014.03.022
Lin, C.-H., Shih, H.-Y., & Sher, P. J. (2007). Integrating technology readiness into technology acceptance: The TRAM model. Psychology & Marketing, 24(7), 641–667. https://doi.org/10.1002/mar
Lin, J. S. C., & Chang, H. C. (2011). The role of technology readiness in self-service technology acceptance. Managing Service Quality, 21(4), 424–444. https://doi.org/10.1108/09604521111146289
Lu, H., Stratton, C. W., & Tang, Y. W. (2020). Outbreak of pneumonia of unknown etiology in Wuhan, China: The mystery and the miracle. Journal of Medical Virology, 92(4), 401–402. https://doi.org/10.1002/jmv.25678
McNair, C. (2018, December 17). Global Proximity Mobile Payment Users [Data and Research on Digital for Business Proffesionals]. EMarketer. https://www.emarketer.com/content/global-proximity-mobile-payment-users
Muñoz-Leiva, F., Climent-Climent, S., & Liébana-Cabanillas, F. (2017). Determinants of intention to use the mobile banking apps: An extension of the classic TAM model. Spanish Journal of Marketing - ESIC, 21(1), 25–38. https://doi.org/10.1016/j.sjme.2016.12.001
Parasuraman, A. (2000). Technology Readiness Index (TRI) a multiple-item scale to measure readiness to embrace new technologies. Journal of Service Research, 2(4), 307–320.
Parasuraman, A., & Colby, C. L. (2015). An updated and streamlined technology readiness index: TRI 2.0. Journal of Service Research, 18(1), 59–74.
Patil, P. P., Dwivedi, Y., & Rana, N. P. (2017). Digital payments adoption: An analysis of literature. LNCS, 61–70. https://doi.org/10.1007/978-3-319-68557-1
Safeena, R., Date, H., Hundewale, N., & Kammani, A. (2013). Combination of TAM and TPB in Internet Banking Adoption. International Journal of Computer Theory and Engineering, 146–150. https://doi.org/10.7763/IJCTE.2013.V5.665
Sainy, R., & Naidu, A. (2018). Does technology readiness predict banking self service technologies usage in India? International Journal of Electronic Banking, 1(2), 129–149. https://doi.org/10.1504/ijebank.2018.10016651
Schierz, P. G., Schilke, O., & Wirtz, B. W. (2010). Understanding consumer acceptance of mobile payment services: An empirical analysis. Electronic Commerce Research and Applications, 9(3), 209–216. https://doi.org/10.1016/j.elerap.2009.07.005
Seol, S., Lee, H., & Zo, H. (2016). Exploring factors affecting the adoption of mobile office in business: An integration of TPB with perceived value. International Journal of Mobile Communications, 14(1), 1. https://doi.org/10.1504/IJMC.2016.073341
Sinha, M., Majra, H., Hutchins, J., & Saxena, R. (2019). Mobile payments in India: The privacy factor. International Journal of Bank Marketing, 37(1), 192–209. https://doi.org/10.1108/IJBM-05-2017-0099
Slade, E. L., Williams, M. D., & Dwivedi, Y. K. (2014). Devising a research model to examine adoption of mobile payments: An extension of UTAUT2. The Marketing Review, 14(3), 310–335. https://doi.org/10.1362/146934714X14024779062036
Sohrabi, C., Alsafi, Z., Neill, N. O., Khan, M., & Kerwan, A. (2020). World Health Organization declares global emergency: A review of the 2019 novel coronavirus (COVID-19). International Journal of Surgery, 76, 71–76.
Sun, S., Law, R., & Schuckert, M. (2020). Mediating effects of attitude, subjective norms and perceived behavioural control for mobile payment-based hotel reservations. International Journal of Hospitality Management, 84, 102331. https://doi.org/10.1016/j.ijhm.2019.102331
Taylor, S., & Todd, P. A. (1995). Understanding Information Technology Usage: A Test of Competing Models. Information Systems Research, 6(2), 144–176. https://doi.org/10.1287/isre.6.2.144
Venkatesh, V. (2000). Determinants of perceived ease of use: Integrating control, intrinsic motivation, and emotion into the technology acceptance model. Information Systems Research, 11(4), 324–365. https://doi.org/1047-7047/00/1104/0342$05.00
Verma, S., Chaurasia, S. S., & Bhattacharyya, S. S. (2019). The effect of government regulations on continuance intention of in-store proximity mobile payment services. International Journal of Bank Marketing, 38(1), 34–62. https://doi.org/10.1108/IJBM-10-2018-0279
WHO. (2020a). Coronavirus disease 2019 (COVID-19) situation report—83. In World Health Organization (Issue April). https://doi.org/10.1001/jama.2020.2633
WHO. (2020b). WHO COVID-19 global data. World Health Organization.
Wiese, M., & Humbani, M. (2019). Exploring technology readiness for mobile payment app users. International Review of Retail, Distribution and Consumer Research. https://doi.org/10.1080/09593969.2019.1626260

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