Consumer Adoption of BRImo Mobile Banking Application: An Extended TAM Perspective

As a result of the pandemic, the way of life in Indonesia has changed to include always donning a mask when traveling, always using hand sanitizer, reducing outdoor activities, and avoiding mobility. Payment methods for transactions have also changed, such as cash, when people want to sell or buy goods. Due to the pandemic, people are asked to use non-cash payment methods such as e-wallet payments or mobile banking transfer methods. The purpose of the cashless payment method is to reduce the potential spread of the virus that would exist on paper money. This research with the Technology Acceptance Model (TAM) aims to determine the basis of users or customers using mobile banking applications with perceived usefulness, perceived ease of use, perceived risk, and perceived enjoyment on attitude toward using BRImo and to determine the effect of system trust and social-cultural influence on the intention to use BRImo. Google Forms was used to conduct an online survey for data collection. The research sample consisted of 200 participants. Respondents were users of the BRImo mobile banking application. This investigation uses PLS-SEM. The findings of this study indicate that perceived usefulness, perceived ease of use, perceived risk, and perceived enjoyment have an influence on attitude toward using BRImo. In addition, system trust and social-cultural influence have a significant impact on intention to use BRImo apps.

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References

• Agrebi S, Jallais J (2015) Explain the intention to use smartphones for mobile shopping. J Retail Consum Serv 22:16–23. https://doi.org/10.1016/j.jretconser.2014.09.003ArticleGoogle Scholar
• Alalwan AA, Baabdullah AM, Rana NP, Tamilmani K, Dwivedi YK (2018) Examining adoption of mobile internet in Saudi Arabia: extending TAM with perceived enjoyment, innovativeness and trust. Technol Soc 55:100–110. https://doi.org/10.1016/j.techsoc.2018.06.007ArticleGoogle Scholar
• Alrushiedat N, Olfman L, Kung M, van der Pol J (2010) Knowledge sharing motivations, perceived enjoyment, and anchoring effects on perceived usefulness of asynchronous online discussions. 16th Americas Conference on Information Systems 2010, AMCIS 2010, 1, 135–145 Google Scholar
• Bailey AA, Pentina I, Mishra AS, Ben Mimoun MS (2020) Exploring factors influencing US millennial consumers’ use of tap-and-go payment technology. Int Rev Retail Distrib Consum Res 30(2):143–163. https://doi.org/10.1080/09593969.2019.1667854ArticleGoogle Scholar
• Bangkara RP, Mimba NPSH (2016) Pengaruh Perceived Usefulness dan Perceived Ease Of Use pada Minat Penggunaan Internet Banking dengan Attitude Toward Using sebagai Variabel Intervening. E-Jurnal Akuntansi Universitas Udayana 16(3):2408–2434 Google Scholar
• Caffaro F, Micheletti Cremasco M, Roccato M, Cavallo E (2020) Drivers of farmers’ intention to adopt technological innovations in Italy: the role of information sources, perceived usefulness, and perceived ease of use. J Rural Stud 76(March):264–271. https://doi.org/10.1016/j.jrurstud.2020.04.028ArticleGoogle Scholar
• Chao CM (2019) Factors determining the behavioral intention to use mobile learning: an application and extension of the UTAUT model. Front Psychol 10(July):1–14. https://doi.org/10.3389/fpsyg.2019.01652ArticleGoogle Scholar
• Davis FD (1993) User acceptance of information technology: system characteristics, user perceptions and behavioral impacts. Int J Man-Machine Stud 38(3):475–487. https://doi.org/10.1006/imms.1993.1022ArticleGoogle Scholar
• Davis FD, Bagozzi RP, Warshaw PR (1989) User acceptance of computer technology: a comparison of two theoretical models. Manag Sci 35(8):982–1003. https://doi.org/10.1287/mnsc.35.8.982ArticleGoogle Scholar
• Harahap LK (2018) Analisis SEM (structural equation modelling) Dengan SMARTPLS (partial Least Square). Fakultas Sains Dan Teknologi Uin Walisongo Semarang 1:1 Google Scholar
• van der Heijden H (2004) User acceptance of hedonic information systems. MIS Q 28(4):695–704 ArticleGoogle Scholar
• Kasilingam DL (2020) Understanding the attitude and intention to use smartphone chatbots for shopping. Technol Soc 62(May):101280. https://doi.org/10.1016/j.techsoc.2020.101280ArticleGoogle Scholar
• Kwateng KO, Atiemo KAO, Appiah C, Owusu Kwateng K, Osei Atiemo KA, Appiah C (2019) Acceptance and use of mobile banking: an application of UTAUT2. J Enterp Inf Manag 32(1):118–151. https://doi.org/10.1108/JEIM-03-2018-0055ArticleGoogle Scholar
• Markus LM, Majchzak A, Gasser L (2004) Time files when You’re fun : cognitive absorption and beliefs about information technology usage. MIS Q 18(4):695–704 Google Scholar
• Merhi M, Hone K, Tarhini A (2019) A cross-cultural study of the intention to use mobile banking between Lebanese and British consumers: extending UTAUT2 with security, privacy and trust. Technol Soc 59:101151. https://doi.org/10.1016/j.techsoc.2019.101151ArticleGoogle Scholar
• Min S, So KKF, Jeong M (2019) Consumer adoption of the Uber mobile application: insights from diffusion of innovation theory and technology acceptance model. J Travel Tour Market 36(7):770–783. https://doi.org/10.1080/10548408.2018.1507866ArticleGoogle Scholar
• Naomi Adisty (2022) Mengulik Perkembangan Penggunaan Smartphone di Indonesia. GoodstatsId:1–1 Google Scholar
• Natarajan T, Balasubramanian SA, Kasilingam DL (2018) The moderating role of device type and age of users on the intention to use mobile shopping applications. Technol Soc 53:79–90. https://doi.org/10.1016/j.techsoc.2018.01.003ArticleGoogle Scholar
• Patel KJ, Patel HJ (2018) Adoption of internet banking services in Gujarat. Int J Bank Mark 36(1):147–169. https://doi.org/10.1108/ijbm-08-2016-0104ArticleGoogle Scholar
• Schurr PH, Ozanne JL (1985) Influences on exchange processes: buyers’ preconceptions of a Seller’s trustworthiness and bargaining toughness. J Consum Res 11(4):939. https://doi.org/10.1086/209028ArticleGoogle Scholar
• Shaikh IM, Qureshi MA, Noordin K, Shaikh JM, Khan A, Shahbaz MS (2020) Acceptance of Islamic financial technology (FinTech) banking services by Malaysian users: an extension of technology acceptance model. Foresight 22(3):367–383. https://doi.org/10.1108/FS-12-2019-0105ArticleGoogle Scholar
• Shin DH (2009) Towards an understanding of the consumer acceptance of mobile wallet. Comput Hum Behav 25(6):1343–1354. https://doi.org/10.1016/j.chb.2009.06.001ArticleGoogle Scholar
• Siagian SB, Tambunan K (2022) Faktor-faktor yang Mempengaruhi Minat Nasabah untuk Menggunakan Layanan Mobile Banking pada PT Bank Syariah Indonesia KCP Perbaungan. JIKEM: Jurnal Ilmu Komputer, Ekonomi Dan Manajemen 2(1):1051–1060 Google Scholar
• Sinurat EM, Sugiyanto LB (2022) Pengaruh perceived usefulness, perceived ease of use dan Promosi Penjualan melalui Mediasi attitude toward using dan perceived security terhadap behavioral intention to use (Studi Empiris: Pengguna Mobile wallet di Jakarta). Bus Manag J 18(1):17. https://doi.org/10.30813/bmj.v18i1.2820ArticleGoogle Scholar
• Tsang MM, Ho SC, Liang TP (2004) Consumer attitudes toward mobile advertising: an empirical study. Int J Electron Commer 8(3):65–78. https://doi.org/10.1080/10864415.2004.11044301ArticleGoogle Scholar
• Vahdat A, Alizadeh A, Quach S, Hamelin N (2021) Would you like to shop via mobile app technology? The technology acceptance model, social factors and purchase intention. Australas Mark J 29(2):187–197. https://doi.org/10.1016/j.ausmj.2020.01.002ArticleGoogle Scholar
• Venkatesh V, Bala H (2008) Technology acceptance model 3 and a research agenda on interventions. Decision Sciences Institute 39(2):273–315 ArticleGoogle Scholar
• Venkatesh V, Davis FD (2000) A theoretical extension of the technology acceptance model: four longitudinal field studies. Manag Sci 46(2):186–204 ArticleGoogle Scholar
• Venkatesh V, Morris MG, Davis GB, Davis FD (2003) User acceptance of information technology: toward a unified view. JSTOR 27(3):2003. https://doi.org/10.1016/j.inoche.2016.03.015ArticleGoogle Scholar
• Wang Y, Wang S, Wang J, Wei J, Wang C (2020) An empirical study of consumers’ intention to use ride-sharing services: using an extended technology acceptance model. Transportation 47(1):397–415. https://doi.org/10.1007/s11116-018-9893-4ArticleGoogle Scholar
• Yang K (2012) Consumer technology traits in determining mobile shopping adoption: an application of the extended theory of planned behavior. J Retail Consum Serv 19(5):484–491. https://doi.org/10.1016/j.jretconser.2012.06.003ArticleGoogle Scholar
• Yang M, Al Mamun A, Mohiuddin M, Nawi NC, Zainol NR (2021) Cashless transactions: a study on intention and adoption of e-wallets. Sustainability (Switzerland) 13(2):1–18. https://doi.org/10.3390/su13020831ArticleGoogle Scholar
• Zhang T, Tao D, Qu X, Zhang X, Zeng J, Zhu H, Zhu H (2020) Automated vehicle acceptance in China: social influence and initial trust are key determinants. Transp Res Part C Emerg Technol 112(September 2019):220–233. https://doi.org/10.1016/j.trc.2020.01.027ArticleGoogle Scholar

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Authors and Affiliations

1. Trilogi University, Jakarta, Indonesia Gita Amriena & Rizka Ramayanti

1. Gita Amriena