Adopsi Penggunaan Layanan Digital Fintech pada Generasi X di Indonesia
DOI:
https://doi.org/10.51903/kompak.v17i2.2181Keywords:
FinTech, Generation X, UTAUT, Behavioral Intention, SEM PLSAbstract
This study aims to analyze the impact of effort expectancy, perceived enjoyment, and performance expectancy on behavioral intention through customer satisfaction in the use of digital fintech services, with a particular focus on Generation X (ages 44-59). Data were collected through a questionnaire adapted from the Unified Theory of Acceptance and Use of Technology (UTAUT) model, involving 175 Generation X respondents in Indonesia. The sampling method used was non-probability sampling with a purposive sampling technique. Data analysis was conducted using Structural Equation Modeling-Partial Least Squares (SEM PLS) with Smart PLS software. The results of the study show that perceived enjoyment does not have a significant effect on behavioral intention, and effort expectancy does not significantly affect customer satisfaction. However, effort expectancy, performance expectancy, and customer satisfaction have a significant effect on behavioral intention. Perceived enjoyment and performance expectancy significantly influence customer satisfaction. On the other hand, effort expectancy does not significantly affect behavioral intention through customer satisfaction, while perceived enjoyment and performance expectancy significantly affect behavioral intention through customer satisfaction
References
Abu Daqar, M. A. M., Arqawi, S., & Karsh, S. A. (2020). Fintech in the eyes of Millennials and Generation Z (the financial behavior and Fintech perception). Banks and Bank Systems, 15(3), 20–28. https://doi.org/10.21511/bbs.15(3).2020.03
Adhini, N. V. (2024). 2023 Perceptions and drivers of the metaverse adoption_ A mixed‐methods study.pdf. International Journal of Consumer Studies.
AFTECH. (2023). Terkait fenomena tech winter yang terjadi , Pandu menambahkan , “ Perusahaan fintech di Indonesia melihat bahwa tech winter dijadikan sebagai momentum untuk melakukan inovasi , Beberapa anggota AFTECH yang diwawancara menyatakan bahwa mereka meluncurkan b. 2023–2025.
Bajunaied, K., Hussin, N., & Kamarudin, S. (2023). Behavioral intention to adopt FinTech services: An extension of unified theory of acceptance and use of technology. Journal of Open Innovation: Technology, Market, and Complexity, 9(1), 100010. https://doi.org/10.1016/j.joitmc.2023.100010
Bashir, I., & Madhavaiah, C. (2015). Consumer attitude and behavioural intention towards Internet banking adoption in India. Journal of Indian Business Research, 7(1), 67–102. https://doi.org/10.1108/JIBR-02-2014-0013
Calvo-Porral, C., & Pesqueira-Sanchez, R. (2020). Generational differences in technology behaviour: comparing millennials and Generation X. Kybernetes, 49(11), 2755–2772. https://doi.org/10.1108/K-09-2019-0598
Chao, C. (2019). Factors Determining the Behavioral Intention to Use Mobile Learning : An Application and Extension of the UTAUT Model. 10(July), 1–14. https://doi.org/10.3389/fpsyg.2019.01652
Chen, Q. L., & Zhou, Z. H. (2016). Unusual formations of superoxo heptaoxomolybdates from peroxo molybdates. Inorganic Chemistry Communications, 67(3), 95–98. https://doi.org/10.1016/j.inoche.2016.03.015
Elok, C. S., Kom, S., & Hidayati, A. (2021). Customer Loyalty in Digital Wallet Industry : the Role of Satisfaction , Effort Expectancy , Performance Expectancy , and Habit. 196(Icech), 340–352.
Emrah Cengiz Ph. (2010). Measuring Customer Satisfaction : Must or Not ? Journal of Naval Science and Engineering, 6(2), 76–88.
Esawe, A. T. (2022). Understanding mobile e-wallet consumers’ intentions and user behavior. Spanish Journal of Marketing - ESIC, 26(3), 363–384. https://doi.org/10.1108/SJME-05-2022-0105
Fitri, N. G., Hamzah, M. L., Zarnelly, & Anofrizen. (2024). Influence of model UTAUT 2 and confidence on user interest in OVO applications. 2024 4th International Conference on Emerging Smart Technologies and Applications (eSmarTA), 1–7. https://doi.org/10.1109/eSmarTA62850.2024.10639014
Handayani, T., & Sudiana, S. (2017). Analisis Penerapan Model Utaut (Unified Theory of Acceptance and Use of Technology) Terhadap Perilaku Pengguna Sistem Informasi (Studi Kasus: Sistem Informasi Akademik Pada Sttnas Yogyakarta). Angkasa: Jurnal Ilmiah Bidang Teknologi, 7(2), 165. https://doi.org/10.28989/angkasa.v7i2.159
Huang, H., Cheng, X., Wei, L., Liu, D., & Deng, M. (2024). Are natural resources a driving force for financial development or a curse for the economy? Policy insight from Next-11 countries. Resources Policy, 88(November 2023). https://doi.org/10.1016/j.resourpol.2023.104466
Kang, J. (2018). Mobile payment in Fintech environment: trends, security challenges, and services. Human-Centric Computing and Information Sciences, 8(1). https://doi.org/10.1186/s13673-018-0155-4
Kazemi, H., Miller, D., Mohan, A., Griffith, Z., Jin, Y., Kwiatkowski, J., Tran, L., & Crawford, M. (2015). 350mW G-band medium power amplifier fabricated through a new method of 3D-copper additive manufacturing. 2015 IEEE MTT-S International Microwave Symposium, IMS 2015, 36(1), 157–178. https://doi.org/10.1109/MWSYM.2015.7167037
Koenig-lewis, N., Marquet, M., & Palmer, A. (2015). Enjoyment and social influence : predicting mobile payment adoption. May, 37–41. https://doi.org/10.1080/02642069.2015.1043278
Kotler, Keller. (2009). Manajemen Pemasaran. Penerbit Erlangga. Jakarta
Merhi, M., Hone, K., Tarhini, A., & Ameen, N. (2020). An empirical examination of the moderating role of age and gender in consumer mobile banking use: a cross-national, quantitative study. Journal of Enterprise Information Management, 34(4), 1144–1168. https://doi.org/10.1108/JEIM-03-2020-0092
Mulyati, Y., Elsandra, Y., & Alfian, A. (2023). Determining Factors of E-Wallet Use Behavioral Intention: Application and Extension of The UTAUT Model. Journal of Economics, Finance and Management Studies, 06(12), 5784–5799. https://doi.org/10.47191/jefms/v6-i12-04
Natarajan, T., Balasubramanian, S. A., & Kasilingam, D. L. (2018). Technology in Society The moderating role of device type and age of users on the intention to use mobile shopping applications. Technology in Society, 53, 79–90. https://doi.org/10.1016/j.techsoc.2018.01.003
Novianti, K. D. P. (2019). Analisis Evaluasi E-Learning Menggunakan Integrasi Model D&M dan UTAUT Integration of D&M and UTAUT Model to Analyze the Result of E-Learning Evaluation. TecnoCom, 18(2), 122–133.
Olivia, M., & Marchyta, N. K. (2022). The Influence of Perceived Ease of Use and Perceived Usefulness on E-Wallet Continuance Intention: Intervening Role of Customer Satisfaction. Jurnal Keilmuan Dan Aplikasi Teknik Industri, 24, 13–22.
Putra, Y. S. (2017). The Oritical Review : Teori Perbedaan Generasi. Jurnal Sains Dan Seni ITS, 6(1), 51–66. http://repositorio.unan.edu.ni/2986/1/5624.pdf%0Ahttp://fiskal.kemenkeu.go.id/ejournal%0Ahttp://dx.doi.org/10.1016/j.cirp.2016.06.001%0Ahttp://dx.doi.org/10.1016/j.powtec.2016.12.055%0Ahttps://doi.org/10.1016/j.ijfatigue.2019.02.006%0Ahttps://doi.org/10.1
Qi, B., Qi, X., & Pathak, S. (2024). The Effect of Internet Celebrity B&B Service Quality on Customers’ Behavioral Intention. Journal of Human, Earth, and Future, 5(2), 173–186. https://doi.org/10.28991/HEF-2024-05-02-03
Septiana, A. E., & Suryani, T. (2022). The Effect of Customer Satisfaction and Trust on Performance Expectancy and Word of Mouth (WOM) at Shopee Aplications Users.
Srivastava, S., Mohta, A., & Shunmugasundaram, V. (2024). Adoption of digital payment FinTech service by Gen Y and Gen Z users: evidence from India. Digital Policy, Regulation and Governance , 26(1), 95–117. https://doi.org/10.1108/DPRG-07-2023-0110
Sultana, N., Chowdhury, R. S., & Haque, A. (2023). Gravitating towards Fintech: A study on Undergraduates using extended UTAUT model. Heliyon, 9(10), e20731. https://doi.org/10.1016/j.heliyon.2023.e20731
Thakor, A. V. (2020). Fintech and banking: What do we know? Journal of Financial Intermediation, 41(July). https://doi.org/10.1016/j.jfi.2019.100833
Venkatesh, V, Bala, H. 2008. Technology Acceptance Model 3 and a Research Agenda on Interventions. Decision Sciences, 39 (2): 273–315.
Venkatesh, V., Morris M. G., Davis G. B, & Davis F. D. (2003). User Acceptance of Information Technology: Toward a Unified View. MIS Quarterly, 27(3), pp. 427-478.
Venkatesh, V., Thong J. Y. L., & Xu X. (2012). Consumer Acceptance and Use of Information Technology: Extending The Unified Theory of Acceptance and Use of Technology. MIS Quarterly, 36(1), 157-178.
Wei, W., Sun, J., Miao, W., Chen, T., Sun, H., Lin, S., & Gu, C. (2024). Using the Extended Unified Theory of Acceptance and Use of Technology to explore how to increase users’ intention to take a robotaxi. Humanities and Social Sciences Communications, 11(1), 1–14. https://doi.org/10.1057/s41599-024-03271-3
Wilfan, A. F., & Martini, E. (2021). Faktor-faktor Yang Mempengaruhi Penggunaan Linkaja Berdasarkan Model Teori Utaut2 (unified Theory Of Acceptance And Use Of Technology2).
Xie, J., Ye, L., Huang, W., & Ye, M. (2021). Understanding FinTech Platform Adoption : Impacts of Perceived Value and Perceived Risk. 1893–1911.
Yan, C., Siddik, A. B., Akter, N., & Dong, Q. (2023). Factors influencing the adoption intention of using mobile financial service during the COVID-19 pandemic: the role of FinTech. Environmental Science and Pollution Research, 30(22), 61271–61289. https://doi.org/10.1007/s11356-021-17437-y
Zha, H., Liu, K., Tang, T., Yin, Y. H., Dou, B., Jiang, L., Yan, H., Tian, X., Wang, R., & Xie, W. (2022). Acceptance of clinical decision support system to prevent venous thromboembolism among nurses: an extension of the UTAUT model. BMC Medical Informatics and Decision Making, 22(1), 1–12. https://doi.org/10.1186/s12911-022-01958-8