This article aims to measure and identify the factors influencing the decision to use Chatbot in e-banking services for GenZ customers in Vietnam through 292 customers. Testing methods: Cronbach’s Alpha trust factor, EFA discovery factor analysis, and regression analysis have shown that 07 factors directly affect GenZ’s decision to use Chatbot. Those factors include (1) Customer attitude; (2) Useful perception; (3) Perception of ease of use; (4) Behavioral control perception; (5) Risk perception; (6) Subjective norms and (7) Trust. On that basis, the article has set out management implications for Vietnamese commercial banks to approach and increase the decision of customers aged 18–24 years in Vietnam.

Aashiek, M., Kumar, P., & Suresh, R. (2022). User adoption of AI-powered chatbots in tourism and the tourism industry.

AbuShanab, E., and Pearson, J. M. (2007). The role of chatbots in the financial services industry. International Journal of Human-Computer Studies, 65(11), 952-960.

Ajzen, I. (1985). From intentions to actions: A theory of planned behavior. In J. Kuhl & J. Beckmann (Eds.), Action control: From cognition to behavior (pp. 11-39). Springer.

Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179-211.

Ajzen, I. (2002). Perceived behavioral control, self-efficacy, locus of control, and the theory of planned behavior. Journal of Applied Social Psychology, 32(4), 665-683.

Bauer, R. A. (1960). Consumer behavior as risk-taking. In R. S. Hancock (Ed.), Dynamic marketing for a changing world (pp. 389-398). American Marketing Association.

Botpress Cộng đồng; 2023; Mẹo thiết kế hội thoại để trò chuyện với Chatbot tốt hơn (https://www.hotcourses.vn/study-abroad-info/study-guides/apa-la-gi/)

Cecilie, B., McDonald, M., & Thompson, J. (2019). Chatbots in customer service: A comprehensive review. Journal of Customer Service Research, 29(4), 403-420.

Chatterjee, S., Rana, N. P., Tamilmani, K., Sharma, S. K., & Lee, J. W. (2021). Artificial intelligence adoption in healthcare: A technology acceptance model perspective. Health Information Science and Systems, 9(1), 1-14.

Cheng, Y., & Jiang, H. (2021). Customer-brand relationship in the era of artificial intelligence: Understanding the role of chatbot marketing efforts. Journal of Product & Brand Management, 31(2), 252-264.

Cheriyan, A., Sharma, R. K., Joseph, A., & Kappil, S. R. (2022). Consumer acceptance towards AI-enabled chatbots: Case of travel and tourism industries. Journal of Positive School Psychology, 6(3), 3880-3889.

Chung, M., Ko, E., Joung, H., & Kim, S. J. (2020). Chatbot e-service and customer satisfaction regarding luxury brands. Journal of Business Research, 117, 587-595.

Chung, N., Koo, D.-M., & Lee, S. (2020). Understanding the factors affecting the acceptance of chatbots: A customer perspective. *Journal of Retailing and Consumer Services*, 57, 102256. https://doi.org/10.1016/j.jretconser.2020.102256

Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. Management Science, 35(8), 982-1003.

Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35(8), 982-1003.

Education Corner. (n.d.). Generation Z: Characteristics and learning preferences. Education Corner. Retrieved August 5, 2024.

Fishbein, M., & Ajzen, I. (1975). Trust, attitude, intention, and behavior: An introduction to theory and research. Addison-Wesley.

Følstad, A. (2022). Chatbots in customer service: A review of the research. Computer Science Review, 44, 100-115.

Folstad, A., & Brandtzæg, P. B. (2017). Chatbots and the new world of HCI. Interactions, 24(4), 38-42.

Huang, M. H., & Benyoucef, M. (2017). User Behavior in Social Commerce: The Role of Social Support and Social Presence. *Journal of Business Research*, 90, 114-123. https://doi.org/10.1016/j.jbusres.2018.05.016

Kucherbaev, P., Pukyn, V., & Romanov, A. (2018). A survey on the role of chatbots in various domains. Journal of Artificial Intelligence Research, 63, 141-162.

Laudon, K. C., & Traver, C. G. (2022). E-commerce 2022: business, technology, and society (17th ed.). Pearson.

Le, C. X. (2023). Nghiên cứu các yếu tố ảnh hưởng đến ý định sử dụng chatbot của khách hàng: Góc nhìn tại Việt Nam [Research on factors motivating customers’ intention to use chatbots: Perspective from Vietnam]. Tạp chí Khoa học Đại học Mở Thành phố Hồ Chí Minh – Kinh tế và Quản trị Kinh doanh, 18(5), 32-46.

Liao, C., Chen, C., & Lin, H. (2022). Understanding user trust in AI chatbots: A model for predicting trust and user experience. Journal of Artificial Intelligence Research, 73, 567-586.

Ma, F., Lyu, Z., & Li, H. (2024). Can ChatGPT predict Chinese equity premiums? Finance Research Letters, 105631.

Ma, X., Liu, Y., Wang, Z., & Chen, J. (2024). Exploring the capability of ChatGPT to predict stock returns in the Chinese market.

Nguyen, T. T. H., & Nguyen, N. D. (2021). Factors affecting intention to use chatbot for shopping online: An empirical study in Vietnam. Journal of Asian Finance, Economics and Business, 8(6), 951-960.

Nguyen, T., & Dinh, Q. (2023). Factors influencing customer adoption of AI-based chatbots in commercial banking.

Pillai, R., & Sivathanu, B. (2020). Adoption of AI-based chatbots for hospitality and tourism. International Journal of Contemporary Hospitality Management, 32(10), 3199-3226.

Pol, L., & Kl, M. (2019). Generation Z: Characteristics and communication preferences. Journal of Contemporary Youth Studies, 14(3), 234-245.

Sarma, R. (2017). E-banking is the transformation of all traditional banking activities and services to a digital environment.

Sharma, G. (2017, April 26). What is Digital Banking? VentureSkies. Retrieved from https://www.ventureskies.com/blog/digital-banking

Shawar, B. A., & Atwell, E. (2007). Chatbots: Are they really useful? In Proceedings of the 10th International Conference on Human-Computer Interaction (pp. 93-100). Springer.

Shereen, A. (2023). Artificial Intelligence in E-Banking Services: Investigating Customer Acceptance of Chatbots, ISSN 1816-6075 (Print), 1818-0523 (Online) Journal of System and Management Sciences Vol. 13 (2023) No. 3, pp. 156-176 DOI:10.33168/JSMS.2023.0311

Taylor, S., & Todd, P. A. (1995). Understanding information technology usage: A test of competing models. Information Systems Research, 6(2), 144-176.

Thamaiyanthi, S., & Phoon, L. (2023). Connecting with Generation Z: Customer acceptance of the use of artificial intelligence in using online services.

Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186-204.

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), 425-478.

World Trade Organization. (n.d.). E-commerce.

Zarouali, B., Van den Broeck, E., Walrave, M., & Poels, K. (2018). Predicting consumer responses to a chatbot on Facebook. Cyberpsychology, Behavior, and Social Networking, 21(8), 491-497.