--

20(6)2025 (IN PRESS)

Sự chấp nhận công nghệ AI trong bán lẻ: Trường hợp thế hệ Z và thế hệ Y


Tác giả - Nơi làm việc:
Bùi Ngọc Tuấn Anh - Trường Đại học Mở Thành phố Hồ Chí Minh, Thành phố Hồ Chí Minh , Việt Nam
Nguyễn Thiên Thy - Trường Đại học Mở Thành phố Hồ Chí Minh, Thành phố Hồ Chí Minh , Việt Nam
Cao Thị Lan Anh - Trường Đại học Mở Thành phố Hồ Chí Minh, Thành phố Hồ Chí Minh , Việt Nam
Phạm Ngọc Hải Yến - Trường Đại học Mở Thành phố Hồ Chí Minh, Thành phố Hồ Chí Minh , Việt Nam
Nguyễn Dương Danh - Trường Đại học Mở Thành phố Hồ Chí Minh, Thành phố Hồ Chí Minh , Việt Nam
Trần Viết Hải - Trường Đại học Mở Thành phố Hồ Chí Minh, Thành phố Hồ Chí Minh , Việt Nam
Tác giả liên hệ, Email: Nguyễn Thiên Thy - 2154110427thy@ou.edu.vn
Ngày nộp: 30-07-2024
Ngày duyệt đăng: 21-01-2025
Ngày xuất bản: 24-03-2025

Tóm tắt
Những năm qua, ứng dụng công nghệ trong ngành bán lẻ ngày càng phát triển và đem lại nhiều giá trị cho cả doanh nghiệp lẫn khách hàng. Bên cạnh việc nâng cao trải nghiệm khách hàng bằng cách cá nhân hóa nhu cầu, công nghệ trong ngành bán lẻ cũng phải đối mặt với nhiều rủi ro, tiêu biểu là mối quan tâm về quyền riêng tư. Nghiên cứu này được thực hiện nhằm khám phá tác động nỗi lo về quyền riêng tư thông qua thuyết khế ước xã hội (SCT), kết hợp mô hình chấp nhận công nghệ (TAM) để đánh giá ý định hành vi đối với công nghệ tự phục vụ (SST) tích hợp trí tuệ nhân tạo tại các cửa hàng bán lẻ. Khảo sát thu được 250 câu trả lời của thế hệ Z và thế hệ Y tại Thành phố Hồ Chí Minh, sử dụng phần mềm Smart PLS 4 để đánh giá dữ liệu. Kết quả cho thấy sự tác động mạnh mẽ của nhận thức về tính hữu ích và dễ sử dụng đến ý định sử dụng. Đồng thời, lo lắng về quyền riêng tư không phải là tác nhân ảnh hưởng tiêu cực đến ý định sử dụng. Kết quả nghiên cứu không chỉ đóng góp về mặt lý thuyết mà còn đề xuất hàm ý thực tiễn cho nhà quản trị khi áp dụng công nghệ mới nhằm nâng cao trải nghiệm của khách hàng.

Chỉ số JEL
M1; M31

Từ khóa
cá nhân hóa; chấp nhận công nghệ AI bán lẻ; lo lắng quyền riêng tư; niềm tin năng lực

Toàn văn:
PDF

Tài liệu tham khảo

Aksoy, N. C., Kabadayi, E. T., lmaz, C., & Alan, A. K. (2023). Personalization in Marketing: How Do People Perceive Personalization Practices in the Business World? Journal of Electronic Commerce Research, 24(4), 269-297.


Alalwan, A. A., Dwivedi, Y. K., Rana, N. P., & Simintiras, A. C. (2016). Jordanian consumers’ adoption of telebanking: Influence of perceived usefulness, trust and self-efficacy. International Journal of Bank Marketing, 34(5), 690-709.


Alkawsi, G., Ali, N. a., & Baashar, Y. (2021). The moderating role of personal innovativeness and users experience in accepting the smart meter technology. Applied Sciences, 11(8), 3297.


Asif, M., & Krogstie, J. (2013). Role of personalization in mobile services adoption. Proceedings of the International Conference on Multimedia and Human Computer Interaction. International ASET,


Awad, N. F., & Krishnan, M. S. (2006). The personalization privacy paradox: An empirical evaluation of information transparency and the willingness to be profiled online for personalization. MIS quarterly, 13-28.


Azam, N. A., Kabiraj, S., Shaoyuan, W., & Azam, M. I. (2023). Adoption of TAM to measure consumer’s attitude towards self-service technology: Utilizing cultural perspectives as a moderator variable. Global Business Review, 09721509221142373.


Baek, T. H., & Morimoto, M. (2012). Stay away from me. Journal of advertising, 41(1), 59-76.


Baruh, L., Secinti, E., & Cemalcilar, Z. (2017). Online privacy concerns and privacy management: A meta-analytical review. Journal of Communication, 67(1), 26-53.


Betz, N. E., & Hackett, G. (1981). The relationship of career-related self-efficacy expectations to perceived career options in college women and men. Journal of counseling psychology, 28(5), 399.


Brown, I., & Inouye, D. K. (1978). Learned helplessness through modeling: The role of perceived similarity in competence. Journal of personality and social psychology, 36(8), 900.


Bulmer, S., Elms, J., & Moore, S. (2018). Exploring the adoption of self-service checkouts and the associated social obligations of shopping practices. Journal of Retailing and Consumer Services, 42, 107-116.


Chin, W. W. (1998). The partial least squares approach to structural equation modeling. Modern methods for business research, 295(2), 295-336.


Collier, J. E., & Sherrell, D. L. (2010). Examining the influence of control and convenience in a self-service setting. Journal of the Academy of Marketing Science, 38, 490-509.


Cudd, M., & Duggal, R. (2000). Industry distributional characteristics of financial ratios: An acquisition theory application. Financial Review, 35(1), 105-120.


Curran, J. M., & Meuter, M. L. (2005). Self‐service technology adoption: comparing three technologies. Journal of services marketing, 19(2), 103-113.


Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS quarterly, 319-340.


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.


Deng, Z., Mo, X., & Liu, S. (2014). Comparison of the middle-aged and older users’ adoption of mobile health services in China. International journal of medical informatics, 83(3), 210-224.


Dinev, T., & Hart, P. (2005). Internet privacy concerns and social awareness as determinants of intention to transact. International Journal of Electronic Commerce, 10(2), 7-29.


Ding, X., Verma, R., & Iqbal, Z. (2007). Self‐service technology and online financial service choice. International journal of service industry management, 18(3), 246-268.


Eastin, M. S., Brinson, N. H., Doorey, A., & Wilcox, G. (2016). Living in a big data world: Predicting mobile commerce activity through privacy concerns. Computers in human behavior, 58, 214-220.


Espinoza, C. (2012). Millennial integration: Challenges millennials face in the workplace and what they can do about them. Antioch University.


Fagan, M. H., Neill, S., & Wooldridge, B. R. (2008). Exploring the intention to use computers: An empirical investigation of the role of intrinsic motivation, extrinsic motivation, and perceived ease of use. Journal of Computer Information Systems, 48(3), 31-37.


Fishbein, M., & Ajzen, I. (1977). Belief, attitude, intention, and behavior: An introduction to theory and research.


Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of marketing research, 18(1), 39-50.


Gouthier, M. H., Nennstiel, C., Kern, N., & Wendel, L. (2022). The more the better? Data disclosure between the conflicting priorities of privacy concerns, information sensitivity and personalization in e-commerce. Journal of Business Research, 148, 174-189.


Ha, Y. (2020). The effects of shoppers' motivation on self-service technology use intention: moderating effects of the presence of employee. The Journal of Asian Finance, Economics and Business, 7(9), 489-497.


Hagberg, J., Sundstrom, M., & Egels-Zandén, N. (2016). The digitalization of retailing: an exploratory framework. International Journal of Retail & Distribution Management, 44(7), 694-712.


Hair Jr, J. F., Howard, M. C., & Nitzl, C. (2020). Assessing measurement model quality in PLS-SEM using confirmatory composite analysis. Journal of Business Research, 109, 101-110.


Halleröd, B. (2011). What do children know about their futures: do children's expectations predict outcomes in middle age? Social Forces, 90(1), 65-83.


Henseler, J., Hubona, G., & Ray, P. A. (2016). Using PLS path modeling in new technology research: updated guidelines. Industrial management & data systems, 116(1), 2-20.


Hock, M., & Ringle, C. M. (2010). Local strategic networks in the software industry: An empirical analysis of the value continuum. International Journal of Knowledge Management Studies, 4(2), 132-151.


Hong, W., Thong, J. Y., Wong, W.-M., & Tam, K.-Y. (2002). Determinants of user acceptance of digital libraries: an empirical examination of individual differences and system characteristics. Journal of management information systems, 18(3), 97-124.


Hoyer, W. D., Kroschke, M., Schmitt, B., Kraume, K., & Shankar, V. (2020). Transforming the customer experience through new technologies. Journal of interactive marketing, 51(1), 57-71.


Hsu, M. K., Wang, S. W., & Chiu, K. K. (2009). Computer attitude, statistics anxiety and self-efficacy on statistical software adoption behavior: An empirical study of online MBA learners. Computers in human behavior, 25(2), 412-420.


Jia, H., Wang, Y., Ge, L., Shi, G., & Yao, S. (2012). Asymmetric effects of regulatory focus on expected desirability and feasibility of embracing self‐service technologies. Psychology & Marketing, 29(4), 209-225.


Kaushik, A. K., & Rahman, Z. (2015). An alternative model of self-service retail technology adoption. Journal of services marketing, 29(5), 406-420.


Khuê, V. (2023). Cải thiện trải nghiệm khách hàng: Gia tăng sức mạnh thương hiệu. Retrieved 26/07/2024 from https://vneconomy.vn/cai-thien-trai-nghiem-khach-hang-gia-tang-suc-manh-thuong-hieu.htm


Komiak, S. Y., & Benbasat, I. (2006). The effects of personalization and familiarity on trust and adoption of recommendation agents. MIS quarterly, 941-960.


Koulopoulos, T., & Keldsen, D. (2016). Gen Z effect: The six forces shaping the future of business. Routledge.


Kumar, V., Ramachandran, D., & Kumar, B. (2021). Influence of new-age technologies on marketing: A research agenda. Journal of Business Research, 125, 864-877.


Lee, H., & Leonas, K. K. (2021). Millennials’ intention to use self-checkout technology in different fashion retail formats: perceived benefits and risks. Clothing and Textiles Research Journal, 39(4), 264-280.


Lowry, P. B., & Gaskin, J. (2014). Partial least squares (PLS) structural equation modeling (SEM) for building and testing behavioral causal theory: When to choose it and how to use it. IEEE transactions on professional communication, 57(2), 123-146.


Meuter, M. L., Ostrom, A. L., Roundtree, R. I., & Bitner, M. J. (2000). Self-service technologies: understanding customer satisfaction with technology-based service encounters. Journal of marketing, 64(3), 50-64.


Ngadiman, N. I. (2022). The Influence of Demographic Factors and Customer Traits on Intention to Use Self-Service Checkout at Tesco Tebrau. iJIM, 16(13), 175.


Nunnally, J., & Bernstein, I. (1994). Psychometric theory McGraw-hill series. Psychology, 3.


Ozturk, A. B., Bilgihan, A., Nusair, K., & Okumus, F. (2016). What keeps the mobile hotel booking users loyal? Investigating the roles of self-efficacy, compatibility, perceived ease of use, and perceived convenience. International Journal of Information Management, 36(6), 1350-1359.


Rao Hill, S., & Troshani, I. (2010). Factors influencing the adoption of personalisation mobile services: empirical evidence from young Australians. International Journal of Mobile Communications, 8(2), 150-168.


Roussos, G., Peterson, D., & Patel, U. (2003). Mobile identity management: An enacted view. International Journal of Electronic Commerce, 8(1), 81-100.


Sarstedt, M. (2013). Partial Least Squares Structural Equation Modeling (PLS-SEM). Organizational Research Methods, 17(2), 182-209.


Sarstedt, M., Ringle, C. M., & Hair, J. F. (2021). Partial least squares structural equation modeling. In Handbook of market research (pp. 587-632). Springer.


Senemoğlu, N. (2007). Gelişim öğrenme ve öğretim kuramdan uygulamaya.


Shank, D. B., & Cotten, S. R. (2014). Does technology empower urban youth? The relationship of technology use to self-efficacy. Computers & Education, 70, 184-193.


Sharma, D., Oman, S., & Yadav, D. (2011). An empirical study on tax payer’s attitude towards e-return filing in India'. Chief Patron Chief Patron.


Sharma, S., Islam, N., Singh, G., & Dhir, A. (2022). Why do retail customers adopt artificial intelligence (AI) based autonomous decision-making systems? IEEE Transactions on Engineering Management, 71, 1846-1861.


Song, C. S., & Kim, Y.-K. (2022). The role of the human-robot interaction in consumers’ acceptance of humanoid retail service robots. Journal of Business Research, 146, 489-503.


The State Of Women In AI (2024). WEF Davos, https://www.thefemalequotient.com/wp-content/uploads/2024/01/The-State-Of-Women-In-AI-WEF-2024.pdf.


Swani, K., Milne, G. R., & Slepchuk, A. N. (2021). Revisiting trust and privacy concern in consumers’ perceptions of marketing information management practices: Replication and extension. Journal of interactive marketing, 56(1), 137-158.


Taylor, D. G., Davis, D. F., & Jillapalli, R. (2009). Privacy concern and online personalization: The moderating effects of information control and compensation. Electronic commerce research, 9, 203-223.


Treiblmaier, H., Madlberger, M., Knotzer, N., & Pollach, I. (2004). Evaluating personalization and customization from an ethical point of view: An empirical study. 37th Annual Hawaii International Conference on System Sciences, 2004. Proceedings of the,


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, 425-478.


Venkatesh, V., Thong, J. Y., & Xu, X. (2012). Consumer acceptance and use of information technology: extending the unified theory of acceptance and use of technology. MIS quarterly, 157-178.


West, A., Clifford, J., & Atkinson, D. (2018). " Alexa, build me a brand" An Investigation into the impact of Artificial Intelligence on Branding. The Business & Management Review, 9(3), 321-330.


Wong, K. K.-K. (2013). Partial least squares structural equation modeling (PLS-SEM) techniques using SmartPLS. Marketing bulletin, 24(1), 1-32.


Wu, K.-W., Huang, S. Y., Yen, D. C., & Popova, I. (2012). The effect of online privacy policy on consumer privacy concern and trust. Computers in human behavior, 28(3), 889-897.


Xu, H., Dinev, T., Smith, J., & Hart, P. (2011). Information privacy concerns: Linking individual perceptions with institutional privacy assurances. Journal of the Association for Information Systems, 12(12), 1.


Zeng, F., Ye, Q., Yang, Z., Li, J., & Song, Y. A. (2022). Which privacy policy works, privacy assurance or personalization declaration? an investigation of privacy policies and privacy concerns. Journal of Business Ethics, 1-18.


Zhao, X., Mattila, A. S., & Eva Tao, L. S. (2008). The role of post‐training self‐efficacy in customers' use of self service technologies. International journal of service industry management, 19(4), 492-505.


Zhou, T. (2020). The effect of information privacy concern on users' social shopping intention. Online Information Review, 44(5), 1119-1133.


Zhu, Y.-Q., & Kanjanamekanant, K. (2021). No trespassing: Exploring privacy boundaries in personalized advertisement and its effects on ad attitude and purchase intentions on social media. Information & Management, 58(2), 103314.



Creative Commons License
© The Author(s) 2025. This is an open access publication under CC BY NC licence.