Tác động nhận thức công nghệ thực tế ảo tăng cường đến quyết định sử dụng mua hàng đa kênh của người tiêu dùng tại TP. Hồ Chí Minh: Tiếp cận từ lý thuyết khuếch tán đổi mới
Nội dung chính của bài viết
Tóm tắt
Hậu đại dịch Covid-19, hành vi của khách hàng đang có những thay đổi lớn. Nhiều khách hàng chuyển sang hình thức mua hàng online thông qua các công nghệ mới nhất trong đó có thực tế ảo (VR) và công nghệ thực tế ảo tăng cường (ARSA). Mục tiêu của bài báo này tìm hiểu các yếu tố công nghệ VR và ARSA tác động đến thái độ, cam kết và quyết định sử dụng mua hàng đa kênh Omnichannel thông qua lý thuyết khuếch tán đổi mới. Bằng phương pháp PLS-SEM với 259 phiếu khảo sát khách hàng tại TPHCM có biết về công nghệ VR và ARSA cho thấy, các yếu tố như sự phức tạp, khả năng thử nghiệm, lợi thế tương đối, khả năng tương thích có tác động sử dụng quyết định sử dụng mua hàng đa kênh Omnichannel thông qua yếu tố trung gian thái độ và cam kết. Dựa trên các nghiên cứu trước đây, ví dụ như sự phức tạp (dễ sử dụng), lợi thế tương đối (tính hữu dụng) và thái độ, nghiên cứu này sẽ bổ sung các yếu tố mới chưa được kiểm định tại Việt nam như khả năng thử nghiệm và khả năng tương thích, trong công nghệ VR và ARSA. Sau cùng đề xuất các số hàm quản trị cho các doanh nghiệp để phát triển VR và ARSA tích hợp vào đa kênh, cũng như hạn chế và hướng nghiên cứu tiếp theo
Chi tiết bài viết
Từ khóa
Cam kết, Ứng dụng công nghệ thực tế ảo, Sử dụng mua hàng đa kênh, Thái độ
Tài liệu tham khảo
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Brynjolfsson, E., Hu, Y. J., & Rahman, M. S. (2013). Competing in the Age of Omnichannel Retailing. MIT Sloan Management Review, 54(4), 23-29.
Chaniotakis, I. E., Lymperopoulos, C., & Soureli, M. (2010). Consumers' intention of buying own-label premium food products. Journal of Product and Brand Management, 19(5), 327-334. https://doi.org/10.1108/10610421011068568
Vinzi, V. E., Chin, W. W., Henseler, J., & Wang, H. (2010). Handbook of partial least squares (Vol. 201, No. 0). Berlin: Springer.
Davis, F. (1986). Technology acceptance model for empirically testing new end-user information systems theory and results. Doctoral Dissertation, MIT.
De Matos, C. A., Ituassu, T. C., & Rossi, C. A. V. (2007). Consumer attitudes toward counterfeits: A review and extension. Journal of Consumer Marketing, 24(1), 36-47. https://doi.org/10.1108/07363760710720975
Cohen, J. (2013). Statistical power analysis for the behavioral sciences. Academic Press.
Fan, X., Chai, Z., Deng, N., & Dong, X. (2020). Adoption of augmented reality in online retailing and consumers’ product attitude: A cognitive perspective. Journal of Retailing and Consumer Services, 53, 101986. https://doi.org/10.1016/j.jretconser.2019.101986.
Fishbein, M., Ajzen, I. (1975). Belief, attitude, intention and behavior: An introduction to theory and research. Philosophy and Rhetoric. 10(2), 130–132. http://worldcat.org/isbn/0201020890
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39-50. https://doi.org/10.1177/002224378101800104
Giner-Sorolla, R. (1999). Effect in attitude: Immediate and deliberative perspectives in dual - process theories in social. New York, USA: The Guilford Press
Hair Jr, J. F., Black, W. C., Babin, B. J., & Anderson, R. (2016). Multivariate Data Analysis London: Cengage Learning. Search in.
Hansen, R., & Sia, S. K. (2015). Hummel's Digital Transformation Toward Omnichannel Retailing: Key Lessons Learned. MIS Quarterly Executive, 14(2), 51-66. https://aisel.aisnet.org/misqe/vol14/iss2/3
Henseler, J., Ringle, C. M., & Sinkovics, R. R. (2009). The Use of Partial Least Squares Path Modeling in International Marketing. Advances in International Marketing (AIM), 20, 277-320.
Holdack, E., Lurie-Stoyanov, K., & Fromme, H. F. (2022). The role of perceived enjoyment and perceived informativeness in assessing the acceptance of AR wearables. Journal of Retailing and Consumer Services, 65, 102259. https://doi.org/10.1016/j.jretconser.2020.102259
Hui, J. S., Greenberg, M. D., & Gerber, E. M. (2014, February). Understanding the role of community in crowdfunding work. In Proceedings of the 17th ACM conference on Computer supported cooperative work & social computing (pp. 62-74).
Juaneda-Ayensa, E., & Mosquera, A. (2016). Omnichannel customer behavior: Key drivers of technology acceptance and use and their effects on purchase intention. Frontiers in Psychology, 7, 01117. https://doi.org/10.3389/fpsyg.2016.01117
Klein, R., & Rai, A. (2009). Interfirm strategic information flows in logistics supply chain relationships. Management Information Systems Quarterly, 33(4), 735-762. https://doi.org/10.2307/20650325
Qin, H., Osatuyi, B., & Xu, L. (2021). How mobile augmented reality applications affect continuous use and purchase intentions: A cognition-affect-conation perspective. Journal of Retailing and Consumer Services, 63, 102680. https://doi.org/10.1016/j.jretconser.2021.102680
Lehrer, C., & Trenz, M. (2022). Omnichannel business. Electronic Markets, 32(2), 687-699. https://doi.org/10.1007/s12525-021-00511-1.
Melero, I., Sese, F. J., & Verhoef, P. C. (2016). Recasting the customer experience in today’s Omnichannel environment. Universia Business Review, 50, 18-37. https://doi.org/10.3232/UBR.2016.V13.N2.01
Morgan, R. M., & Hunt, S. D. (1994). The commitment-trust theory of relationship marketing. The Journal of Marketing, 58(3), 20-38. https://doi.org/10.1177/002224299405800302
Park, M., & Yoo, J. (2020). Effects of perceived interactivity of augmented reality on consumer responses: A mental imagery perspective. Journal of Retailing and Consumer Services, 52, 101912. https://doi.org/10.1016/j.jretconser.2019.101912
Plotkina, D., & Saurel, H. (2019). Me or just like me? The role of virtual try-on and physical appearance in apparel M-retailing. Journal of Retailing and Consumer Services, 51, 362-377. https://doi.org/10.1016/j.jretconser.2019.07.002
Sung, E. C. (2021). The effects of augmented reality mobile app advertising: Viral marketing via shared social experience. Journal of Business Research, 122, 75-87. https://doi.org/10.1016/j.jbusres.2020.08.034
Rauschnabel, P. A., Felix, R., & Hinsch, C. (2019). Augmented reality marketing: How mobile AR-apps can improve brands through inspiration. Journal of Retailing and Consumer Services, 49, 43-53. https://doi.org/10.1016/j.jretconser.2019.03.004
Rigby, D. (2011). The future of shopping. Harvard Business Review, 89(12), 65-76. https://www.oresky.eu/wp-content/uploads/2016/09/The-Future-of-Shopping.pdf
Rogers, E. (1995). Diffusion of Innovations. The Free Press, New York.
Van Slyke, C., Ilie, V., Lou, H., & Stafford, T. (2007). Perceived critical mass and the adoption of a communication technology. European Journal of Information Systems, 16(3), 270-283. https://doi.org/10.1057/palgrave.ejis.3000680
Wang, X., Yuen, K. F., Wong, Y. D., & Teo, C. C. (2018). An innovation diffusion perspective of e-consumers’ initial adoption of self-collection service via automated parcel station. The International Journal of Logistics Management, 29(1), 237-260. https://doi.org/10.1108/IJLM-12-2016-0302
Zhang, T., Wang, W. Y. C., Cao, L., & Wang, Y. (2019). The role of virtual try-on technology in online purchase decision from consumers’ aspect. Internet Research, 29(3), 529-551. https://doi.org/10.1108/IntR-12-2017-0540
Brynjolfsson, E., Hu, Y. J., & Rahman, M. S. (2013). Competing in the Age of Omnichannel Retailing. MIT Sloan Management Review, 54(4), 23-29.
Chaniotakis, I. E., Lymperopoulos, C., & Soureli, M. (2010). Consumers' intention of buying own-label premium food products. Journal of Product and Brand Management, 19(5), 327-334. https://doi.org/10.1108/10610421011068568
Vinzi, V. E., Chin, W. W., Henseler, J., & Wang, H. (2010). Handbook of partial least squares (Vol. 201, No. 0). Berlin: Springer.
Davis, F. (1986). Technology acceptance model for empirically testing new end-user information systems theory and results. Doctoral Dissertation, MIT.
De Matos, C. A., Ituassu, T. C., & Rossi, C. A. V. (2007). Consumer attitudes toward counterfeits: A review and extension. Journal of Consumer Marketing, 24(1), 36-47. https://doi.org/10.1108/07363760710720975
Cohen, J. (2013). Statistical power analysis for the behavioral sciences. Academic Press.
Fan, X., Chai, Z., Deng, N., & Dong, X. (2020). Adoption of augmented reality in online retailing and consumers’ product attitude: A cognitive perspective. Journal of Retailing and Consumer Services, 53, 101986. https://doi.org/10.1016/j.jretconser.2019.101986.
Fishbein, M., Ajzen, I. (1975). Belief, attitude, intention and behavior: An introduction to theory and research. Philosophy and Rhetoric. 10(2), 130–132. http://worldcat.org/isbn/0201020890
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39-50. https://doi.org/10.1177/002224378101800104
Giner-Sorolla, R. (1999). Effect in attitude: Immediate and deliberative perspectives in dual - process theories in social. New York, USA: The Guilford Press
Hair Jr, J. F., Black, W. C., Babin, B. J., & Anderson, R. (2016). Multivariate Data Analysis London: Cengage Learning. Search in.
Hansen, R., & Sia, S. K. (2015). Hummel's Digital Transformation Toward Omnichannel Retailing: Key Lessons Learned. MIS Quarterly Executive, 14(2), 51-66. https://aisel.aisnet.org/misqe/vol14/iss2/3
Henseler, J., Ringle, C. M., & Sinkovics, R. R. (2009). The Use of Partial Least Squares Path Modeling in International Marketing. Advances in International Marketing (AIM), 20, 277-320.
Holdack, E., Lurie-Stoyanov, K., & Fromme, H. F. (2022). The role of perceived enjoyment and perceived informativeness in assessing the acceptance of AR wearables. Journal of Retailing and Consumer Services, 65, 102259. https://doi.org/10.1016/j.jretconser.2020.102259
Hui, J. S., Greenberg, M. D., & Gerber, E. M. (2014, February). Understanding the role of community in crowdfunding work. In Proceedings of the 17th ACM conference on Computer supported cooperative work & social computing (pp. 62-74).
Juaneda-Ayensa, E., & Mosquera, A. (2016). Omnichannel customer behavior: Key drivers of technology acceptance and use and their effects on purchase intention. Frontiers in Psychology, 7, 01117. https://doi.org/10.3389/fpsyg.2016.01117
Klein, R., & Rai, A. (2009). Interfirm strategic information flows in logistics supply chain relationships. Management Information Systems Quarterly, 33(4), 735-762. https://doi.org/10.2307/20650325
Qin, H., Osatuyi, B., & Xu, L. (2021). How mobile augmented reality applications affect continuous use and purchase intentions: A cognition-affect-conation perspective. Journal of Retailing and Consumer Services, 63, 102680. https://doi.org/10.1016/j.jretconser.2021.102680
Lehrer, C., & Trenz, M. (2022). Omnichannel business. Electronic Markets, 32(2), 687-699. https://doi.org/10.1007/s12525-021-00511-1.
Melero, I., Sese, F. J., & Verhoef, P. C. (2016). Recasting the customer experience in today’s Omnichannel environment. Universia Business Review, 50, 18-37. https://doi.org/10.3232/UBR.2016.V13.N2.01
Morgan, R. M., & Hunt, S. D. (1994). The commitment-trust theory of relationship marketing. The Journal of Marketing, 58(3), 20-38. https://doi.org/10.1177/002224299405800302
Park, M., & Yoo, J. (2020). Effects of perceived interactivity of augmented reality on consumer responses: A mental imagery perspective. Journal of Retailing and Consumer Services, 52, 101912. https://doi.org/10.1016/j.jretconser.2019.101912
Plotkina, D., & Saurel, H. (2019). Me or just like me? The role of virtual try-on and physical appearance in apparel M-retailing. Journal of Retailing and Consumer Services, 51, 362-377. https://doi.org/10.1016/j.jretconser.2019.07.002
Sung, E. C. (2021). The effects of augmented reality mobile app advertising: Viral marketing via shared social experience. Journal of Business Research, 122, 75-87. https://doi.org/10.1016/j.jbusres.2020.08.034
Rauschnabel, P. A., Felix, R., & Hinsch, C. (2019). Augmented reality marketing: How mobile AR-apps can improve brands through inspiration. Journal of Retailing and Consumer Services, 49, 43-53. https://doi.org/10.1016/j.jretconser.2019.03.004
Rigby, D. (2011). The future of shopping. Harvard Business Review, 89(12), 65-76. https://www.oresky.eu/wp-content/uploads/2016/09/The-Future-of-Shopping.pdf
Rogers, E. (1995). Diffusion of Innovations. The Free Press, New York.
Van Slyke, C., Ilie, V., Lou, H., & Stafford, T. (2007). Perceived critical mass and the adoption of a communication technology. European Journal of Information Systems, 16(3), 270-283. https://doi.org/10.1057/palgrave.ejis.3000680
Wang, X., Yuen, K. F., Wong, Y. D., & Teo, C. C. (2018). An innovation diffusion perspective of e-consumers’ initial adoption of self-collection service via automated parcel station. The International Journal of Logistics Management, 29(1), 237-260. https://doi.org/10.1108/IJLM-12-2016-0302
Zhang, T., Wang, W. Y. C., Cao, L., & Wang, Y. (2019). The role of virtual try-on technology in online purchase decision from consumers’ aspect. Internet Research, 29(3), 529-551. https://doi.org/10.1108/IntR-12-2017-0540