Các yếu tố ảnh hưởng đến ý định mua lại trực tuyến: Trường hợp nghiên cứu trên địa bàn Thành phố Hồ Chí Minh
DOI:
https://doi.org/10.24311/jabes/2023.34.3.4Keywords:
Online Shopping, Perceived Risks of Online Shopping, TAM, Ho Chi Minh City, Personalization, Online Repurchase IntentionAbstract
This study aims to explore the factors affecting the online repurchase intention of people living in Ho Chi Minh City through an extended version of the Technology Acceptance Model (TAM). By employing the Partial Least Squares Structural Equation Modeling (PLS-SEM) method on a sample of 610 observations, the results reveal that there are four factors influencing the online repurchase intention of people living in Ho Chi Minh City including (1) attitudes toward online shopping, (2) perceived usefulness, (3) perceived ease of use, and (4) environmental awareness. Among these factors, attitude is the strongest predictor of the repurchase intention and also mediates the relationship between other independent variables and the repurchase intention. Notably, perceived risks of online shopping and personalization did not affect the repurchase intention. From the above findings, some implications for online businesses to enhance the customers’ intention to continue shopping online are suggested.
References
Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50, 179–211. doi: 10.1016/0749-5978(91)90020-T
Busalim, A. H., Hussin, A. R. C., & Iahad, N. A. (2019). Factors influencing customer engagement in social commerce websites: A systematic literature review. Journal of Theoretical and Applied Electronic Commerce Research, 14(2), 1–14. doi: 10.4067/S0718-18762019000200102
Chiu, C., Chang, C., Cheng, H., & Fang, Y. (2009). Determinants of customer repurchase intention in online shopping. Online Information Review, 33(4), 761–784. doi: 10.1108/14684520910985710
Cục Thương mại điện tử và Kinh tế số. (2021). Sách trắng Thương mại điện tử Việt Nam 2021. Truy cập ngày 8/5/2022, từ https://trungtamwto.vn/tin-tuc/18190-sach-trang-thuong-mai-dien-tu-viet-nam-2021?msclkid=43e9edf1ceb911ec86230e6a3726d52a
Cunningham, S. M. (1967). The major dimensions of perceived risk. In Risk Taking and Information Handling in Consumer Behaviour (pp. 82–108). Boston Graduate School of Business Administration, Harvard University Press.
Đặng Thị Bích Ngọc. (2021). Phát triển thương mại điện tử để tăng sức cạnh tranh cho doanh nghiệp. Truy cập ngày 27/11/2022, từ https://tapchicongthuong.vn/bai-viet/phat-trien-thuong-mai-dien-tu-de-tang-suc-canh-tranh-cho-doanh-nghiep-nho-va-vua-tai-viet-nam-80083.htm
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340. doi: 10.2307/249008
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. doi: 10.1287/mnsc.35.8.982
Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1992). Extrinsic and intrinsic motivation to use computers in the workplace1. Journal of Applied Social Psychology, 22(14), 1111–1132. doi: 10.1111/j.1559-1816.1992.tb00945.x
Fishbein, M., & Ajzen, I. (1975). Belief, Attitude, Intention, and Behavior: An Introduction to Theory and Research. Reading, Mass: Addison-Wesley.
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50. doi: 10.2307/3151312
Gefen, D. (2003). TAM or just plain habit: A look at experienced online shoppers. Journal of Organizational and End User Computing (JOEUC), 15(3), 1–13. doi: 10.4018/joeuc.2003070101
Hair Jr, J. F., Sarstedt, M., Hopkins, L., & G. Kuppelwieser, V. (2014). Partial least squares structural equation modeling (PLS-SEM): An emerging tool in business research. European Business Review, 26(2), 106–121. doi: 10.1108/EBR-10-2013-0128
Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), 2–24. doi: 10.1108/EBR-11-2018-0203
Hopwood, B., Mellor, M., & O’Brien, G. (2005). Sustainable development: Mapping different approaches. Sustainable Development, 13(1), 38–52. doi: 10.1002/sd.244
Hsu, M.-H., Yen, C.-H., Chiu, C.-M., & Chang, C.-M. (2006). A longitudinal investigation of continued online shopping behavior: An extension of the theory of planned behavior. International Journal of Human-Computer Studies, 64(9), 889–904. doi: 10.1016/j.ijhcs.2006.04.004
Hu, L., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6(1), 1–55. doi: 10.1080/10705519909540118
Järveläinen, J. (2004). Perceived usefulness and ease-of-use items in B2C electronic commerce. In W. Lamersdorf, V. Tschammer, & S. Amarger (Eds.), Building the E-Service Society (pp. 475–489). Boston, MA: Springer US. doi: 10.1007/1-4020-8155-3_26
Kang, M., Shin, D.-H., & Gong, T. (2016). The role of personalization, engagement, and trust in online communities. Information Technology & People, 29(3), 580–596. doi: 10.1108/ITP-01-2015-0023
Khalifa, M., & Liu, V. (2007). Online consumer retention: Contingent effects of online shopping habit and online shopping experience. European Journal of Information Systems, 16(6), 780–792. doi: 10.1057/palgrave.ejis.3000711
Kwon, K., & Kim, C. (2012). How to design personalization in a context of customer retention: Who personalizes what and to what extent?. Electronic Commerce Research and Applications, 11(2), 101–116. doi: 10.1016/j.elerap.2011.05.002
Lee, G., & Lin, H. (2005). Customer perceptions of e‐service quality in online shopping. International Journal of Retail & Distribution Management, 33(2), 161–176. doi: 10.1108/09590550510581485
Liang, T.-P., Chen, H.-Y., & Turban, E. (2009). Effect of personalization on the perceived usefulness of online customer services: A dual-core theory. Proceedings of the 11th International Conference on Electronic Commerce (pp. 279–288). New York, NY.: Association for Computing Machinery. doi: 10.1145/1593254.1593296
Marza, S., Idris, I., & Abror, A. (2019, April). The influence of convenience, enjoyment, perceived risk, and trust on the attitude toward online shopping. Proceedings of the 2nd Padang International Conference on Education, Economics, Business and Accounting (PICEEBA-2 2018) (pp. 304–313). Atlantis Press. doi: 10.2991/piceeba2-18.2019.40
Mortimer, G., Fazal e Hasan, S., Andrews, L., & Martin, J. (2016). Online grocery shopping: The impact of shopping frequency on perceived risk. The International Review of Retail, Distribution and Consumer Research, 26(2), 202–223. doi: 10.1080/09593969.2015.1130737
Nguyen, L., Nguyen, T. H., & Tan, T. K. P. (2021). An empirical study of customers’ satisfaction and repurchase intention on online shopping in Vietnam. The Journal of Asian Finance, Economics and Business, 8(1), 971–983. doi: 10.13106/JAFEB.2021.VOL8.NO1.971
Nguyen Thi Binh, Tran Thi Lan Anh, Tran Thi Thu Hien, Le Thanh Thao, Tran Phan Nhat Hang, & Nguyen Minh Hieu. (2022). Factors influencing continuance intention of online shopping of generation Y and Z during the new normal in Vietnam. Cogent Business & Management, 9(1), 2143016. doi: 10.1080/23311975.2022.2143016
Nguyen, X. T., Lai, M.-T., & Yan, H. (2017). The effect of perceived risk on repurchase intention and word – of – mouth in the mobile telecommunication market: A case study from Vietnam. International Business Research, 10(3), 8–19. doi: 10.5539/ibr.v10n3p8
Pentz, C. D., du Preez, R., & Swiegers, L. (2020). To bu(Y) or not to bu(Y): Perceived risk barriers to online shopping among South African generation Y consumers. Cogent Business & Management, 7(1), 1827813. doi: 10.1080/23311975.2020.1827813
Phùng Ngọc Bảo. (2020). Thành phố Hồ Chí Minh giữ vững vai trò đầu tàu phát triển của vùng kinh tế trọng điểm phía Nam. Truy cập ngày 25/12/2022, từ https://www.tapchicongsan.org.vn/web/guest/thuc-tien-kinh-nghiem1/-/2018/820620/thanh-pho-ho-chi-minh-giu-vung-vai-tro-dau-tau-phat-trien-cua-vung-kinh-te-trong-diem-phia-nam.aspx
Rosqvist, L. S., & Hiselius, L. W. (2016). Online shopping habits and the potential for reductions in carbon dioxide emissions from passenger transport. Journal of Cleaner Production, 131, 163–169. doi: 10.1016/j.jclepro.2016.05.054
Sarkar, S., & Khare, A. (2017). Moderating effect of price perception on factors affecting attitude towards online shopping. Journal of Marketing Analytics, 5(2), 68–80. doi: 10.1057/s41270-017-0018-2
Saut, M., & Saing, T. (2021). Factors affecting consumer purchase intention towards environmentally friendly products: A case of generation Z studying at universities in Phnom Penh. SN Business & Economics, 1(6), 83. doi: 10.1007/s43546-021-00085-2
Statista. (2022). Global retail e-commerce market size 2014-2023. Retrieved May 3, 2022, from https://www.statista.com/statistics/379046/worldwide-retail-e-commerce-sales/
Su, N. D., Nguyen, A. N. N., Nguyen, T. N. L., Luu, T. T., & Nguyen, P. Q. D. (2022). Modeling consumers’ trust in mobile food delivery apps: Perspectives of technology acceptance model, mobile service quality and personalization-privacy theory. Journal of Hospitality Marketing & Management, 31(5), 535–560. doi: 10.1080/19368623.2022.2020199
Tsai, H.-T., & Huang, H.-C. (2007). Determinants of e-repurchase intentions: An integrative model of quadruple retention drivers. Information & Management, 44(3), 231–239. doi: 10.1016/j.im.2006.11.006
VECOM. (2022). Báo cáo chỉ số thương mại điện tử việt nam 2022. Truy cập ngày 16/12/2022, từ https://vecom.vn/bao-cao-chi-so-thuong-mai-dien-tu-viet-nam-2022
Venkatesh, V., & Davis, F. D. (2000). A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies. Management Science, 46(2), 186–204. doi: 10.1287/mnsc.46.2.186.11926
Voorhees, C. M., Brady, M. K., Calantone, R., & Ramirez, E. (2016). Discriminant validity testing in marketing: An analysis, causes for concern, and proposed remedies. Journal of the Academy of Marketing Science, 44(1), 119–134. doi: 10.1007/s11747-015-0455-4
Wu, J., & Song, S. (2021). Older adults’ online shopping continuance intentions: Applying the technology acceptance model and the theory of planned behavior. International Journal of Human–Computer Interaction, 37(10), 938–948. doi: 10.1080/10447318.2020.1861419
Wu, L.-Y., Chen, K.-Y., Chen, P.-Y., & Cheng, S.-L. (2014). Perceived value, transaction cost, and repurchase-intention in online shopping: A relational exchange perspective. Journal of Business Research, 67(1), 2768–2776. doi: 10.1016/j.jbusres.2012.09.007
Yang, H., & Yoo, Y. (2004). It’s all about attitude: Revisiting the technology acceptance model. Decision Support Systems, 38(1), 19–31. doi: 10.1016/S0167-9236(03)00062-9
Zhang, Y., Fang, Y., Wei, K.-K., Ramsey, E., McCole, P., & Chen, H. (2011). Repurchase intention in B2C e-commerce - A relationship quality perspective. Information & Management, 48(6), 192–200. doi: 10.1016/j.im.2011.05.003
Zhou, T., Lu, Y., & Wang, B. (2009). The relative importance of website design quality and service quality in determining consumers’ online repurchase behavior. Information Systems Management, 26(4), 327–337. doi: 10.1080/10580530903245663
Downloads
Published
Issue
Section
License
Copyright (c) 2023 JOURNAL OF ASIAN BUSINESS AND ECONOMIC STUDIES

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.



