Tác động của cá nhân hóa đến ý định tiếp tục sử dụng nền tảng thương mại điện tử: vai trò trung gian của cảm nhận hữu ích và cảm nhận thích thú
Tóm tắt: 0
| 
PDF: 0 
##plugins.themes.academic_pro.article.main##
Author
Từ khóa:
Cảm nhận cá nhân hóa
Cảm nhận hữu ích
Cảm nhận thích thú
Ý định tiếp tục sử dụng
Thương mại điện tử
fsQCA
Tóm tắt
Nghiên cứu xem xét tác động của Cảm nhận cá nhân hóa (CNH) đến Ý định tiếp tục sử dụng (YD) trên các nền tảng Thương mại điện tử (TMĐT) thông qua cơ chế trung gian của Cảm nhận hữu ích (HI) và Cảm nhận thích thú (TT). Dữ liệu thu thập từ 384 người dùng tại Việt Nam có tối thiểu 06 tháng kinh nghiệm sử dụng nền tảng TMĐT, được phân tích bằng phương pháp PLS-SEM kết hợp fsQCA. Phân tích PLS-SEM khẳng định CNH không chỉ tác động trực tiếp mà còn gián tiếp thúc đẩy YD thông qua việc nâng cao mức độ HI và TT của người dùng. Phân tích fsQCA chỉ ra rằng không tồn tại yếu tố đơn lẻ mang tính quyết định, đồng thời làm rõ sự tương tác giữa các nhóm điều kiện dẫn đến hành vi. Nhóm điều kiện CNH kết hợp với HI đạt giá trị giải thích đặc thù cao nhất, ngoài ra, HI được xác định là yếu tố quan trọng trong các nhóm điều kiện, đóng vai trò bù đắp cho các hạn chế về mặt chức năng nhằm duy trì YD.
Tài liệu tham khảo
-
[1] Google, Temasek, and Bain & Company, e-Conomy SEA 2025: From Digital Decade to AI Reality - Accelerating the future in ASEAN, e-Conomy SEA Report, 11 Nov. 2025. [Accessed: 19-Jan-2026].
[2] M. A. Gomes, P. Meisen, and T. Meisen, “Efficient Personalization in E-Commerce: Leveraging Universal Customer Representations with Embeddings,” Journal of Theoretical and Applied Electronic Commerce Research, vol. 20, no. 1, p. 12, Jan. 2025, doi: https://doi.org/10.3390/jtaer20010012
[3] E. Maslowska, E. G. Smit, and B. van den Putte, “It Is All in the Name: A Study of Consumers' Responses to Personalized Communication,” Journal of Interactive Advertising, vol. 16, no. 1, pp. 74-85, 2016, doi: https://doi.org/10.1080/15252019.2016.1161568
[4] N. C. Aksoy et al., “Personalization in marketing: how do people perceive personalization practices in the business world?,” Journal of Electronic Commerce Research, vol. 24, no. 4, pp. 269-297, 2023.
[5] C. Li, “When does web-based personalization really work? The distinction between actual personalization and perceived personalization,” Computers in Human Behavior, vol. 54, pp. 25–33, Aug. 2015, doi: https://doi.org/10.1016/j.chb.2015.07.049
[6] X. He, Q. Liu, and S. Jung, “The Impact of recommendation system on User satisfaction: A moderated mediation approach,” Journal of Theoretical and Applied Electronic Commerce Research, vol. 19, no. 1, pp. 448–466, Feb. 2024, doi: https://doi.org/10.3390/jtaer19010024
[7] D. Shin, “How do users interact with algorithm recommender systems? The interaction of users, algorithms, and performance,” Computers in Human Behavior, vol. 109, p. 106344, Mar. 2020, doi: https://doi.org/10.1016/j.chb.2020.106344
[8] B. P. Knijnenburg, M. C. Willemsen, Z. Gantner, H. Soncu, and C. Newell, “Explaining the user experience of recommender systems,” User Modeling and User-Adapted Interaction, vol. 22, no. 4–5, pp. 441–504, Mar. 2012, doi: https://doi.org/10.1007/s11257-011-9118-4
[9] F. E. Zaizi, S. Qassimi, and S. Rakrak, “Multi-objective optimization with recommender systems: A systematic review,” Information Systems, vol. 117, p. 102233, Jun. 2023, doi: https://doi.org/10.1016/j.is.2023.102233
[10] N. C. Aksoy, E. T. Kabadayi, C. Yilmaz, and A. K. Alan, “A typology of personalisation practices in marketing in the digital age,” Journal of Marketing Management, vol. 37, no. 11–12, pp. 1091–1122, Jul. 2021, doi: https://doi.org/10.1080/0267257X.2020.1866647
[11] O. Tyrväinen, H. Karjaluoto, and H. Saarijärvi, “Personalization and hedonic motivation in creating customer experiences and loyalty in omnichannel retail,” Journal of Retailing and Consumer Services, vol. 57, p. 102233, Aug. 2020, doi: https://doi.org/10.1016/j.jretconser.2020.102233
[12] U. Noor, M. Mansoor, and A. Shamim, “Customers create customers!–Assessing the role of perceived personalization, online advertising engagement and online users’ modes in generating positive e-WOM,” Asia-Pacific Journal of Business Administration, vol. 16, no. 2, pp. 392–409, Oct. 2022, doi: https://doi.org/10.1108/APJBA-11-2021-0569
[13] S. Alimamy and J. Gnoth, “I want it my way! The effect of perceptions of personalization through augmented reality and online shopping on customer intentions to co-create value,” Computers in Human Behavior, vol. 128, p. 107105, Dec. 2021, doi: https://doi.org/10.1016/j.chb.2021.107105
[14] V. A. Vieira, D. N. Rafael, and R. Agnihotri, “Augmented reality generalizations: A meta-analytical review on consumer-related outcomes and the mediating role of hedonic and utilitarian values,” Journal of Business Research, vol. 151, pp. 170–184, Jul. 2022, doi: https://doi.org/10.1016/j.jbusres.2022.06.030
[15] X. Wang and D. H.-L. Goh, “Video Game Acceptance: A Meta-Analysis of the Extended Technology Acceptance Model,” Cyberpsychology Behavior and Social Networking, vol. 20, no. 11, pp. 662–671, Nov. 2017, doi: https://doi.org/10.1089/cyber.2017.0086
[16] M. Ayalew and S. Zewdie, “What factors determine the online consumer behavior in this digitalized world? A systematic literature,” Human Behavior and Emerging Technologies, vol. 2022, pp. 1–18, Nov. 2022, doi: https://doi.org/10.1155/2022/1298378
[17] J. Yin, X. Qiu, and Y. Wang, “The Impact of AI-Personalized Recommendations on Clicking Intentions: Evidence from Chinese E-Commerce,” Journal of Theoretical and Applied Electronic Commerce Research, vol. 20, no. 1, p. 21, Feb. 2025, doi: https://doi.org/10.3390/jtaer20010021
[18] P. B. Pires, M. Prisco, C. Delgado, and J. D. Santos, “A Conceptual Approach to Understanding the Customer Experience in E-Commerce: An Empirical study,” Journal of Theoretical and Applied Electronic Commerce Research, vol. 19, no. 3, pp. 1943–1983, Jul. 2024, doi: https://doi.org/10.3390/jtaer19030096
[19] H. Yang, Y. Luo, Y. Qiu, J. Zou, M. Masukujjaman, and A. M. Ibrahim, “Modeling the Enablers of Consumers’ E-Shopping Behavior: A Multi-Analytic Approach,” Sustainability, vol. 15, no. 8, p. 6564, Apr. 2023, doi: https://doi.org/10.3390/su15086564
[20] A. Alanadoly and S. Salem, “Fashion involvement, opinion-seeking and product variety as stimulators for fashion e-commerce: an investigated model based on S-O-R model,” Asia Pacific Journal of Marketing and Logistics, vol. 34, no. 10, pp. 2410–2434, Dec. 2021, doi: https://doi.org/10.1108/APJML-06-2021-0447
[21] N. Hasan and Y. Bao, “A mixed-method approach to assess users’ intention to use mobile health (mHealth) using PLS-SEM and fsQCA,” Aslib Journal of Information Management, vol. 74, no. 4, pp. 589–630, Jan. 2022, doi: https://doi.org/10.1108/AJIM-07-2021-0211
[22] S. M. Rasoolimanesh, C. M. Ringle, M. Sarstedt, and H. Olya, “The combined use of symmetric and asymmetric approaches: partial least squares-structural equation modeling and fuzzy-set qualitative comparative analysis,” International Journal of Contemporary Hospitality Management, vol. 33, no. 5, pp. 1571–1592, May 2021, doi: https://doi.org/10.1108/IJCHM-10-2020-1164
[23] G. K. An and T. T. A. Ngo, “AI-powered personalized advertising and purchase intention in Vietnam’s digital landscape: The role of trust, relevance, and usefulness,” Journal of Open Innovation Technology Market and Complexity, vol. 11, no. 3, p. 100580, Jun. 2025, doi: https://doi.org/10.1016/j.joitmc.2025.100580
[24] J. W. Palmer, “Web site usability, design, and performance metrics,” Information Systems Research, vol. 13, no. 2, pp. 151–167, Jun. 2002, doi: https://doi.org/10.1287/isre.13.2.151.88
[25] S. Y. X. Komiak and I. Benbasat, “The effects of personalization and familiarity on trust and adoption of recommendation agents,” MIS Quarterly, vol. 30, no. 4, pp. 941–960, Dec. 2006, doi: https://doi.org/10.2307/25148760
[26] F. D. Davis, R. P. Bagozzi, and P. R. Warshaw, “Extrinsic and intrinsic motivation to use computers in the workplace1,” Journal of Applied Social Psychology, vol. 22, no. 14, pp. 1111–1132, Jul. 1992, doi: https://doi.org/10.1111/j.1559-1816.1992.tb00945.x
[27] F. D. Davis, R. P. Bagozzi, and P. R. Warshaw, “Extrinsic and intrinsic motivation to use computers in the workplace,” Journal of Applied Social Psychology, vol. 22, no. 14, pp. 1111–1132, Jul. 1992, doi: https://doi.org/10.1111/j.1559-1816.1992.tb00945.x
[28] D. Tsekouras, T. Li, and I. Benbasat, “Scratch my back and I’ll scratch yours: The impact of user effort and recommendation agent effort on perceived recommendation agent quality,” Information & Management, vol. 59, no. 1, p. 103571, Nov. 2021, doi: https://doi.org/10.1016/j.im.2021.103571
[29] E. Engström, I. Vartanova, J. V. Johansson, M. Persson, and P. Strimling, “Comparing and modeling the use of online recommender systems,” Computers in Human Behavior Reports, vol. 15, p. 100449, Jul. 2024, doi: https://doi.org/10.1016/j.chbr.2024.100449
[30] D. Mican and D.-A. Sitar-Taut, “The effect of perceived usefulness of recommender systems and information sources on purchase intention,” Kybernetes, vol. 53, no. 7, pp. 2301–2321, Mar. 2023, doi: https://doi.org/10.1108/K-08-2022-1145
[31] U. Gretzel and D. R. Fesenmaier, “Persuasion in recommender systems,” International Journal of Electronic Commerce, vol. 11, no. 2, pp. 81–100, Dec. 2006, doi: https://doi.org/10.2753/JEC1086-4415110204
[32] J. R. Lewis and J. Sauro, “Effect of perceived ease of use and usefulness on UX and behavioral outcomes,” International Journal of Human-Computer Interaction, vol. 40, no. 20, pp. 6676–6683, Sep. 2023, doi: https://doi.org/10.1080/10447318.2023.2260164
[33] A. Mishra, A. Shukla, N. P. Rana, W. L. Currie, and Y. K. Dwivedi, “Re-examining post-acceptance model of information systems continuance: A revised theoretical model using MASEM approach,” International Journal of Information Management, vol. 68, p. 102571, Aug. 2022, doi: https://doi.org/10.1016/j.ijinfomgt.2022.102571
[34] A. Mehrabian and J. A. Russell, An Approach to Environmental Psychology. Cambridge, MA, USA: MIT Press, 1974.
[35] J. Jacoby, “Stimulus-organism-response reconsidered: an evolutionary step in modeling (consumer) behavior,” Journal of Consumer Psychology, vol. 12, no. 1, pp. 51–57, 2002.
[36] H. Lee, “Interest-Based E-Commerce and users’ purchase intention on social network platforms,” IEEE Access, vol. 12, pp. 87451–87466, Jan. 2024, doi: https://doi.org/10.1109/ACCESS.2024.3417440
[37] S.-C. Lin, H.-T. Tseng, F. Shirazi, et al., “Exploring factors influencing impulse buying in live streaming shopping: a stimulus-organism-response (SOR) perspective,” Asia Pacific Journal of Marketing and Logistics, vol. 35, no. 6, pp. 1383–1403, Aug. 2022, doi: https://doi.org/10.1108/APJML-12-2021-0903
[38] J. Jeong, D. Kim, X. Li, Q. Li, I. Choi, and J. Kim, “An Empirical investigation of personalized recommendation and reward effect on customer behavior: A Stimulus–Organism–Response (SOR) model perspective,” Sustainability, vol. 14, no. 22, p. 15369, Nov. 2022, doi: https://doi.org/10.3390/su142215369
[39] B. Taheri, A. Yousaf, M. Gannon, and A. Mishra, “e-commerce website customer engagement: Delineating the role of UTAUT, vividness, and compulsion,” Journal of Retailing and Consumer Services, vol. 79, p. 103835, Mar. 2024, doi: https://doi.org/10.1016/j.jretconser.2024.103835
[40] B. Ying, Y. Duan, S. Zheng, and X. Zheng, “Impact of information overload on Consumer Decision‐Making in the Agri‐Food Sector: A Stimulus‐Organism‐Response Theory Perspective,” Journal of Consumer Affairs, vol. 59, no. 4, Nov. 2025, doi: https://doi.org/10.1111/joca.70031
[41] H. Pang, X. Jin, and W. Zhang, “Deciphering the underlying repercussions of cognitive overload on university students’ fatigue, frustration and academic productivity: Implementation of stimulus–organism–response model,” Acta Psychologica, vol. 260, p. 105469, Aug. 2025, doi: https://doi.org/10.1016/j.actpsy.2025.105469
[42] S. Laato, A. K. M. n. Islam, A. Farooq, and A. Dhir, “Unusual purchasing behavior during the early stages of the COVID-19 pandemic: The stimulus-organism-response approach,” Journal of Retailing and Consumer Services, vol. 57, p. 102224, Jul. 2020, doi: https://doi.org/10.1016/j.jretconser.2020.102224
[43] A. Bhattacherjee, “An empirical analysis of the antecedents of electronic commerce service continuance,” Decision Support Systems, vol. 32, no. 2, pp. 201–214, Dec. 2001, doi: https://doi.org/10.1016/S0167-9236(01)00111-7
[44] V. Kumar and O. G. Ayodeji, “E-retail factors for customer activation and retention: An empirical study from Indian e-commerce customers,” Journal of Retailing and Consumer Services, vol. 59, p. 102399, Nov. 2020, doi: https://doi.org/10.1016/j.jretconser.2020.102399
[45] C. Wen, V. R. Prybutok, and C. Xu, “An integrated model for customer online repurchase intention,” Journal of Computer Information Systems, vol. 52, no. 1, pp. 14–23, 2011.
[46] F. D. Davis, “Perceived usefulness, perceived ease of use and user acceptance of information technology,” MIS Quarterly, vol. 13, no. 3, pp. 319–340, 1989.
[47] T. Huang, “Using SOR framework to explore the driving factors of older adults smartphone use behavior,” Humanities and Social Sciences Communications, vol. 10, no. 1, Oct. 2023, doi: https://doi.org/10.1057/s41599-023-02221-9
[48] J. Serrano-Malebrán and J. Arenas-Gaitán, “When does personalization work on social media? a posteriori segmentation of consumers,” Multimedia Tools and Applications, vol. 80, no. 30, pp. 36509–36528, Sep. 2021, doi: https://doi.org/10.1007/s11042-021-11303-2
[49] A. Bleier and M. Eisenbeiss, “The importance of trust for personalized online advertising,” Journal of Retailing, vol. 91, no. 3, pp. 390–409, May 2015, doi: https://doi.org/10.1016/j.jretai.2015.04.001
[50] E. Aguirre, D. Mahr, D. Grewal, K. De Ruyter, and M. Wetzels, “Unraveling the personalization paradox: The Effect of Information Collection and Trust-Building strategies on online advertisement effectiveness,” Journal of Retailing, vol. 91, no. 1, pp. 34–49, Nov. 2014, doi: https://doi.org/10.1016/j.jretai.2014.09.005
[51] D. Mican, D.-A. Sitar-Tăut, and O.-I. Moisescu, “Perceived usefulness: A silver bullet to assure user data availability for online recommendation systems,” Decision Support Systems, vol. 139, p. 113420, Oct. 2020, doi: https://doi.org/10.1016/j.dss.2020.113420
[52] O.-I. Bunea, R.-A. Corboș, S. I. Mișu, M. Triculescu, and A. Trifu, “The Next-Generation Shopper: A study of Generation-Z perceptions of AI in Online shopping,” Journal of Theoretical and Applied Electronic Commerce Research, vol. 19, no. 4, pp. 2605–2629, Sep. 2024, doi: https://doi.org/10.3390/jtaer19040125
[53] Y. W. Song, H. S. Lim, and J. Oh, “‘We think you may like this’: An investigation of electronic commerce personalization for privacy‐conscious consumers,” Psychology and Marketing, vol. 38, no. 10, pp. 1723–1740, May 2021, doi: https://doi.org/10.1002/mar.21501
[54] T. Natarajan, S. A. Balasubramanian, and D. L. Kasilingam, “Understanding the intention to use mobile shopping applications and its influence on price sensitivity,” Journal of Retailing and Consumer Services, vol. 37, pp. 8–22, Mar. 2017, doi: https://doi.org/10.1016/j.jretconser.2017.02.010
[55] S. Hu, J. Liu, H. Li, J. Yin, and X. Liu, “Exploring the mechanism of AI-Powered Personalized Product recommendation on Generation Z users’ spontaneous buying intention on Short-Form Video platforms: A Perceived Evaluation Perspective,” Journal of Theoretical and Applied Electronic Commerce Research, vol. 20, no. 4, p. 290, Oct. 2025, doi: https://doi.org/10.3390/jtaer20040290
[56] R. Pereira and C. Tam, “Impact of enjoyment on the usage continuance intention of video-on-demand services,” Information & Management, vol. 58, no. 7, p. 103501, Jun. 2021, doi: https://doi.org/10.1016/j.im.2021.103501
[57] A. Costa, V. Marozzo, and T. Abbate, “Consumers’ attitudes toward virtual try-on technology: an extended TAM model”, International Journal of Retail & Distribution Management, vol. 53, no. 13, pp. 184–199, Nov. 2025, doi: https://doi.org/10.1108/IJRDM-01-2025-0060
[58] Md. S. Rahman, Md. M. Sabbir, and J. Zhang, “Understanding customer experience and engagement in digital assistant-based retail interactions,” International Journal of Retail & Distribution Management, vol. 54, no. 1, pp. 45–59, Nov. 2025, doi: https://doi.org/10.1108/IJRDM-03-2025-0171
[59] H. X. Chong, A. H. Hashim, S. Osman, J. L. Lau, and E. C.-X. Aw, “The future of e-commerce? Understanding livestreaming commerce continuance usage,” International Journal of Retail & Distribution Management, vol. 51, no. 1, pp. 1–20, Aug. 2022, doi: https://doi.org/10.1108/IJRDM-01-2022-0007
[60] V. Patel, K. Das, R. Chatterjee, and Y. Shukla, “Does the interface quality of mobile shopping apps affect purchase intention? An empirical study,” Australasian Marketing Journal (AMJ), vol. 28, no. 4, pp. 300–309, Sep. 2020, doi: https://doi.org/10.1016/j.ausmj.2020.08.004
[61] V. Venkatesh, “Determinants of Perceived Ease of Use: Integrating Control, Intrinsic Motivation, and Emotion into the Technology Acceptance Model,” Information Systems Research, vol. 11, no. 4, pp. 342–365, Dec. 2000, doi: https://doi.org/10.1287/isre.11.4.342.11872
[62] L. Hu, R. Filieri, F. Acikgoz, L. Zollo, and R. Rialti, “The effect of utilitarian and hedonic motivations on mobile shopping outcomes. A cross‐cultural analysis,” International Journal of Consumer Studies, vol. 47, no. 2, pp. 751–766, Sep. 2022, doi: https://doi.org/10.1111/ijcs.12868
[63] D. T. Cuong, “Positive emotions influencing consumer shopping behavior on e-commerce platforms,” Management & Marketing, vol. 19, no. 1, pp. 15–31, Mar. 2024, doi: https://doi.org/10.2478/mmcks-2024-0002
[64] F. Hateftabar, “Analyzing the adoption of online tourism purchases: effects of perceived tourism value and personal innovativeness,” Current Issues in Tourism, vol. 26, no. 11, pp. 1861–1877, May 2022, doi: https://doi.org/10.1080/13683500.2022.2071682
[65] S. R. Adawiyah, B. Purwandari, I. Eitiveni, and E. H. Purwaningsih, “The influence of AI and AR technology in personalized recommendations on customer usage intention: a case study of cosmetic products on Shopee,” Applied Sciences, vol. 14, no. 13, p. 5786, Jul. 2024, doi: https://doi.org/10.3390/app14135786
[66] Y. Luo, L. Yang, Q. Ye, and Q. Liao, “Effects of customization and personalization affordances on perceived value and continuance intention of smartwatch use,” Technological Forecasting and Social Change, vol. 194, p. 122752, Jul. 2023, doi: https://doi.org/10.1016/j.techfore.2023.122752
[67] J. Lee, C. Kim, and K. C. Lee, “Exploring the personalization-intrusiveness-intention framework to evaluate the effects of personalization in social media,” International Journal of Information Management, vol. 66, p. 102532, May 2022, doi: https://doi.org/10.1016/j.ijinfomgt.2022.102532
[68] A. R. Smink, E. A. Van Reijmersdal, G. Van Noort, and P. C. Neijens, “Shopping in augmented reality: The effects of spatial presence, personalization and intrusiveness on app and brand responses,” Journal of Business Research, vol. 118, pp. 474–485, Jul. 2020, doi: https://doi.org/10.1016/j.jbusres.2020.07.018
[69] T.-P. Liang, H.-Y. Chen, and E. Turban, “Effect of personalization on the perceived usefulness of online customer services,” Effect of Personalization on the Perceived Usefulness of Online Customer Services: A Dual-core Theory, pp. 279–288, Aug. 2009, doi: https://doi.org/10.1145/1593254.1593296
[70] M. Ashraf, n. I. Jaafar, and A. Sulaiman, “System- vs. consumer-generated recommendations: affective and social-psychological effects on purchase intention,” Behaviour and Information Technology, vol. 38, no. 12, pp. 1259–1272, Feb. 2019, doi: https://doi.org/10.1080/0144929X.2019.1583285
[71] C. Bianchi and M. A. Saleh, “Investigating the drivers of E-Commerce continuance intentions among older consumers in Latin America,” Journal of Internet Commerce, vol. 23, no. 4, pp. 384–413, Oct. 2024, doi: https://doi.org/10.1080/15332861.2024.2424141
[72] J. Hair, C. L. Hollingsworth, A. B. Randolph, and A. Y. L. Chong, “An updated and expanded assessment of PLS-SEM in information systems research,” Industrial Management & Data Systems, vol. 117, no. 3, pp. 442–458, Mar. 2017, doi: https://doi.org/10.1108/IMDS-04-2016-0130
[73] A. G. Woodside, “Moving beyond multiple regression analysis to algorithms: Calling for adoption of a paradigm shift from symmetric to asymmetric thinking in data analysis and crafting theory,” Journal of Business Research, vol. 66, no. 4, pp. 463–472, Jan. 2013, doi: https://doi.org/10.1016/j.jbusres.2012.12.021
[74] C. C. Ragin, “Fuzzy sets: Calibration versus measurement,” in The Oxford Handbook of Political Science: Methodology, vol. 2, 2007.
[75] S. Kraus, D. Ribeiro-Soriano, and M. Schüssler, “Fuzzy-set qualitative comparative analysis (fsQCA) in entrepreneurship and innovation research – the rise of a method,” International Entrepreneurship and Management Journal, vol. 14, no. 1, pp. 15–33, Jul. 2017, doi: https://doi.org/10.1007/s11365-017-0461-8
[76] A. Marx, B. Rihoux, and C. Ragin, “The origins, development, and application of Qualitative Comparative Analysis: the first 25 years,” European Political Science Review, vol. 6, no. 1, pp. 115–142, Feb. 2013, doi: https://doi.org/10.1017/S1755773912000318
[77] I. O. Pappas and A. G. Woodside, “Fuzzy-set Qualitative Comparative Analysis (fsQCA): Guidelines for research practice in Information Systems and marketing,” International Journal of Information Management, vol. 58, p. 102310, Feb. 2021, doi: https://doi.org/10.1016/j.ijinfomgt.2021.102310
[78] A. G. Woodside, E. Ko, and T. Huan, “The new logic in building isomorphic theory of management decision realities,” Management Decision, vol. 50, no. 5, pp. 765–777, May 2012, doi: https://doi.org/10.1108/00251741211227429
[79] J. F. Hair et al., “Executing and interpreting applications of PLS-SEM: Updates for family business researchers,” Journal of Family Business Strategy, vol. 12, no. 3, p. 100392, Nov. 2020, doi: https://doi.org/10.1016/j.jfbs.2020.100392
[80] J. Henseler, G. Hubona, and P. A. Ray, “Using PLS path modeling in new technology research: updated guidelines,” Industrial Management & Data Systems, vol. 116, no. 1, pp. 2–20, Jan. 2016, doi: https://doi.org/10.1108/IMDS-09-2015-0382
[81] C. Fornell and D. F. Larcker, “Evaluating Structural Equation Models with Unobservable Variables and Measurement Error,” Journal of Marketing Research, vol. 18, no. 1, pp. 39–50, Feb. 1981, doi: https://doi.org/10.1177/002224378101800104
[82] J. Henseler, C. M. Ringle, and M. Sarstedt, “A new criterion for assessing discriminant validity in variance-based structural equation modeling,” Journal of the Academy of Marketing Science, vol. 43, no. 1, pp. 115–135, Aug. 2014, doi: https://doi.org/10.1007/s11747-014-0403-8
[83] C. C. Ragin, “What is qualitative comparative analysis?,” University of Arizona, Tucson, AZ, USA, 2008.
[84] J. Dul, “Identifying single necessary conditions with NCA and fsQCA,” Journal of Business Research, vol. 69, no. 4, pp. 1516–1523, Nov. 2015, doi: https://doi.org/10.1016/j.jbusres.2015.10.134
[85] N. Al-Qaysi, n. Mohamad-Nordin, and M. Al-Emran, “Factors Affecting the adoption of social media in Higher Education: A Systematic Review of the technology Acceptance model,” Studies in Systems, Decision and Control, pp. 571–584, Jun. 2020, doi: https://doi.org/10.1007/978-3-030-47411-9_31
[86] M. Gao and L. Huang, “The mediating role of perceived enjoyment and attitude consistency in omni-channel retailing,” Asia Pacific Journal of Marketing and Logistics, vol. 36, no. 3, pp. 599–621, Sep. 2023, doi: https://doi.org/10.1108/APJML-01-2023-0079
[87] E. C.-X. Aw, G. W.-H. Tan, S. H.-W. Chuah, K.-B. Ooi, and n. Hajli, “Be my friend! Cultivating parasocial relationships with social media influencers: findings from PLS-SEM and fsQCA,” Information Technology and People, vol. 36, no. 1, pp. 66–94, Jan. 2022, doi: https://doi.org/10.1108/ITP-07-2021-0548
[88] J. Tang and F. Yang, “Value-in-Use and Sustaining Use intention on E-Commerce Platforms: The Service-Dominant Logic Perspective,” Sustainability, vol. 17, no. 3, p. 1335, Feb. 2025, doi: https://doi.org/10.3390/su17031335
[89] A. Ruangkanjanases, A. Khan, O. Sivarak, U. Rahardja, and S.-C. Chen, “Modeling the Consumers’ Flow Experience in E-commerce: The Integration of ECM and TAM with the Antecedents of Flow Experience,” SAGE Open, vol. 14, no. 2, Apr. 2024, doi: https://doi.org/10.1177/21582440241258595
[90] T. T. Nguyen, H. T. T. Truong, and T. Le-Anh, “Online purchase intention under the integration of Theory of Planned Behavior and Technology acceptance model,” SAGE Open, vol. 13, no. 4, Oct. 2023, doi: https://doi.org/10.1177/21582440231218814
[91] X. Yang, L. Zhang, and Z. Feng, “Personalized tourism recommendations and the E-Tourism user experience,” Journal of Travel Research, vol. 63, no. 5, pp. 1183–1200, Jul. 2023, doi: https://doi.org/10.1177/00472875231187332
[92] T. Teepapal, “AI-driven personalization: Unraveling consumer perceptions in social media engagement,” Computers in Human Behavior, vol. 165, p. 108549, Dec. 2024, doi: https://doi.org/10.1016/j.chb.2024.108549
[93] Y. Ping, Y. Li, and J. Zhu, “Beyond accuracy measures: the effect of diversity, novelty and serendipity in recommender systems on user engagement,” Electronic Commerce Research, vol. 25, no. 3, pp. 2177–2204, Feb. 2024, doi: https://doi.org/10.1007/s10660-024-09813-w
[94] P. Raman, “Examining the importance of gamification, social interaction and perceived enjoyment among young female online buyers in India,” Young Consumers Insight and Ideas for Responsible Marketers, vol. 22, no. 3, pp. 387–412, Sep. 2020, doi: https://doi.org/10.1108/YC-05-2020-1148
[95] Q. Yan et al., “Effects of product portfolios and recommendation timing in the efficiency of personalized recommendation,” Journal of Consumer Behaviour, vol. 15, no. 6, pp. 516–526, Jun. 2016, doi: https://doi.org/10.1002/cb.1588
[96] S.-C. Huang, A. D. K. Silalahi, I. J. Eunike, and D. Riantama, “Understanding impulse buying in E-commerce: The Big Five traits perspective and moderating effect of time pressure and emotions,” Telematics and Informatics Reports, vol. 15, p. 100157, Jul. 2024, doi: https://doi.org/10.1016/j.teler.2024.100157
[97] T. Lam, “Transparency requirements after the pandemic: traceability information, information usefulness and trust,” Industrial Management & Data Systems, vol. 124, no. 10, pp. 2965–2988, 2024, doi: https://doi.org/10.1108/IMDS-03-2024-0171
Xem thêm
##plugins.themes.academic_pro.article.sidebar##
Đã Xuất bản
Mar 20, 2026
Download
Cách trích dẫn
Quan, N. H., L. T. H. Ha, N. M. Yen, và N. L. Phuong. “Tác động của Cá nhân hóa đến ý định tiếp tục sử dụng nền tảng thương mại điện tử: Vai Trò Trung Gian của cảm nhận hữu ích Và cảm nhận thích Thú”. Tạp Chí Khoa học Và Công nghệ Đại học Đà Nẵng, vol 24, số p.h 2, Tháng Ba 2026, tr 68-76, doi:10.31130/ud-jst.2026.24(2).057.
