Digital Marketing Strategies for Thai Elderly Consumers: The Role of Digital Financial Trust and Social Proof
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This study examines the relationships between human capital, economic factors, digital tech-nology access, digital financial experience, and social proof on online purchase behavior among Thai older adults, testing interaction effects between digital financial experience and social proof. Secondary data from the ICT Household Survey (Q2/2024) comprising 53,491 respondents aged 60+, representing 14.0 million weighted population, were analyzed using Weighted Hierarchical Binary Logistic Regression. Results show 17.9% of older adults purchased products online. The strongest correlates were e-Payment (OR=3.41, 95% CI: 3.05–3.81, p<0.001), e-Banking (OR=2.18, 95% CI: 1.95–2.44, p<0.001), and social media use (OR=1.52, 95% CI: 1.38–1.68, p<0.001). A significant synergistic interaction was found between digital financial experience and social proof (OR=3.11, 95% CI: 2.54–3.81, p<0.001). Findings reveal digital access alone is insufficient; older adults require digital trust from successful financial transaction experiences and social validation. This study proposes the Trust-Finance Flywheel Model as a Conceptual Explanatory Framework derived from associational evidence and suggests four strategies: (1) cre-ating successful transaction experiences, (2) building social proof, (3) Assisted Commerce Model, and (4) Age-Specific User Experience.
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References
สำนักงานสถิติแห่งชาติ. (2567). รายงานการสำรวจการใช้เทคโนโลยีสารสนเทศและการสื่อสารในครัวเรือน พ.ศ. 2567 ไตรมาส 2 (ICTH 2567 Q2) [เอกสารที่ไม่ได้ตีพิมพ์]. สำนักงานสถิติแห่งชาติ.
อุบล ไม้พุ่ม. (2566). การยอมรับเทคโนโลยีโทรศัพท์มือถือที่ส่งผลกับความตั้งใจซื้อสินค้าอุปโภคบริโภคออนไลน์ผ่านแอปพลิเคชั่นของผู้บริโภคกลุ่มเบบี้บูมเมอร์ในกรุงเทพมหานคร. วารสารวไลยอลงกรณ์ปริทัศน์, 13(1), 33–46. https://so06.tci-thaijo.org/index.php/var/article/view/260252
Amouzadeh, E., Dianat, I., Faradmal, J., & Babamiri, M. (2025). Optimizing mobile app design for older adults: Systematic review of age-friendly design. Aging Clinical and Experimental Research, 37, 248. https://doi.org/10.1007/s40520-025-03157-7
Berg, H., & Liljedal, K. T. (2022). Elderly consumers in marketing research: A systematic literature review and directions for future research. International Journal of Consumer Studies, 46(5), 1640-1664. https://doi.org/10.1111/ijcs.12830
Chakraborty, R., Lee, J., Bagchi-Sen, S., Upadhyaya, S., & Rao, H. R. (2016). Online shopping in-tention in the context of data breach in online retail stores: An examination of older and younger adults. Decision Support Systems, 83, 47–56. https://doi.org/10.1016/ j.dss.2015.12.007
Cialdini, R. B. (2021). Influence: The psychology of persuasion (New and expanded ed.). Harper Business.
Gefen, D., Karahanna, E., & Straub, D. W. (2003). Trust and TAM in online shopping: An integrated model. MIS Quarterly, 27(1), 51-90. https://doi.org/10.2307/30036519
Hong, W., Liang, C., Ma, Y., & Zhu, J. (2025). Intergenerational digital feedback and digital social integration of older adults: An empirical study from personal initiative perspective. Humanities and Social Sciences Communications, 12, 1144. https://doi.org/10.1057/s41599-025-05518-z
Hosmer, D. W., Lemeshow, S., & Sturdivant, R. X. (2013). Applied logistic regression (3rd ed.). Wiley. https://doi.org/10.1002/9781118548387
Jantavongso, S. (2022). Toward global digital literate citizens: A case of Thailand's aging generation. The Electronic Journal of Information Systems in Developing Countries, 88(2), e12207. https://doi.org/10.1002/isd2.12207
Kebede, A. S., Ozolins, L.-L., Holst, H., & Galvin, K. (2022). Digital engagement of older adults: Scoping review. Journal of Medical Internet Research, 24(12), e40192. https://doi.org/10.2196/40192
Lian, J.-W., & Yen, D. C. (2014). Online shopping drivers and barriers for older adults: Age and gender differences. Computers in Human Behavior, 37, 133-143. https://doi.org/10.1016/j.chb.2014.04.028
Miller, L. M. S., Callegari, R. A., Abah, T., & Fann, H. (2024). Digital literacy training for low-income older adults through undergraduate community-engaged learning: Single-group pretest-posttest study. JMIR Aging, 7(1), e51675. https://doi.org/10.2196/51675
Olumekor, M., Polbitsyn, S. N., Khan, M. S., Singh, H. P., & Alhamad, I. A. (2025). Ageing and digital shopping: Measurement and validation of an innovative framework. PLOS ONE, 20(3), e0315125. https://doi.org/10.1371/journal.pone.0315125
Pavlou, P. A. (2003). Consumer acceptance of electronic commerce: Integrating trust and risk with the technology acceptance model. International Journal of Electronic Commerce, 7(3), 101–134. https://doi.org/10.1080/10864415.2003.11044275
Rajaobelina, L., Brun, I., Line, R., & Cloutier-Bilodeau, C. (2021). Not all elderly are the same: Fostering trust through mobile banking service experience. International Journal of Bank Marketing, 39(1), 85–106. https://doi.org/10.1108/IJBM-05-2020-0288
Van Dijk, J. A. G. M. (2005). The deepening divide: Inequality in the information society. SAGE Publications. https://doi.org/10.4135/9781452229812
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. https://doi.org/10.2307/30036540
Wang, Z., & Huang, X. (2023). Understanding the role of digital finance in facilitating consumer online purchases: An empirical investigation. Finance Research Letters, 55, 103939. https://doi.org/10.1016/j.frl.2023.103939