การยินยอมคุกกี้: ความรำคาญที่รับรู้ ความเชื่อมั่นในแบรนด์ และความตั้งใจซื้อสินค้าออนไลน์

kunnika Jakor

Authors

kunnika Jakor Rajamangala University of Technology Phra Nakhon https://orcid.org/0009-0007-3918-5865

Abstract

This article investigates the effect of perceived annoyance from cookie consent messages on consumers' brand trust and purchase intention when purchasing goods or services online. This study was quantitative research that developed a questionnaire instrument from a literature review. Data was collected from 287 people who had purchased products or services online through online channels that displayed cookie consent and were analyzed using structural equation modeling (SEM). The results of the study found that perceived annoyance did not directly or indirectly influence brand trust and purchase intention. However, brand trust had a significant positive influence on purchase intentions, indicating that brand trust remains the most important factor driving online shopping behavior. Therefore, building and maintaining brand trust yields more pronounced results than simply focusing on reducing consumer annoyance. Entrepreneurs and marketers can use these findings to develop communication strategies that build trust and increase the chances of stimulating and maintaining repeat purchases among online consumers over the long term.

References

Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological Bulletin, 103(3), 411–423. https://doi.org/10.1037/0033-2909.103.3.411

Bagozzi, R. P., Gopinath, M., & Nyer, P. U. (1999). The role of emotions in marketing. Journal of the Academy of Marketing Science, 27(2), 184–206. https://doi.org/10.1177/0092070399272005

Balaskas, S., Kotsari, G., & Rigou, M. (2024). Perspectives of young digital natives on digital marketing: Exploring annoyance and effectiveness with eye-tracking analysis. Future Internet, 16(4), Article 125. https://doi.org/10.3390/fi16040125

Brehm, J. W. (1966). A theory of psychological reactance. Academic Press.

Byrne, B. M. (2013). Structural equation modeling with AMOS: Basic concepts, applications, and programming (2nd ed.). Routledge.

Chin, W. W. (1998). The partial least squares approach to structural equation modeling. In G. A. Marcoulides (Ed.), Modern methods for business research (pp. 295–336). Lawrence Erlbaum Associates.

Choi, N. H., Qiao, X., & Wang, L. (2020). Effects of multisensory cues, self-enhancing imagery, and self goal-achievement emotion on purchase intention. Journal of Asian Finance, Economics and Business, 7(1), 141–151. https://doi.org/10.13106/jafeb.2020.vol7.no1.141

Dam, T. C. (2020). Influence of brand trust, perceived value on brand preference and purchase intention. The Journal of Asian Finance, Economics and Business, 7(10), 939–947. https://doi.org/10.13106/jafeb.2020.vol7.no10.939

Degeling, M., Utz, C., Lentzsch, C., Hosseini, H., Schaub, F., & Holz, T. (2018). We value your privacy... now take some cookies: Measuring the GDPR's impact on web privacy. arXiv preprint arXiv:1808.05096. (pp. 1-20). https://doi.org/10.14722/ndss.2019.23378

Delgado-Ballester, E. (2004). Applicability of a brand trust scale across product categories: A multigroup invariance analysis. European Journal of Marketing, 38(5/6), 573–592. https://doi.org/10.1108/03090560410529222

Falk, R. F., & Miller, N. B. (1992). A primer for soft modeling. University of Akron Press.

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/10.2307/3150980

Ghosh, M. (2024). Meta-analytic review of online purchase intention: Conceptualising the study variables. Cogent Business & Management, 11(1), Article 2296686. https://doi.org/10.1080/23311975.2023.2296686

Habib, H., Li, M., Young, E., & Cranor, L. (2022, April). “Okay, whatever”: An evaluation of cookie consent interfaces. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (pp. 1–27). Association for Computing Machinery. https://doi.org/10.1145/3491102.3501985

Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate data analysis (7th ed.). Pearson Education.

Hu, L. T., & 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. https://doi.org/10.1080/10705519909540118

Kline, R. B. (2023). Principles and practice of structural equation modeling (5th ed.). Guilford Press.

Mathur, A., Acar, G., Friedman, M. J., Lucherini, E., Mayer, J., Chetty, M., & Narayanan, A. (2019). Dark patterns at scale: Findings from a crawl of 11K shopping websites. Proceedings of the ACM on Human-Computer Interaction, 3(CSCW), 1–32. https://doi.org/10.1145/3359183

Morgan, R. M., & Hunt, S. D. (1994). The commitment-trust theory of relationship marketing. Journal of Marketing, 58(3), 20–38. https://doi.org/10.1177/002224299405800302

Nunnally, J. C., & Bernstein, I. H. (1994). Psychometric theory (3rd ed.). McGraw-Hill.

Pavlou, P. A., & Fygenson, M. (2006). Understanding and predicting electronic commerce adoption: An extension of the theory of planned behavior. MIS Quarterly, 30(1), 115–143. https://doi.org/10.2307/25148720

Santo, P. E., & Marques, A. M. A. (2022). Determinants of the online purchase intention: Hedonic motivations, prices, information and trust. Baltic Journal of Management, 17(1), 56–71. https://doi.org/10.1108/BJM-04-2021-0140

Singh, A. K., Upadhyaya, N., Seth, A., Hu, X., Sastry, N., & Mondal, M. (2022, September). What cookie consent notices do users prefer: A study in the wild. In Proceedings of the 2022 European Symposium on Usable Security (pp. 28–39). Internet Society. https://doi.org/10.1145/3549015.3555675

Stewart, K. J. (2003). Trust transfer on the World Wide Web. Organization Science, 14(1), 5–17. https://doi.org/10.1287/orsc.14.1.5.12810

Sun, Y., Huang, Y., Fang, X., & Yan, F. (2022). The purchase intention for agricultural products of regional public brands: Examining the influences of awareness, perceived quality, and brand trust. Mathematical Problems in Engineering, 2022, Article 4991059. https://doi.org/10.1155/2022/4991059

Utz, C., Degeling, M., Fahl, S., Schaub, F., & Holz, T. (2019, November). (Un)informed consent: Studying GDPR consent notices in the field. In Proceedings of the 2019 ACM SIGSAC Conference on Computer and Communications Security (pp. 973–990). Association for Computing Machinery. https://doi.org/10.1145/3319535.3354212

Voigt, C., Schlögl, S., & Groth, A. (2021, July). Dark patterns in online shopping: Of sneaky tricks, perceived annoyance and respective brand trust. In F. F.-H. Nah & K. Siau (Eds.), HCI in Business, Government and Organizations. HCII 2021. Lecture Notes in Computer Science (Vol. 12783, pp. 143–155). Springer. https://doi.org/10.1007/978-3-030-77750-0_10

Wang, J., Shahzad, F., Ahmad, Z., Abdullah, M., & Hassan, N. M. (2022). Trust and consumers’ purchase intention in a social commerce platform: A meta-analytic approach. SAGE Open, 12(2), Article 21582440221091262. https://doi.org/10.1177/21582440221091262

Weiss, H. M., & Cropanzano, R. (1996). Affective events theory: A theoretical discussion of the structure, causes and consequences of affective experiences at work. In B. M. Staw & L. L. Cummings (Eds.), Research in organizational behavior (Vol. 18, pp. 1–74). JAI Press.