Analisis Faktor-Faktor yang Mempengaruhi Persepsi Konsumen Terhadap Implementasi Data Pribadi Pada E-commerce Shopee di Indonesia
Abstract
Penelitian ini bertujuan untuk menganalisis pengaruh personal traits dan prior negative experience terhadap perceived
benefit, privacy concern, dan trust serta dampaknya terhadap willingness to disclose personal data pada pengguna ecommerce Shopee di Indonesia. Teknik analisis data yang digunakan adalah Partial Least Squares Structural
Equation Modeling (PLS-SEM), dengan data dikumpulkan dari 285 responden. Hasil penelitian menunjukkan bahwa
extraversion, agreeableness, dan openness berpengaruh positif signifikan terhadap perceived benefit. Neuroticism dan
conscientiousness berpengaruh signifikan terhadap privacy concern dan trust, sementara prior negative experience
meningkatkan privacy concern namun menurunkan willingness to disclose personal data. Selain itu, perceived benefit
dan trust berpengaruh positif signifikan terhadap willingness to disclose personal data, sementara privacy concern
berpengaruh negatif. Hasil ini mendukung Privacy Calculus Theory, di mana keputusan pengguna untuk berbagi data
ditentukan oleh pertimbangan manfaat dan risiko. Nilai R² konstruk endogen menunjukkan kekuatan penjelasan model
berada pada kategori moderat hingga kuat. Temuan ini dapat menjadi acuan bagi pengelola platform digital dalam
merancang strategi peningkatan kepercayaan dan kenyamanan pengguna terkait perlindungan data pribadi.
Kata kunci: personality traits, prior negative experience, privacy calculus, data pribadi, e-commerce, shopee
References
Bandara, R., Fernando, M., & Akter, S. (2019). Explicating the privacy paradox: A qualitative inquiry of online
shopping consumers. Journal of Retailing and Consumer Services, 52, 101947.
https://doi.org/10.1016/j.jretconser.2019.101947
Barth, S., De Jong, M. D., Junger, M., Hartel, P. H., & Roppelt, J. C. (2019). Putting the privacy paradox to the test:
Online privacy and security behaviors among users with technical knowledge, privacy awareness, and
financial resources. Telematics and Informatics, 41, 55–69. https://doi.org/10.1016/j.tele.2019.03.003
Candiwan, & Faiz Savindraputra. (2019). Is information privacy awareness important for Indonesian social media
Instagram users? International Journal of Advanced Trends in Computer Science and Engineering, 8(1.5),
–287. https://doi.org/10.30534/ijatcse/2019/4981.52019
Girsang, M. J., Candiwan, N., Hendayani, R., & Ganesan, Y. (2020). Can Information Security, Privacy and
Satisfaction Influence The E-Commerce Consumer Trust? 2020 8th International Conference on Information
and Communication Technology (ICoICT), 1–7. https://doi.org/10.1109/icoict49345.2020.9166247
Hair, J., Hair, J. F., Jr, Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2021). A primer on Partial Least squares
Structural Equation Modeling (PLS-SEM). SAGE Publications
Hanna, N., Wozniak, R., & Hanna, M. (2017). Consumer behavior: An Applied Approach.
He, J., Liang, X., & Xue, J. (2024). Unraveling the Influential Mechanisms of Smart Interactions on Stickiness
Intention: A Privacy Calculus Perspective. Journal of Theoretical and Applied Electronic Commerce
Research, 19(4), 2582–2604. https://doi.org/10.3390/jtaer19040124
Kozyreva, A., Lorenz-Spreen, P., Hertwig, R., Lewandowsky, S., & Herzog, S. M. (2021). Public attitudes towards
algorithmic personalization and use of personal data online: evidence from Germany, Great Britain, and the
United States. Humanities and Social Sciences Communications, 8(1). https://doi.org/10.1057/s41599-021-
-w
Laudon, K. C., & Traver, C. G. (2023). E-Commerce 2023: Business, Technology, Society, Global Edition. Pearson
Higher Ed.
Li, Y. (2012). Theories in online information privacy research: A critical review and an integrated framework.
Decision Support Systems, 54(1), 471–481. https://doi.org/10.1016/j.dss.2012.06.010
Markovic, D. (2023, July 5). Council Post: The involvement of big data and AI in personalizing E-Commerce. Forbes.
Popov, I. (2023, February 7). Council Post: Why should E-Commerce businesses consider online personalization?
Sudarwanto, A. S., & Kharisma, D. B. B. (2021). Comparative study of personal data protection regulations in
Indonesia, Hong Kong and Malaysia. Journal of Financial Crime, 29(4), 1443–1457.
https://doi.org/10.1108/jfc-09-2021-0193
Tian, S., Zhang, B., & He, H. (2024). Role of Algorithm Awareness in Privacy Decision-Making Process: A Dual
Calculus Lens. Journal of Theoretical and Applied Electronic Commerce Research, 19(2), 899–920.
https://doi.org/10.3390/jtaer19020047
Van Hoboken, J., & Fathaigh, R. Ó. (2021). Smartphone platforms as privacy regulators. Computer Law & Security
Review, 41, 105557. https://doi.org/10.1016/j.clsr.2021.105557
Widodo, T., Setiadjie, R. P., & Sary, F. P. (2017). Analysis of the e-commerce use behavior on music products. 2017
International Conference on Engineering Technology and Technopreneurship (ICE2T), 1–6.
https://doi.org/10.1109/ice2t.2017.8215958
Zhou, C., Bai, D., Li, T., & Yu, J. (2024). Personalized recommendation, behavior-based pricing, or both? Examining
privacy concerns from a cost perspective. Omega, 103223. https://doi.org/10.1016/j.omega.2024.103223
