Data leaks: Can e-commerce convince users?

Cheng-Wen Lee; Romi Ilham; Chia Chang Hu

doi:10.31893/multirev.2026047

Keywords:

confirmation expectation

Abstract

The growth of e-commerce has surpassed 270 million users, and personal data breaches on e-commerce platforms are extremely detrimental to users. This data can be misused by criminals, particularly those involved in fraud and social engineering, such as telemarketing, phishing/scams, password cracking, online loan account creation, and others. Data leaks have become a growing concern, raising questions about trust and privacy issues in e-commerce. This study aims to analyze e-commerce user satisfaction as influenced by trust and privacy cynicism, with the framework of expectation confirmation theory, in response to data leaks on the Tokopedia e-commerce platform in Indonesia. This research uses a quantitative approach, involving 427 active Tokopedia users from various regions in Indonesia, aged over 18 years, who have been members for at least one year. The data was analyzed using the Structured Equation Model - Partial Least Square (SEM-PLS) method with Smart PLS version 4 software. The research findings reveal that confirmation expectations have a significant relationship with perceived usefulness, trust, and satisfaction; perceived usefulness significantly affects both satisfaction and trust; trust significantly influences satisfaction; privacy cynicism also has a significant effect on both satisfaction and trust. Moreover, this study highlights the critical role of individual perceived expectations of e-commerce use in enhancing ongoing satisfaction. However, as the digital age progresses, these expectations tend to weaken as e-commerce usability improves. The findings of this study provide important insights into understanding user behavior and satisfaction in the context of e-commerce platforms and data protection.
References
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2. Açikgöz, F., Perez‐Vega, R., Okumuş, F., & Stylos, N. (2023). Consumer engagement with AI‐powered voice assistants: A behavioral reasoning perspective. Psychology and Marketing. https://doi.org/10.1002/mar.21873
3. Ackermann, K. A., Burkhalter, L., Mildenberger, T., Frey, M., & Bearth, A. (2022). Willingness to share data: Contextual determinants of consumers’ decisions to share private data with companies. Journal of Consumer Behaviour, 21(2), 375–386. https://doi.org/10.1002/cb.2012
4. Agustina, D. (2017). Fitur social commerce dalam website e-commerce di Indonesia. Informatika Mulawarman: Journal Ilmiah Ilmu Komputer, 12(1), 25. https://doi.org/10.30872/jim.v12i1.219
5. Asosiasi Penyelenggara Jasa Internet Indonesia. (2020). Laporan Survei Internet APJII 2019–2020 (pp. 1–146). Asosiasi Penyelenggara Jasa Internet Indonesia. https://apjii.or.id/survei
6. Baruh, L., Secinti, E., & Cemalcilar, Z. (2017). Online privacy concerns and privacy management: A meta-analytical review. Journal of Communication, 67(1), 26–53. https://doi.org/10.1111/jcom.12276
7. Bhattacherjee, A. (2001). Understanding information systems continuance: An expectation-confirmation model. MIS Quarterly, 25(3), 351. https://doi.org/10.2307/3250921
8. Chakraborty, R., Lee, J., Bagchi-Sen, S., Upadhyaya, S., & Raghav Rao, H. (2016). Online shopping intention 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
9. Chawla, N., & Kumar, B. (2022). E-commerce and consumer protection in India: The emerging trend. Journal of Business Ethics, 180(2), 581–604. https://doi.org/10.1007/s10551-021-04884-3
10. Chen, R., & Sharma, S. K. (2013). Self-disclosure at social networking sites: An exploration through relational capitals. Information Systems Frontiers, 15(2), 269–278. https://doi.org/10.1007/s10796-011-9335-8
11. Chin, W. W. (1998). The partial least squares approach for structural equation modeling. In Modern methods for business research (pp. 295–336). Lawrence Erlbaum Associates Publishers.
12. Choi, H., & Jung, Y. (2020). Online users’ cynical attitudes towards privacy protection: Examining privacy cynicism. Asia Pacific Journal of Information Systems. https://doi.org/10.14329/apjis.2020.30.3.547
13. Daragmeh, A., Saleem, A., Bárczi, J., & Sági, J. (2022). Drivers of post-adoption of e-wallet among academics in Palestine: An extension of the expectation confirmation model. Frontiers in Psychology. https://doi.org/10.3389/fpsyg.2022.984931
14. DataBoks. (2023). Nilai transaksi bruto segmen bisnis GoTo periode Januari–September (2022–2023). Katadata. https://databoks.katadata.co.id/datapublish/2023/11/01/transaksi-gojek-dan-tokopedia-turun-hingga-kuartal-iii-2023-apa-penyebabnya
15. Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly: Management Information Systems, 13(3), 319–339. https://doi.org/10.2307/249008
16. Degutis, M., Urbonavičius, S., Hollebeek, L. D., & Anselmsson, J. (2023). Consumers’ willingness to disclose their personal data in e-commerce: A reciprocity-based social exchange perspective. Journal of Retailing and Consumer Services, 74, 103385. https://doi.org/10.1016/j.jretconser.2023.103385
17. Ghane, S., Fathian, M., & Gholamian, M. R. (2011). Full relationship among e-satisfaction, e-trust, e-service quality, and e-loyalty: The case of Iran e-banking. Journal of Theoretical and Applied Information Technology, 33(1), 1–6.
18. Hair, J. F., Hult, G. T. M., Ringle, C. M., Sarstedt, M., Danks, N. P., & Ray, S. (2021). Partial least squares structural equation modeling (PLS-SEM) using R. Practical Assessment, Research and Evaluation, 21(1).
19. 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). https://doi.org/10.1108/EBR-11-2018-0203
20. Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115–135. https://doi.org/10.1007/s11747-014-0403-8
21. Hoffmann, C., Lutz, C., & Ranzini, G. (2016). Privacy cynicism: A new approach to the privacy paradox. Cyberpsychology, 10(4). https://doi.org/10.5817/CP2016-4-7
22. IISPA. (2023). Internet penetration & behavior survey 2023 (Issue April).
23. Kartika, D. K. (2020). The shock of tens billion Tokopedia in the middle of data leaking cases. Medio, 2(2), 114–122.
24. Khan, M. I., Loh, J., Hossain, A., & Talukder, M. J. H. (2023). Cynicism as strength: Privacy cynicism, satisfaction and trust among social media users. Computers in Human Behavior, 142, 107638. https://doi.org/10.1016/j.chb.2022.107638
25. Kumar, K., & Natarajan, S. (2020). An extension of the expectation confirmation model (ECM) to study continuance behavior in using e-health services. Innovative Marketing, 16(2). https://doi.org/10.21511/im.16(2).2020.02
26. Kurniadi, H., & Ali Saeed Rana, J. (2023). The power of trust: How does consumer trust impact satisfaction and loyalty in Indonesian digital business? Innovative Marketing, 19(2), 236–249. https://doi.org/10.21511/im.19(2).2023.19
27. Li, F., & Liu, Q. (2019). Mobile SNS addiction and user continuance: An empirical investigation of WeChat. Tehnički Vjesnik – Technical Gazette. https://doi.org/10.17559/tv-20190315145418
28. Li, L., Wang, Q., & Li, J. (2022). Examining continuance intention of online learning during COVID-19 pandemic: Incorporating the theory of planned behavior into the expectation–confirmation model. Frontiers in Psychology. https://doi.org/10.3389/fpsyg.2022.1046407
29. Lutz, C., Hoffmann, C., & Ranzini, G. (2020). Data capitalism and the user: An exploration of privacy cynicism in Germany. New Media & Society. https://doi.org/10.1177/1461444820912544
30. Lynn, P. (2008). The problem of nonresponse. In International handbook of survey methodology. Routledge. https://doi.org/10.4324/9780203843123.ch3
31. Lyu, T., Guo, Y., & Chen, H. (2023). Understanding people’s intention to use facial recognition services: The roles of network externality and privacy cynicism. Information Technology & People. https://doi.org/10.1108/itp-10-2021-0817
32. Nguyen, G.-D., & Ha, M. T. (2021). The role of user adaptation and trust in understanding continuance intention towards mobile shopping: An extended expectation-confirmation model. Cogent Business & Management. https://doi.org/10.1080/23311975.2021.1980248
33. Nissenbaum, H. (2011). Privacy in context: Technology, policy, and the integrity of social life (Vol. 1). Stanford University Press. https://doi.org/10.5325/jinfopoli.1.2011.0149
34. Noraga, D., Batu, L., & Alversia, Y. (2021). UTAUT2 analysis on the use of on-demand services application with perceived privacy as moderating effect.
35. Ooijen, I. van, Segijn, C. M., & Opree, S. J. (2022). Privacy cynicism and its role in privacy decision-making. Communication Research. https://doi.org/10.1177/00936502211060984
36. Othman, R., Rahim, K. F., Kamarulzaman, R. A. binti, Amat, D. W., & Sham, R. (2019). Literature review on internet benefits, risks and issues: A case study for cyber parenting in Malaysia. Malaysian E-Commerce Journal. https://doi.org/10.26480/mecj.02.2019.12.14
37. Perkasa, J., & Saly, J. N. (2022). Legal liability of marketplace companies against leaking of user data due to third party breaking according to Law Number 8 of 1999 concerning consumer protection (Case example: Tokopedia user data leaking in 2020). In Proceedings of the 3rd Tarumanagara International Conference on the Applications of Social Sciences and Humanities (TICASH 2021) (Vol. 655, No. 8, pp. 606–614). https://doi.org/10.2991/assehr.k.220404.096
38. Podsakoff, P. M., MacKenzie, S. B., Lee, J.-Y., & Podsakoff, N. P. (2003). Common method biases in behavioral research: A critical review of the literature and recommended remedies. Journal of Applied Psychology, 88(5), 879–903. https://doi.org/10.1037/0021-9010.88.5.879
39. Rajaobelina, L., Tep, S. P., Arcand, M., & Ricard, L. (2021). Creepiness: Its antecedents and impact on loyalty when interacting with a chatbot. Psychology and Marketing. https://doi.org/10.1002/mar.21548
40. Reio, T. G. (2010). The threat of common method variance bias to theory building. Human Resource Development Review, 9(4), 405–411. https://doi.org/10.1177/1534484310380331
41. Rice, B. L., Golden, C. D., Randriamady, H. J., Arisco, N. J., & Hartl, D. L. (2018). Integrating approaches to study land use change and hotspots of malaria transmission in rural Madagascar: An observational study. The Lancet Planetary Health. https://doi.org/10.1016/s2542-5196(18)30104-9
42. Rolph, E. A., & Srinivasan, S. S. (2003). E‐satisfaction and e‐loyalty: A contingency framework. Psychology & Marketing, 20(2), 123–138. https://doi.org/10.1002/mar.10063
43. Sarstedt, M., Hair, J. F., Nitzl, C., Ringle, C. M., & Howard, M. C. (2020). Beyond a tandem analysis of SEM and PROCESS: Use of PLS-SEM for mediation analyses! International Journal of Market Research, 62(3). https://doi.org/10.1177/1470785320915686
44. Sativa, A., & Astuti, S. R. T. (2016). Analisis pengaruh e-trust dan e-service quality terhadap e-loyalty dengan e-satisfaction sebagai variabel intervening (Studi pada pengguna e-commerce C2C Tokopedia). Diponegoro Journal of Management, 5(3).
45. Setyaningsih, O. (2014). Pengaruh persepsi kualitas pelayanan e-commerce terhadap kepuasan pelanggan, kepercayaan dan loyalitas pada produk fashion. Journal Bisnis & Manajemen, 14(1), 67–80.
46. Sharma, G., & Lijuan, W. (2014). Ethical perspectives on e-commerce: An empirical investigation. Internet Research, 24(4), 414–435. https://doi.org/10.1108/IntR-07-2013-0162
47. Tanjung, R., Rakeyan, S., & Karawang, S. (2022). The relationship between customer value and trust in consumer satisfaction and its impact on consumer loyalty. International Journal of Science Education and Technology Management, 1(1), 59–69. https://ijsetm.my.id
48. van Schaik, P., Jansen, J., Onibokun, J., Camp, J., & Kusev, P. (2018). Security and privacy in online social networking: Risk perceptions and precautionary behaviour. Computers in Human Behavior, 78, 283–297. https://doi.org/10.1016/j.chb.2017.10.007
49. Westland, J. C. (2014). Sample calibration in Likert-metric survey data. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.2489010
50. Yu, N., & Huang, Y. T. (2022). Why do people play games on mobile commerce platforms? An empirical study on the influence of gamification on purchase intention. Computers in Human Behavior, 126, 106991. https://doi.org/10.1016/j.chb.2021.106991
51. Yussif, A.-M., Belko, S., & Oavare, O. P. (2022). CSR as an elixir for enhanced corporate image: Experiences from the University for Development Studies, Tamale and C.K. Tedam University of Technology and Applied Sciences, Navrongo, Ghana. The International Journal of Humanities & Social Studies. https://doi.org/10.24940/theijhss/2022/v10/i6/hs2204-020
52. Yutanto, H., Ilham, R., Candraningrat, & Armansyah, R. F. (2023). Unveiling the evolution: How history, politics, culture, and technology shape accounting systems for SMEs in Indonesia. Journal of Theoretical and Applied Information Technology, 101(23), 7739–7748.

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

How to cite

Lee, C.-W., Ilham, R., & Hu, C. C. (2025). Data leaks: Can e-commerce convince users?. Multidisciplinary Reviews, 9(1), 2026047. https://doi.org/10.31893/multirev.2026047

[1] Acikgoz, F., & Vega, R. P. (2022). The role of privacy cynicism in consumer habits with voice assistants: A technology acceptance model perspective. International Journal of Human-Computer Interaction, 38(12), 1138–1152. https://doi.org/10.1080/10447318.2021.1987677

[2] Açikgöz, F., Perez‐Vega, R., Okumuş, F., & Stylos, N. (2023). Consumer engagement with AI‐powered voice assistants: A behavioral reasoning perspective. Psychology and Marketing. https://doi.org/10.1002/mar.21873

[3] Ackermann, K. A., Burkhalter, L., Mildenberger, T., Frey, M., & Bearth, A. (2022). Willingness to share data: Contextual determinants of consumers’ decisions to share private data with companies. Journal of Consumer Behaviour, 21(2), 375–386. https://doi.org/10.1002/cb.2012

[4] Agustina, D. (2017). Fitur social commerce dalam website e-commerce di Indonesia. Informatika Mulawarman: Journal Ilmiah Ilmu Komputer, 12(1), 25. https://doi.org/10.30872/jim.v12i1.219

[5] Asosiasi Penyelenggara Jasa Internet Indonesia. (2020). Laporan Survei Internet APJII 2019–2020 (pp. 1–146). Asosiasi Penyelenggara Jasa Internet Indonesia. https://apjii.or.id/survei

[6] Baruh, L., Secinti, E., & Cemalcilar, Z. (2017). Online privacy concerns and privacy management: A meta-analytical review. Journal of Communication, 67(1), 26–53. https://doi.org/10.1111/jcom.12276

[7] Bhattacherjee, A. (2001). Understanding information systems continuance: An expectation-confirmation model. MIS Quarterly, 25(3), 351. https://doi.org/10.2307/3250921

[8] Chakraborty, R., Lee, J., Bagchi-Sen, S., Upadhyaya, S., & Raghav Rao, H. (2016). Online shopping intention 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

[9] Chawla, N., & Kumar, B. (2022). E-commerce and consumer protection in India: The emerging trend. Journal of Business Ethics, 180(2), 581–604. https://doi.org/10.1007/s10551-021-04884-3

[10] Chen, R., & Sharma, S. K. (2013). Self-disclosure at social networking sites: An exploration through relational capitals. Information Systems Frontiers, 15(2), 269–278. https://doi.org/10.1007/s10796-011-9335-8

[11] Chin, W. W. (1998). The partial least squares approach for structural equation modeling. In Modern methods for business research (pp. 295–336). Lawrence Erlbaum Associates Publishers.

[12] Choi, H., & Jung, Y. (2020). Online users’ cynical attitudes towards privacy protection: Examining privacy cynicism. Asia Pacific Journal of Information Systems. https://doi.org/10.14329/apjis.2020.30.3.547

[13] Daragmeh, A., Saleem, A., Bárczi, J., & Sági, J. (2022). Drivers of post-adoption of e-wallet among academics in Palestine: An extension of the expectation confirmation model. Frontiers in Psychology. https://doi.org/10.3389/fpsyg.2022.984931

[14] DataBoks. (2023). Nilai transaksi bruto segmen bisnis GoTo periode Januari–September (2022–2023). Katadata. https://databoks.katadata.co.id/datapublish/2023/11/01/transaksi-gojek-dan-tokopedia-turun-hingga-kuartal-iii-2023-apa-penyebabnya

[15] Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly: Management Information Systems, 13(3), 319–339. https://doi.org/10.2307/249008

[16] Degutis, M., Urbonavičius, S., Hollebeek, L. D., & Anselmsson, J. (2023). Consumers’ willingness to disclose their personal data in e-commerce: A reciprocity-based social exchange perspective. Journal of Retailing and Consumer Services, 74, 103385. https://doi.org/10.1016/j.jretconser.2023.103385

[17] Ghane, S., Fathian, M., & Gholamian, M. R. (2011). Full relationship among e-satisfaction, e-trust, e-service quality, and e-loyalty: The case of Iran e-banking. Journal of Theoretical and Applied Information Technology, 33(1), 1–6.

[18] Hair, J. F., Hult, G. T. M., Ringle, C. M., Sarstedt, M., Danks, N. P., & Ray, S. (2021). Partial least squares structural equation modeling (PLS-SEM) using R. Practical Assessment, Research and Evaluation, 21(1).

[19] 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). https://doi.org/10.1108/EBR-11-2018-0203

[20] Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115–135. https://doi.org/10.1007/s11747-014-0403-8

[21] Hoffmann, C., Lutz, C., & Ranzini, G. (2016). Privacy cynicism: A new approach to the privacy paradox. Cyberpsychology, 10(4). https://doi.org/10.5817/CP2016-4-7

[22] IISPA. (2023). Internet penetration & behavior survey 2023 (Issue April).

[23] Kartika, D. K. (2020). The shock of tens billion Tokopedia in the middle of data leaking cases. Medio, 2(2), 114–122.

[24] Khan, M. I., Loh, J., Hossain, A., & Talukder, M. J. H. (2023). Cynicism as strength: Privacy cynicism, satisfaction and trust among social media users. Computers in Human Behavior, 142, 107638. https://doi.org/10.1016/j.chb.2022.107638

[25] Kumar, K., & Natarajan, S. (2020). An extension of the expectation confirmation model (ECM) to study continuance behavior in using e-health services. Innovative Marketing, 16(2). https://doi.org/10.21511/im.16(2).2020.02

[26] Kurniadi, H., & Ali Saeed Rana, J. (2023). The power of trust: How does consumer trust impact satisfaction and loyalty in Indonesian digital business? Innovative Marketing, 19(2), 236–249. https://doi.org/10.21511/im.19(2).2023.19

[27] Li, F., & Liu, Q. (2019). Mobile SNS addiction and user continuance: An empirical investigation of WeChat. Tehnički Vjesnik – Technical Gazette. https://doi.org/10.17559/tv-20190315145418

[28] Li, L., Wang, Q., & Li, J. (2022). Examining continuance intention of online learning during COVID-19 pandemic: Incorporating the theory of planned behavior into the expectation–confirmation model. Frontiers in Psychology. https://doi.org/10.3389/fpsyg.2022.1046407

[29] Lutz, C., Hoffmann, C., & Ranzini, G. (2020). Data capitalism and the user: An exploration of privacy cynicism in Germany. New Media & Society. https://doi.org/10.1177/1461444820912544

[30] Lynn, P. (2008). The problem of nonresponse. In International handbook of survey methodology. Routledge. https://doi.org/10.4324/9780203843123.ch3

[31] Lyu, T., Guo, Y., & Chen, H. (2023). Understanding people’s intention to use facial recognition services: The roles of network externality and privacy cynicism. Information Technology & People. https://doi.org/10.1108/itp-10-2021-0817

[32] Nguyen, G.-D., & Ha, M. T. (2021). The role of user adaptation and trust in understanding continuance intention towards mobile shopping: An extended expectation-confirmation model. Cogent Business & Management. https://doi.org/10.1080/23311975.2021.1980248

[33] Nissenbaum, H. (2011). Privacy in context: Technology, policy, and the integrity of social life (Vol. 1). Stanford University Press. https://doi.org/10.5325/jinfopoli.1.2011.0149

[34] Noraga, D., Batu, L., & Alversia, Y. (2021). UTAUT2 analysis on the use of on-demand services application with perceived privacy as moderating effect.

[35] Ooijen, I. van, Segijn, C. M., & Opree, S. J. (2022). Privacy cynicism and its role in privacy decision-making. Communication Research. https://doi.org/10.1177/00936502211060984

[36] Othman, R., Rahim, K. F., Kamarulzaman, R. A. binti, Amat, D. W., & Sham, R. (2019). Literature review on internet benefits, risks and issues: A case study for cyber parenting in Malaysia. Malaysian E-Commerce Journal. https://doi.org/10.26480/mecj.02.2019.12.14

[37] Perkasa, J., & Saly, J. N. (2022). Legal liability of marketplace companies against leaking of user data due to third party breaking according to Law Number 8 of 1999 concerning consumer protection (Case example: Tokopedia user data leaking in 2020). In Proceedings of the 3rd Tarumanagara International Conference on the Applications of Social Sciences and Humanities (TICASH 2021) (Vol. 655, No. 8, pp. 606–614). https://doi.org/10.2991/assehr.k.220404.096

[38] Podsakoff, P. M., MacKenzie, S. B., Lee, J.-Y., & Podsakoff, N. P. (2003). Common method biases in behavioral research: A critical review of the literature and recommended remedies. Journal of Applied Psychology, 88(5), 879–903. https://doi.org/10.1037/0021-9010.88.5.879

[39] Rajaobelina, L., Tep, S. P., Arcand, M., & Ricard, L. (2021). Creepiness: Its antecedents and impact on loyalty when interacting with a chatbot. Psychology and Marketing. https://doi.org/10.1002/mar.21548

[40] Reio, T. G. (2010). The threat of common method variance bias to theory building. Human Resource Development Review, 9(4), 405–411. https://doi.org/10.1177/1534484310380331

[41] Rice, B. L., Golden, C. D., Randriamady, H. J., Arisco, N. J., & Hartl, D. L. (2018). Integrating approaches to study land use change and hotspots of malaria transmission in rural Madagascar: An observational study. The Lancet Planetary Health. https://doi.org/10.1016/s2542-5196(18)30104-9

[42] Rolph, E. A., & Srinivasan, S. S. (2003). E‐satisfaction and e‐loyalty: A contingency framework. Psychology & Marketing, 20(2), 123–138. https://doi.org/10.1002/mar.10063

[43] Sarstedt, M., Hair, J. F., Nitzl, C., Ringle, C. M., & Howard, M. C. (2020). Beyond a tandem analysis of SEM and PROCESS: Use of PLS-SEM for mediation analyses! International Journal of Market Research, 62(3). https://doi.org/10.1177/1470785320915686

[44] Sativa, A., & Astuti, S. R. T. (2016). Analisis pengaruh e-trust dan e-service quality terhadap e-loyalty dengan e-satisfaction sebagai variabel intervening (Studi pada pengguna e-commerce C2C Tokopedia). Diponegoro Journal of Management, 5(3).

[45] Setyaningsih, O. (2014). Pengaruh persepsi kualitas pelayanan e-commerce terhadap kepuasan pelanggan, kepercayaan dan loyalitas pada produk fashion. Journal Bisnis & Manajemen, 14(1), 67–80.

[46] Sharma, G., & Lijuan, W. (2014). Ethical perspectives on e-commerce: An empirical investigation. Internet Research, 24(4), 414–435. https://doi.org/10.1108/IntR-07-2013-0162

[47] Tanjung, R., Rakeyan, S., & Karawang, S. (2022). The relationship between customer value and trust in consumer satisfaction and its impact on consumer loyalty. International Journal of Science Education and Technology Management, 1(1), 59–69. https://ijsetm.my.id

[48] van Schaik, P., Jansen, J., Onibokun, J., Camp, J., & Kusev, P. (2018). Security and privacy in online social networking: Risk perceptions and precautionary behaviour. Computers in Human Behavior, 78, 283–297. https://doi.org/10.1016/j.chb.2017.10.007

[49] Westland, J. C. (2014). Sample calibration in Likert-metric survey data. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.2489010

[50] Yu, N., & Huang, Y. T. (2022). Why do people play games on mobile commerce platforms? An empirical study on the influence of gamification on purchase intention. Computers in Human Behavior, 126, 106991. https://doi.org/10.1016/j.chb.2021.106991

[51] Yussif, A.-M., Belko, S., & Oavare, O. P. (2022). CSR as an elixir for enhanced corporate image: Experiences from the University for Development Studies, Tamale and C.K. Tedam University of Technology and Applied Sciences, Navrongo, Ghana. The International Journal of Humanities & Social Studies. https://doi.org/10.24940/theijhss/2022/v10/i6/hs2204-020

[52] Yutanto, H., Ilham, R., Candraningrat, & Armansyah, R. F. (2023). Unveiling the evolution: How history, politics, culture, and technology shape accounting systems for SMEs in Indonesia. Journal of Theoretical and Applied Information Technology, 101(23), 7739–7748.

Abstract

References

How to cite