Mediating Effect of Online Shopping Satisfaction Between Online Shopping Experience and Customer Loyalty
This study wants to know what factors influence customer satisfaction which can lead to loyalty in the online shopping context by looking at the phenomena and problems faced by customers. The previous research was used as literature for this study with a quantitative method to see the impact of independent variables on the dependent variable and descriptive analysis for regression results. The authors pointed out factors of e-fulfillment: condition, timeliness, availability, ease of return, e-business quality, and product quality have effects on the satisfaction and loyalty of customers in online shopping. The sample for this study still does not adequately describe the population because it only uses snowball sampling. This study can help online shop owners, entrepreneurs, researchers, and students to get literature on e-fulfillment factors that can affect customer satisfaction and make repeat transactions. This study modifies the e-fulfillment factors that influence customer satisfaction and loyalty in the context of online shopping in Indonesia.
Al-Adwan, A. S., Kokash, H., Adwan, A. Al, Alhorani, A., & Yaseen, H. (2020). Building customer loyalty in online shopping: the role of online trust, online satisfaction and electronic word of mouth. International Journal of Electronic Marketing and Retailing, 11(3), 278–306.
Al-Haraizah, A., & Al-Nady, B. (2015). Customer Market Perceptions as sustainable drivers for Business to business Electronic commerce Success: An Applied Study on Sample of E-Retailers in Amman City. International Journal of Information and Communication Technology, 5(6).
Gallino, S., & Moreno, A. (2018). The value of fit information in online retail: Evidence from a randomized field experiment. Manufacturing & Service Operations Management, 20(4), 767–787.
Garson, G. D. (2016). Partial least squares. Regression and structural equation models. Statistical Publishing Associates.
Hair, J., & Alamer, A. (2022). Partial Least Squares Structural Equation Modeling (PLS-SEM) in second language and education research: Guidelines using an applied example. Research Methods in Applied Linguistics, 1(3), 100027.
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), 2–24.
Sarstedt, M., Ringle, C. M., Cheah, J.-H., Ting, H., Moisescu, O. I., & Radomir, L. (2020). Structural model robustness checks in PLS-SEM. Tourism Economics, 26(4), 531–554.
Sarstedt, M., Ringle, C. M., & Hair, J. F. (2021). Partial least squares structural equation modeling. In Handbook of market research (pp. 587–632). Springer.
Schermelleh-Engel, K., Moosbrugger, H., & Müller, H. (2003). Evaluating the fit of structural equation models: Tests of significance and descriptive goodness-of-fit measures. MPR-Online, 8(2), 23–74.
Sur, S. (2018). Theoretical review of growth of e-commerce in India and its relevance in future business sustainability. Abhigyan, 36(3), 41–50.
Copyright (c) 2025 Bagus Rizaldi Ravsyanjani, Endang Pamularsih, Fazry Wildan, Artha Sejati Ananda
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
