Assessing the Impact of Reverse Logistics Service Quality on Customer Satisfaction: A Servqual-Based Analysis
Authors
Fakulti Pengurusan Teknologi dan Teknousahawanan, Universiti Teknikal Malaysia Melaka (Malaysia)
Fakulti Pengurusan Teknologi dan Teknousahawanan, Universiti Teknikal Malaysia Melaka (Malaysia)
Fakulti Pengurusan Teknologi dan Teknousahawanan, Universiti Teknikal Malaysia Melaka (Malaysia)
Fakulti Pengurusan Teknologi dan Teknousahawanan, Universiti Teknikal Malaysia Melaka (Malaysia)
Article Information
DOI: 10.47772/IJRISS.2025.92800016
Subject Category: Technology
Volume/Issue: 9/28 | Page No: 151-169
Publication Timeline
Submitted: 2025-11-08
Accepted: 2025-11-14
Published: 2025-12-18
Abstract
Reverse logistics has become a critical component of modern supply chains due to increasing activities of logistics locally and globally. Hence, frequency of product returns also increase because of various reasons, including damaged or defective items, items not meeting expectations (wrong size, color, or fit), incorrect items being sent, misleading advertisements, buyer's remorse, or difficulty using the product defects. Due to these, customers expect for efficient service recovery. This study investigates the factors that influence customer satisfaction in returning defective products. Using survey-based quantitative analysis, this research examines the roles of quality of replacement product, timeline of refunds, customer service quality, clarity of return policy, and demonstration of understanding as independent variables and customer satisfaction in returning defective products as dependent variable. By applying SERVQUAL model as underpinning theory, this study found that all the hypotheses are supported except for the timeline of refunds. The findings provide theoretical contributions in growing body of literature on reverse logistics and customer satisfaction by providing empirical evidence on the factors influencing customer satisfaction in the context of returning defective products. For practical contributions, companies may enhance their return processes and improve customer loyalty.
Keywords
Reverse Logistics; Determinants of Customer Satisfaction; SERVQUAL Model
Downloads
References
1. Bhandari, P. (2022). Understanding regression analysis: Coefficients, significance, and interpretation. Scribbr. https://www.scribbr.com/statistics/regression-analysis [Google Scholar] [Crossref]
2. Bryman, A. (2012). Social research methods (4th ed.). Oxford University Press. [Google Scholar] [Crossref]
3. Clark, J. (2022). The role of reverse logistics in sustainable waste management. Journal of Environmental Supply Chain, 15(3), 101–115. [Google Scholar] [Crossref]
4. Creswell, J. W. (2014). Research design: Qualitative, quantitative, and mixed methods approaches (4th ed.). SAGE Publications. [Google Scholar] [Crossref]
5. Daugherty, P. J., Myers, M. B., & Richey, R. G. (2002). Information support for reverse logistics: The influence of relationship commitment. Journal of Business Logistics, 23(1), 85–106. https://doi.org/10.1002/j.2158-1592.2002.tb00021.x [Google Scholar] [Crossref]
6. Field, A. (2013). Discovering statistics using IBM SPSS statistics (4th ed.). SAGE Publications. [Google Scholar] [Crossref]
7. Fleischmann, M. (2001). Quantitative models for reverse logistics. Springer Science & Business Media. [Google Scholar] [Crossref]
8. Fleischmann, M., Bloemhof-Ruwaard, J. M., Dekker, R., van der Laan, E., van Nunen, J. A. E. E., & Van Wassenhove, L. N. (1997). Quantitative models for reverse logistics: A review. European Journal of Operational Research, 103(1), 1–17. https://doi.org/10.1016/S0377-2217(97)00230-0 [Google Scholar] [Crossref]
9. Fowler, F. J. (2013). Survey research methods (5th ed.). SAGE Publications. [Google Scholar] [Crossref]
10. Garcia, M. (2019). Customer satisfaction and product returns: Understanding consumer expectations. International Journal of Retail and Distribution Management, 47(6), 530–546. [Google Scholar] [Crossref]
11. Goodman, J., Ward, M., & Galbraith, C. (2017). Delivering knock your socks off service in the digital age. AMACOM. [Google Scholar] [Crossref]
12. Grönroos, C. (1994). From marketing mix to relationship marketing: Towards a paradigm shift in marketing. Management Decision, 32(2), 4–20. https://doi.org/10.1108/00251749410054774 [Google Scholar] [Crossref]
13. Guide, V. D. R., & Van Wassenhove, L. N. (2003). Managing product returns for remanufacturing. Production and Operations Management, 12(4), 442–453. https://doi.org/10.1111/j.1937-5956.2003.tb00212.x [Google Scholar] [Crossref]
14. Han, Y., Lee, S., & Park, J. (2023). Assessing customer satisfaction in logistics and reverse supply chains. Journal of Service Quality Management, 29(2), 77–91. [Google Scholar] [Crossref]
15. Helm, S., Kim, S. H., & Van Riper, S. (2020). Customer dissatisfaction: Antecedents and consequences. Journal of Business Research, 120, 74–83. https://doi.org/10.1016/j.jbusres.2020.07.038 [Google Scholar] [Crossref]
16. Johnson, T. (2019). E-commerce returns and the evolution of reverse logistics. Logistics Review Journal, 10(4), 233–248. [Google Scholar] [Crossref]
17. Krejcie, R. V., & Morgan, D. W. (1970). Determining sample size for research activities. Educational and Psychological Measurement, 30(3), 607–610. [Google Scholar] [Crossref]
18. Kumar, P., & Kaushik, M. (2021). Replacement product quality and customer satisfaction in post-purchase processes. Journal of Retailing and Consumer Services, 58, 102–118. [Google Scholar] [Crossref]
19. Kumar, P., & Kumar, A. (2020). Empathy and customer satisfaction in the service sector. Journal of Business Research, 120, 181–191. https://doi.org/10.1016/j.jbusres.2020.07.041 [Google Scholar] [Crossref]
20. Kumar, R., Gupta, N., & Sharma, S. (2022). Understanding customer empathy in service recovery. International Journal of Service Management, 33(1), 44–59. [Google Scholar] [Crossref]
21. McCollough, M. A., Berry, L. L., & Yadav, M. S. (2000). An empirical investigation of customer satisfaction after service failure and recovery. Journal of Service Research, 3(2), 121–137. https://doi.org/10.1177/109467050032002 [Google Scholar] [Crossref]
22. Murphy, P. R., & Poist, R. F. (1989). Management of logistics retromovements: An empirical analysis of physical distribution managers. Logistics and Transportation Review, 25(2), 107–115. [Google Scholar] [Crossref]
23. Nguyen, T., Tran, L., & Pham, D. (2021). The role of refund timeliness in e-commerce satisfaction. Electronic Commerce Review, 18(2), 189–202. [Google Scholar] [Crossref]
24. Noyes, J. M., Casebeer, W. D., & Verhoef, P. C. (2019). Quantitative analysis in behavioral research. Behavioral Methods Journal, 14(3), 201–218. [Google Scholar] [Crossref]
25. Ogunleye, J. O. (2013). Customer satisfaction in reverse logistics: A study of the service sector. Journal of Business and Management, 7(1), 101–112. https://doi.org/10.9790/487X-07110112 [Google Scholar] [Crossref]
26. Oliver, R. L. (2014). Satisfaction: A behavioral perspective on the consumer (2nd ed.). Routledge. [Google Scholar] [Crossref]
27. Pallant, J. (2020). SPSS survival manual: A step-by-step guide to data analysis using IBM SPSS (7th ed.). Routledge. [Google Scholar] [Crossref]
28. Parasuraman, A., Zeithaml, V. A., & Berry, L. L. (1988). SERVQUAL: A multiple-item scale for measuring consumer perceptions of service quality. Journal of Retailing, 64(1), 12–40. [Google Scholar] [Crossref]
29. Rahman, Z., Singh, P., & Tan, C. (2022). Customer service quality and loyalty in e-commerce. Journal of Retail Service Management, 17(4), 288–302. [Google Scholar] [Crossref]
30. Rahman, Z., & others. (2018). Customer responsiveness in services. International Journal of Business Excellence, 15(3), 257–272. [Google Scholar] [Crossref]
31. Robinson, D. (2017). The challenges of managing customer returns through reverse logistics. Journal of Operations and Retail Studies, 8(1), 65–78. [Google Scholar] [Crossref]
32. Rogers, D. S., & Tibben-Lembke, R. S. (1999). Going backwards: Reverse logistics trends and practices. University of Nevada, Reno, Center for Logistics Management. [Google Scholar] [Crossref]
33. Rogers, D. S., & Tibben-Lembke, R. S. (2001). An examination of reverse logistics practices. Journal of Business Logistics, 22(2), 129–148. https://doi.org/10.1002/j.2158-1592.2001.tb00007.x [Google Scholar] [Crossref]
34. Sahu, P., & others. (2021). Automating refunds: Effects on service reliability. Service Systems, 6(1), 45–60. [Google Scholar] [Crossref]
35. Sari, P. D., & Kusuma, R. A. (2020). The impact of tangibility on customer satisfaction. Asian Journal of Management Studies, 8(4), 36–42. [Google Scholar] [Crossref]
36. Saunders, M., Lewis, P., & Thornhill, A. (2007). Research methods for business students (4th ed.). Pearson Education. [Google Scholar] [Crossref]
37. Smith, A. K., & Bolton, R. N. (2002). The effect of customers’ emotional responses to service failures on their recovery effort evaluations and satisfaction judgments. Journal of the Academy of Marketing Science, 30(1), 5–23. [Google Scholar] [Crossref]
38. Smith, J. (2020). Customer expectations in e-commerce returns. International Journal of Marketing and Consumer Behavior, 15(2), 88–102. [Google Scholar] [Crossref]
39. Srivastava, S. K. (2008). Network design for reverse logistics. Omega, 36(4), 535–548. https://doi.org/10.1016/j.omega.2006.11.012 [Google Scholar] [Crossref]
40. Verhoef, P. C., & Casebeer, W. D. (1997). Quantitative methods in service management. Journal of Business Analytics, 9(2), 99–112. [Google Scholar] [Crossref]
41. Yuen, K. F., & Thai, V. V. (2023). Refund processing and consumer behavior in reverse logistics. Journal of Supply Chain and Consumer Studies, 14(1), 23–39. [Google Scholar] [Crossref]
42. Zeithaml, V. A., Berry, L. L., & Parasuraman, A. (2000). Conceptual framework for understanding customer expectations of service. Journal of Marketing Science, 64(1), 111–124. [Google Scholar] [Crossref]
43. Zeithaml, V. A., Bitner, M. J., & Gremler, D. D. (2013). Services marketing: Integrating customer focus across the firm (6th ed.). McGraw-Hill/Irwin. [Google Scholar] [Crossref]
Metrics
Views & Downloads
Similar Articles
- LeafQuest: A Mobile-Based Augmented Reality for Plant Placement, Discovery, and Growth
- Participatory Ergonomic Intervention Approach on Musculoskeletal Disorder (MSD) in Construction Sectors: A Systematic Review
- Integrating GIS into Traffic Incident Management: A Web-Based System
- RideSmart: A Personalized Motorcycle Product Recommendation System Using TF-IDF and Descriptive Analytics for Javidson Motorshop
- Educational Technology Course Design in Pre-Service Teachers Education: A Bibliometric Review of the Research Landscape