Reverse Logistics and Customer Loyalty in E-Commerce: An Empirical Study of Online Consumers

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@article{1722677,
      author = {Dr. Geetha M.},
      title = {Reverse Logistics and Customer Loyalty in E-Commerce: An Empirical Study of Online Consumers},
      journal = {Iconic Research And Engineering Journals},
      year = {2026},
      volume = {10},
      number = {2},
      pages = {3176-3194},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1722677.pdf},
      abstract = {This study develops and tests a customer-centered explanation of how reverse logistics influences loyalty in e-commerce. Rather than conceptualizing product returns solely as an operational burden, the framework distinguishes reverse logistics service quality, return policy fairness, and ease of return and examines the mechanisms through which these dimensions generate perceived value, trust, customer satisfaction, and customer loyalty. A quantitative, explanatory, time-separated consumer survey is proposed. Eligible participants are adult online shoppers with a recent completed product return, refund, or exchange. A final sample of approximately 800 respondents is recommended on the basis of conservative power analysis and SEM requirements. Seven latent constructs are measured with four reflective indicators each on seven-point Likert scales. Covariance-based SEM using robust maximum likelihood is specified as the primary estimator, supplemented by an ordered-categorical WLSMV robustness model. Reliability, convergent validity, discriminant validity, common method variance, mediation, measurement invariance, alternative-model comparisons, and sensitivity analyses are incorporated. Findings shows that Customer satisfaction has the strongest relationship with loyalty, while trust contributes both directly and through satisfaction. Reverse logistics service quality affects loyalty primarily through trust, value, and satisfaction; policy fairness operates predominantly through trust and satisfaction; and return ease operates through value and satisfaction. A full-mediation specification is more parsimonious than competing direct-effects models. The framework positions reverse logistics as a relational mechanism linking post-purchase operational performance to loyalty rather than treating returns as a purely logistical outcome.  The study integrates reverse-logistics quality, fairness, convenience, perceived value, trust, satisfaction, and loyalty in a single covariance-based model and specifies rigorous competing-model, common-method, mediation, and robustness procedures.},
      keywords = {reverse logistics; e-commerce returns; customer loyalty; return policy fairness; logistics service quality; perceived value; trust; customer satisfaction; structural equation modeling},
      month = {August},
      doi = {https://doi.org/10.64388/IREV10I2-1722677}
  }