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The purpose of this paper is to examine the potential impacts of various variables on product return activities after online shopping. Previous studies on customer behaviour have been predominantly concerned with return on used products and other product-quality-related constructs in the model. This study aims to specially examine the logistics service-related and customer intention–related variables for general products under the e-commerce circumstance.

Structured questionnaire data for this study were collected in the two southeast cities of China (162 useable responses). Structural equation modelling was used to examine the latent variables.

The results confirmed that product return intention has the greatest impact on online shopping returns with a direct effect of 0.63, followed by the flexibility in return (logistics service) with a direct effect of 0.49.

Such a model not only enriches the theoretical understanding of customer behaviour studies but also offers online shopping stores and platforms a quantitative benchmark and new perspective on the design of online shopping supply chains by considering product returns so as to improve the customer satisfaction.

Some essential issues about modeling of reverse logistics (RL) systems and product recovery networks include consideration of the qualities of the returned products, taking into account uncertainty and integrating the forward and reverse flows. The purpose of this paper is to develop the integrated RL model, which focuses on the control of inventory and production planning problems in a case of uncertainty in demand, quantities and qualities of returns.

The model involves a forward production route, three alternative recovery routes and a disposal route. Various levels of qualities are considered for returned products. A fuzzy mixed integer programming model (FMIP) is developed to provide a solution for the problems of production planning and inventory control. After maximizing the satisfaction degree, different solutions can have the same maximum. Moreover, policies that use all recovery routes and reduce the overall uncertainty have no chance to be chosen. To tackle these problems, a two-phase approach method is applied.

According to the results of the numerical example, using different and appropriate recovery options based on the quality of returns can significantly decrease the recovery costs. Similarly, it is shown that the two-phase approach can be an effective and efficient method to reach a satisfactory solution for such problems.

In this study, after maximizing the FMIP model, a two-phase approach ‒ as a novel optimization technique in this research ‒ is employed to achieve a desirable solution.

Forecasting product returns plays an important role in the operations of reverse logistics (RL). However, their contribution to sustainability performance is yet to be explored. The purpose of this paper is to explore the product returns in Indian electronics industry and examine the relationship of forecasting product returns with triple bottom line performance of RL.

In this study, based on past literature review, four hypotheses, relating to forecasting of product returns and its association with performance, were developed. A questionnaire was sent to 700 respondents from the Indian electronics industry. Overall, 208 received responses were found suitable for the research. The necessary statistical analysis was carried out to ensure the reliability and validity of the questionnaire. In order to test different hypotheses, partial least square path modelling (PLSPM) technique of structural equation modeling was utilized.

Measurement model had shown sufficient data fit for the modeling. PLSPM results reveal that the accuracy in forecasting product returns is positively associated with operational performance of RL. It also plays an important role in the sustainability efforts of an organization.

Managers can utilize results of study for exploring and emphasizing issues of product returns for improving RL performance. One of the limitations is that data are collected only from Indian electronics industry. Another limitation is that only product returns are considered for the operational and TBL performance of RL. In future, study may be carried out considering different factors in other sectors and countries.

The intent of forecasting product returns is considered to be operational efficiency. It can make significant contributions to the sustainability efforts of an organization. Review of the past literature indicates that research in the field of RL is in developing stage, and issues related to forecasting product returns are under-represented. The paper adds value to the few available articles on product returns.

The purpose of this paper is to explore, describe and categorise practices of managing product returns empirically in internet retailing.

A multiple case study was conducted involving 12 e-commerce firms and 4 logistics service providers. An integrative data collection approach of semi-structured interviews, documentation and observations was used to gain comprehensive managerial and operational descriptions of returns management (RM) processes.

The findings show inconsistent RM processes, with a plethora of practices implemented and organised differently across firms. RM processes are ambiguous; their design is a result of incremental changes over time, lacking strategy and goals. There is a mismatch between how they are described and understood in the literature and how they are actually used. Practices in gatekeeping, avoidance and reverse logistics are defined and categorised. These serve as a typology of practices for managers to (re)consider, along with 15 propositions on how RM is practised.

The range of RM practices and the processes reflect a lack of scholarly attention and strategic view. Research is needed to develop clear goals on how the RM process can be better aligned with business strategies.

The typology of practices is a benchmark for internet retailers in their design of efficient RM processes.

Systematic and empirical research on RM is scarce compared to forward management. The study bridges this gap as one of the first to describe RM practices in depth, define service as a key activity, and identify a mismatch between theory and practice.

The purpose of this paper is to conceptualise customer-oriented product returns service (COPRS) performance, and develop and validate its measure.

This study uses qualitative consumer interviews and a quantitative survey to conceptualise, operationalise and validate the measure of COPRS performance.

The findings indicate 12 components with 46 measurable items for COPRS performance, including assurance, compensation, convenience, empathy, employee empowerment, explanation, feedback, information availability, reliability, responsiveness, tangibles and timeliness.

The measure could facilitate future empirical studies in the product returns service area. Future research could apply the COPRS performance measure across industries or in different settings such as cross-cultural or other retailing contexts.

Managers could evaluate their existing returns service performance in different key aspects based on the COPRS performance metrics and then improve their returns offerings accordingly. It also alerts practitioners to pay more attention to functional integration in designing returns service strategies to enhance customer satisfaction.

The study is one of the first to develop a new measure that substantiates the notion of an integrated marketing and reverse logistics interface, which is an underrepresented body of knowledge in the marketing and operations management disciplines.

The purpose of this paper is to explore the processing of product returns at five case companies using a complex adaptive systems (CAS) logic to identify agent interactions, organization, schema, learning and the emergence of adaptations in the reverse supply chain.

Using a multiple-case study design, this research applies abductive reasoning to examine data from in-depth, semi-structured interviews and direct researcher observations collected during site visits at case companies.

Costly or high-risk returns may require agents to specialize the depth of their mental schema. Processing agents need freedom to interact, self-organize and learn from other agents to generate emergent ideas and adapt.

Limiting the depth of individual agent schema allows managers to better allocate labor to processing product returns during peak volume. To boost adaptability, managers need to craft a dynamic environment that encourages agents with diverse schema to interact, anticipate, and self-organize to brainstorm new ideas. Managers need to resist the urge to “control” the dynamic environment that ensues.

This paper builds on existing research that studies the key decision points in the analysis of product returns by exploring how processing-agent behaviors can create adaptability in the reverse supply chain. Additionally, this research follows in the tradition of Choi et al. (2001) and Surana et al. (2005) and proposes the application of CAS to a specific part of the supply chain – the processing of product returns.

The purpose of this paper is to provide a multidimensional understanding of the management of feedback from customer product returns and the management practices that lead to the occurrence of product returns in the context of knowledge management. The characteristics of product returns indicate that to manage them requires specific knowledge management, as the nature of their management is rather complex.

Understanding of feedback concept for the purpose of product returns avoidance management and its linkages with knowledge management through the theoretical review was performed first. Second, soft systems methodology (SSM) to analyze the very complex situation, as the product returns present, provided the conceptual framework for empirical research. The principles and best practices of SSM were followed and an analysis of documents together with the theoretical knowledge of feedback, product returns and knowledge management served as the basis for the action research.

The research highlighted the importance of knowledge management (even in a rather simple form) for the solution of the problematic situation and underlined the necessary interconnections between different areas of business processes management and the need to manage knowledge. It also showed that product returns act as important feedback for the whole organization.

This paper is the first attempt to apply current knowledge of the feedback construct into the knowledge and product returns management. It is also the first attempt to apply SSM to product returns management.

The purpose of this paper is to investigate the dynamic acquisition pricing strategy for collecting used products (also known as cores or returns) in a finite planning horizon. In particular, this paper studies a cost-minimization model in which a firm offers acquisition price that impacts the quantity of the returns, and remanufactures the used product to satisfy the customer demand.

This paper uses multi-period stochastic dynamic programming theory to model a remanufacturing system that faces the random demand for remanufactured products. The number of the returns at each period is uncertain and increases linearly with the acquisition price offered.

The study shows that when the uncertainty of demand for remanufactured products increases, the remanufacturer should hold a higher core stock level to minimize the expected total cost and thus a higher acquisition price is needed to attract returns. However, given demand uncertainty, the optimal price decreases in the initial core stock level in each period. It also indicates that the optimal acquisition price increases in the variance of the returns, but decreases in the mean of the returns.

The findings suggest that a remanufacturer could reduce the expected total cost by adjusting the acquisition price according to the number of returns periodically.

Introducing the impact of supply uncertainty on the acquisition price of used products, this paper uses a multi-period dynamic model, instead of single period model in previous studies, to examine the remanufacturer’s dynamic acquisition pricing policy.

The purpose of this paper is to investigate how online apparel retailers make trade-offs in achieving efficiency in handling consumer returns, attempting to reduce the number of consumer returns they are faced with and increasing sales through returns management.

The authors use literature to develop propositions and employed a case study research design to understand how online apparel retailers make trade-offs in returns management practices in order to verify the propositions. Case study subjects have been anonimized.

The authors have developed and verified five propositions with the aim to understand how retailers make trade-offs in reducing the number of online consumer returns, increasing the effectiveness of handling online consumer returns and increasing sales through returns management.

The research is limited by the use of interview data from cases, a focus on apparel retail only and by the use of companies located in the Netherlands only.

The propositions help managers make trade-offs in reducing the number of returns versus increasing sales through returns management versus increasing the effectiveness of handling consumer returns.

Consumer returns lead to a significant flow of items from consumers back to online retailers, in particular in fashion. Reduction of this flow decreases social and environmental impacts through reduced transport and handling requirements.

Several authors identify that more empirical research is welcome in the area of returns management. The research aims to contribute to this gap by focussing at how online apparel retailers make trade-offs in achieving efficiency in handling returns, increasing sales through returns management and attempting to reduce the number of consumer returns they receive.

Product returns management (PRM) is a core supply chain management process. Though the importance of value creation and appropriation is acknowledged, extant studies on value in product returns tend to be limited to the residual asset value (cost recovery) of the returned products. Further, value discussion in PRM is limited to the value implications for a single party in the returns transaction rather than all the product returns chain entities. The purpose of this paper is to explore value creation and appropriation in a triad of supplier-retailer-3PL in the product returns chain.

The study uses an inductive qualitative approach. Semi-structured interviews with executives in a triad of organisations formed the primary data source for the study.

The paper identifies six value drivers and develops a value creation and appropriation framework. It shows that facilitation, value orientation, process alignment and relational factors are key drivers of value creation and appropriation in PRM.

The findings reinforce the view that value creation and appropriation are the outcomes of multi-party interactions in a product return chain. The framework presented contributes to the literature by showing the linkages amongst key drivers.

The findings show the important role of external process facilitation and how a 3PL contributes to value creation in a triadic relationship.

Research based on a triadic product returns chain is a unique dimension of this study.