Bridging the gap between practice and theory: a mixed-methods exploration to develop a returns management capability framework Open Access

The National Retail Federation reports that retailers estimate 16.9% of their annual sales to be returned, with total returns in the retail industry reaching around $890 billion in the United States in 2024. Product returns, driven by increasing product variety, fluctuating consumer demands and the growth of online retail, have created mounting challenges for companies. The strategic financial implications of returns management have been widely acknowledged by both academics and practitioners because it has the potential to reduce costs, create new revenue opportunities and improve profitability (e.g. Alkalha et al., 2026; Jones et al., 2021; Mollenkopf et al., 2007; Rintamäki et al., 2021). Furthermore, product returns are considered a crucial element of customer service, as proper handling of returns is essential to protect customer relationships and enhance customer lifetime value (e.g. Daugherty et al., 2018; Russo et al., 2022). For example, the ease of the return process and how consumers are treated during the process have a significant impact on repeat sales and additional revenues (Hao et al., 2024; Jones et al., 2023). Therefore, as an important area in supply chain management, product returns management has gained an increasing amount of research attention in recent years (Ambilkar et al., 2022).

However, despite its importance, product returns management remains a significant challenge for many companies because of the uncertainties and complexities that are inherent in returns management operations (Kroll, 2024; Rogers and Tibben-Lembke, 2001). The quantity, quality (condition), timing and demand of returned products can be difficult to predict; the steps and procedures involved in handling product returns can be variable and complicated, and many decisions and activities need to be made and performed by different parties in the process (Agrawal and Singh, 2020; Das and Chowdhury, 2012). Unfortunately, there is a lack of understanding of the actual dimensions associated with successful returns management (Starbuck, 2017). In fact, most empirical academic research to date has centred on either the drivers of product returns or the consequences of returns (Ertekin, 2018). Hence, Ambilkar et al. (2022) called for a more integrative approach to better understand product returns management and develop effective strategies. Therefore, the current study is undertaken to address this research gap by exploring the following questions: (1) What are the specific dimensions of returns management capability from a holistic perspective? And (2) How can companies effectively develop returns management capability with an integrative approach?

These questions were explored using a mixed-method approach. The specific dimensions of returns management capability were first explored qualitatively using the combination of a literature review and semi-structured interviews with industry practitioners. Next, a quantitative analysis was conducted to validate the proposed dimensions of returns management capability. A latent profile analysis was also performed to gain deeper insights. Finally, a second round of interviews with industry practitioners was conducted to develop an understanding of how companies can develop returns management capability in different aspects. An overview of the different studies incorporated in this research is shown in Figure 1. The results of this study not only identify the dimensions of returns management capability but also provide guidance for future development that can benefit both research and practice.

The current study contributes to the existing body of knowledge in several ways. First, to provide companies with an actionable framework, this study extends prior research by focusing on identifying the specific dimensions of returns management capability required to support returns management processes and programs. A capability is defined as the capacity for a team or collection of resources to perform some task or activity (Grant, 1991). It has been argued that capabilities can provide a strategic foundation for firms and, ultimately, can be a source of competitive advantage (Guntuka et al., 2026). While past research made tremendous contributions by identifying the steps or processes in product returns management (e.g. Rogers and Tibben-Lembke, 2001), more explicit insights focusing on relevant capability dimensions are needed to guide companies' efforts in managing these steps and processes. Second, the current study develops and tests a set of reliable scales to measure these identified returns management capability dimensions. The newly developed instrument will not only facilitate further academic research on this important topic but also offer managers a valuable tool to assess and deploy their companies' returns management efforts. Third, a holistic view was employed to explore returns management capability. Because returns management encompasses a wide range of processes, activities and participants, a lack of understanding of the entire picture can be a significant obstacle to optimal performance in returns management. Our findings suggest that developing different returns management capability dimensions should prioritise adopting a sustainability orientation and be supported by enabling factors such as adaptability and cross-firm collaboration. The returns management's emphasis on sustainability, and the circular economy in particular, aligns with the theoretical argument made by Hazen et al. (2021). The inclusion of enabling factors underscores the need to consider other organisational capabilities beyond the scope of returns management. Therefore, the results of this study provide researchers and practitioners with a comprehensive yet concise framework for better understanding, developing and implementing effective return management strategies.

The qualitative research execution in this study adhered to the rigorous criteria proposed by Lincoln and Guba (1985). The conceptualisation of returns management capability employed a content analysis technique to generate rich insights from texts or transcripts, providing a more detailed understanding of the focal construct (Carter et al., 2017; Krippendorff, 2004, 2018). The content analysis included a literature review and semi-structured interviews.

The goal of the literature review was to identify key returns management capability dimensions. Dimensions that facilitate and support returns management have received somewhat limited coverage in the academic literature, despite their critical role in meeting firm goals related to operational and financial performance (Jones et al., 2023; Russo et al., 2022). Similar to Richey et al. (2022) approach, returns management capability is conceptualised as a second-order concept composed of multiple first-order “dimensions”, each of which is characterised by a set of closely related activities. In the literature review, a process perspective was used, as it can provide the foundation for building capabilities to support strategic initiatives. This is in line with Stalk et al. (1992, p. 62) summary: “The building blocks of corporate strategy are not products and markets but business processes. Competitive success depends on transforming a company's key processes into strategic capabilities that consistently provide superior value to the customer”. Extending this perspective to the domain of returns management, we suggest that effective returns management capability can underpin a company's ability to differentiate itself, which can lead to a strategic advantage – for example, enhanced customer lifetime value (Ertekin, 2018).

This literature review was conducted using major academic databases (e.g. ABI/Inform, Elsevier Science Direct, Emerald Insight and Wiley Online Library) and Google Scholar to identify articles from leading operations management, logistics and supply chain journals (Fahimnia et al., 2019; Kristensen and Jonsson, 2018). The journals included in the initial search were consistent with the recommendations of Kaufmann and Gaeckler (2015) and Wang et al. (2024), who identified fifteen journals relevant to the logistics and supply chain management field. Specific details regarding the journals included and the search terms used are provided in Supplementary File S3. Studies were required to identify core aspects of returns management rather than treating it as a generic concept. The references of the retrieved articles were then reviewed to identify additional relevant publications. Some of the identified articles were in journals not on the original list. This approach identified 31 articles that met the search criteria. A detailed list of these articles is available in Supplementary File S1.

Three researchers read the 31 articles in their entirety and independently coded the core aspects of returns management in these articles. A total of 148 returns management activities were identified. To achieve parsimony and practical applicability in dimension classification, each researcher further consolidated the identified processes into fewer dimensions by combining similar related terms. A comparison of all three researchers' individual codings was conducted, and disagreements were discussed to reach consensus.

Activities associated with returns processing were the most frequently discussed dimension in this literature review. Commonly mentioned processing activities included returned product receiving, inspection, testing, selection and processing (e.g. Hjort et al., 2019; Lechner and Reimann, 2020; Russo et al., 2019). Another key dimension that emerged from the literature review and analysis was asset recovery. Based on the articles reviewed, companies perform activities such as rework, repair, remanufacturing/refurbishing, reuse and repackaging to capture maximum value (e.g. Ambilkar et al., 2022; Hazen et al., 2011; Lechner and Reimann, 2020). Extant research has also identified network design as a key dimension of returns management. Network design-related activities included topics such as consolidation, transportation, routing, re-distribution and warehousing (e.g. Bernon et al., 2016; Fleischmann et al., 2001). Customer interface and information systems support also emerged as distinctive dimensions. Customer interface activities include activities such as return authorisation, customer service and relationship management (e.g. Ambilkar et al., 2022; Hjort et al., 2019; Stock and Mulki, 2009). Returns management-related information systems support activities include product returns data and analysis, communication between different parties, etc (Huscroft et al., 2013). The outcome of the returns management classifications from the literature review is presented in Table B in Supplementary File S1.

In-depth semi-structured interviews were conducted via virtual meetings with industry experts in the returns management field. These interviews were conducted independently of the literature review and enabled us to gain a more holistic understanding of returns management capability from both academic and practitioner perspectives. The interview questions were developed to advance two research goals: (1) understand returns management capability dimensions from a managerial perspective, and (2) compare managers' responses to the literature review analysis results to ensure that our conceptualisation of returns management capability has practical relevance. Interview participants were chosen based on the research objective as well as theoretical sampling guidelines, whereby researchers jointly collect, code and analyse the data to develop the theory as it emerges (Belk et al., 1989). A total of ten in-depth interviews were conducted. Because information saturation suggests that the full complexity of the concepts has been captured, data collection ceased when redundant information appeared (Suddaby, 2006). The interviewees represented various industries heavily engaged in returns management activities. Interviewees held supply chain positions (manager and above), had an average of 16.5 years of relevant experience and possessed a high level of understanding of their respective companies' returns management strategies and activities. Therefore, they were deemed highly qualified study participants. Interviewee demographics and a copy of the interview guide are presented in Supplementary Files S1 and S2a.

The semi-structured interviews lasted 45–75 min each, with a focus on learning about industry professionals' understanding of returns management capability and identifying common themes. After the interviews were conducted, three steps for conducting the content analysis were followed: preparation, organisation and reporting (Elo and Kyngäs, 2008). Additional details surrounding the content analysis can be found in Supplementary File S3. Findings from the content analysis were consolidated with the literature review results. This was achieved using the approach suggested by Magnani and Gioia (2023), which involves three primary steps: (1) creating analytic codes and categories to form a data structure with both informant-centred (first-order) codes, (2) theory-centred (second-order) themes and (3) aggregate dimensions. An overview of the qualitative findings is shown in Figure 2.

The combined results of the literature review and semi-structured interviews provided a good understanding of returns management capability dimensions and how they are utilised in practice. Synthesising these findings, definitions and descriptions were generated for each of the returns management capability dimensions identified.

Customer interface is the ability to manage customer interactions during the returns process, including tasks such as communicating with customers, designing customer-friendly return processes and resolving customer disputes. Every interviewee stressed the importance of the customer and keeping the customer happy. This can be very challenging, as one retailer suggested that “business customers, online customers, and in-store customers all want different return experiences”. Several interviewees indicated their respective companies feel pressure from customers, particularly online customers, for better service on returns. As a result, they are trying to streamline the return process for customers, i.e. make it more user-friendly, while simultaneously working to curb the increasing volume of returns by tightening product return policies. One interviewee started the meeting by saying, “We want to have a resolution policy, not a returns policy. What can we do to keep the product in the customer's hands? We want to keep the unit sold!” This same person went on to say, “The aim is to balance customer satisfaction and (still) control returns. You can't push too hard”.

Information systems support is the ability of a company's systems to effectively capture information about returned merchandise, consolidate relevant information, and track and report returns management performance. This notion is consistent with the arguments in existing literature that a high level of visibility through information exchange is crucial for successful returns management (e.g. Daugherty et al., 2002; Mollenkopf et al., 2007). Interviewees discussed the importance of information systems support related to the complexity of managing information, the timeliness of receiving the necessary information, and the potential insights to be gained from access to the right information. One of the interviewees acknowledged that his company does not have a “well-maintained and proactively managed database for returns management”. This is a critical issue because they operate with “so many different agreements with different vendors and so many different requirements related to dates, serial numbers, and many other types of rules”. He characterised the ability to make sound decisions without effective information systems support as daunting. Another person noted that companies “need a system that has the information and can drive the processes instead of a person in the backroom of the store needing to make the decisions”. With respect to information timing, it was repeatedly noted that getting early notice of returns is a necessity to handle returns efficiently.

Processing is the ability to efficiently intake, handle, evaluate and make disposition decisions on returned products with qualified employees. Returns management is a challenging task for most companies because of the uncertainties involved. “Just getting returned products sorted and checked can be overwhelming, because standardized procedures often don't work in returns management”. For example, for certain types of products, customers must use the product to determine if they want to keep or return the product. Inspecting these open-box, lightly used products requires “knowledge, skills, time, and subjective judgment” by employees to ensure proper handling. As one interviewee noted, it is “very hard to automate returns material handling and inspection”. Several of the interviewees said that the rapid growth in e-commerce has significantly compounded issues related to “keeping up with the return volume”. It was also said that handling consumer products is much more difficult than industrial products because of product variety, order size and varying service requirements. Speeding up the returns process was mentioned as a “wish list” item by many of the interviewees. Manufacturers cited “the length of time it takes to get returned merchandise from retail stores to returns centre” as a critical issue in returns processing, along with increasing visibility related to knowing what products are coming back and when they will receive them.

Asset recovery is the ability to effectively recover maximum value from returned products by restoring returned products to resalable condition, distributing remanufactured/refurbished products through proper channels and reusing materials. While returns management “used to just be a cost of doing business”, companies have begun to recognise that it is critical to “capture as much value as possible” from the returns management processes. One company reported that its yearly asset recovery from returned merchandise increased from $4 million to over $11 million. Consistent with the literature review findings, companies are utilising different approaches for asset recovery. The primary decision regarding recovery activities is whether to use a DIY (do-it-yourself) or an outsourcing approach. With respect to keeping returns management in-house, two primary drivers were noted. Frequently, the more “value-adding” activities and “easy-to-perform” activities are kept in-house. Less value-adding and more challenging activities are often outsourced to external partners. Reclaiming value related to product returns is a consistent goal for both manufacturers and retailers. While firms can sometimes return products in good condition to the store shelf at full price or try to resell products by marking the price down due to slight damage or imperfections, it was noted that in instances where returns handling and asset recovery are not as clear cut, retailers often just “shift the burden to vendors”. As one person expressed it, our “goal is to have as limited of a commitment as possible. It's a yes/no situation. Can it go on the shelf again? If not, a return to the vendor is considered”.

Network design is the ability to plan and implement efficient and effective product returns management networks by designing optimal facility layouts, identifying the most efficient transportation modes and routes, and utilising forward logistics networks. A successful returns management program requires an effective network of supply chain parties and facilities. Product return flows are challenging to manage due to uncertainties related to quantities and types of products involved, as well as to the origins and destinations of the returned products, and the types of disposition. “The sheer volume of returns puts a lot of burden on companies,” and many simply don't have the ability to handle all returns by themselves. All interviewees stressed the importance of selecting the right partners with the requisite capabilities. One person referred to a 3C (complexity, connectivity, and compatibility) approach: “You and your partners must be able to handle complex problems, eliminate or avoid connectivity issues, and there must be compatibility (of business philosophies)”. This statement highlights the core concept of managing product returns networks: multiple parties involved are required to design networks that can smoothly facilitate returns management processes without barriers. Therefore, network design issues were considered a critical returns management capability dimension.

In summary, effective returns management often requires the balanced development of multiple capability dimensions. Using one interviewee's words, “there are different capabilities, but it is hard to disentangle them”. Such comments validated the need to take a holistic perspective to investigate returns management capability dimensions. Based on the qualitative analyses combining both a literature review and interviews, we propose that returns management capability encompasses five different dimensions: customer interface, information systems support, processing, asset recovery and network design (Figure 3).

Given the theoretically novel nature of this study and the lack of existing scales, new measurement scales were developed to assess the emergent dimensions of returns management capability. Conceptually, all returns management capability dimensions are viewed as latent variables that cannot be observed directly, which necessitates the development of multiple-item measures to adequately capture each dimension (Churchill, 1979; Hinkin, 1998). Based on the interview results, a deductive approach to initial item generation was used (Boateng et al., 2018; Hinkin, 1998). Following Hitt et al. (2016) suggestion to enhance transparency in the scale development process, a detailed explanation of the steps taken to generate and test the new scale is provided in Supplementary File S3. The scale items, item-level means, standard deviations and standardised factor loadings are available in Table 1.

To ensure that the confirmatory evidence was applicable to the intended population (Lambert and Newman, 2023), data were collected from supply chain executives in the United States across a variety of organisations. Further, since the single-respondent survey approach is most suitable to serve the current study's research objectives (Montabon et al., 2018), one respondent per organisation was targeted. This also helps to minimise any issues associated with nested data that would occur if multiple responses per organisation were collected. Survey responses were collected using a panel of supply chain management managers and executives provided by Qualtrics along with personal contacts. This resulted in an initial sample of 584 individuals. Since returns management is a somewhat specialised activity in many organisations, respondents were required to have up-to-date familiarity with their company's returns management activities. This reduced the sample pool to 474 individuals. To combat validity issues associated with insufficient effort responding, responses were screened using multiple methods shown to be effective in identifying such “careless” responses, such as directed responses and internal consistency indices (Kung et al., 2018; Ward and Meade, 2023). Responses failing these checks were removed from the sample, resulting in a final sample size of 428. The respondents had an average of 10.8 years of supply chain experience and represented a variety of industries. Consistent with our desire to target respondents with sufficient expertise to accurately answer questions concerning returns management capability and its related dimensions, 88.8% of respondents held managerial positions (i.e. managers, directors, vice presidents, etc.).

As outlined in the Supplementary Materials, the data were subjected to multiple analyses to quantitatively and qualitatively refine and validate the proposed items to form five scales, each assessed with four items. The descriptive statistics for the proposed returns management capability dimensions assessed using the final scales, along with the performance measure, are shown in Table 2.

To further confirm the construct validity of the proposed measure, a CFA with five factors and four indicators per factor was estimated using fixed-factor scaling. The model exhibited adequate fit, and all factor loadings were positive and statistically significant at p < 0.001, with standardised loadings ranging from 0.59 to 0.93, providing evidence for the unidimensionality of each construct (Gerbing and Anderson, 1988). To further investigate convergent and discriminant validity of this measure, the average variance extracted (AVE) for each factor was also examined, with results shown in Table D in the Supplementary File. The AVE for all five returns management capability dimensions exceeded 0.50 with values ranging from 0.55 to 0.79, indicating that the variance captured by the construct is greater than the error variance and is indicative of adequate convergent validity (Fornell and Larcker, 1981; Shook et al., 2004). When looking at all pairwise comparisons, the AVE for both constructs is higher than the variance shared between them, indicating sufficient discriminant validity (Farrell, 2010; Hair et al., 2006). While this criterion is well established, recent work has highlighted that it is a biased test prone to false positives (Rönkkö and Cho, 2022). Even though no indications of insufficient discriminant validity were found, consistent with best practice, a more accurate indicator of discriminant validity, the CI_CFA (sys), was also considered. Consistent with the findings using the more established criteria, the results using the CI_CFA (sys) criterion also indicate sufficient discriminant validity, with results shown in the lower portion of Table D in the Supplementary File. Collectively, the results of the factor analyses support the validity of the proposed returns management capability measure.

To uncover additional insight into how companies are embracing the different dimensions of returns management capability, a latent profile analysis (LPA) was conducted. By focusing on unobserved heterogeneity in the population, entity-centred approaches like LPA represent a complementary perspective to more traditional variable-centred approaches (Wang and Hanges, 2011). While the entity-centred perspective is relatively new compared with the established variable-centred approach, scholars have repeatedly demonstrated that adopting this perspective can meaningfully advance our theoretical understanding of phenomena (Gabriel et al., 2018; Wang and Hanges, 2011). Entity-centred approaches are particularly relevant for understanding company decisions that are made holistically rather than on an attribute-by-attribute (i.e. variable) basis, as they focus on the expression of certain profiles, or constellations, or characteristics (Gabriel et al., 2018), which seems particularly appropriate in the present context, given the results of the qualitative analysis.

Entity-centred approaches have traditionally been conducted using cluster analysis (e.g. K means, hierarchical); however, LPA has recently emerged as a viable alternative that addresses several shortcomings inherent in cluster analysis (Gabriel et al., 2018; Wang and Hanges, 2011). For example, LPA takes a probabilistic approach to assigning group membership rather than forcing entities into one discrete cluster or another and provides researchers with formal criteria to help select the appropriate number of latent groups (Wang and Hanges, 2011). Lacking this degree of decision support, traditional clustering methods “always identify clusters” even when such clusters aren't meaningful in the data (Gabriel et al., 2018). As a result, the LPA has been shown to outperform traditional cluster analysis methods (Vermunt and Magidson, 2004).

The degree to which companies adopted different strategies when it comes to their approach to returns management was investigated by considering their level of performance across returns management capability dimensions. Consistent with our theorising, both within and between cluster variance and covariance were allowed when estimating models. To determine the most appropriate model, several different indices of model fit for models with differing numbers of classes were reviewed, and the results are summarised in Table 3. In addition to the tabulated fit indices, the reliability of the model classification was considered by reviewing the entropy metrics of the considered models and found that all were similar (range of 0.75–0.79) and satisfactory (Asparouhov and Muthén, 2014).

While the performance of an LPA model can be assessed by numerous fit indices (e.g. AIC, BIC), these indices assess model fit differently and do not provide a ready means of assessing the statistical significance of differences between competing models, which makes it somewhat difficult to choose the most appropriate model when there is disagreement across these indices. To overcome these shortcomings and capitalise on the formal statistical tests that are possible with LPA, the bootstrapped likelihood ratio test (BLRT) was utilised to inform the decision regarding the correct model to interpret. By comparing the likelihoods of a model with k classes vs. one with k+1 classes, the BLRT provides a level of statistical significance indicating whether adding the additional class associated with the more complex model (i.e. k+1 classes) explains significantly more variance than the more parsimonious one with k classes. As shown in Table 3, there is a statistically significant improvement in model fit up through three latent classes. However, moving from three to four latent classes does not meaningfully improve model fit. Therefore, based on the totality of fit information, the three-class model was selected.

Summary information pertaining to the companies probabilistically assigned to each class is shown in Table 4. The three emergent classes correspond to companies that perform relatively well on returns management capability across dimensions, those that scored relatively low across dimensions and those that exhibit some variability in capability across dimensions (labelled “mixed”). As shown in Table 4, all three classes have a meaningful proportion of the sampled companies, with just over half of the companies being assigned to the low category, while the mixed class, which has the lowest proportion of companies, still encompasses more than 16% of the sample. Thus, there does seem to be some differentiation in the returns management capability dimensions for the companies included in our sample. Given the cross-sectional nature of the data, the decisions underlying these differences cannot be fully unpacked, but several potential mechanisms are discussed below.

The information systems support and processing capability dimensions exhibited the highest reported levels of performance regardless of LPA class membership. In contrast, the dimensions related to the optimisation of the overall system – the design of cost-efficient networks and the identification of avenues to capture the value of returned goods – appeared to be somewhat lagging. The primary differentiator of the mixed and high classes seems to be the emphasis placed on the externally facing aspects of the returns management process. That is, companies belonging to the higher classes tended to focus more on their ability to provide a high-quality customer interface. While the cross-sectional nature of the data does not allow for an expansive empirical investigation of this deviation, it is possible that some companies develop their internal competencies before shifting their focus to bolstering externally focused efforts. Such a trajectory would be consistent with the need to stabilise internal processes before effectively dealing with consumers (i.e. the customer interface). If this is the case, the identified classes may reflect companies at different points in their trajectories of development of returns management capability.

To validate the research findings and deepen understanding of the returns management capability dimensions in a broader supply chain management setting, additional interviews were conducted to complement the initial qualitative research efforts and quantitative analysis. Similar to the approach used by Falcone et al. (2024), these semi-structured interviews emphasised open-ended conversations to facilitate a flexible and nuanced examination of our existing findings. These interviews allowed the researchers to assess the practicality of the research findings and gather additional information that could refine the contributions of this study.

A total of 12 interviews with industry experts were conducted, with five participants from US-based companies and seven from E.U.-based companies. All interviewees are seasoned returns management professionals with an average of 19.9 years of work experience, and all hold managerial or higher job titles. The reason for expanding to the European context is to gain additional insights from managers beyond the US and examine the generalisability of our findings to a broader context. An overview of the interviewee demographics and questionnaire used in this round of interviews is provided in Supplementary Files S1 and S2. All interviews lasted 45–75 min and were conducted virtually, which allowed them to be recorded and transcribed. We stopped conducting additional interviews when it was determined that information saturation had been reached.

The interviewees were first presented with the five dimensions of returns management capability we developed, and they unanimously confirmed the accuracy and applicability of our conceptualisation. They also noted that each company may have different levels of emphasis on these specific dimensions, which was anticipated and is in line with the LPA results. Providing additional context, the interviewees indicated that emphasis on different capability dimensions often depended on the company's supply chain position and the product return format being used. Additional details surrounding these findings are provided in Supplementary File S3.

In general, the interviewees noted that although specific returns management processes and activities may vary across different settings, the five dimensions identified in the study are broadly applicable yet specific enough to capture the key dimensions of returns management capability of both business and consumer-facing companies. All interviewees were encouraged to provide comments on whether the current research has missed any important elements of returns management capability. These open conversations generated meaningful information. Most notably, three topics emerged as especially relevant: sustainability as a strategic orientation and two enabling factors: adaptability and cross-firm collaboration.

Sustainability is a prominent theme that emerged in these interviews, underscoring the crucial role of returns management in companies' sustainability efforts. While many American companies still prioritise the cost perspective in returns management, the interviewed European supply chain professionals constantly emphasised the connections between returns management capability and the company's environmental sustainability initiatives. It is apparent that the interviewed European companies pay special attention to sustainability in different aspects of their returns management processes. For example, one interviewee indicated that their company focused on optimising logistics of returned products by “using sustainable carriers to reduce environmental impact”.

From this perspective, returns management capability should help companies create social and environmental good, in addition to economic benefits such as cost savings and higher profits. The differences between American and European discussions of sustainability in a returns management context may be attributed to stricter government regulations and a higher level of acceptance of corporate social responsibility in Europe. Despite varying levels of emphasis on sustainability in their current returns management practices, companies in any country must recognise that pursuing economic efficiency in returns management does not have to be mutually exclusive from achieving environmental sustainability. In fact, all European interviewees emphasised the importance of effectively aligning returns management capability with broader sustainability initiatives whenever possible. One interviewee indicated that even when high return rates are inevitable, their company still “aims to minimize environmental impacts by finding alternative uses for returned items”.

Specifically, the European interviewees explained in detail how sustainability is a pertinent consideration for all returns management capability dimensions identified in this study. From a customer interface perspective, multiple interviewees emphasised the importance of minimising consumers' bracketing behaviour (i.e. buying multiple sizes or colours of a product with the intention of returning most of the purchase). Companies should certainly strive to develop capabilities to curb such behaviour because it has tremendous negative environmental and financial sustainability implications. With the asset recovery and processing dimensions, many interviewees noted that they aimed to maximise the value that they could recover from returns while minimising the number of returned products that ended up in landfills. From a network design perspective, interviewees hoped to create efficient return networks with the goal of reducing unnecessary movement and carbon emissions. Information systems support was identified by the European interviewees as a mechanism that could help firms to achieve triple-bottom-line sustainability goals more efficiently across all dimensions. European companies' emphasis on sustainability in returns management certainly added a crucial concept that is closely related to our conceptualisation of returns management capability. Based on these findings, Table 5 presents sustainability as a strategic orientation that can be used to guide the development of returns management capabilities.

While all interviewees offered validation of our conceptualisation of returns management capability, they also noted additional enabling factors relevant to returns management. Their valuable input suggested that returns management capability cannot be achieved in isolation. Instead, companies should develop returns management capability with the support of certain key enabling factors, and two such factors that emerged from these interviews are adaptability and cross-firm collaboration.

Adaptability: Richey et al. (2022) defined adaptability in their responsiveness view of logistics and supply chain management as “the firm and supply chain's willingness and ability to strategically adjust or reconfigure structurally based upon the understanding and expectations of externalities” (p. 79). Their conceptualisation of adaptability also applies to the context of returns management capability. The fast-changing market environment and technological advancements require companies to take a dynamic approach to returns management. In other words, companies must be able to constantly update their returns management capability and practices to keep up with external and internal changes. For example, the growing online purchase volume demands that companies develop new omnichannel capabilities and redesign the returns management processes so they can effectively and efficiently handle product returns very differently from traditional brick-and-mortar purchases. Another example given by several interviewees is that the international expansion of business requires companies to modify their returns management capability and processes to adapt to different consumer behaviours, societal expectations and legal requirements across countries. Two European interviewees reported that expanding into countries with very high return rates had made their companies “adapt the product return operations to be aligned with the new marketplace conditions” and “develop better strategies to communicate the environmental impact of product returns to consumers in the new markets in order to encourage more sustainable shopping behaviours”.

Cross-firm collaboration: Our conceptualisation of returns management capability focuses on specific aspects of the returns management process, and the interviewees emphasised that these identified returns management capability dimensions require the support of strong relationship management. Returns management involves numerous internal and external parties, each of which contributes to the development of return management capability. As one interviewee indicated, “the partner's policies and business model will impact our operational procedure to handle the returns”. Many of the interviewed companies outsource certain returns management activities and processes to third parties, and managing those outsourcing relationships becomes extremely important. Because the networks for handling product returns almost always expand across company borders, tackling the 3C concepts (complexity, connectivity and compatibility) is a critical component of returns management network design. Therefore, without the collaborative efforts with external partners, it is often not feasible to achieve or optimise the dimensions of returns management capability. For example, information system support capability is not possible if upstream or downstream partners are not willing to share necessary information. Therefore, cross-firm collaboration, a key supply chain management concept (Cao and Zhang, 2011), becomes especially crucial in this setting. As an interviewee asserted, “We understand and pay special attention to developing strong relationships with different partners such as 3PLs and e-commerce partners in our returns management”.

In summary, these additional qualitative interviews provided crucial insights to help validate and position our conceptualisation of returns management capability within the broader organisational ecosystem. The identified five returns management capability dimensions should all have a sustainability orientation, encompassing economic, social and environmental aspects. In addition, the development of returns management capability requires the support of enabling factors such as adaptability and cross-firm collaboration.

Returns management is a broad, complex and often strategic supply chain process (Mollenkopf et al., 2011). Identifying key dimensions of returns management capability helps advance the understanding of this concept and can provide a focus for companies to commit necessary resources and develop suitable strategies. The current study employed multiple methods of data collection and analysis to present a comprehensive picture of returns management activities and associated capability dimensions. This enabled us to build a robust typology of returns management capability (along with associated measures) as well as a broader conceptual framework to facilitate future theoretical and empirical advancements in this important area.

This study advances literature by presenting a holistic view of returns management capability. Such an approach is critical for understanding performance and guiding future research in this area (Vlachos et al., 2026). While returns management has gained interest from researchers (Ambilkar et al., 2022; Wang et al., 2017), existing literature has largely viewed returns management capability as a broad and vague concept. While a few studies examined more specific aspects (e.g. Autry, 2005; Bernon et al., 2011; Daugherty et al., 2001; Richey et al., 2005), little empirical research has examined the concept of returns management capability. This study not only identified and defined key dimensions of returns management capability but also provided a much-needed instrument to advance research on this important topic. The development of a scale that can be used to measure returns management capabilities is a key contribution of this study, as it lays the groundwork for future quantitative research in this area (Lyu et al., 2026). The holistic perspective taken in the current study provides meaningful insights that should enable future researchers to adopt a more rigorous theoretical and empirical exploration of returns management capability performance moving forward.

The LPA identified three different classes of firms based on their returns management capability performance. This analysis enabled improved understanding of organisational approaches to returns management capability development. Specifically, the findings of this analysis indicate that firms likely progress along different developmental paths. The way that an individual firm is likely to develop different returns management capability dimensions is expected to be based on internal (e.g. firm priorities, experience, and resource availability) and external (e.g. customer expectations, legal requirements, and competitor actions) factors. It has been noted in previous research that a lack of internal alignment in an organisation often results in poorly coordinated supply chains (Karlsson et al., 2023). Therefore, the development of an effective returns management capability cannot be achieved without collaboration and alignment among both internal and external partners (Hjort et al., 2019). For both e-commerce and physical retailers to manage returns effectively, they need to be integrated with partners, ranging from transportation providers that pick up returns to third-party logistics (3PL) companies that process them. The ability to adjust operations based on a changing environment is another factor that enables the development of a returns management capability. Therefore, the findings of this analysis provide additional understanding of how different capability dimensions can be developed over time. Specifically, the newly developed framework suggests that returns management capability may be productively viewed through an alignment lens (Powell, 1992). In doing so, our work introduces important theoretical nuances and highlights the need to adopt a contingency-based view that considers the roles of both internal and external alignment in the development and deployment of returns management capability.

This study also contributes to existing literature by highlighting areas of convergence and divergence between academic and practitioner perspectives. Exploring this misalignment can help resolve “lost before translation” issues that result in academic work having little relevance to the problems faced by organisations (e.g. Shapiro et al., 2007). Such issues have long hindered business scholars' ability to produce meaningful theoretical advancements that are adequately aligned with business reality (Hambrick, 1994). One misalignment that was identified in this study was that while scholars have placed a great deal of emphasis on improving returns processing and asset recovery, practitioners consistently emphasised the importance of their customers. Results also showed that network design has received less attention from practitioners than academic researchers. Most likely, this is related to the challenging nature and complexity involved in developing returns management networks (Russo et al., 2021; Wang et al., 2017). By identifying these misalignments, the findings of this study should contribute to the returns management literature by recognising the importance of all capabilities working together in this context (e.g. Karlsson et al., 2023; Faires et al., 2025).

Findings in this study further extend the literature by highlighting adaptability and cross-firm collaboration as key enabling factors for supporting the effective implementation of a returns management capability. Results also emphasise the pivotal and evolving role of sustainability (financial, environmental and social) as a strategic orientation for firms looking to develop a returns management capability. Specifically, while sustainability has been widely accepted as a core corporate value in the academic literature, our study found that US-based companies significantly lag their European counterparts in terms of connecting returns management with sustainability efforts. Therefore, within the US context, these findings provide another opportunity to better align academic and practitioner thinking on the importance of sustainability to returns management capability.

This study was motivated by the challenges in real-world returns management practices. Therefore, industry professionals were key participants in different phases of the study. Because this study was guided by practice, a high level of managerial relevance is expected. Within this study, respondents were asked to indicate how well they were doing with respect to the tasks associated with each of the five returns management capability dimensions. Respondents indicated only moderate assessments of their returns management capabilities, with average dimension scores ranging from 4.65 to 5.33 on a 7-point scale. This suggests that the companies have tremendous opportunities to improve on all returns management capability dimensions. It is noteworthy that almost across the board, the respondents who participated in the interviews in this study indicated that returns management is receiving more attention – and usually more resources – than in the past. Concerns about the potential negative customer reactions to sub-par returns handling, along with the pressures to recover returns-related assets, have made returns management a higher priority for many companies, highlighting the importance of better understanding returns management capability (e.g. Bian and Xiao, 2025; Griffis et al., 2012; Hao et al., 2024). One interviewee said of returns management, “everyone is doing it, but almost no one is doing it well”. The findings of this study should therefore guide companies looking to improve their returns management capability.

For professionals working in returns management, this study identifies five distinct yet related areas that require resource commitment and operational excellence. Each of these dimensions has unique characteristics and emphases, warranting differentiated attention. The traditional focus on processing and asset recovery is no longer sufficient to remain competitive in returns management. Companies must also engage in areas such as customer interface, information systems support, and network design. In fact, we argue that firms benefit from taking an integrative approach to developing these dimensions. By providing clear definitions of each, this research offers a baseline for assessing strengths and identifying areas for improvement. When prioritising future development efforts, firms should recognise that these dimensions are not independent and that improvements or neglect in any one area will likely have implications for the others.

Building on this integrative perspective, our findings further illustrate how these dimensions interact in practice to shape both customer and operational outcomes. Specifically, the RMC dimensions work together to shape the overall customer and operational experience, rather than functioning as independent elements. In particular, the information systems support capability appears to serve as a foundational enabler, providing timely, accurate data for effective customer interactions and issue resolution. However, possessing these capabilities does not guarantee their effective use in customer-facing processes, highlighting an important distinction between what firms can do and what they choose to implement. Similarly, visibility into returns flows and the ability to process products efficiently can support more effective network design and asset recovery decisions. At the same time, choices related to return channels can create important trade-offs. For example, channel design may influence both asset recovery opportunities (e.g. packaging reuse) and the customer experience, while more lenient returns policies may constrain recovery options by increasing the likelihood of damaged or aged products and requiring more flexible processing systems. Taken together, these interdependencies suggest that firms should adopt a holistic approach to building and managing RMC, as focusing on individual dimensions in isolation may lead to suboptimisation, where improvements in one area come at the expense of overall capability performance.

Without a clear understanding of critical returns management capability dimensions, companies may struggle when allocating limited resources. The newly developed measurement scales can provide a useful assessment tool to evaluate progress in implementing these strategies and offer a blueprint for continued improvements. Additionally, the proposed framework provides a formalised structure for companies to develop returns management capability, supported by enabling factors and strategic priorities such as sustainability. These efforts should not be static or limited to one department (Faires et al., 2025). Instead, achieving a high level of returns management capability requires constant adjustments as well as the support of other functional areas and supply chain partners.

The LPA in this study identified three different classes of companies in terms of returns management capability, and the analysis results suggested that companies with relatively low returns management capability are more likely to focus on developing the processing dimension more than the other dimensions. This pattern could arise out of necessity. That is, as products are returned, they must be processed to avoid consuming the company's physical and capital resources. The other two classes of companies with higher capability scores did not seem to maintain similarly elevated levels in this dimension. This suggests that a more sustained emphasis on enhancing returns management capability leads to a greater relative focus on broader, and in some sense, more strategic dimensions of returns management capability to provide strategic differentiation for the firm.

Companies were also shown to place somewhat greater emphasis on internal capability dimensions that deal with the intake of returned products. Companies looking to strengthen their returns management capability dimensions will likely need to consider additional customer interface development. Alternatively, it could be that this pattern is indicative of a broader strategic focus on internal relative to external competencies, implying that these companies may not aspire to improve their performance on these dimensions over time. If this is the case, firms are encouraged to adopt a more holistic approach to developing their returns management capability.

While this study made important additions to the existing returns management literature, future research can further contribute to this topic based on our findings. Beyond the immediate empirical findings, this study establishes a foundation for cumulative research on returns management by introducing a validated measure of returns management capability. The scale provides a tool that can systematically examine antecedents, boundary conditions and performance implications of returns processes across organisational and supply chain contexts. As a result, future work can move beyond descriptive accounts of returns practices towards theory testing and comparative empirical investigation. Table 6 outlines a future research agenda by presenting illustrative research questions and the types of contributions that studies leveraging the scale could generate for the returns management and broader operations and supply chain management literature.

Our research represents an initial attempt to examine the returns management capability concept from a holistic perspective. Based on the findings in this study, it is apparent that returns management capability development can and should be aligned with corporate sustainability strategies. The identification of five dimensions provides a detailed framework to further the current understanding of returns management capability. At the same time, developing a strong returns management capability requires the support of other broader organisational capabilities, such as adaptability and relationship management. Supply chain scholars and returns management professionals are encouraged to validate, reject or modify the proposed framework by applying it in different research contexts and real-world practice scenarios.

The supplementary material for this article can be found online.