Customer Returns Research Articles

Return management in e-commerce firms: A machine learning approach to predict product returns and examine variables influencing returns

The advent of technology with internet penetration has led to exponential growth in sales through online mediums worldwide. Although the growth has increased sales and created opportunities for many firms and sellers to flourish, it also brings in the challenge of customer returns, making it a formidable challenge for businesses. For effective return handling and control, predicting product returns correctly is of utmost importance for firms. The study comprehensively examines the return management process, elucidating its multiple features and characteristics, focusing on the types of returns and the involvement of various stakeholders. Logistic regression, random forest, and gradient-boosting machine learning techniques were used on a data set to scrutinize critical variables influencing returns. Comparing the models using the ROC curve and AUC, gradient boosting performed better in predicting returns than other models. The study identifies significant variables affecting e-commerce return rates, such as total order amount, product category, and cash on delivery charge, an additional fee charged on this mode of payment. Managerial insights recommend that firms conduct due diligence and thorough assessments before introducing products from specific vendors. Quality improvement in certain categories of products, incentivizing card payments, and nominalizing the cash on delivery fees, which could be seen as burdensome by customers, are some of the steps firms need to reduce returns. Strategies like confirming weekend orders and updating replenishment times regularly by vendors can help firms mitigate returns effectively. The study contributes to the academic understanding of return management in e-commerce and offers actionable insights for practitioners.

Investigating Returns Management across E-Commerce Sectors and Countries: Trends, Perspectives, and Future Research

Background: The systematic literature review with additional descriptive analysis at hand focuses on analysing returns management in e-commerce, which is an increasingly critical issue as the volume of online shopping is rising. Methods: Drawing from a comprehensive search of academic databases and a manual review of Google Scholar, 54 articles dating from 2007 onwards were collected and fully read. Results: The review reveals a main research effort emerging mainly from Germany and other countries, with a notable focus on fashion retail. The bulk of these studies aim to understand and reduce the frequency of customer returns, addressing a substantial operational challenge for online retailers. The findings provide multiple research streams extracted from the collected literature and combined to an overview. Conclusions: Through this, there are tendencies which can be interpreted to derive the evolution of the research field. The illustrated results in this review paint a detailed picture of the existing research landscape. This highlights the importance of ongoing research, which, e.g., holds potential benefits for customer satisfaction and environmental sustainability. The review also lists future research directions, recommending the continued investigation of areas such as predictive analytics and customer behaviour to further refine returns management practices.

Reducing Outgoing Quality Level (OQL) in Textile Manufacturing Through Six Sigma Methodology: A Case Study

Globally, the textile industry plays a significant role in production but faces many challenges that affect its operation and sustainability. Product quality remains an essential concern despite technological advancements and quality control measures. Raw materials, production methods, and skills differ, resulting in customer dissatisfaction and damage to reputation. A quality management strategy is necessary to overcome these problems and promote quality improvement. This includes the implementation of the Lean Six Sigma approach. This article focuses on improving textile quality by developing the Six Sigma DMAIC method. An analysis of three months' data from a textile company shows that an increase in the Outgoing Quality Level (OQL) from 3% to 6% resulted in significant economic losses, amounting to PKR-240,000 due to rework, residual costs, customer returns, and lost sales time. By utilizing Six Sigma tools, the company reduced OQL from 6% to 4%, thus lowering product losses and increasing operational efficiency. As a result of these findings, the textile industry can improve quality and profitability through a Lean Six Sigma approach.

Toward a circular supply chain: The enabling role of information and financial flows in open and closed loop designs

Paramount to the transition to the circular economy is the transformation of existing supply chains. We build on the theory of the supply chain to study circular design features and the enabling role of information and financial flows needed for circularity. We study five exemplars for environmental leadership to illuminate how material flows are enabled by information and financial flows to leverage cross-industry waste flows (i.e., open loops) and customer returns (i.e., closed loops). While both open and closed loop designs can lead to a bottom-up transition towards the circular economy, there are differences in the enabling role played by outward and inward information flows. Further, we unpack the supporting role of inward and outward financial flows toward customers, suppliers and non-supply chain stakeholders for creating a viable supply and demand circular market and a wider community in which circular supply chain can be embedded.

Optimizing Financial Strategies to Minimize Customer Returns in E-Commerce Ecosystems

The rise of e-commerce has transformed the retail landscape, offering convenience and accessibility to consumers worldwide. However, alongside the benefits come challenges, with customer returns being a significant concern for e-commerce businesses. This research paper investigates the role of financial management strategies in reducing customer returns within e-commerce ecosystems. By examining various tactics such as pricing optimization, inventory management, and customer service investments, this study aims to provide insights into effective approaches for minimizing returns while maintaining financial sustainability. Through a comprehensive review of existing literature and empirical analysis, this paper offers practical recommendations for e-commerce businesses to enhance their financial management practices and mitigate the impact of customer returns on profitability.

Customer-to-customer returns logistics: Can it mitigate the negative impact of online returns?

Customer returns are a major problem for online retailers due to their economic and environmental impact. This paper investigates a new concept for handling online returns: customer-to-customer (C2C) returns logistics. The idea behind the C2C concept is to deliver returned items directly to the next customer, bypassing the retailer’s warehouse. To incentivize customers to purchase C2C return items, retailers can promote return items on their webshop with a discount. We build the mathematical models behind the C2C concept to determine how much discount to offer to ensure enough customers are induced to purchase C2C return items and to maximize the retailer’s expected total profit. Our first model, the base model (BM), is a customer-based formulation of the problem and provides an easy-to-implement constant-discount-level policy. Our second model formulates the real-world problem as a Markov decision process (MDP). Since our MDP suffers from the curse of dimensionality, we resort to simulation optimization (SO) and reinforcement learning (RL) methods to obtain reasonably good solutions. We apply our methods to data collected from a Dutch fashion retailer. We also provide extensive numerical experiments to claim generality. Our results indicate that the constant-discount-level policy obtained with the BM performs well in terms of expected profit compared to SO and RL. With the C2C concept, significant benefits can be achieved in terms of both expected profit and return rate. Even in cases where the cost-effectiveness of the C2C returns program is not pronounced, the proportion of customer-to-warehouse returns to total demand becomes lower. Therefore, the system can be defined as more environmentally friendly. The C2C concept can help retailers financially address the problem of online returns and meet the growing need for reducing their environmental impact.

Return compensation strategy of online retailer for online reviews

With the development of the Internet, consumers tend to go online shopping. Online reviews have become an important reference for consumers to make purchase decisions, and they contain reliable and rich information about products and needs that influence consumers’ and companies’ decisions. However, consumers are sometimes unable to accurately judge product quality through online reviews, resulting in the quality of the product not meeting the expectations of consumers. Then, consumers sometimes choose to return products and make negative reviews about the product, which can damage the retailer’s interests. To reduce the damage to profits, online retailers have adopted a return compensation policy. In this paper, we establish a two-stage model based on the retailer’s return compensation policy. Meanwhile, considering the effects of customer returns and online reviews, we construct two scenarios with and without return compensation policies to compare the equilibrium results of the game in different scenarios, and to analyze the effects of online reviews and product mismatch on retailers’ profits. The results indicate that: (1) return compensation compensates consumers for the loss of utility due to product mismatch, promotes positive consumer reviews of that product, and leads to an increase in both product sales and total profits. (2) Product mismatch is negatively associated with the number of positive reviews and positively associated with the number of negative reviews in the case where an online retailer offers return compensation.

Factors that Affect the Level of Customer Satisfaction and Repurchase Intention on Tokopedia

This study investigates the roles of various factors such as Customer Service, Shipping, Tracking, Returns, Sales Promotion, Customer Satisfaction, and Repurchase Intention within the Tokopedia E-Commerce application. Data collection took place over a week, from July 13 to July 20, 2023, with a sample size of 144 respondents. The research employed a descriptive research design and gathered empirical data through online surveys. Structural Equation Modeling was utilized to analyze the data and test several hypotheses. Findings indicate that Customer Service and Tracking do not significantly impact Customer Satisfaction, whereas Shipping, Returns, and Sales Promotion positively influence Customer Satisfaction. Additionally, Customer Satisfaction positively affects Repurchase Intention. The managerial implication suggests that optimizing Customer Service and Tracking could enhance Repurchase Intention. Future research may explore different samples and incorporate additional variables.

Pengaruh Pengendalian Internal Persediaan Terhadap Efektivitas Pengelolaan Persediaan Barang Dagang

One of the problems faced by UMKM in Bengkulu City is that there are still poor quality and damaged commercial goods. This is due to the lack of control and inspection of merchandise received from factories and customer returns. This study aims to determine the effect of internal control of supplies on the effectiveness of trade inventory management in UMKM in Bengkulu City. This study uses a simple linear regression analysis method using SPSS version 26. Data collection techniques are obtained from primary data using purposive sampling method by distributing questionnaires. The result of this study is a correlation coefficient of 0.420 which shows that the relationship between independent and dependent variables is classified in the medium category, the magnitude of influence between internal control of inventory on the effectiveness of trade inventory management in UMKM in Bengkulu City is 17.6%. The results offer hypothesis test show that internal control of inventory has a significant influence on the effectiveness of trade inventory management in UMKM in Bengkulu City.

When it rains, it pours? The impact of weather on customer returns in the brick-and-mortar retail store

With the increase in weather's unpredictability, the retail industry has been actively integrating weather data to make more informed decisions. However, knowledge about the impact of weather on customer returns is limited. It is crucial to understand customer return behavior so that companies could design strategies that are beneficial for both the business and its customers. In our study, we explore the role of weather (weather types and temperature) in shaping customer return behavior. Transaction data from 328 brick-and-mortar retail stores situated in 56 cities across China were analyzed using ordinary least squares regression. The results demonstrate that rainy days, in comparison to cloudy ones, reduce the likelihood of customers venturing out to make returns. Additionally, we observe that extreme temperature conditions, whether excessively cold or hot, also deter customers from initiating returns. However, the impact of weather on returns is subject to variations introduced by different return channels and holiday periods. Together, our research demonstrated a novel factor that impacts customer return. With the ever-dynamic symphony of the weather, this research broadens the scope of weather's influence on consumer behavior to encompass the domain of returns, while providing valuable implications for retailers to respond to weather-related fluctuations in customer return behavior.

Volleyball premier league algorithm with ACO and ALNS for simultaneous pickup–delivery location routing problem

The reverse logistics problem, which involves customer returns and incurs high additional logistics costs, has become a topic of increasing interest. This problem is modeled as the location routing problem with simultaneous pickup and delivery under time constraints (LRPSPDTW), which is a more complex version of the location routing problem (LRP). Previous studies have shown that existing algorithms are unable to provide satisfactory solution accuracy for this problem. In order to address this, a novel algorithm called the hybrid volleyball premier league (HVPL) algorithm is proposed. Drawing inspiration from the competition mechanism of the original volleyball premier league (VPL) algorithm, the HVPL algorithm incorporates adaptive large neighborhood search (ALNS) and improved ant colony optimization (ACO) as sub-algorithms, allowing them to work together synergistically and strike a balance between exploration and exploitation. The learning and elimination phases of the VPL algorithm have been redesigned to enhance convergence speed. Furthermore, the Bellman’s algorithm has been enhanced to determine depot locations and construct vehicle paths for the solution. Prior to solving the LRPSPDTW problem, benchmark testing was conducted using 35 latest benchmark functions. Experimental results and Friedman mean rank test demonstrated that HVPL exhibits superior exploration and exploitation capabilities. HVPL was subsequently tested on 66 instances based on the modified Solomon’s benchmark and the NEO research group benchmarks, and the results showcased its outperformance over other methods in the majority of cases.

Manufacturer’s quality improvement and Retailer’s In-store service in the presence of customer returns

A manufacturer can improve product quality and a retailer can provide in-store service in order to improve customer satisfaction and manage customer returns in a supply chain. In this paper, we develop a model for a supply chain in which the retailer offers a full-refund customer returns policy, and the customer is heterogenous in willingness-to-pay for product quality and faces uncertainty as to the fitness of the product. We examine the manufacturer’s optimal quality improvement strategy and the retailer’s optimal in-store service strategy. Our study shows that the optimal customer returns management strategy from the perspective of the supply chain as a whole coincides with the individual interests of both the manufacturer and the retailer. We show that each of the four supply chain strategies (no quality improvement and no in-store service, in-store service but no quality improvement, quality improvement but no in-store service, and both quality improvement and in-store service) can be a dominant supply chain strategy, depending on several factors. These factors include the degree of the increase in product quality and/or the degree of the increase in the likelihood of the customer’s satisfaction due to in-store service, and the relative efficiencies of producing and selling the product with/without the manufacturer’s quality improvement and/or with/without the retailer’s in-store service. We show that when either the manufacturer can flexibly determine the quality improvement level, or the retailer can flexibly adjust in-store service level, or both can decide their respective strategies, the dominant strategy includes both in-store service by the retailer and quality improvement by the manufacturer.

Online product pricing considering product quality and return policy

With the rapid development of O2O, offline experience and online purchase have become a method of purchase for more and more customers. Through offline experience, consumers can feel the quality of products directly. Such channel switching behavior of consumers will produce a “showroom” effect and affect the return rate of online channels. This study adopts the multinomial logit model to maximize profits by considering the difference in quality between online and offline products, quality defects, and offline service. Then, a pricing decision model is developed to analyze the influence of returning goods due to quality problems on the retailers’ optimal pricing and profit. The result shows that retailers can obtain the optimal profit when the offline service is maintained at a certain level. As the return rate increases, the optimal pricing increases, but the maximum profit decreases. The optimal pricing decreases with the increase in online product quality, but the maximum profit increases accordingly. In the omni-channel environment, customers can freely switch between channels according to utility and preference when purchasing products. Based on customer returns, retailers can dynamically adjust their service, control product quality, and set optimal product pricing, thus achieving maximum profits. This study can provide a theoretical basis and decision support for omni-channel retailers in platform operation and revenue management.

The influence of return channel type on the relationship between return service quality and customer loyalty in omnichannel retailing

PurposeThis study investigates the impacts of return channel type on the relationships between return service quality (RSQ) and customer loyalty (CL) in an omnichannel retailing environment.Design/methodology/approachData comes from Chinese customers having a return experience in omnichannel retailing that uses the channel type of both buy-online-return-in-store (BORIS) and buy-in-store-return-to-online warehouses (BSROW). The authors use the structural equation modeling to test the hypotheses and the bootstrapping method to test the mediation and moderation effect.FindingsFor BORIS channel, satisfaction of customer returns (CRS) partially mediates the relationship between convenience and CL, and fully mediates that between CL and responsiveness, transparency and competence, respectively. For BSROW channel, CRS partially mediates the relationship between responsiveness and CL, and fully mediates that between CL and convenience, transparency and competence, respectively. The mediation effects indicate that omnichannel customers may feel more satisfied due to higher omnichannel fulfillment (responsiveness and convenience) and omnichannel trust (transparency and competence) provided by retailers. Return channel type moderates the relationship between RSQ-convenience and CL. The results show the different expectations between BORIS and BSROW customers in the return process.Research limitations/implicationsThis paper serves as a pioneering study to apply cognition-affect-behavior paradigm into the field of return management in omnichannel retailing.Practical implicationsThe findings suggest retailers develop their strategies on customer returns and post-sales service quality improvement in the omnichannel. Also, retailers should develop an integrated return system across channels to provide convenient service to BORIS customers and quick response to BSROW customers.Originality/valueStudying return service management in the omnichannel from customer's cognition appraisal, this study contributes to the literature of the reverse service management by bringing in the effect of omnichannel type to explore the relationship between RSQ and CL.

Inventory model for non-instantaneous deteriorating items with hybrid price and stock-dependent demand in the view of delay in payments, inflation, and customer returns

Inventory model for non-instantaneous deteriorating items with hybrid price and stock-dependent demand in the view of delay in payments, inflation, and customer returns

Impact of advertisements on retailer's inventory for time-varying perishable rate with preservation technology investment under customer return and trade credit policy

In any business worldwide, inventory management is a challenging task for every organisation. This article demonstrates an inventory model for deteriorating products from the retailer's point of view in which: 1) demand is determined by price and frequency of advertisement; 2) the influence of trade credit on expanding small business and their consumers is the focus of this research; 3) product deteriorates with an expiry date; 4) retailer invests money in preservation technology to preserve the deterioration of a product; 5) customer returns the product to the company are the significant factors among the interrelation of supplier and retailer for a highly demanding product. The main objective of this article is to optimise the retailer's total profit in terms of cycle length, price, frequency of advertisement, and capital in preservation technology. Also, for optimality, an algorithm is created. Finally, the results were validated by solving two numerical illustrations and conducting sensitivity analysis of the main factors resulting from the following managerial implications: 1) if the retailer receives a longer allowable delay period from the supplier, the retailer can maximise total profit; 2) an increase in the ordering cost per order the overall profit decreases.

Product destruction: Exploring unsustainable production-consumption systems and appropriate policy responses

The practice of product destruction, whereby retailers or manufacturers dispose of viable consumer products such as unsold goods or customer returns, is an extreme expression of the linearity of our current production-consumption system. This qualitative exploratory study aims to uncover why companies engage in this highly unsustainable and resource-inefficient behaviour and to explore the potential policy interventions required to effectively address the issue. In-depth interviews were conducted with eleven experts from the textiles and electronics sectors to understand the driving forces behind this practice and provide a bottom-up perspective on appropriate policy interventions. The research identified two distinct sets of factors that contribute to product destruction. Upstream factors influence overall levels of customer returns and unsold stock and primarily include aspects of the retailer's business model, consumer expectations and product design. Downstream factors drive companies to dispose of these products rather than to pursue product life-extension strategies such as repair and reuse. Key downstream factors include economic incentives, profit-margin considerations, liability and brand integrity concerns, the availability of reuse networks and management issues. Consequently, to meaningfully address product destruction, a policy mix is required to simultaneously target upstream and downstream factors and change the behaviour of different actors, from manufacturers and retailers to consumers and reuse organisations.

A deterministic model for perishable inventory with variable demand under demand dependent production rate, inflation, and customer returns

A deterministic model for perishable inventory with variable demand under demand dependent production rate, inflation, and customer returns

Return freight insurance strategies for the online retailer and insurance company

In online purchases, customers often exhibit considerable hesitations due to quality uncertainty and return freight fees. In response, online retailers may buy the return freight insurance (RFI) service from insurance companies that compensate the customers when they return the purchased item. With the RFI service, insurance companies generally verify the quality information posted by the retailer to avoid excessive customer returns. Thus, the RFI service not only reduces the customer’s return freight but also acts as an imperfect quality signal for customers to mitigate quality uncertainty. We characterize the RFI’s imperfect signaling effect by signal efficiency, and develop a game-theoretic model to investigate the RFI strategies of insurance companies and the retailer. Our results shed light on how signal efficiency and return freight fees drive their RFI strategies. The insurance companies charge an extremely small RFI premium for the retailer selling high-quality products; for the retailer selling low-quality products, the RFI premium becomes large for those with a medium return freight fee, or with a small signal efficiency. The retailer selling high-quality products always adopts the RFI service. The retailer selling low-quality products does not adopt the RFI service when the return freight fee is large. Given a medium return freight fee, the retailer with low-quality products prefers the RFI service when the signal efficiency is medium. Given a small return freight fee, only when the signal efficiency is large does the retailer with low-quality products adopt the RFI service. Our results provide new explanations for the prevalence of the RFI service for retailers selling products of different quality, and shed light on the RFI premium strategy for insurance companies.

Sourcing strategies of manufacturers with customer returns and product design efforts

AbstractWe develop game‐theoretic models to study the sourcing strategies of the two competing manufacturers who face customer returns due to product design mismatch. The manufacturers have opportunities to reduce the likelihood of customer returns by putting efforts into improving product design. Each manufacturer has the option to outsource product design and production to an upstream supplier or keep product design and production internally. We show that the sourcing decisions of the two manufacturers depend on the level of relative return from design investment (determined by the cost of design efforts, degree of horizontal product differentiation, and expected costs related to returns). We identify the sourcing strategy equilibrium and show that the higher cost of design effort and/or the higher degree of horizontal product differentiation expand, while the higher costs related to returns shrink, the range in which symmetric outsourcing is an equilibrium. Furthermore, as compared to symmetric insourcing, symmetric outsourcing not only softens the price competition but may also increase design effort levels, and thus both manufacturers are better off from outsourcing. However, symmetric outsourcing may hurt both consumer surplus and social welfare.