Due to legal, economic and socio-environmental factors, reverse logistics practices and extended producer responsibility have developed into a necessity in many countries. The end results and expectations may differ, but the motivation remains the same. Two significant components in a reverse logistics system -product recovery options and return channels - are the focus of this thesis. The two main issues examined are allocation of the returned products to recovery options, and selection of the collection methods for product returns. The initial segment of this thesis involves the formulation of a linear programming model to determine the optimal allocation of returned products differing in quality to specific recovery options. This model paves the way for a study on the effects of flexibility on product recovery allocation. A computational example utilising experimental data was presented to demonstrate the viability of the proposed model. The results revealed that in comparison to a fixed match between product qualities and recovery options, the product recovery operation appeared to be more profitable with a flexible allocation. The second segment of this thesis addresses the methods employed for the initial collection of returned products. A mixed integer nonlinear programming model was developed to facilitate the selection of optimal collection methods for these products. This integrated model takes three different initial collection methods into consideration. The model is used to solve an illustrative example optimally. However, as the complexity of the issue renders this process ineffective in the face of larger problems, the Lagrangian relaxation method was proposed to generate feasible solutions within reasonable computational times. This method was put to the test and the results were found to be encouraging.

Handling product returns has become a critical activity for organizations as the volume of gods flowing back through the supply chain rapidly increases. Few research studies have published specific empirical data concerning the reverse logistics practices of companies. Information technology and information support has long been recognized as a competitive weapon – capable of enhancing company performance and achieving efficient reverse logistics. Reverse logistics is very unlike the forward, as it is more reactive and also has less visibility. Unlike forward logistics, incoming products from reverse logistics are not tracked broadly because of the lack of information systems resources necessary.The investigated apparel company in this study is operating on the global market and expands their sales twenty per cent each year, resulting in increased pressure in the return flow. To meet this future demands, the return process has to be more efficient and not so time consuming. This study emerged from a case study made at the return department of this apparel company based on a research question. An improvement area was discovered through interviews, internal documents and observations. This area was investigated in existing theories through books and scientific research papers. From the theories and the case study, a hypothesis was created in order to be tested. To strengthen the hypothesis, an experiment was developed and performed at selected retailers and at the apparel company.Research Question Where in the product return process can improvements be made in order to make the information flow more efficient between retailers and an apparel company?HypothesisBy creating a web-based return form, the information flow between retailers and an apparel company will be more efficient, resulting in a more effective and structured product return process.Through the experiment, various factors that strengthen the hypothesis were discovered. For instance, the information flow becomes more effective when retailers have clear guidelines how to send back products and when inserting the information into the computer system before returning. As the apparel company knows what is coming back, the disposition of returned products can be predetermined which will speed up the return process. Shared and available information across various parties facilitate the daily work with better communication. Furthermore, activities that are existing today within the return process can be eliminated which result in more effective product return process. Refund for retailers can be made quicker which result in more satisfied retailers and creates stronger relationships. / Program: Master programme in Applied Textile Management

One of the newest emerging areas of research in supply chain management is ReverseLogistics. It involves all activities related to the flow of products from the customerback to the supplier. In the last decade scholars have developed theories and models,however empirical data is still in its infancy. In response, this paper strives to close thisgap by conducting research to create new knowledge on the first element of reverselogistics, which is the product return process. The main intention of having a returnprocess is to handle returned products efficiently in order to recover value and to savecosts. Therefore, it is a value-adding operation and can become profitable for thecompany.The purpose of this study is to investigate the implementation and perception of thereturn process of Swedish e-retailers. Sweden is considered to be one of the mostmatured e-commerce markets. In addition, e-retailers experience the highest rate ofproduct returns. Together those two factors influenced the decision to dedicate thisthesis to this particular region and industry.Initially, this paper introduces reverse logistics focusing specifically on the productreturn process. An overview of the existing theories and concepts within the returnprocess is presented and summarized, resulting in the creation of the Boomerang ReturnModel. Based on this foundation the questionnaire was created. By cooperating with theSwedish e-retail federation - Svensk Distanshandel, access to the industry was gained toperform a quantitative study.It was found that the empirical data only gives insight into the implementation andperception of the return process of small sized companies. The findings demonstrate thelimited awareness of the importance of an efficient return process. Companies tend toperceive the return process as unimportant instead of value adding. Hence, there is anopportunity for improvements in the Swedish e-retail market. From these findings amodified version of the Boomerang Return Model was created to adjust the initialmodel particularly for small sized companies. The model can be utilized as a theoreticalgroundwork in future research. Additionally, it could also serve as guidance for smallcompanies how to implement an appropriate return process.

We model a two period game with duopoly market under either quantity or price competition. In the first period, the manufacturer decides on whether to accept the returned products. The optimal ratio of refurbishing is then determined in the second period once the manufacturer has decided to do refurbishing. We identify the optimality conditions that lead to different possible equilibrium outcomes for different scenarios in which two firms may play symmetrically or asymmetrically. Our extensive numerical analysis substantiates the analytical results and we focus on the effect on the subgame perfect equilibrium caused by various parameters. Among our results, we find that, as the return ratio increases, the profits generated from the refurbished market become harder to compensate the loss in the new product market. Besides, the increase of substitution effect in the quantity competition enhances the degree of satisfaction for the refurbished products and it hurts firm¡¦s performance in the more profitable new product market. However, the effect of substitution effect in the price competition is entirely opposite. For instance, when the substitution effect is high, only one firm enters the refurbished product market; and when the substitution effect is low, both firms enter the refurbished product market.

<p>One of the newest emerging areas of research in supply chain management is ReverseLogistics. It involves all activities related to the flow of products from the customerback to the supplier. In the last decade scholars have developed theories and models,however empirical data is still in its infancy. In response, this paper strives to close thisgap by conducting research to create new knowledge on the first element of reverselogistics, which is the product return process. The main intention of having a returnprocess is to handle returned products efficiently in order to recover value and to savecosts. Therefore, it is a value-adding operation and can become profitable for thecompany.The purpose of this study is to investigate the implementation and perception of thereturn process of Swedish e-retailers. Sweden is considered to be one of the mostmatured e-commerce markets. In addition, e-retailers experience the highest rate ofproduct returns. Together those two factors influenced the decision to dedicate thisthesis to this particular region and industry.Initially, this paper introduces reverse logistics focusing specifically on the productreturn process. An overview of the existing theories and concepts within the returnprocess is presented and summarized, resulting in the creation of the Boomerang ReturnModel. Based on this foundation the questionnaire was created. By cooperating with theSwedish e-retail federation - Svensk Distanshandel, access to the industry was gained toperform a quantitative study.It was found that the empirical data only gives insight into the implementation andperception of the return process of small sized companies. The findings demonstrate thelimited awareness of the importance of an efficient return process. Companies tend toperceive the return process as unimportant instead of value adding. Hence, there is anopportunity for improvements in the Swedish e-retail market. From these findings amodified version of the Boomerang Return Model was created to adjust the initialmodel particularly for small sized companies. The model can be utilized as a theoreticalgroundwork in future research. Additionally, it could also serve as guidance for smallcompanies how to implement an appropriate return process.</p>

Product return is a necessary part of the exchange process between companies and customers. It accounts for approximately 16% of total sales and a reduction in retailer / manufacturer profits by 3.8% on average. However, industry data also indicates that a significant portion of products are returned for reasons other than product failure – e.g., change of mind, found a lower price elsewhere, or fraudulent and unethical reasons. Consequently, many firms (e.g., REI) have altered their generous return policies to protect their profits. However, it’s been found that the restricted return policy could also reduce customer satisfaction, increase the perceived risk, and thus negatively affect customers’ loyalty towards a particular store or firm. Thus having a restrictive return policy does not help either. Extant literature mainly focuses on return policies. Little attention has been devoted to the product return behavior itself, thus missing the consumer’s perspective. This study, therefore, focuses on understanding consumers’ return behaviors, including different types of return behaviors, and the drivers and consequences of these different return behaviors. Towards this goal, this study first categorizes all possible types of consumers’ return behaviors into two broad categories - legitimate return behaviors and opportunistic return behaviors. Second, both internal (i.e., variety seeking, impulsiveness, perceived uniqueness, materialism, level of morality, and self-monitoring) and external drivers (i.e., product compatibility, returning cost, perceived risk, complexity of procedure, and social group influence) of consumers’ product return behaviors are identified. Third, the relationship between these drivers of return behavior and the type of return behavior are examined. Finally, the influence of these two different types of return behaviors on consumer’s re-patronage intention is examined. This study uses a survey method to collect data in two phases - pilot phase and main study. In the pilot phase, data were collected from students and used to assess the factor structure, reliability and validity. In the main study, data were collected from both students (N=367) and non-students using M-Turk (N=395). The psychometric properties of the scale items were once again assessed using covariance based Confirmatory Factor Analysis procedure. Finally, multivariate regression was used to test the hypothesized relationships between the drivers of return behavior, types of return behavior, and the re-patronage intention. The findings indicate that product compatibility and desire for uniqueness negatively influence legitimate return behavior; whereas impulsiveness, perceived risk and social group have a positive influence. For opportunistic return behavior, social group and immorality positively influence both legitimate and opportunistic return behavior. However, other drivers have no influence on consumers’ return behavior. Finally, legitimate return behavior positively influences consumer’s re-patronage intention, while opportunistic return behavior has a negative influence. This study makes two major contributions. First, it contributes to the theoretical understanding of complex return behavior, including legitimate return and opportunistic return behavior, and thus adds depth to the literature of product returns. Second, by identifying the drivers of product return behaviors such as product compatibility, perceived risk of keeping the product, social group influence, and immorality, this study offers managers knowledge that will help reduce product returns, thus increasing their profits.