As legislations have become stricter and the competition on markets is getting stronger, companies facing return flows strive for the implementation of efficient and cost-effective reverse logistic procedures. At the same time, when managing reverse logistics, they are not only confronted with a high degree of uncertainties concerning the quality, quantity and timing or the product returns, but also with a dynamically changing environment. Various aspects, such the increasing amount of return flows, shorter repair and lead times as well as increasing disposal costs, affect the reverse logistic system and need to be managed proficiently. Additionally, handling product returns requires supportive computer aided modelling tools that are capable of handling the dynamic and complex characteristics of the reverse logistic system and allow an improved estimation of the impact of a changing environment and management decisions. For the purpose of this study, the system dynamics modelling approach has been identified as particularly suitable for illustrating the system in question with a special focus on understanding the dynamic behaviour over time. A generic system dynamics model has been exemplarily created and simulated using the program iThink. The model comprises end-to-end processes of the main reverse logistic activities related to customer returns and has been used for studying the strategic design and optimization of the reverse logistic system. In order to consider relevant uncertainties as well as environmental concerns and economic efficiency, representative policies have been applied where, inter alia, with the help of the graphical illustration of the processes, effective strategies could be implemented. A general evaluation of the system dynamics methodology has revealed the significant advantages of using supportive modelling techniques for strategic decision making. Particularly for complex systems that change over time, such as reverse logistics, applying appropriate computer aided modelling tools in order to anticipate the overall effect on processes caused by varying surroundings has proven essential. An effective utilization of system dynamics may significantly reduce the forecasting and planning risks within individual frameworks, such as capacity planning. Moreover, the generic approach allows the application of the model to any other industry that is characterized by uncertain capacity utilization and varying technical, economical and legal conditions.

The global supply chain expanded significantly in the last decades of the 20th century, especially in the automobile, food, and textile industries. This growth of the globalized business era brings both challenges and motivation for researchers and practitioners with interests in logistics and supply chain management. Logistics and Supply Chain Management in the Globalized Business Era provides an introduction as well as up-to-date information in the logistics and supply chain management fields. The book focuses on applying theory to practices and provides both quantitative and qualitative methods for decision makers; additionally, it details current information regarding digitalization, information technology, and optimization techniques. It is ideal for supply chain managers, executives, operations managers, business owners, suppliers, researchers, postgraduate students, laypersons, researchers, and professionals.

Inhaltsangabe:Introduction: As the world population is growing continuously and emerging markets are expanding, natural recourses are being used even more intensively. Because of the scarcity of natural resources, industry faces a changing business environment. Due to government regulations, companies nowadays must handle not only in terms of efficiency, but also of sustainable development and new market opportunities. Thus, with the progression of the logistics sector in recent years, supply chain management and especially the concept of reverse logistics have become more important for both, industry and science. By utilizing reverse logistics, companies aim at maximizing their product revenue while reducing the costs of product returns. Accordingly, implementing an effective concept of reverse logistics, while manufacturing environmentally friendly products, has become a strategic issue. In order to meet the requirements, companies are confronted with the problem of reducing the uncertainties regarding the quality, quantity and timing of the product returns. In this context, a high level of uncertainty leads to a strong increase in complexity compared to the traditional forward supply chains. Using modern computer aided modelling techniques such as system dynamics, helps to counteract this complexity since they not only enable a better understanding of the dynamic behaviour of such complex systems but also allow an improved estimation of the impact of a changing environment and management decisions. This thesis contributes towards an improvement of the strategic decision making process in the field of reverse logistics by providing a generic simulation model which can be used to analyse the influence of different environmental and economical policies with respect to prevailing market conditions. To achieve this objective, the following approach is proposed: In Chapter 2, the theoretical foundation of reverse logistics is characterized forming the framework for the subsequent analytical approach concerning the appropriate model development. For this purpose, first, an overview of the state of the art concerning the processes and influencing factors within the field of reverse logistics is provided. This is achieved by describing the theoretical background of the topic, including a characterization of the impact of individual reverse logistic activities on each other and on their environment. Afterwards, current challenges and trends when [...]

Circular Economy Supply Chains highlights the need for cross-industry flows and the need for different actors in circular value cycles. This book intends to move beyond a buyer-supplier view, embracing a holistic network or ecosystem view, to consider a cross-industry system perspective.

This book addresses decision making in reverse logistics, which concerns the integration of used and obsolete products back into the supply chain as valuable resources. It covers a wide range of aspects, related to distribution, production and inventory management, and supply chain management. For each topic, it highlights key managerial issues in real-life examples and explains which quantitative models are available for addressing them. By treating a broad range of issues in a unified way, the book offers the reader a comprehensive view on the field of reverse logistics.

Chapter 1 examines the relationships between absorptive capacity and effective knowledge management through the analysis of quantitative data drawn from managers and employees in residential aged care organizations in Western Australia. Chapter 2 provides an application of system dynamics modelling in firms in the poultry industry in Bangladesh.

Quality Management in Reverse Logistics intends to develop, collect, examine and evaluate a number of quality management (QM) tools and techniques, which can be applied in practice in order to understand, review and improve any closed-loop supply chain process. In other words, the book aims to examine the existing relationship between various well-developed and thoroughly studied quality issues, such as QM, quality assurance, standardization of processes and statistical quality control and the emerging research area of reverse logistics. Quality Management in Reverse Logistics contains modeling and quantitative methods that could be used by practitioners and academics in the reverse logistics industry, as well as a thorough description of QM tools and techniques. The book leads the potential reader to broaden their scope of thinking and acting in the new, promising area of reverse logistics, where QM can be applied.