Supply chain management is a well-developed area. The traditional supply chains are dynamic systems which include the forward and reverse flows of physical products and the related information and fund. However, a service supply chain is different because the real "product" may take the form of a "service" which implies that many traditionally crucial decisions in supply chain management such as product shipping problems are no longer important. Here, a service supply chain is defined as a supply network that transfers resources into services or servitised products, with or without physical products, to satisfy customer needs. As a result, managing a service supply chain system requires innovative strategies with new models. Currently, there is an absence of a comprehensive reference source that provides the state-of-the-art findings on this important topic. It will thus be significant to develop a well-balanced edited volume that includes both theoretical results (from different perspectives) and application cases/studies on service supply chain systems. This book is a pioneering text on service supply chain systems. It features papers which adopt the systems engineering approach in conducting service supply chain analysis. It includes both theoretical results (from different perspectives) and application cases/studies on service supply chain systems. It will be a good reference book for industrialists and academics who are interested in the service industry, service operations, service management, and service sciences.

Fashion Retail Supply Chain Management: A Systems Optimization Approach is a comprehensive reference source that provides the state-of-the-art findings on many important emerging research issues related to retail supply chain management and optimization problems. The book takes an explicit systems approach, and discusses retailled fashion supply chain coordination mechanisms and consumer market informationdriven fashion retail supply chain models, as well as suggesting future research avenues. This volume will be of interest not only to those involved in the fashion industry, but also to academics and practitioners in the wider fields of business, manufacturing engineering, systems engineering and supply chain management.

Fast fashion is an industrial trend that refers to the concept of shortening lead time (production, distribution) and offering new products to the market as fast as possible. Despite an abundance of research results, there is no comprehensive reference source that covers the state-of-the-art findings on both theoretical modeling and empirical research on fast fashion systems. This edited volume consists of three sections - review and exploratory studies, analytical models, and empirical research - made up of many interesting contributions in the respective domain. The result is a well-balanced handbook which includes both theoretical results (from various perspectives) and empirical findings. This volume will be of interest not only to those involved in the fashion industry, but also to academics and practitioners in the wider fields of business, manufacturing engineering, systems engineering and supply chain management.

This book focuses on optimal control and systems engineering in the big data era. It examines the scientific innovations in optimization, control and resilience management that can be applied to further success. In both business operations and engineering applications, there are huge amounts of data that can overwhelm computing resources of large-scale systems. This "big data" provides new opportunities to improve decision making and addresses risk for individuals as well in organizations. While utilizing data smartly can enhance decision making, how to use and incorporate data into the decision making framework remains a challenging topic. Ultimately the chapters in this book present new models and frameworks to help overcome this obstacle. Optimization and Control for Systems in the Big-Data Era: Theory and Applications is divided into five parts. Part I offers reviews on optimization and control theories, and Part II examines the optimization and control applications. Part III provides novel insights and new findings in the area of financial optimization analysis. The chapters in Part IV deal with operations analysis, covering flow-shop operations and quick response systems. The book concludes with final remarks and a look to the future of big data related optimization and control problems.

Using various research methodologies, such as reviews, case studies, analytical modeling and empirical studies, this book investigates luxury fashion retail management and provides relevant insights, which are beneficial to both industrialists and academics. Readers gain an understanding of luxury fashion retailing, including proper operations and strategic management, which now are the most crucial items on the luxury fashion industry's senior management agenda.

This book focuses on optimal control and systems engineering in the big data era. It examines the scientific innovations in optimization, control and resilience management that can be applied to further success. In both business operations and engineering applications, there are huge amounts of data that can overwhelm computing resources of large-scale systems. This "big data" provides new opportunities to improve decision making and addresses risk for individuals as well in organizations. While utilizing data smartly can enhance decision making, how to use and incorporate data into the decision making framework remains a challenging topic. Ultimately the chapters in this book present new models and frameworks to help overcome this obstacle. Optimization and Control for Systems in the Big-Data Era: Theory and Applications is divided into five parts. Part I offers reviews on optimization and control theories, and Part II examines the optimization and control applications. Part III provides novel insights and new findings in the area of financial optimization analysis. The chapters in Part IV deal with operations analysis, covering flow-shop operations and quick response systems. The book concludes with final remarks and a look to the future of big data related optimization and control problems.

Using various research methodologies, such as reviews, case studies, analytical modeling and empirical studies, this book investigates luxury fashion retail management and provides relevant insights, which are beneficial to both industrialists and academics. Readers gain an understanding of luxury fashion retailing, including proper operations and strategic management, which now are the most crucial items on the luxury fashion industry's senior management agenda.

This handbook is a compilation of comprehensive reference sources that provide state-of-the-art findings on both theoretical and applied research on sustainable fashion supply chain management. It contains three parts, organized under the headings of "Reviews and Discussions," "Analytical Research," and "Empirical Research," featuring peer-reviewed papers contributed by researchers from Asia, Europe, and the US. This book is the first to focus on sustainable supply chain management in the fashion industry and is therefore a pioneering text on this topic. In the fashion industry, disposable fashion under the fast fashion concept has become a trend. In this trend, fashion supply chains must be highly responsive to market changes and able to produce fashion products in very small quantities to satisfy changing consumer needs. As a result, new styles will appear in the market within a very short time and fashion brands such as Zara can reduce the whole process cycle from conceptual design to a final ready-to-sell "well-produced and packaged" product on the retail sales floor within a few weeks. From the supply chain's perspective, the fast fashion concept helps to match supply and demand and lowers inventory. Moreover, since many fast fashion companies, e.g., Zara, H&M, and Topshop, adopt a local sourcing approach and obtain supply from local manufacturers (to cut lead time), the corresponding carbon footprint is much reduced. Thus, this local sourcing scheme under fast fashion would enhance the level of environmental friendliness compared with the more traditional offshore sourcing. Furthermore, since the fashion supply chain is notorious for generating high volumes of pollutants, involving hazardous materials in the production processes, and producing products by companies with low social responsibility, new management principles and theories, especially those that take into account consumer behaviours and preferences, need to be developed to address many of these issues in order to achieve the goal of sustainable fashion supply chain management. The topics covered include Reverse Logistics of US Carpet Recycling; Green Brand Strategies in the Fashion Industry; Impacts of Social Media on Consumers' Disposals of Apparel; Fashion Supply Chain Network Competition with Eco-labelling; Reverse Logistics as a Sustainable Supply Chain Practice for the Fashion Industry; Apparel Manufacturers' Path to World-class Corporate Social Responsibility; Sustainable Supply Chain Management in the Slow-Fashion Industry; Mass Market Second-hand Clothing Retail Operations in Hong Kong; Constraints and Drivers of Growth in the Ethical Fashion Sector: The case of France; and Effects of Used Garment Collection Programmes in Fast Fashion Brands.

Fashion Branding and Consumer Behaviors presents eye-opening theory, literature review and original research on the mutual influence of branding strategies and consumer response. Contributors use multiple methods to analyze consumers' psychosocial needs and the extent that their fulfillment goes beyond the usefulness or value of the items they purchase as well as the fashion industry's means of communicating brand identity and enhancing brand loyalty. Along the way, these studies raise important questions about consumer behaviors, consumer welfare, environmental ethics and the future of consumer research. Included in the coverage: A symbolic interactionist perspective on fashion brand personality and advertisement response. Optimizing fashion branding strategies in a fluctuating market. An analysis of fashion brand extensions by artificial neural networks. Domestic or foreign luxury brands? A comparison of status- and non-status- seeking teenagers. The impact of consumers' need for uniqueness on purchase perception. How brand awareness relates to market outcome, brand equity and the marketing mix. A breakthrough volume on the complexities of how and why we buy, Fashion Branding and Consumer Behaviors will captivate researchers and practitioners in the fields of consumer psychology, marketing and economics.

Forecasting is a crucial function for companies in the fashion industry, but for many real-life forecasting applications in the, the data patterns are notorious for being highly volatile and it is very difficult, if not impossible, to analytically learn about the underlying patterns. As a result, many traditional methods (such as pure statistical models) will fail to make a sound prediction. Over the past decade, advances in artificial intelligence and computing technologies have provided an alternative way of generating precise and accurate forecasting results for fashion businesses. Despite being an important and timely topic, there is currently an absence of a comprehensive reference source that provides up-to-date theoretical and applied research findings on the subject of intelligent fashion forecasting systems. This three-part handbook fulfills this need and covers materials ranging from introductory studies and technical reviews, theoretical modeling research, to intelligent fashion forecasting applications and analysis. This book is suitable for academic researchers, graduate students, senior undergraduate students and practitioners who are interested in the latest research on fashion forecasting.

The Economic Order Quantity (EOQ) inventory model first appeared in 1913, and in its centennial, it is still one of the most important inventory models. Despite the abundance of both classical and new research results, there was (until now) no comprehensive reference source that provides the state-of-the-art findings on both theoretical and applied research on the EOQ and its related models. This edited handbook puts together all these interesting works and the respective insights into an edited volume. The handbook contains papers which explore both the deterministic and the stochastic EOQ-model based problems and applications. It is organized into three parts: Part I presents three papers that provide an introduction and review of various EOQ related models. Part II includes four technical analyses on single-echelon EOQ-model based inventory problems. Part III consists of five papers on applications of the EOQ model for multi-echelon supply chain inventory analysis.

This handbook is a compilation of comprehensive reference sources that provide state-of-the-art findings on both theoretical and applied research on sustainable fashion supply chain management. It contains three parts, organized under the headings of "Reviews and Discussions," "Analytical Research," and "Empirical Research," featuring peer-reviewed papers contributed by researchers from Asia, Europe, and the US. This book is the first to focus on sustainable supply chain management in the fashion industry and is therefore a pioneering text on this topic. In the fashion industry, disposable fashion under the fast fashion concept has become a trend. In this trend, fashion supply chains must be highly responsive to market changes and able to produce fashion products in very small quantities to satisfy changing consumer needs. As a result, new styles will appear in the market within a very short time and fashion brands such as Zara can reduce the whole process cycle from conceptual design to a final ready-to-sell "well-produced and packaged" product on the retail sales floor within a few weeks. From the supply chain's perspective, the fast fashion concept helps to match supply and demand and lowers inventory. Moreover, since many fast fashion companies, e.g., Zara, H&M, and Topshop, adopt a local sourcing approach and obtain supply from local manufacturers (to cut lead time), the corresponding carbon footprint is much reduced. Thus, this local sourcing scheme under fast fashion would enhance the level of environmental friendliness compared with the more traditional offshore sourcing. Furthermore, since the fashion supply chain is notorious for generating high volumes of pollutants, involving hazardous materials in the production processes, and producing products by companies with low social responsibility, new management principles and theories, especially those that take into account consumer behaviours and preferences, need to be developed to address many of these issues in order to achieve the goal of sustainable fashion supply chain management. The topics covered include Reverse Logistics of US Carpet Recycling; Green Brand Strategies in the Fashion Industry; Impacts of Social Media on Consumers' Disposals of Apparel; Fashion Supply Chain Network Competition with Eco-labelling; Reverse Logistics as a Sustainable Supply Chain Practice for the Fashion Industry; Apparel Manufacturers' Path to World-class Corporate Social Responsibility; Sustainable Supply Chain Management in the Slow-Fashion Industry; Mass Market Second-hand Clothing Retail Operations in Hong Kong; Constraints and Drivers of Growth in the Ethical Fashion Sector: The case of France; and Effects of Used Garment Collection Programmes in Fast Fashion Brands.

Risk analysis is crucial in stochastic supply chain models. Over the past few years, the pace has quickened for research attempting to explore risk analysis issues in supply chain management problems, while the majority of recent papers focus on conceptual framework or computational numerical analysis. Pioneered by Nobel laureate Markowitz in the 1950s, the mean-risk (MR) formulation became a fundamental theory for risk management in finance. Despite the significance and popularity of MR-related approaches in finance, their applications in studying multi-echelon supply chain management problems have only been seriously explored in recent years. While the MR approach has already been shown to be useful in conducting risk analysis in stochastic supply chain models, there is no comprehensive reference source that provides the state-of-the-art findings on this important model for supply chain management. Thus it is significant to have a book that reviews and extends the MR related works for supply chain risk analysis. This book is organized into five chapters. Chapter 1 introduces the topic, offers a timely review of various related areas, and explains why the MR approach is important for conducting supply chain risk analysis. Chapter 2 examines the single period inventory model with the mean-variance and mean-semi-deviation approaches. Extensive discussions on the efficient frontiers are also reported. Chapter 3 explores the infinite horizon multi-period inventory model with a mean-variance approach. Chapter 4 investigates the supply chain coordination problem with a versatile target sales rebate contract and a risk averse retailer possessing the mean-variance optimization objective. Chapter 5 concludes the book and discusses various promising future research directions and extensions. Every chapter can be taken as a self-contained article, and the notation within each chapter is consistently employed.

As a fundamental problem in stochastic inventory control, the newsvendor problem has been studied since the 18th century in the economic literature, and has been widely used to analyze supply chains in fashion and seasonal product industries. Since the 1950s, the newsvendor problem has been extensively studied in operations research and extended to model a variety of real-life problems. The simplest and most elementary version of the newsvendor problem is an optimal stocking problem in which a newsvendor needs to decide how many newspapers to order for future demand, where the future demand is uncertain and follows a stationary distribution. Research in this area has greatly increased over the last few years, and now the Handbook of Newsvendor Problems: Models, Extensions and Applications captures the state of the art. The handbook consists of two sections -- Models and Extensions, and Applications. Each section includes many interesting works in the respective domain. Section I presents papers on topics like the multi-product newsvendor problems; the newsvendor problem with law invariant coherent measures of risk; a Copula approach to inventory pooling problems with newsvendor products; repeated newsvendor games with transshipments; cooperative newsvendor games; an economic interpretation for the price-setting newsvendor problem; newsvendor models with alternative risk preferences within expected utility theory and prospect theory frameworks; and newsvendor problems with VaR and CVaR consideration. Section II presents papers on such topics as a two-period newsvendor problem for closed-loop supply chain analysis; the remanufacturing newsvendor problem; inventory centralization in a newsvendor setting when shortage costs differ; production planning on an unreliable machine for multiple items; analysis of the newsvendor problem under carbon emissions policies; optimal decisions of the manufacturer and distributor in a fresh product supply chain involving long distance transportation; a newsvendor perspective on profit target setting for multiple divisions; and a portfolio approach to multi-product newsvendor problem with budget constraint. This well-balanced handbook presents a wealth of theoretical results from different perspectives. With contributions from many of the leading researchers in the field, the Handbook of Newsvendor Problems: Models, Extensions and Applications is a timely addition to the literature and consolidates all the new and exciting works related to the newsvendor problem into one high quality source.

Fashion Branding and Consumer Behaviors presents eye-opening theory, literature review and original research on the mutual influence of branding strategies and consumer response. Contributors use multiple methods to analyze consumers' psychosocial needs and the extent that their fulfillment goes beyond the usefulness or value of the items they purchase as well as the fashion industry's means of communicating brand identity and enhancing brand loyalty. Along the way, these studies raise important questions about consumer behaviors, consumer welfare, environmental ethics and the future of consumer research. Included in the coverage: * A symbolic interactionist perspective on fashion brand personality and advertisement response.* Optimizing fashion branding strategies in a fluctuating market.* An analysis of fashion brand extensions by artificial neural networks.* Domestic or foreign luxury brands? A comparison of status- and non-status- seeking teenagers.* The impact of consumers' need for uniqueness on purchase perception.* How brand awareness relates to market outcome, brand equity and the marketing mix.A breakthrough volume on the complexities of how and why we buy, Fashion Branding and Consumer Behaviors will captivate researchers and practitioners in the fields of consumer psychology, marketing and economics.

Forecasting is a crucial function for companies in the fashion industry, but for many real-life forecasting applications in the, the data patterns are notorious for being highly volatile and it is very difficult, if not impossible, to analytically learn about the underlying patterns. As a result, many traditional methods (such as pure statistical models) will fail to make a sound prediction. Over the past decade, advances in artificial intelligence and computing technologies have provided an alternative way of generating precise and accurate forecasting results for fashion businesses. Despite being an important and timely topic, there is currently an absence of a comprehensive reference source that provides up-to-date theoretical and applied research findings on the subject of intelligent fashion forecasting systems. This three-part handbook fulfills this need and covers materials ranging from introductory studies and technical reviews, theoretical modeling research, to intelligent fashion forecasting applications and analysis. This book is suitable for academic researchers, graduate students, senior undergraduate students and practitioners who are interested in the latest research on fashion forecasting.

Channel coordination is a core subject of supply chain management. Over the past decade, much research effort has been devoted to exploring the detailed mechanisms for achieving supply chain coordination under uncertainty, generating many fruitful analytical and empirical results. Despite the abundance of research results, there is an absence of a comprehensive reference source that provides state-of-the-art findings on both theoretical and applied research on the subject. In addition, with the advance of knowledge and technologies, many new topics on supply chain coordination under uncertainty have appeared in recent years. This handbook extensively examines supply chain coordination challenges with a focal point on discovering innovative measures that can help tackle the existing and emerging challenges. The book is organized into five parts, which include chapters on innovative analytical models for coordination, channel power and bargaining, technological advancements and applications, empirical analysis, cases studies and review. This handbook provides new empirical and analytical results with precious insights, which will not only help supply chain agents to understand more about the latest measures for supply chain coordination under uncertainty, but also help practitioners and researchers to know how to improve supply chain performance based on innovative methods.

The Economic Order Quantity (EOQ) inventory model first appeared in 1913, and in its centennial, it is still one of the most important inventory models. Despite the abundance of both classical and new research results, there was (until now) no comprehensive reference source that provides the state-of-the-art findings on both theoretical and applied research on the EOQ and its related models. This edited handbook puts together all these interesting works and the respective insights into an edited volume.

The handbook contains papers which explore both the deterministic and the stochastic EOQ-model based problems and applications. It is organized into three parts: Part I presents three papers that provide an introduction and review of the EOQ, a consideration of multi-period lot sizing with stationary demand, and EOQ models with supply disruptions. Part II includes four technical analyses on single-echelon EOQ- model based inventory problems. Part III consists of five papers on applications of the EOQ model for multi-echelon supply chain inventory analysis."

As a fundamental problem in stochastic inventory control, the newsvendor problem has been studied since the 18th century in the economic literature, and has been widely used to analyze supply chains in fashion and seasonal product industries. Since the 1950s, the newsvendor problem has been extensively studied in operations research and extended to model a variety of real-life problems. The simplest and most elementary version of the newsvendor problem is an optimal stocking problem in which a newsvendor needs to decide how many newspapers to order for future demand, where the future demand is uncertain and follows a stationary distribution. Research in this area has greatly increased over the last few years, and now the Handbook of Newsvendor Problems: Models, Extensions and Applications captures the state of the art. The handbook consists of two sections -- Models and Extensions, and Applications. Each section includes many interesting works in the respective domain. Section I presents papers on topics like the multi-product newsvendor problems; the newsvendor problem with law invariant coherent measures of risk; a Copula approach to inventory pooling problems with newsvendor products; repeated newsvendor games with transshipments; cooperative newsvendor games; an economic interpretation for the price-setting newsvendor problem; newsvendor models with alternative risk preferences within expected utility theory and prospect theory frameworks; and newsvendor problems with VaR and CVaR consideration. Section II presents papers on such topics as a two-period newsvendor problem for closed-loop supply chain analysis; the remanufacturing newsvendor problem; inventory centralization in a newsvendor setting when shortage costs differ; production planning on an unreliable machine for multiple items; analysis of the newsvendor problem under carbon emissions policies; optimal decisions of the manufacturer and distributor in a fresh product supply chain involving long distance transportation; a newsvendor perspective on profit target setting for multiple divisions; and a portfolio approach to multi-product newsvendor problem with budget constraint. This well-balanced handbook presents a wealth of theoretical results from different perspectives. With contributions from many of the leading researchers in the field, the Handbook of Newsvendor Problems: Models, Extensions and Applications is a timely addition to the literature and consolidates all the new and exciting works related to the newsvendor problem into one high quality source.

Risk analysis is crucial in stochastic supply chain models. Over the past few years, the pace has quickened for research attempting to explore risk analysis issues in supply chain management problems, while the majority of recent papers focus on conceptual framework or computational numerical analysis. Pioneered by Nobel laureate Markowitz in the 1950s, the mean-risk (MR) formulation became a fundamental theory for risk management in finance. Despite the significance and popularity of MR-related approaches in finance, their applications in studying multi-echelon supply chain management problems have only been seriously explored in recent years. While the MR approach has already been shown to be useful in conducting risk analysis in stochastic supply chain models, there is no comprehensive reference source that provides the state-of-the-art findings on this important model for supply chain management. Thus it is significant to have a book that reviews and extends the MR related works for supply chain risk analysis. This book is organized into five chapters. Chapter 1 introduces the topic, offers a timely review of various related areas, and explains why the MR approach is important for conducting supply chain risk analysis. Chapter 2 examines the single period inventory model with the mean-variance and mean-semi-deviation approaches. Extensive discussions on the efficient frontiers are also reported. Chapter 3 explores the infinite horizon multi-period inventory model with a mean-variance approach. Chapter 4 investigates the supply chain coordination problem with a versatile target sales rebate contract and a risk averse retailer possessing the mean-variance optimization objective. Chapter 5 concludes the book and discusses various promising future research directions and extensions. Every chapter can be taken as a self-contained article, and the notation within each chapter is consistently employed.

Quick Response (QR) policy is a market-driven business strategy in which supply chain members work together to react quickly to volatile market demand. Nowadays, with advances in information technologies (such as RFID and ERP systems), new challenges and opportunities arise for the application of QR. This handbook explores QR extensively with a view to discovering innovative QR measures that can help tackle the observed and emerging challenges. The book is organized into four parts, which include chapters on analytical modeling and analyses, information technologies, cases, reviews, and applications. This handbook provides new analytical and empirical results with valuable insights, which will not only help supply chain agents to better understand the latest applications of QR in business, but also help practitioners and researchers to know how to improve the effectiveness of QR using innovative methods.

Channel coordination is a core subject of supply chain management. Over the past decade, much research effort has been devoted to exploring the detailed mechanisms for achieving supply chain coordination under uncertainty, generating many fruitful analytical and empirical results. Despite the abundance of research results, there is an absence of a comprehensive reference source that provides state-of-the-art findings on both theoretical and applied research on the subject. In addition, with the advance of knowledge and technologies, many new topics on supply chain coordination under uncertainty have appeared in recent years. This handbook extensively examines supply chain coordination challenges with a focal point on discovering innovative measures that can help tackle the existing and emerging challenges. The book is organized into five parts, which include chapters on innovative analytical models for coordination, channel power and bargaining, technological advancements and applications, empirical analysis, cases studies and review. This handbook provides new empirical and analytical results with precious insights, which will not only help supply chain agents to understand more about the latest measures for supply chain coordination under uncertainty, but also help practitioners and researchers to know how to improve supply chain performance based on innovative methods.

Fashion Retail Supply Chain Management: A Systems Optimization Approach is a comprehensive reference source that provides the state-of-the-art findings on many important emerging research issues related to retail supply chain management and optimization problems. The book takes an explicit systems approach, and discusses retailled fashion supply chain coordination mechanisms and consumer market informationdriven fashion retail supply chain models, as well as suggesting future research avenues. This volume will be of interest not only to those involved in the fashion industry, but also to academics and practitioners in the wider fields of business, manufacturing engineering, systems engineering and supply chain management.

Quick Response (QR) policy is a market-driven business strategy in which supply chain members work together to react quickly to volatile market demand. Nowadays, with advances in information technologies (such as RFID and ERP systems), new challenges and opportunities arise for the application of QR. This handbook explores QR extensively with a view to discovering innovative QR measures that can help tackle the observed and emerging challenges. The book is organized into four parts, which include chapters on analytical modeling and analyses, information technologies, cases, reviews, and applications. This handbook provides new analytical and empirical results with valuable insights, which will not only help supply chain agents to better understand the latest applications of QR in business, but also help practitioners and researchers to know how to improve the effectiveness of QR using innovative methods.

Fashion Supply Chain Management (FSCM) is an important topic in the modern fashion industry. In addition to the traditional functions of logistics management in fashion companies, which include inventory management, transportation management, and facility control, FSCM places a strong emphasis on collaboration and partnership among channel members along the fashion supply chain. Obviously, FSCM provides a very strong area for establishing a competitive edge for fashion companies. Fashion Supply Chain Management: Industry and Business Analysis focuses on reporting both quantitative research on FSCM and exploratory studies on emerging supply chain management issues in the fashion industry. This reference will help both academicians and practitioners understand more about the latest development and solution schemes in FSCM, as it is a pioneering text which reports many important research results in quantitative FSCM.