Focusing on retail supply chain management, this comprehensive reference explores emerging research issues and optimization problems. It presents various models, including retail-led and consumer utility-driven fashion supply chain optimization, while also addressing systems with information updating. Additionally, the book highlights future research directions, making it a valuable resource for understanding the complexities of fashion retail supply chains.
Risk analysis is crucial in stochastic supply chain models. 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.
Theory and Applications
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.
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.