Information Systems for the Fashion and Apparel Industry
- 1st Edition - April 8, 2016
- Editor: Tsan-Ming Jason Choi
- Language: English
- Hardback ISBN:9 7 8 - 0 - 0 8 - 1 0 0 5 7 1 - 2
- eBook ISBN:9 7 8 - 0 - 0 8 - 1 0 0 5 8 0 - 4
Information Systems for the Fashion and Apparel Industry brings together trends and developments in fashion information systems, industrial case-studies, and insights from an i… Read more
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Request a sales quoteInformation Systems for the Fashion and Apparel Industry brings together trends and developments in fashion information systems, industrial case-studies, and insights from an international team of authors. The fashion and apparel industry is fast-growing and highly influential. Computerized information systems are essential to support fashion business operations and recent developments in social media, mobile commerce models, radio frequency identification (RFID) technologies, and ERP systems are all driving innovative business measures in the industry.
After an introductory chapter outlining key decision points and information requirements in fast fashion supply chains, Part One focuses on the principles of fashion information systems, with chapters covering how decision making in the apparel supply chains can be improved through the use of fuzzy logic, RFID technologies, evolutionary optimization techniques, and artificial neural networks. Part Two then reviews the range of applications for information systems in the fashion and apparel industry to improve customer choice, aid design, implement intelligent forecasting and procurement systems, and manage inventory and returns.
- Provides systematic and comprehensive coverage of information systems for the fashion and apparel industry
- Combines recent developments and industrial best-practices in apparel supply chain management in order to meet the needs of the fashion and apparel industry professionals and academics
- Features input from a team of highly knowledgeable authors with a range of professional and academic experience, overseen by an editor who is a leading expert in the field
- Reviews the range of applications for information systems in the fashion and apparel industry to improve customer choice, aid design, implement intelligent forecasting and procurement systems, and manage inventory and returns
Industry professionals, academic researchers and postgraduate students in fashion and apparel, as well as professionals and academics interested in information systems and supply chains
- The Textile Institute and Woodhead Publishing
- List of contributors
- Woodhead Publishing Series in Textiles
- Preface
- 1. Introduction: Key decision points and information requirements in fast fashion supply chains
- 1.1. Introduction
- 1.2. Key decision points
- 1.3. Information requirements
- 1.4. Concluding remarks
- 2. The use of fuzzy logic techniques to improve decision making in apparel supply chains
- 2.1. Introduction and background
- 2.2. Fuzzy logic techniques
- 2.3. The target market selection in apparel supply chain using fuzzy decision making
- 2.4. Conclusion
- 3. Using radiofrequency identification (RFID) technologies to improve decision-making in apparel supply chains
- 3.1. Introduction
- 3.2. Literature review
- 3.3. Case studies
- 3.4. Conclusions and future research directions
- 4. Using big data analytics to improve decision-making in apparel supply chains
- 4.1. Introduction
- 4.2. Literature review
- 4.3. Romanian clothing and fashion industry
- 4.4. Community-influenced decision-making: the answer is in the social cloud
- 4.5. Conclusions
- Appendix A: The evolution of the Romanian investments during 2008–2012
- Appendix B: The evolution of Romanian exports and imports
- Appendix C: The evolution of clothing sector exports during 2008–2012
- Appendix D: The strategy to promote the Romanian exports
- 5. Using artificial neural networks to improve decision making in apparel supply chain systems
- 5.1. Introduction
- 5.2. Decision process involved in the apparel supply chain
- 5.3. Applications of ANN in apparel supply chain to improve their decision
- 5.4. Conclusion and limitations of using ANNs in apparel supply chain systems
- 6. Smart systems for improved customer choice in fashion retail outlets
- 6.1. Context overview
- 6.2. Research parameter
- 6.3. Model proposition
- 6.4. Deploying smart systems compilation of customers' choice through modular customization model
- 6.5. Conclusion
- 7. Intelligent procurement systems to support fast fashion supply chains in the apparel industry
- 7.1. Introduction
- 7.2. Two-period models with reordering during the selling season
- 7.3. Multiple-order models with all orders placed before the selling season
- 7.4. Conclusion
- 8. Intelligent demand forecasting systems for fast fashion
- 8.1. Introduction
- 8.2. Fashion and fast fashion sales forecasting
- 8.3. Sales forecasting methods for fast fashion retailing
- 8.4. Intelligent system based on sales forecasting and replenishment modules
- 8.5. Conclusion
- 9. Fashion design using evolutionary algorithms and fuzzy set theory – a case to realize skirt design customizations
- 9.1. Introduction
- 9.2. Style classification and style feature database
- 9.3. Sketch design using fuzzy numbers and IGA
- 9.4. Intelligent pattern designs
- 9.5. Results and discussions
- 9.6. Conclusions and future research
- 10. Intelligent systems for managing returns in apparel supply chains
- 10.1. Introduction
- 10.2. Literature review
- 10.3. Critical factors of returns management in apparel supply chains
- 10.4. Quantity model for managing returns in apparel supply chains
- 10.5. Intelligent system implementation for managing returns in apparel supply chains
- 10.6. Conclusions and future direction
- 11. Vendor-managed inventory systems in the apparel industry
- 11.1. Introduction
- 11.2. Vendor-managed inventory research
- 11.3. Research design
- 11.4. Case data
- 11.5. Discussion
- 11.6. Conclusion and future research
- 12. Enterprise resource planning systems for use in apparel supply chains
- 12.1. Introduction
- 12.2. Enterprise resource planning systems in the apparel industry: review
- 12.3. Case studies
- 12.4. Conclusion
- 13. Intelligent demand forecasting supported risk management systems for fast fashion inventory management
- 13.1. Introduction and background
- 13.2. Demand forecasting supported inventory control
- 13.3. Inventory models with risk considerations
- 13.4. An intelligent fast fashion demand forecasting supported risk minimization inventory control model
- 13.5. Concluding remarks and future research
- Index
- No. of pages: 306
- Language: English
- Edition: 1
- Published: April 8, 2016
- Imprint: Woodhead Publishing
- Hardback ISBN: 9780081005712
- eBook ISBN: 9780081005804
TC
Tsan-Ming Jason Choi
Professor Tsan-Ming CHOI (Jason) is a management scientist, operations researcher and systems engineer. He is now Chair in Operations and Supply Chain Management, and Director of the Centre for Supply Chain Research at University of Liverpool Management School (ULMS). He has published extensively in leading journals in the fields of operations management, engineering management, logistics, and supply chain management. His recent research has been funded by many external funding bodies such as Research Grants Council (HK), University Grants Council (HK), M.O.E. (TW), and M.O.S.T. (TW). He is also serving the academic community as the Co-Editor-in-Chief of Transportation Research Part E: Logistics and Transportation Review, a Senior Editor of Production and Operations Management, and Decision Support Systems, a Department Editor of IEEE Transactions on Engineering Management, an Associate Editor of Decision Sciences, and IEEE TSMC-Systems, and an editorial board member of International Journal of Production Economics, International Journal of Production Research, and International Transactions in Operational Research. He is currently an external member of the engineering panel, Research Grants Council (HK) in which he helps handle reviews, give recommendations and monitor the progress of General Research Fund (GRF) proposals and funded projects. In two consecutive years under two different chief editors (2013 and 2014), he received the best associate editor awards of the IEEE SMC Society (USA). Over the past two decades, he served as an officer/exco member/secretary/treasurer of professional societies such as Production and Operations Management Society (HK), IEEE SMC Society (HK), and IEEE TEM Society (HK). Since 2020, he has been consistently ranked by p-ranking as a top 20 most productive researcher (in business and economics) in all related journal ranking lists in the world (including CABS). He is also listed as a Highly Cited Researcher by Clarivate (Web of Science) and a Top 2% scientist by Stanford University. Most recently, in February 2023, he received the JOM Ambassador Paper Award 2023 for his Journal of Operations Management paper on "green supply chain with quick response technology" published in 2020. Before joining ULMS, he taught at The Chinese University of Hong Kong (CUHK), The Hong Kong Polytechnic University (PolyU) and National Taiwan University (NTU), altogether for over two decades. In particular, he was honoured as a Yushan Fellow Professor at NTU, a President’s Award Winning Professor at PolyU, and a distinguished alumnus of CUHK's Faculty of Engineering.
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