IEEE Transactions on
Special Issue: Impacts of Technology Management on the Apparel Retailing and Manufacturing Industry in the Data Analytics Era
Prof. Tsan-Ming Choi (Jason), Hong Kong Polytechnic University,
Prof. Hing Kai Chan, University of Nottingham Ningbo China,
The apparel retailing and manufacturing industry has entered the data analytics era  with which productivity is much enhanced with the use of information technologies and business intelligence. Internet of Things (IoTs), cloud and services computing, mobile devices, big data analytics, virtual or augmented reality, and artificial intelligence are all common terminologies in real world business operations in apparel . For example, the sportswear brand Nike is known to use machine learning techniques to enhance its new product design, new service offering (e.g., the speedy customization) as well as demand forecasting . Louis Vuitton, a luxury fashion brand, is reported to use social media analytics in its revenue management. It also conducts real-time fashion show online . As the scope of the above techniques cover a wide range of knowledge, managing them well requires a multi-disciplinary mind-set . By the same token, it is uneasy to generalize some existing applications that are case-dependent. In this connection, there is a big room for further exploration.
Advanced manufacturing processes also improve and even change supply chain business models [11, 14]. Additive manufacturing, with the use of 3D Printing (3DP), is a typical example that has been receiving increased attention . Nike and Adidas are forerunners in employing this technology to speed up prototyping and manufacturing processes . 3DP is a disruptive and innovative technology in the digital manufacturing era . It can accelerate product development , reduce manufacturing lead time , reduce inventory related costs , provide mass customization ability , and so on. That being said, 3DP has not yet delivered its full potential and its applications in the industry is rather limited . It is worth investigating why such technological innovations (not just 3DP) require a long period of time to be put in place even if the technology is fairly mature, and why they are not fully integrated to the business operations. This is an interesting phenomenon for technology and engineering management researchers to reflect on. Without better knowledge, such effort on development would become a waste if the technology cannot be deployed successfully in the industry. Bluetooth is a classic example that had been waiting for long to become popular until successful applications could be identified. At some points the technology had been considered “dead” .
Blockchain technology is another popular topic that could be beneficial in the apparel industry by recording the transactions to improve traceability . In simple words, blockchain is a distributed ledger that recorded information which can be shared by a community securely . It is secure because each member of the community maintains his or her own copy of the information and all members must validate any new transactions collectively. Due to this capability, the technology can help avoid counterfeits in the fashion apparel industry . That being said, it is till premature to integrate the technology in fashion apparel supply chains. The situation is similar to the applications of 3DP mentioned above. Is it just another high profile hype?
To wrap up, the applications of all these technological advances are widely advocated and explored in manufacturing and services operations . However, relatively little is known about the proper management of these technologies in the fashion apparel industry, which covers upstream textiles supplies, clothing manufacturing, distribution, to downstream fashion retailing. Moreover, how much these state-of-the-art technologies would actually improve the whole fashion apparel supply chain’s productivity and capability , as well as whether individual fashion companies and workers are all benefitted  remain under-explored. Sometimes technologies are advancing much quicker than the pace that we can manage them. “Intellectual Property Rights” is a typical example that almost always lags behind the respective innovation. In this regard, there is a need to call for more theoretical and empirical studies in technology and engineering management. In addition, there are debates on “what’s next” after the current data analytics era has ended, and how technology should and would position itself for the fashion apparel industry at that time is an interesting topic to explore.
These motivate us to propose this special issue. As technology development goes in multiple dimensions , this special issue addresses the topic from multiple perspectives, including fashion apparel supply chain management, technology management, people, information systems management, and technology deployment, etc.
Some Relevant Topics
- Impacts of information technologies for fashion business operations.
- Additive manufacturing in clothing production.
- Blockchain technology for apparel supply chains.
- Values of technologies for improving fashion supply chain’s productivity and capability.
- Technology management in fashion operations with the use of business intelligence.
- Big data analytics for smart fashion business operations.
- Enhancing worker welfare in fashion business using technologies.
- Using information technology to improve fashion supply chain capability.
- Fashion supply chain risk management with the use of technology.
- Global fashion supply chain coordination with the use of technology.
- Artificial intelligence and its impacts on the fashion industry.
- Technology driven system of systems (SoS) engineering management for the fashion industry.
- Information systems project management for improving fashion supply chain operations.
- Fashion marketing and technology deployment.
Notes for Prospective Authors:
Submitted papers should not have been previously published nor be currently under consideration for publication elsewhere.
Conference papers may only be submitted if the paper has been completely re-written and if appropriate written permissions have been obtained from any copyright holders of the original paper.
Manuscripts should be submitted through the publisher’s online system. Submissions will be reviewed according to the journal’s rigorous standards and procedures through double-blind peer review by at least two qualified reviewers.
Please prepare the manuscript according to IEEE-TEM’s guidelines (http://ieee-tmc.org/tem-guidelines) and submit to the journal’s Manuscript Central site (https://mc.manuscriptcentral.com/tem-ieee). Please clearly state in the cover letter that the submission is for this special issue.
- Interested authors send abstracts by January 31st, 2020
- Decisions on acceptance of abstracts by March 30th, 2020
- Papers submitted by August 31st, 2020
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Guest Editor Bios
Tsan-Ming Choi (Jason), Ph.D., is currently Professor of Fashion Business at The Hong Kong Polytechnic University. His current research interests mainly focus on supply chain systems optimization, and he has published over 16 books and over 160 papers in Web of Science listed journals, which include IEEE Transactions on Engineering Management, Production and Operations Management, Decision Sciences, IEEE Transactions on Automatic Control, IEEE Transactions on Cybernetics, IEEE Transactions on Systems, Man and Cybernetics – Systems, Naval Research Logistics, etc. He is the incoming Co-Editor-in-Chief of Transportation Research – Part E (starting in 2019), a senior editor of Production and Operations Management, and Decision Support Systems, an associate editor of IEEE Transactions on Systems, Man, and Cybernetics – Systems, and Information Sciences, and an editorial board member of INFORMS Service Science, and International Journal of Production Research. Prof. Choi received The President’s Award for Excellent Achievements of The Hong Kong Polytechnic University in 2008, and the Best Associate Editor Award of IEEE Systems, Man, and Cybernetics Society in two consecutive years (2013 and 2014).
Hing Kai Chan, Ph.D., is a professor of operations management. Prior to joining the Nottingham University Business School China in September 2014, he was a Senior Lecturer in the Norwich Business School, University of East Anglia in UK. Dr Chan has published over 100 academic articles and (co-)edited several special issues for reputable international journals. His publications appear in various IEEE Transactions, Production and Operations Management, Decision Support Systems, European Journal of Operational Research, International Journal of Production Economics, International Journal of Production Research, among others. He is the co-editor of Industrial Management & Data Systems, and was an Associate Editor of IEEE Transactions on Industrial Electronics and IEEE Transactions on Industrial Informatics. Dr Chan also serves as an Editorial Board Member (or similar) in a number of journals such as Transportation Research Part E: Logistics and Transportation Review, and Online Information Review. Prof. Chan is a Fellow of the Institution of Engineering and Technology (FIET), and the Higher Education Academy (FHEA). He is also a Senior Member of the Institute of Electrical and Electronics Engineers.
IEEE Transactions on Engineering Management is journal of the Technology and Engineering Management Society of IEEE, published quarterly since 1954. It is dedicated to the publication of peer-reviewed original contributions, by researchers and practitioners, regarding the theory and practice of engineering, technology, and innovation management.
Editor in Chief
Tugrul U Daim, PhD PICMET Fellow
Professor and Director
Technology Management Doctoral Program
Department of Engineering and Technology Management
Maseeh College of Engineering and Computer Science
Portland State University, Portland OR