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Coordination of a fashion and textile supply chain with demand variations

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Abstract

Owing to the changing fashion trends and a volatile market situation, demand in fashion and textile (FT) industry is unpredictable and could vary and change completely in a short time, which makes it more difficult to coordinate a FT supply chain. A change in product preference due to fashion trends is the main reason why the demand of FT industry shows more variations than other industries. In this paper, we use a well known contract, the all-unit quantity discount policy (AQDP), to coordinate a FT supply chain with certain demand, and we further consider it under the demand variations scenario to investigate whether it can still coordinate the supply chain. In detail, before the selling season, an AQDP is provided by the manufacturer to the retailer, and under which the FT supply chain coordination achieved with a certain demand. During the selling season, demand variation is realized after an abrupt changing of fashion trends, therefore, the manufacturer may need to revise the original AQDP to insure the supply chain is still coordinated. Utilizing the mechanism design theory, we prove that: (i) while the traditional AQDP can coordinate the supply chain when no demand variations, it cannot always coordinate the supply chain after the demand variations; (ii) when the AQDP fails, we can use the proposed capacitated linear pricing policy (CLPP) to achieve a new coordination; (iii) a more dominant decision maker, who can set a higher profit goal, is favorable to stabilization of the supply chain system under demand variations. Numerical examples are proposed also to show our results.

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Correspondence to Ke Wang.

Additional information

This work was supported by the National Natural Science Foundation of China (Grant Nos. 70901068, 71271198), the Funds for International Cooperation and Exchange of the National Natural Science Foundation of China (Grant No. 71110107024) and Chinese Universities Scientific Fund. Qinglong Gou would also like to acknowledge the Science Fund for Creative Research Groups of the National Natural Science Foundation of China (Grant No. 71121061) for supporting his research.

Ke Wang is a Ph.D student in the School of Management at University of Science and Technology of China (USTC), Hefei, China. He received his Bachelor’s degree in Business and Administration from the University of Electronic Science and Technology of China, Chengdu, China, in 2010. Currently, he is working toward Ph.D degree (master-doctorate program) in Management Science and Engineering from the University of Science and Technology of China (USTC). His research interests include supply chain management, behavior operation management and supply chain contract management.

Qinglong Gou is an associate professor in the School of Management at USTC. He received his BS in Economics, MS and PhD in Management Science and Engineering from USTC in 2000, 2003, 2007, respectively. His research interests are mainly in the interface between marketing and operations management. He has published articles in Omega, Int. J. Production Economics, Int. J. Information Technology and Decision Making and other journals.

Jinwen Sun is a master student in the school of Management at USTC, Hefei, China. She received her Bachelor’s degree in Management Science from Anhui University of Finance & Economics, Bengbu, China, in 2009. Currently, she is working toward master degree in Logistics Engineering from the USTC. Her research interests are mainly in supply chain risk management and supply chain contract management.

Xiaohang Yue is an Associate Professor of Operations Management at the University of Wisconsin, Milwaukee. He receives his PhD in Operations Management from the University of Texas at Dallas, USA. His research interests are mainly in supply chain management and supply chain risk management. He has published articles in POMS, EJOR, Omega, Int. J. Production Economics and other high quality journals.

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Wang, K., Gou, Q., Sun, J. et al. Coordination of a fashion and textile supply chain with demand variations. J. Syst. Sci. Syst. Eng. 21, 461–479 (2012). https://doi.org/10.1007/s11518-012-5205-2

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