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Quick Response Fashion Supply Chains in the Big Data Era

In: Optimization and Control for Systems in the Big-Data Era

Author

Listed:
  • Tsan-Ming Choi

    (The Hong Kong Polytechnic University)

Abstract

The quick response strategy has been widely adopted in the fashion industry. With a shortened lead time, quick response allows fashion supply chain members to conduct forecast information updating which helps to reduce demand uncertainty. In the big data era, forecast information updating is even more effective as more data points can be collected easily to improve forecasting. In this paper, after reviewing the related literature, we explore how the quick response strategy with n observations can improve the whole fashion supply chain’s performance. We study how the number of observations affects the expected values of quick response for the fashion supply chain, the fashion retailer, and the fashion manufacturer. Then, we analytically how the robust win–win coordination can be achieved in the quick response fashion supply chain using the commonly seen wholesale pricing markdown contract. Insights are generated.

Suggested Citation

  • Tsan-Ming Choi, 2017. "Quick Response Fashion Supply Chains in the Big Data Era," International Series in Operations Research & Management Science, in: Tsan-Ming Choi & Jianjun Gao & James H. Lambert & Chi-Kong Ng & Jun Wang (ed.), Optimization and Control for Systems in the Big-Data Era, chapter 0, pages 253-267, Springer.
    • Handle: RePEc:spr:isochp:978-3-319-53518-0_14
    DOI: 10.1007/978-3-319-53518-0_14
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    Cited by:

    1. Yanping Cheng & Yunjuan Kuang & Xiutian Shi & Ciwei Dong, 2018. "Sustainable Investment in a Supply Chain in the Big Data Era: An Information Updating Approach," Sustainability, MDPI, vol. 10(2), pages 1-18, February.
    2. Shaojian Qu & Yongyi Zhou, 2017. "A Study of The Effect of Demand Uncertainty for Low-Carbon Products Using a Newsvendor Model," IJERPH, MDPI, vol. 14(11), pages 1-24, October.
    3. Shen, Bin & Choi, Tsan-Ming & Chan, Hau-Ling, 2019. "Selling green first or not? A Bayesian analysis with service levels and environmental impact considerations in the Big Data Era," Technological Forecasting and Social Change, Elsevier, vol. 144(C), pages 412-420.

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