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Impacts of retailer’s risk averse behaviors on quick response fashion supply chain systems

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  • Tsan-Ming Choi

    (The Hong Kong Polytechnic University)

Abstract

Supply chain systems for fashion apparel products face a high level of risk as the market demand is very volatile and unpredictable. In order to cope with demand volatility, the quick response system which aims to shorten replenishment lead time has been well-established. With a shortened lead time, retailers can postpone the ordering decision and improve their demand forecast by gathering updated market information. However, there is a limit for quick response in which the market demand forecast is never fully accurate and uncertainty can never be fully eliminated. Thus, to keep the level of risk under control, retailers tend to possess a risk-averse behaviour in making their respective inventory decisions. In this paper, we explore the make-to-order quick response fashion supply chain with a risk averse retailer. We employ the mean-risk framework to incorporate the retailer’s risk averse behavior into the optimization model. With the focal point on uncovering the impacts brought by the retailer’s risk averse behavior to the quick response fashion supply chain system, we analytically derive important theoretical insights regarding the retailer’s optimal decisions, the implied inventory service levels, the values of quick response, and the contractual arrangements to attain Pareto improvement when the retailer is risk averse.

Suggested Citation

  • Tsan-Ming Choi, 2018. "Impacts of retailer’s risk averse behaviors on quick response fashion supply chain systems," Annals of Operations Research, Springer, vol. 268(1), pages 239-257, September.
    • Handle: RePEc:spr:annopr:v:268:y:2018:i:1:d:10.1007_s10479-016-2257-6
    DOI: 10.1007/s10479-016-2257-6
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    Cited by:

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    5. Avinadav, Tal & Chernonog, Tatyana & Ben-Zvi, Tal, 2019. "The effect of information superiority on a supply chain of virtual products," International Journal of Production Economics, Elsevier, vol. 216(C), pages 384-397.
    6. Rufeng Wang & Xiongwei Zhou & Bo Li, 2022. "Pricing strategy of dual-channel supply chain with a risk-averse retailer considering consumers’ channel preferences," Annals of Operations Research, Springer, vol. 309(1), pages 305-324, February.
    7. Choi, Tsan-Ming & Wen, Xin & Sun, Xuting & Chung, Sai-Ho, 2019. "The mean-variance approach for global supply chain risk analysis with air logistics in the blockchain technology era," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 127(C), pages 178-191.
    8. Adhikari, Arnab & Bisi, Arnab & Avittathur, Balram, 2020. "Coordination mechanism, risk sharing, and risk aversion in a five-level textile supply chain under demand and supply uncertainty," European Journal of Operational Research, Elsevier, vol. 282(1), pages 93-107.
    9. Xu, Jian & Duan, Yongrui, 2020. "Pricing, ordering, and quick response for online sellers in the presence of consumer disappointment aversion," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 137(C).

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