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Effects of higher order moments on the newsvendor problem

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  • Sun, Qi
  • Dong, Yucheng
  • Xu, Weidong

Abstract

In this paper, we propose a stochastic programming model for the well-known single-period newsvendor problem by adopting the conditional Value-at-Risk (CVaR) as the risk metric in the objective function. The demand uncertainty is modeled in terms of discrete scenarios that reflect the empirical distributions implied by market demand data. Our numerical results demonstrate that the higher order moments (skewness and kurtosis) of demand have obvious effects on the newsvendor problem, and the stochastic programming framework provides a flexible and effective decision support tool for the newsvendor problem.

Suggested Citation

  • Sun, Qi & Dong, Yucheng & Xu, Weidong, 2013. "Effects of higher order moments on the newsvendor problem," International Journal of Production Economics, Elsevier, vol. 146(1), pages 167-177.
    • Handle: RePEc:eee:proeco:v:146:y:2013:i:1:p:167-177
    DOI: 10.1016/j.ijpe.2013.06.019
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    Cited by:

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    2. Xin-Sheng Xu & Felix T. S. Chan, 2019. "Optimal Option Purchasing Decisions for the Risk-Averse Retailer with Shortage Cost," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 36(02), pages 1-25, April.
    3. Raza, Syed Asif & Rathinam, Sivakumar, 2017. "A risk tolerance analysis for a joint price differentiation and inventory decisions problem with demand leakage effect," International Journal of Production Economics, Elsevier, vol. 183(PA), pages 129-145.
    4. Xinsheng, Xu & Zhiqing, Meng & Rui, Shen & Min, Jiang & Ping, Ji, 2015. "Optimal decisions for the loss-averse newsvendor problem under CVaR," International Journal of Production Economics, Elsevier, vol. 164(C), pages 146-159.

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