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The value of information on supply risk under random yields

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  • Cheong, Taesu
  • Song, Sang Hwa

Abstract

For companies facing challenge of managing unreliable supply sources, one of the operational goals is to increase the overall profit by improving performance of uncertain supply. We here develop stochastic decision frameworks which evaluate necessary information about uncertainties and help newsvendor and suppliers to enhance supply reliability. We first analyze the newsvendor’s purchasing decision under supply uncertainty and the derived decision framework is used to identify stochastic dominance conditions. We found that partial supply risk information is sufficient to determine regular ordering quantity, but to improve the overall profit, it is important to gather more information about stochastic dominance conditions.

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  • Cheong, Taesu & Song, Sang Hwa, 2013. "The value of information on supply risk under random yields," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 60(C), pages 27-38.
    • Handle: RePEc:eee:transe:v:60:y:2013:i:c:p:27-38
    DOI: 10.1016/j.tre.2013.09.006
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    1. Ju, Wanrong & Gabor, Adriana F. & van Ommeren, J.C.W., 2015. "An approximate policy for a dual-sourcing inventory model with positive lead times and binomial yield," European Journal of Operational Research, Elsevier, vol. 244(2), pages 490-497.
    2. Xue, Weili & Choi, Tsan-Ming & Ma, Lijun, 2016. "Diversification strategy with random yield suppliers for a mean–variance risk-sensitive manufacturer," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 90(C), pages 90-107.
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    4. Zhang, Baofeng & Wu, Desheng Dash & Liang, Liang, 2018. "Trade credit model with customer balking and asymmetric market information," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 110(C), pages 31-46.
    5. Huang, Yanting & Wang, Zongjun, 2017. "Values of information sharing: A comparison of supplier-remanufacturing and manufacturer-remanufacturing scenarios," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 106(C), pages 20-44.

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