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A portfolio approach to managing procurement risk using multi-stage stochastic programming

Author

Listed:
  • Y Shi

    (1] South China University of Technology, Guangzhou, PR China[2] The University of Hong Kong, Hong Kong SAR, PR China)

  • F Wu

    (Xi'an Jiaotong University, Xi'an, PR China)

  • L K Chu

    (The University of Hong Kong, Hong Kong SAR, PR China)

  • D Sculli

    (The University of Hong Kong, Hong Kong SAR, PR China)

  • Y H Xu

    (The University of Hong Kong, Hong Kong SAR, PR China)

Abstract

Procurement is a critical supply chain management function that is susceptible to risk, due mainly to uncertain customer demand and purchase price volatility. A procurement approach in the form of a portfolio that incorporates the common procurement means is proposed. Such means include long-term contracts, spot procurements and option-based supply contracts. The objective is to explore possible synergies among the various procurement means, and so be able to produce optimal or near optimal results in profit while mitigating risk. The implementation of the portfolio approach is based on a multi-stage stochastic programming model in which replenishment decisions are made at various stages along a time horizon, with replenishment quantities being determined by simultaneously considering the stochastic demand and the price volatility of the spot market. The model attempts to minimise the risk exposure of procurement decisions measured as conditional value-at-risk. Numerical experiments to test the effectiveness of the proposed model are performed using demand data from a large air conditioner manufacturer in China and price volatility data from the Shanghai steel market. The results indicate that the proposed model can fairly reliably outperform other approaches, especially when either the demand and/or prices exhibit significant variability.

Suggested Citation

  • Y Shi & F Wu & L K Chu & D Sculli & Y H Xu, 2011. "A portfolio approach to managing procurement risk using multi-stage stochastic programming," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(11), pages 1958-1970, November.
  • Handle: RePEc:pal:jorsoc:v:62:y:2011:i:11:p:1958-1970
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    Cited by:

    1. Xu, Xinsheng & Ji, Ping & Chan, Felix T.S., 2022. "On maximizing a loss-averse buyer’s expected utility in a multi-sourcing problem," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 202(C), pages 388-404.
    2. William W. Wilson & Jesse Klebe, 2021. "Commodity procurement as contingent claims: Capturing risk and real options in flour milling," Agribusiness, John Wiley & Sons, Ltd., vol. 37(2), pages 348-370, April.
    3. Silva, Rodolfo Rodrigues Barrionuevo & Martins, André Christóvão Pio & Soler, Edilaine Martins & Baptista, Edméa Cássia & Balbo, Antonio Roberto & Nepomuceno, Leonardo, 2022. "Two-stage stochastic energy procurement model for a large consumer in hydrothermal systems," Energy Economics, Elsevier, vol. 107(C).
    4. Huo, Baofeng & Gu, Minhao & Jiang, Bin, 2018. "China-related POM research: Literature review and suggestions for future research," International Journal of Production Economics, Elsevier, vol. 203(C), pages 134-153.

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