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A Bayesian Learning Approach for Making Procurement Policies Under Price Uncertainty

In: The 19th International Conference on Industrial Engineering and Engineering Management

Author

Listed:
  • Zhi-xue Xie

    (Tsinghua University)

  • Li Zheng

    (Tsinghua University)

Abstract

In this paper we consider a procurement problem under purchase price uncertainty, which is the case encountered by companies who purchase from spot markets with fluctuating prices. We develop a procurement model by introducing the dynamics of information revelation via Bayesian learning, derive its optimal solution and identify some thresholds to improve purchase timing decisions. Using historical spot price data of crudes oils, we verify the effectiveness of proposed policies compared to the current policy of Chinese oil refineries, and find the Bayesian learning model does perform well—billions of dollars could be saved over the past several years.

Suggested Citation

  • Zhi-xue Xie & Li Zheng, 2013. "A Bayesian Learning Approach for Making Procurement Policies Under Price Uncertainty," Springer Books, in: Ershi Qi & Jiang Shen & Runliang Dou (ed.), The 19th International Conference on Industrial Engineering and Engineering Management, edition 127, chapter 0, pages 1-10, Springer.
    • Handle: RePEc:spr:sprchp:978-3-642-38391-5_1
    DOI: 10.1007/978-3-642-38391-5_1
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