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The stochastic ordering of mean-preserving transformations and its applications

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  • Zhu, Wanshan
  • Wu, Zhengping

Abstract

The stochastic variability measures the degree of uncertainty for random demand and/or price in various operations problems. Its ordering property under mean-preserving transformation allows us to study the impact of demand/price uncertainty on the optimal decisions and the associated objective values. Based on Chebyshev’s algebraic inequality, we provide a general framework for stochastic variability ordering under any mean-preserving transformation that can be parameterized by a single scalar, and apply it to a broad class of specific transformations, including the widely used mean-preserving affine transformation, truncation, and capping. The application to mean-preserving affine transformation rectifies an incorrect proof of an important result in the inventory literature, which has gone unnoticed for more than two decades. The application to mean-preserving truncation addresses inventory strategies in decentralized supply chains, and the application to mean-preserving capping sheds light on using option contracts for procurement risk management.

Suggested Citation

  • Zhu, Wanshan & Wu, Zhengping, 2014. "The stochastic ordering of mean-preserving transformations and its applications," European Journal of Operational Research, Elsevier, vol. 239(3), pages 802-809.
    • Handle: RePEc:eee:ejores:v:239:y:2014:i:3:p:802-809
    DOI: 10.1016/j.ejor.2014.06.017
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