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Weighted Almost Stochastic Dominance: Revealing the Preferences of Most Decision Makers in the St. Petersburg Paradox

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  • Chin Hon Tan

    (Department of Industrial and Systems Engineering, National University of Singapore, Singapore 117576)

Abstract

There are instances where “most” individuals prefer one prospect over another in practice, but such preferences are not revealed by conventional stochastic dominance rules. Almost stochastic dominance aims to reveal such preferences. However, almost stochastic dominance does not reveal the preferences observed in the St. Petersburg paradox. In this paper, we generalize the conditions of almost stochastic dominance by introducing a weighting function and illustrate how our proposed condition reveals the preferences of most individuals in the St. Petersburg paradox.

Suggested Citation

  • Chin Hon Tan, 2015. "Weighted Almost Stochastic Dominance: Revealing the Preferences of Most Decision Makers in the St. Petersburg Paradox," Decision Analysis, INFORMS, vol. 12(2), pages 74-80, June.
    • Handle: RePEc:inm:ordeca:v:12:y:2015:i:2:p:74-80
    DOI: 10.1287/deca.2014.0310
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    References listed on IDEAS

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    Cited by:

    1. Chin Hon Tan & Chunling Luo, 2017. "Clear Preferences Under Partial Distribution Information," Decision Analysis, INFORMS, vol. 14(1), pages 65-73, March.
    2. Zhao, Kena & Ng, Tsan Sheng & Tan, Chin Hon & Pang, Chee Khiang, 2021. "An almost robust model for minimizing disruption exposures in supply systems," European Journal of Operational Research, Elsevier, vol. 295(2), pages 547-559.

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