Five. Beyond Risk: Ambiguity in Supply Chains

  1. Panos Kouvelis3,
  2. Lingxiu Dong3,
  3. Onur Boyabatli4 and
  4. Rong Li4
  1. Karthik Natarajan1,
  2. Melvyn Sim2 and
  3. Chung-Piaw Teo2

Published Online: 11 OCT 2011

DOI: 10.1002/9781118115800.ch5

The Handbook of Integrated Risk Management in Global Supply Chains

The Handbook of Integrated Risk Management in Global Supply Chains

How to Cite

Natarajan, K., Sim, M. and Teo, C.-P. (2011) Beyond Risk: Ambiguity in Supply Chains, in The Handbook of Integrated Risk Management in Global Supply Chains (eds P. Kouvelis, L. Dong, O. Boyabatli and R. Li), John Wiley & Sons, Inc., Hoboken, NJ, USA. doi: 10.1002/9781118115800.ch5

Editor Information

  1. 3

    Olin Business School, Washington University, St. Louis, Missouri, USA

  2. 4

    Lee Kong Chian School of Business, Singapore Management University, Singapore

Author Information

  1. 1

    Department of Management Sciences, College of Business, City University of Hong Kong, Kowloon, Hong Kong

  2. 2

    Department of Decision Sciences, NUS Business School, National University of Singapore, Singapore

Publication History

  1. Published Online: 11 OCT 2011
  2. Published Print: 4 NOV 2011

ISBN Information

Print ISBN: 9780470535127

Online ISBN: 9781118115800



  • ambiguity;
  • finance;
  • maximin expected utility (MEU) theory;
  • risk;
  • single period newsvendor;
  • supply chain


This chapter reviews the notion of ambiguity arising from economics and finance and link it to the supply chain context. One of the popular approaches to account for aversion to ambiguity is the maximin expected utility (MEU) theory developed by Gilboa and Schmeidler. The chapter also reviews implications of this theory in a single period newsvendor setting. The newsvendor problem forms the foundation of many operations management models where a manager needs to decide on the order quantity before knowing the true demand. The chapter revisits a model proposed by Scarf that accounts for imperfect demand distribution information and discusses extensions of this model. It focuses on a supply chain inventory positioning problem that integrates the newsvendor model with a transportation model.

Controlled Vocabulary Terms

Production and operations management; supply chain