Twenty. A Bayesian Framework for Supply Chain Risk Management Using Business Process Standards

  1. Panos Kouvelis8,
  2. Lingxiu Dong8,
  3. Onur Boyabatli9 and
  4. Rong Li9
  1. Changhe Yuan1,
  2. Feng Cheng2,
  3. Henry Dao3,
  4. Markus Ettl4,
  5. Grace Lin5,6 and
  6. Karthik Sourirajan7

Published Online: 11 OCT 2011

DOI: 10.1002/9781118115800.ch20

The Handbook of Integrated Risk Management in Global Supply Chains

The Handbook of Integrated Risk Management in Global Supply Chains

How to Cite

Yuan, C., Cheng, F., Dao, H., Ettl, M., Lin, G. and Sourirajan, K. (2011) A Bayesian Framework for Supply Chain Risk Management Using Business Process Standards, 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.ch20

Editor Information

  1. 8

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

  2. 9

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

Author Information

  1. 1

    Department of Computer Science and Engineering, Mississippi State University, Mississippi State, Mississippi, USA

  2. 2

    Federal Aviation Administration, Washington, DC, USA

  3. 3

    IBM Global Business Services, Waltham, Massachusetts, USA

  4. 4

    IBM T.J. Watson Research Center, Yorktown Heights, New York, USA

  5. 5

    Department of IEOR, Columbia University, New York, New York, USA

  6. 6

    Green Value Net, Inc., Chappaqua, New York, USA

  7. 7

    ZS Associates, Chicago, Illinois, USA

Publication History

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

ISBN Information

Print ISBN: 9780470535127

Online ISBN: 9781118115800

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Keywords:

  • Bayesian framework;
  • business process standards;
  • supply chain risk management (SCRM)

Summary

This chapter describes a framework and methodology for supply chain risk analysis that uses Bayesian graphical models to identify, quantify, mitigate, and respond to the risks affecting a company’s global supply chain. It illustrates the methodology using a comprehensive case study based on global logistics process performance data. The chapter addresses the process gap and methodology gap by exploring a two-dimensional supply chain risk management (SCRM) framework, which utilizes the Bayesian approach and the Supply Chain Operations Reference Model (SCOR) model as the modeling and analysis methodologies. It develops a framework for developing an end-to-end risk model for a supply chain by utilizing multiple information sources, including business process standards, heterogeneous operational data, and expert knowledge based on the risk categorization framework.

Controlled Vocabulary Terms

Business process modeling; Risk management; Supply chain