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On Risk Management with Information Flows in Business Processes

Author

Listed:
  • Xue Bai

    (Department of Operations and Information Management, School of Business, University of Connecticut, Storrs Connecticut 06269)

  • Ramayya Krishnan

    (The H. John Heinz III College, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213)

  • Rema Padman

    (The H. John Heinz III College, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213)

  • Harry Jiannan Wang

    (Department of Accounting and Management Information Systems, Alfred Lerner College of Business and Economics, University of Delaware, Newark, Deleware 19716)

Abstract

This article investigates the economic consequences of data errors in the information flows associated with business processes. We develop a process modeling-based methodology for managing the risks associated with such data errors. Our method focuses on the topological structure of a process and takes into account its effect on error propagation and risk mitigation using both expected loss and conditional value-at-risk risk measures. Using this method, optimal strategies can be designed for control resource allocation to manage risk in a business process. Our work contributes to the literature on both ex ante risk management-based business process design and ex post risk assessments of existing business processes and control models. This research applies not only to the literature on and practice of process design and risk management but also to business decision support systems in general. An order-fulfillment process of an online pharmacy is used to illustrate the methodology.

Suggested Citation

  • Xue Bai & Ramayya Krishnan & Rema Padman & Harry Jiannan Wang, 2013. "On Risk Management with Information Flows in Business Processes," Information Systems Research, INFORMS, vol. 24(3), pages 731-749, September.
    • Handle: RePEc:inm:orisre:v:24:y:2013:i:3:p:731-749
    DOI: 10.1287/isre.1120.0450
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    References listed on IDEAS

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    Cited by:

    1. Qi Liu & Gengzhong Feng & Giri Kumar Tayi & Jun Tian, 2021. "Managing Data Quality of the Data Warehouse: A Chance-Constrained Programming Approach," Information Systems Frontiers, Springer, vol. 23(2), pages 375-389, April.

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