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Bridging the research-practice gap in disaster relief: using the IFRC Code of Conduct to develop an aid model

Author

Listed:
  • John B. Coles

    (SUNY at Buffalo
    CUBRC Inc.)

  • Jing Zhang

    (University at Buffalo)

  • Jun Zhuang

    (University at Buffalo)

Abstract

Bridging the gap between research and practice has been a recognized problem in many fields, and has been especially noticeable in the field of disaster relief. As the number and impact of disasters have increased, there has been a jump in interest from the research community in an attempt to provide tools and solutions for some of the challenges in the field. The International Federation of Red Cross and Red Crescent Societies (IFRC) Code of Conduct (CoC) for Disaster Operations provides a qualitative set of guidelines that is an excellent building block for operational theory, but is insufficiently rigorous in guiding quantitative decision making. In this paper, we review the CoC, exploring each of the ten core principles and identifying three significant operational trade-offs. We then propose a model framework that can be implemented as a stand-alone model, or can be used as a foundation for other quantitative aid allocation models. Finally, we provide an example of how the proposed model could be used to guide decision making in a Microsoft Excel $$^{{\text{\textregistered} }}$$ ® environment using CoinOR’s OpenSolver $$^{\text{\textregistered} }$$ ® . New insights in the field of aid disbursement are provided by examining the challenges of financial management and investment as dictated by the CoC. This paper fills a unique gap in the literature by addressing the issue of financial allocation as guided by a qualitative standard used by the disaster relief community, and serves as a complement to the work in the field of humanitarian logistics.

Suggested Citation

  • John B. Coles & Jing Zhang & Jun Zhuang, 2022. "Bridging the research-practice gap in disaster relief: using the IFRC Code of Conduct to develop an aid model," Annals of Operations Research, Springer, vol. 312(2), pages 1337-1357, May.
  • Handle: RePEc:spr:annopr:v:312:y:2022:i:2:d:10.1007_s10479-017-2488-1
    DOI: 10.1007/s10479-017-2488-1
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