Skip to main content

Advertisement

Log in

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

  • MCDM-SD
  • Published:
Annals of Operations Research Aims and scope Submit manuscript

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.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1

Similar content being viewed by others

References

  • Altay, N., & Green, W. G. (2006). OR/MS research in disaster operations management. European Journal of Operational Research, 175(1), 475–493.

    Google Scholar 

  • Andre, G., & Collins, S. (2001). Raising standards in emergency relief: How useful are sphere minimum standards for humanitarian assistance? British Medical Journal, 323(7315), 740–742.

    Google Scholar 

  • Balcik, B., & Beamon, B. M. (2008). Facility location in humanitarian relief. International Journal of Logistics, 11(2), 101–121.

    Google Scholar 

  • Balcik, B., Beamon, B. M., & Smilowitz, K. (2008). Last mile distribution in humanitarian relief. Journal of Intelligent Transportation Systems, 12(2), 51–63.

    Google Scholar 

  • Barbaroso, G., & Arda, Y. (2004). A two-stage stochastic programming framework for transportation planning in disaster response. Journal of the Operational Research Society, 55(1), 43–53.

    Google Scholar 

  • Barbarosoğlu, G., Özdamar, L., & Cevik, A. (2002). An interactive approach for hierarchical analysis of helicopter logistics in disaster relief operations. European Journal of Operational Research, 140(1), 118–133.

    Google Scholar 

  • Beamon, B. M., & Balcik, B. (2008). Performance measurement in humanitarian relief chains. International Journal of Public Sector Management, 21(1), 4–25.

    Google Scholar 

  • Beamon, B. M., & Kotleba, S. A. (2006). Inventory modelling for complex emergencies in humanitarian relief operations. International Journal of Logistics: Research and Applications, 9(1), 1–18.

    Google Scholar 

  • Birkmann, J. (2006). Measuring vulnerability to natural hazards: Towards disaster resilient societies. Tokyo: United Nations University Press.

    Google Scholar 

  • Bryant, C., & Lindenberg, M. (2001). Going global: Transforming relief and development NGOs. Yorktown Heights, NY: Kumarian Press.

    Google Scholar 

  • Clay Whybark, D. (2007). Issues in managing disaster relief inventories. International Journal of Production Economics, 108(1), 228–235.

    Google Scholar 

  • Collett, E. (2016). The paradox of the eu-turkey refugee deal. http://www.migrationpolicy.org/news/paradox-eu-turkey-refugee-deal. Accessed March 2017.

  • Currion, P., Silva, C., & van de Walle, B. (2007). Open source software for disaster management. Communications of the ACM, 50(3), 61–65.

    Google Scholar 

  • De Angelis, V., Mecoli, M., Nikoi, C., & Storchi, G. (2007). Multiperiod integrated routing and scheduling of world food programme cargo planes in angola. Computers & Operations Research, 34(6), 1601–1615.

    Google Scholar 

  • Ebrahim, A. (2003). Accountability in practice: Mechanisms for ngos. World Development, 31(5), 813–829.

    Google Scholar 

  • Eckhart, J., Allen, J., & Tuomala, J. (2013). Stop starving scale: Unlocking the potential of global ngos. http://www.bridgespan.org/getmedia/ca2c40f0-5a70-475f-9e6c-90682b178bc5/StopStarvingScale-UnlockingthePotentialofGlobalNGOs.pdf.aspx. Accessed March 2017.

  • Esty, D. C. (1998). Non-governmental organizations at the world trade organization: Cooperation, competition, or exclusion. Journal of International Economics Law, 1(1), 123–147.

    Google Scholar 

  • Fanack (2016). Syrian refugees increasingly used as bargaining chips. https://chronicle.fanack.com/turkey/history-past-to-present/turkey-coping-with-refugees/. Accessed March 2017.

  • Gabiam, N. (2012). When humanitarianism becomes development: The politics of international aid in syria’s palestinian refugee camps. American Anthropologist, 114(1), 95–107.

    Google Scholar 

  • Gao, H., Barbier, G., & Goolsby, R. (2011). Harnessing the crowdsourcing power of social media for disaster relief. IEEE Intelligent Systems, 26(3), 10–14.

    Google Scholar 

  • Guay, T., Doh, J. P., & Sinclair, G. (2004). Non-governmental organizations, shareholder activism, and socially responsible investments: Ethical, strategic, and governance implications. Journal of Business Ethics, 52(1), 125–139.

    Google Scholar 

  • Gunter, M. M. (2015). Iraq, Syria, Isis and the Kurds: Geostrategic concerns for the U.S. and Turkey. Midle East Policy, 22(1), 102–111.

    Google Scholar 

  • Hausken, K., & Zhuang, J. (2016). The strategic interaction between a company and the government surrounding disasters. Annals of Operations Research, 237(1), 27–40.

    Google Scholar 

  • Hilhorst, D. (2005). Dead letter or living document? ten years of the code of conduct for disaster relief. Disasters, 29(4), 351–369.

    Google Scholar 

  • Hulkower, R. (2010). The history of the hippocratic oath: Outdated, inauthentic, and yet still relevant. The Einstein Journal of Biology and Medicine, 25/26(1), 1–46.

    Google Scholar 

  • Hunter, L. M., Twine, W., & Patterson, L. (2007). “locusts are now our beef”: Adult mortality and household dietary use of local environmental resources in rural south africa. Scandinavian Journal of Public Health, 35(69), 165–174.

    Google Scholar 

  • Kent, R. C. (1987). Anatomy of disaster relief: The international network in action. London, England: Pinter Publishers.

    Google Scholar 

  • Khan, M. M., & Ahmed, S. (2003). Relative efficiency of government and non-government organisations in implementing a nutrition intervention programme—a case study from Bangladesh. Public Health Nutrition, 6(01), 19–24.

    Google Scholar 

  • Kovacs, G., & Spens, K. M. (2011). Trends and developments in humanitarian logistics—a gap analysis. International Journal of Physical Distribution & Logistics Management, 41(1), 32–45.

    Google Scholar 

  • Lee, H. L. (2000). Creating value through supply chain integration. Supply Chain Management Review, 4(4), 30–36.

    Google Scholar 

  • Lowell, S., Trelstad, B., & Meehan, B. (2005). The ratings game: Evaluating the three groups that rate the charities. Stanford Social Innovation Review, 3(2), 38–45.

    Google Scholar 

  • Mete, H. O., & Zabinsky, Z. B. (2010). Stochastic optimization of medical supply location and distribution in disaster management. International Journal of Production Economics, 126(1), 76–84.

    Google Scholar 

  • Moore, S., Eng, E., & Daniel, M. (2003). International NGOs and the role of network centrality in humanitarian aid operations: A case study of coordination during the 2000 mozambique floods. Disasters, 27(4), 305–318.

    Google Scholar 

  • Mortimer, J. (2015). Kurdish refugees reject government-run camp in Turkey. http://www.al-monitor.com/pulse/originals/2015/03/turkey-kobane-kurdish-refugees.html. Accessed March 2017.

  • National Society of Professional Engineers (2007). NSPE code of ethics for engineers. http://www.nspe.org/resources/ethics/code-ethics. Accessed March 2017.

  • PBS (2016). Inside the harsh living conditions for Syrian refugees in Turkey. http://www.pbs.org/newshour/bb/inside-the-harsh-living-conditions-for-syrian-refugees-in-turkey/. Accessed March 2017.

  • Rawls, C. G., & Turnquist, M. A. (2010). Pre-positioning of emergency supplies for disaster response. Transportation Research Part B: Methodological, 44(4), 521–534.

    Google Scholar 

  • Red Cross Federation, I. (1965). The seven fundamental principles. http://www.ifrc.org/vision-et-mission/vision-et-mission/les-7-principes-les-7-principes/. Accessed March 2017.

  • Red Cross Federation, I. (1994). Code of conduct. http://www.ifrc.org/en/publications-and-reports/code-of-conduct/. Accessed March 2017.

  • Sara, S. (2016). Turkey gripped by fear in aftermath of failed coup. http://www.abc.net.au/news/2016-10-04/turkey-gripped-by-fear-in-aftermath-of-failed-coup/7894250. Accessed March 2017.

  • Sbayti, H., & Mahmassani, H. S. (2006). Optimal scheduling of evacuation operations. Transportation Research Record: Journal of the Transportation Research Board, 1964(1), 238–246.

    Google Scholar 

  • Seaman, J. (1999). Malnutrition in emergencies: How can we do better and where do the responsibilities lie? Disasters, 23(4), 306–315.

    Google Scholar 

  • Shapiro, M. (1997). The problems of independent agencies in the United States and the European Union. Journal of European Public Policy, 4(2), 276–277.

    Google Scholar 

  • Simatupang, T. M., Wright, A. C., & Sridharan, R. (2002). The knowledge of coordination for supply chain integration. Business Process Management Journal, 8(3), 289–308.

    Google Scholar 

  • Smilowitz, K. R., & Dolinskaya, I. (2011). Decision-making tools for distribution networks in disaster relief, McCormick, Northwestern Engineering, Center for the Commercialization of Innovative Transportation Technologies.

  • Sperling, L. (2002). Emergency seed aid in Kenya: Some case study insights on lessons learned during the 1990s. Disasters, 26(4), 329–342.

    Google Scholar 

  • Sphere Project (2011). Sphere handbook: Humanitarian charter and minimum standards in disaster response. http://www.refworld.org/docid/4ed8ae592.htm. Accessed March 2017.

  • Stephenson, M, Jr. (2005). Making humanitarian relief networks more effective: Operational coordination, trust and sense making. Disasters, 29(4), 337–350.

    Google Scholar 

  • Stephenson, M, Jr., & Schnitzer, M. (2006). Interorganizational trust, boundary spanning, and humanitarian relief coordination. Nonprofit Management and Leadership, 17(2), 211–233.

    Google Scholar 

  • Sutton, J., Palen, L., & Shklovski, I. (2008). Backchannels on the front lines: Emergent uses of social media in the 2007 southern california wildfires. In Proceedings of the 5th international ISCRAM conference, Washington, DC, pp. 624–632.

  • The Guardian (2015). Lack of funds: World food programme drops aid to one-third of syrian refugees. https://www.theguardian.com/world/2015/sep/05/lack-of-funds-world-food-programme-drops-aid-to-one-third-of-syrian-refugees. Accessed March 2017.

  • Tzeng, G. H., Cheng, H. J., & Huang, T. D. (2007). Multi-objective optimal planning for designing relief delivery systems. Transportation Research Part E: Logistics and Transportation Review, 43(6), 673–686.

    Google Scholar 

  • Van Hoving, D. J., Wallis, L. A., Docrat, F., & De Vries, S. (2010). Haiti disaster tourisma medical shame. Prehospital & Disaster Medicine, 25(3), 201–202.

    Google Scholar 

  • Vitoriano, B., Ortuño, M. T., Tirado, G., & Montero, J. (2011). A multi-criteria optimization model for humanitarian aid distribution. Journal of Global Optimization, 51(2), 189–208.

    Google Scholar 

  • Vitoriano, B., Ortuno, T., & Tirado, G. (2009). Hads, a goal programming-based humanitarian aid distribution system. Journal of Multi-Criteria Decision Analysis, 16(1–2), 55–64.

    Google Scholar 

  • WFP (2015). WFP forced to make deeper cuts in food assistance for Syrian refugees due to lack of funding. https://www.wfp.org/news/news-release/wfp-forced-make-deeper-cuts-food-assistance-syrian-refugees-due-lack-funding. Accessed March 2017.

  • Xiang, Y., & Zhuang, J. (2016). Medical resource allocation serving disaster victims with deteriorating health conditions. Annals of Operations Research, 236(1), 177–196.

    Google Scholar 

  • Xu, J., & Zhuang, J. (2016). Modeling costly learning and counter-learning in a defender-attacker game with private defender information. Annals of Operations Research, 236(1), 271–289.

    Google Scholar 

  • Xu, J., Zhuang, J., & Liu, Z. (2016). Modeling and mitigating the effects of supply chain disruption in a defender-attacker game. Annals of Operations Research, 236(1), 255–270.

    Google Scholar 

  • Xu, L., & Beamon, B. (2006). Supply chain coordination and cooperation mechanisms: An attribute-based approach. Journal of Supply Chain Management, 42(1), 4–12.

    Google Scholar 

  • Yan, S., & Shih, Y. (2009). Optimal scheduling of emergency roadway repair and subsequent relief distribution. Computers & Operations Research, 36(6), 2049–2065.

    Google Scholar 

  • Yates, D., & Paquette, S. (2011). Emergency knowledge management and social media technologies: A case study of the 2010 Haitian earthquake. International Journal of Information Management, 31(1), 6–13.

    Google Scholar 

  • Yi, W., & Özdamar, L. (2007). A dynamic logistics coordination model for evacuation and support in disaster response activities. European Journal of Operational Research, 179(3), 1177–1193.

    Google Scholar 

  • Zhuang, J., Saxton, G., & Wu, H. (2014). Publicity vs. impact in nonprofit disclosures and donor preferences: A sequential game with one nonprofit organization and n donors. Annals of Operations Research, 221(1), 469–491.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Jun Zhuang.

Additional information

This research was partially supported by the United States Department of Homeland Security (DHS) through the National Center for Risk and Economic Analysis of Terrorism Events (CREATE) under award number 2010-ST-061-RE0001. This research was also patricianly supported by the United States National Science Foundation under award numbers 1200899 and 1334930. However, any opinions, findings, and conclusions or recommendations in this document are those of the authors and do not necessarily reflect views of the DHS, CREATE, or NSF. The authors assume responsibility for any errors.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Coles, J.B., Zhang, J. & Zhuang, J. Bridging the research-practice gap in disaster relief: using the IFRC Code of Conduct to develop an aid model. Ann Oper Res 312, 1337–1357 (2022). https://doi.org/10.1007/s10479-017-2488-1

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10479-017-2488-1

Keywords

Navigation