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Quality & Quantity

, Volume 53, Issue 4, pp 2103–2115 | Cite as

Setting research priorities in the field of emergency management: which piece of information are you willing to pay more?

  • Carlo DragoEmail author
  • Matteo Ruggeri
Article
  • 44 Downloads

Abstract

In this paper we show how EVPPI analysis can be a good tool to formalize the decision making process leading the design and implementation of interventions aimed at preventing and controlling the consequences of extraordinary events. More concretely we the economics of emergency as the approach aimed at defining how to identify which interventions would be more efficient to be implemented in order to minimize the risk of incurring in unexpected circumstances/events. Our rationale is that when dealing with complex decisions potentially leading to extraordinary circumstances, the first step for a decision makers should be to minimize the sources of uncertainty by mean of further research. This would inevitably entail investments and reallocation of resources. Our approach aims to define how to decide where is more efficient to intervene. Our paper provides a theoretical framework of the EVPPI and an application based on a hypothetical natural disaster. In the last section we discuss the limits of our approach and implications for further research.

Keywords

Emergency management Expected value for partial parameter information (EVPPI) Uncertainty Decision making Montecarlo simulations 

JEL Classifications

D7 D8 C63 

Notes

Acknowledgements

Authors wish to thank the anonymous referees for suggestions. Moreover authors would like to honor the memory of the Sgt. Riccardo Padula of the Italian Red Cross for having inspired this work. Sgt Padula passed away on Thursday 7th March, the day we received the first revisions from the journal.

References

  1. Armacost, R.L., Pet-Armacost, J.A.: Risk-based management of waterway safety. Int. J. Emerg. Manag. 1(2), 96–109 (2002)CrossRefGoogle Scholar
  2. Barrett, A.M.: Value of global catastrophic risk (GCR) information: cost-effectiveness-based approach for GCR reduction. Decis. Anal. (2017).  https://doi.org/10.1287/deca.2017.0350 Google Scholar
  3. Beutels, P., Edmunds, W.J., Smith, R.D.: Partially wrong? Partial equilibrium and the economic analysis of public health emergencies of international concern. Health Econ. 17(11), 1317–1322 (2008)CrossRefGoogle Scholar
  4. Bostrom, N., Cirkovic, M.M. (eds.): Global Catastrophic Risks. Oxford University Press, Oxford (2008)Google Scholar
  5. Burke, R.: Lessons from Katrina: commanding the military during disaster response—then and now. Int. J. Emerg. Manag. 12(3), 221–240 (2016)CrossRefGoogle Scholar
  6. Clemen, R.T., Reilly, T.: Making Hard Decisions. Duxbury, Pacific Grove (2001)Google Scholar
  7. Coyle, D., Oakley, J.: Estimating the expected value of partial perfect information: a review of methods. Eur. J. Health Econ. 9(3), 251–259 (2008)CrossRefGoogle Scholar
  8. Evans, J.S., Kibble, A., Mitchem, L.: An evidence-based approach to protect public health during prolonged fires. Int. J. Emerg. Manag. 12(1), 1–9 (2016)CrossRefGoogle Scholar
  9. Felli, J.C., Hazen, G.B.: A Bayesian approach to sensitivity analysis. Health Econ. 8, 263–268 (1999)CrossRefGoogle Scholar
  10. Garrick, B.J.: Quantifying and Controlling Catastrophic Risks. Academic Press, Burlington (2008)Google Scholar
  11. Green, L.V., Kolesar, P.J.: Improving emergency responsiveness with management science. Manag. Sci. 50(8), 1001–1014 (2004)CrossRefGoogle Scholar
  12. Hwang, K., Hyung, J.P.: Dynamics of accountability in crisis management. Int. J. Emerg. Manag. 12(1), 95–112 (2016)CrossRefGoogle Scholar
  13. Irshad, M.: Economic recovery of disaster survivors: a critical analysis. Int. J. Emerg. Manag. 13(4), 368–381 (2017)CrossRefGoogle Scholar
  14. Jacobson, E.U., Argon, N.T., Ziya, S.: Priority assignment in emergency response. Oper. Res. 60(4), 813–832 (2012)CrossRefGoogle Scholar
  15. Joakim, E.P., Mortsch, L., Oulahen, G., Harford, D., Klein, Y., Damude, K., Tang, K.: Using system dynamics to model social vulnerability and resilience to coastal hazards. Int. J. Emerg. Manag. 12(4), 366–391 (2016)CrossRefGoogle Scholar
  16. Kahan, J.H.: Living with terrorism: unimaginable nightmare or prospective reality. J. Homel. Secur. Emerg. Manag. 13(2), 231–247 (2016)CrossRefGoogle Scholar
  17. Keisler, J.: Value of information in portfolio decision analysis. Decis. Anal. 1(3), 177–189 (2004)CrossRefGoogle Scholar
  18. Kirkpatrick, S.J., Jensen, J., Bundy, J.: Local recovery coordinators and the national disaster recovery framework: questions regarding the form, necessity, and potential of the role. Int. J. Emerg. Manag. (2017).  https://doi.org/10.1515/jhsem-2016-0068 Google Scholar
  19. Larson, R.C., Metzger, M.D., Cahn, M.F.: Responding to emergencies: lessons learned and the need for analysis. Interfaces 36(6), 486–501 (2006)CrossRefGoogle Scholar
  20. Lee, E.K., Maheshwary, S., Mason, J., Glisson, W.: Large-scale dispensing for emergency response to bioterrorism and infectious-disease outbreak. Interfaces 36(6), 591–607 (2006)CrossRefGoogle Scholar
  21. Majchrzak, A., Sirkka, L., Hollingshead, A.B.: Coordinating expertise among emergent groups responding to disasters. Organ. Sci. 18(1), 147–161 (2004)CrossRefGoogle Scholar
  22. Maras, M.H., Miranda, M.D.: State intervention during public health emergencies: is the United States prepared for an Ebola outbreak? J. Homel. Secur. Emerg. Manag. 12(2), 257–273 (2015)Google Scholar
  23. McLeish, C., Nightingale, P.: Biosecurity, bioterrorism and the governance of science: the increasing convergence of science and security policy. Res. Policy 36, 1635–1654 (2007).  https://doi.org/10.1016/j.respol.2007.10.003 CrossRefGoogle Scholar
  24. McNie, E., Sarewitz, D.: Improving the public value of science: a typology to inform discussion, design and implementation of research. Res. Policy 45(4), 884–895 (2014)CrossRefGoogle Scholar
  25. Savas, E.G.: The political properties of crystalline H2O: planning for snow emergencies in New York. Manag. Sci. 20(2), 137–145 (1973)CrossRefGoogle Scholar
  26. Schmidt, G.: Managing work-related stress in humanitarian fieldwork: aid workers and resilience resources. Int. J. Emerg. Manag. 13(4), 382–397 (2017)CrossRefGoogle Scholar
  27. Schmidt, G.: Terrorist attacks with explosive weapons: pattern of injuries and health constraints. Int. J. Emerg. Manag. 14(1), 40–50 (2018)CrossRefGoogle Scholar
  28. Scott, M., Jane, K.: A systematic review of the international disaster case management literature in the aftermath of Hurricane Katrina. Int. J. Emerg. Manag. 12(3), 241–262 (2016)CrossRefGoogle Scholar
  29. Tsai, C.: Seismic risk assessment and design of tourism buildings using probability analysis. Int. J. Emerg. Manag. 14(1), 90–106 (2018)CrossRefGoogle Scholar
  30. Wang, A., Wang, E., Xiangyang, L.: Emergency response information sharing and fusing in multi-subject coalitions. Int. J. Emerg. Manag. 13(2), 117–130 (2017)CrossRefGoogle Scholar
  31. Weitzman, M.L.: On modeling and interpreting the economics of catastrophic climate change. Rev. Econ. Stat. 91(1), 1–19 (2009)CrossRefGoogle Scholar
  32. Willis, H.H., Moore, M.: Improving the value of analysis for biosurveillance. Decis. Anal. 11(1), 63–81 (2014)CrossRefGoogle Scholar
  33. Zhang, B., Vos, M., Veijalainen, J.: Decomposing issue patterns in crisis communication: the case of the lost airliner. Int. J. Emerg. Manag. (2018).  https://doi.org/10.1504/IJEM.2018.089166 Google Scholar

Copyright information

© Springer Nature B.V. 2019

Authors and Affiliations

  1. 1.University “Niccolò Cusano”RomeItaly
  2. 2.NCI University in London, Faculty of Business and ManagementLondonUK
  3. 3.Università Cattolica del Sacro CuoreRomeItaly
  4. 4.Italian Red Cross, Military CorpsRomeItaly

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