Advertisement

The Game-Theoretic National Interstate Economic Model: Economically Optimizing U.S. Aviation Security Policies Against Terrorist Attacks

  • Ha Hwang
  • JiYoung ParkEmail author
Chapter
Part of the Advances in Spatial Science book series (ADVSPATIAL)

Abstract

The study proposes an approach to assessing airport and aviation security policies, which incorporates terrorist attack behaviors with economic impacts stemming from disruption of U.S. airport systems. Terrorist attacks involve complicated strategic behaviors of terrorists, while various defenders need to consider the degree of negative impacts that may occur via complicated paths. Simultaneous attacks will make this situation more complicated, because defending entities must secure airports and aviation systems with more tightly integrated inter-governmental collaborations. This study, for the first time, suggests a dynamic method to design the complicated micro-level behavioral strategies with macro-level economic impacts. In terms of game strategies, the current study only considers a competitive game situation between a defender and an attacker. In terms of the macro-level economic model, the National Interstate Economic Model (NIEMO) is introduced, which is a spatially disaggregated economic model used for the U.S. By combining these two approaches, a new framework is called the Game Theoretic National Interstate Economic Model (G-NIEMO). G-NIEMO, then, can be used to assess probabilistic costs of airport closure when potential terrorist attacks occur under the circumstance of considering the allocation of a government’ resources for designing airport security optimally by event location and industry type. NIEMO has been widely applied through a variety of empirical studies, but the competitive game model has not yet combined successfully. Based on the basic algorithm applied in the “attacker-defender game,” this chapter explains how G-NIEMO could be achieved. Further, establishing a cooperative coordination system and collective countermeasures against terrorism is necessary to cope with much more complicated forms of terrorist attacks such as simultaneous attacks and cyber-attacks. G-NIEMO can meet these needs through a collaborative gaming model. When applying G-NIEMO practically to simulate comprehensive defense strategies, for example, for urban critical infrastructure systems, corresponding estimated probabilistic impacts can be prepared. Therefore, G-NIEMO can be used to establish equilibrium strategies for protecting U.S. territory, creating general guidelines and assessing government resource allocations.

Keywords

National Aviation Security Terrorism Game Theory G-NIEMO Probabilistic Economic Impacts 

References

  1. American Institute of Aeronautics and Astronautics (2013) A framework for aviation cybersecurity. An AIAA decision paperGoogle Scholar
  2. ARTBA (2010) The 2010 U.S. Transportation Construction Industry Profile. ARTBA Transportation Development Foundation, available at: http://www.artba.org/Economics/Econ-Breakouts/04_EconomicImpactInterruptedService.pdf. Accessed November 2012
  3. Benkler Y (2011a) The penguin and the leviathan: the triumph of cooperation over self-interest. Crown, New YorkGoogle Scholar
  4. Benkler Y (2011b) The unselfish gene. Harv Bus Rev 89(7–8):76–85Google Scholar
  5. Bier VM (2007) Choosing what to protect. Risk Anal 27(3):607–620CrossRefGoogle Scholar
  6. Bier V, Oliveros S, Samuelson L (2007) Choosing what to protect: strategic defensive allocation against an unknown attacker. J Public Econ Theory 9(4):563–587CrossRefGoogle Scholar
  7. Bier VM, Haphuriwat N, Menoyo J, Zimmerman R, Culpen AM (2008) Optimal resource allocation for defense of targets based on differing measures of attractiveness. Risk Anal 28(3):763–770CrossRefGoogle Scholar
  8. Brown G, Carlyle M, Salmerón J, Wood K (2005) Analyzing the vulnerability of critical infrastructure to attack and planning defenses. In: Greenberg HJ, Smith JC (eds) Tutorials in operations research: emerging theory, methods, and applications. INFORMS, Hanover, pp 102–123Google Scholar
  9. CBP (2008) About border security. Available at http://www.cbp.gov/xp/cgov/border_security/bs/. Accessed September 2008
  10. Chenery HB (1953) The structure and growth of the Italian economy: United States of America, Mutual Security AgencyGoogle Scholar
  11. Daniel G, Arce M, Sandler T (2003) An evolutionary game approach to fundamentalism and conflict. J Inst Theor Econ JITE 159(1):132–154CrossRefGoogle Scholar
  12. De Mesquita EB (2005a) Conciliation, counterterrorism, and patterns of terrorist violence. Int Organ 59(01):145–176CrossRefGoogle Scholar
  13. De Mesquita EB (2005b) The terrorist endgame: a model with moral hazard and learning. J Confl Resolut 49(2):237–258CrossRefGoogle Scholar
  14. Dighe NS, Zhuang J, Bier VM (2009) Secrecy in defensive allocations as a strategy for achieving more cost-effective attacker deterrence. Int J Performability Eng 5(1):31–43Google Scholar
  15. Dixon PB, Lee B, Muehlenbeck T, Rimmer MT, Rose A, Verikios G (2010) Effects on the US of an H1N1 epidemic: analysis with a quarterly CGE model. J Homel Secur Emerg Manag 7(1)Google Scholar
  16. Gibbons R (1992) Game theory for applied economists. Princeton University Press, Princeton, NJCrossRefGoogle Scholar
  17. Gordon P, Moore JE II, Park JY, Richardson HW (2007) The economic impacts of a terrorist attack on the US commercial aviation system. Risk Anal 27(3):505–512CrossRefGoogle Scholar
  18. Gordon P, Moore JE II, Park JY, Richardson HW (2009a) The economic costs of border closure: a state-by-state analysis. In: Richardson HW, Gordon P, Moore JE II (eds) Global business and the terrorist threat. Edward Elgar, Cheltenham, pp 341–374Google Scholar
  19. Gordon P, Park JY, Richardson HW (2009b) Modeling input-output impacts with substitutions in the household sector: a numerical example. Econ Model 26(3):696–701CrossRefGoogle Scholar
  20. Guan P, Zhuang J (2016) Modeling resources allocation in attacker-defender games with “warm up” CSF. Risk Anal 36(4):776–791.  https://doi.org/10.1111/risa.12502 CrossRefGoogle Scholar
  21. Hao M, Zhuang J, Jin S (2009) Robustness of optimal defensive resource allocations in the face of less fully rational attacker. In: Proceedings of the 2009 industrial engineering research conference, Miami, FL, pp 886–891Google Scholar
  22. Hausken K, Zhuang J (2011) Governments’ and terrorists’ defense and attack in a T-period game. Decis Anal 8(1):46–70CrossRefGoogle Scholar
  23. Hausken K, Zhuang J (2012) The timing and deterrence of terrorist attacks due to exogenous dynamics. J Oper Res Soc 63(6):726–735CrossRefGoogle Scholar
  24. Hausken K, Bier V, Zhuang J (2009) Defending against terrorism, natural disaster, and all hazards. In: Bier VM, Azaiez MN (eds) Game theoretic risk analysis of security threats. Springer, New York, pp 65–97CrossRefGoogle Scholar
  25. Hirshleifer J (1989) Conflict and rent-seeking success functions: ratio vs. difference models of relative success. Public Choice 63(2):101–112CrossRefGoogle Scholar
  26. Hirshleifer J (1995) Anarchy and its breakdown. J Pol Econ 103:26–52CrossRefGoogle Scholar
  27. Isard W (1951) Interregional and regional input-output analysis: a model of a space economy. Rev Econ Stat 33:318–328CrossRefGoogle Scholar
  28. Lakdawalla D, Zanjani G (2005) Insurance, self-protection, and the economics of terrorism. J Public Econ 89(9):1891–1905CrossRefGoogle Scholar
  29. Lee B, Park JY, Gordon P, Moore JE II, Richardson HW (2012) Estimating the state-by-state economic impacts of a foot-and-mouth disease attack. Int Reg Sci Rev 35(1):26–47CrossRefGoogle Scholar
  30. Major JA (2002) Advanced techniques for modeling terrorism risk. J Risk Finance 4(1):15–24CrossRefGoogle Scholar
  31. Moses LN (1955) The stability of interregional trading patterns and input-output analysis. Am Econ Rev 45:803–832Google Scholar
  32. Muggy L, Heier Stamm JL (2014) Game theory applications in humanitarian operations: a review. J Humanitarian Logist Supply Chain Manag 4(1):4–23CrossRefGoogle Scholar
  33. Nikoofal ME, Zhuang J (2012) Robust allocation of a defensive budget considering an attacker’s private information. Risk Anal 32(5):930–943CrossRefGoogle Scholar
  34. Nowak M, Highfield R (2011) SuperCooperators: altruism, evolution, and why we need each other to succeed. Simon and Schuster, New YorkGoogle Scholar
  35. Osborne MJ (2004) An introduction to game theory. Oxford University Press, New YorkGoogle Scholar
  36. Oxford Economics (2009) Aviation: the real world wide web. Onward, OxfordGoogle Scholar
  37. Oxford Economics (2010) The economic impacts of air travel restrictions due to volcanic ash. Available at: http://www.oxfordeconomics.com/FREE/PDFS/OEAVIATION09.PDF. Accessed November 2012
  38. Park JY (2008) The economic impacts of a dirty-bomb attack on the Los Angeles and Long Beach Port: applying supply-driven NIEMO (National Interstate Economic Model). J Homel Secur Emerg Manag 5(1)Google Scholar
  39. Park C, Park JY (2016) Panama canal expansion, U.S. trade diversion from west coast seaports and urban innovation. J Open Innov 2(12)Google Scholar
  40. Park JY, Park CK, Nam S (2006) The state-by-state economic impacts of mad cow disease on the United States. In: A proceeding paper of 2006 American Agricultural Economic Association (AAEA) annual meeting, Long Beach, CA, July 23–26Google Scholar
  41. Park JY, Gordon P, Moore JE II, Richardson HW, Wang L (2007) Simulating the state-by-state effects of terrorist attacks on three major U.S. ports: applying NIEMO (National Interstate Economic Model). In: Richardson HW, Gordon P, Moore JE II (eds) The economic costs and consequences of terrorism. Edward Elgar, Cheltenham, pp 208–234Google Scholar
  42. Park JY, Gordon P, Moore JE II, Richardson HW (2008a) The state-by-state economic impacts of the 2002 shutdown of the Los Angeles-Long Beach ports. Growth Change 39(4):548–572CrossRefGoogle Scholar
  43. Park JY, Gordon P, Moore JE II, Richardson HW, Kim S, Kim Y (2008b) Estimating the state-by-state economic impacts of hurricane Katrina. In: Richardson HW, Gordon P, Moore JE II (eds) Natural disaster analysis after hurricane Katrina. Edward Elgar, Cheltenham, pp 147–186Google Scholar
  44. Park JY, Gordon P, Moore JE II, Richardson HW (2009) A two-step approach to estimating state-by-state commodity trade flows. Ann Reg Sci 43(4):1033–1072CrossRefGoogle Scholar
  45. Park JY, Cho J, Gordon P, Moore JE II, Richardson HW, Yoon S (2011) Adding a freight network to a national interstate input-output model: a TransNIEMO application for California. J Transp Geogr 19(6):1410–1422CrossRefGoogle Scholar
  46. Park JY, Gordon P, Moore JE II, Richardson HW (2013) The interregional and interindustry impacts of the gulf oil spill: applying the National Interstate Economic Model (NIEMO). J Homel Secur Emerg Manag 10(1):231–244Google Scholar
  47. Park JY, Son M, Hwang H, Cho D, Park C (2016) A new framework to quantifying the economic impacts of cyberattacks on aviation systems: a Korean game-theoretic interregional economic model. In: Kim E, Kim BH (eds) Quantitative regional economic and environmental analysis for sustainability in Korea (New frontiers in regional science: Asian perspectives). Springer, Singapore, pp 153–168CrossRefGoogle Scholar
  48. Park JY, Son M, Park C (2017a) Natural disasters and deterrence of economic innovation: a case of temporary job losses by hurricane Sandy. J Open Innov 3:5CrossRefGoogle Scholar
  49. Park JY, Gordon P, Moore JE II, Richardson HW (2017b) A new approach to quantifying the impact of hurricane-disrupted oil refinery operations utilizing secondary data. Group Decis Negotiation 26(6):1125–1144CrossRefGoogle Scholar
  50. Park JY, Levy J, Son M, Park C, Hwang H (2018) Advances in cybersecurity design: an integrated framework to quantify the economic impacts of cyber-terrorist behavior. In: Masys AJ (ed) Security by design: innovative perspectives on complex problems. Springer, Cham, pp 317–339CrossRefGoogle Scholar
  51. Richardson HW, Park JY (2014) The Joplin tornado of 2011. In: Richardson HW, Park JY, Moore JE II, Pan Q (eds) National economic impact analysis of terrorist and natural disasters. Edward Elgar, Cheltenham, pp 192–203Google Scholar
  52. Richardson HW, Gordon P, Moore JE II, Kim SJ, Park JY, Pan Q (2007) Tourism and terrorism: the national and interregional economic impacts of attacks on major U.S. theme parks. In: Richardson HW, Gordon P, Moore JE II (eds) The economic costs and consequences of terrorism. Edward Elgar, Cheltenham, pp 235–253CrossRefGoogle Scholar
  53. Richardson HW, Park JY, JE Moore II, Pan Q (2014) National economic impact analysis of terrorist and natural disasters. Edward Elgar, CheltenhamCrossRefGoogle Scholar
  54. Sandler T (2003) Terrorism & game theory. Simulat Gaming 34(3):319–337CrossRefGoogle Scholar
  55. Sandler T, Lapan HE (1988) The calculus of dissent: an analysis of terrorists’ choice of targets. Synthese 76(2):245–261CrossRefGoogle Scholar
  56. Sandler T, Siqueira K (2006) Global terrorism: deterrence versus pre-emption. Can J Econ/Revue canadienne d’économique 39(4):1370–1387CrossRefGoogle Scholar
  57. Sandler T, Siqueira K (2009) Games and terrorism recent developments. Simulat Gaming 40(2):164–192CrossRefGoogle Scholar
  58. Sandler T, Tschirhart JT, Cauley J (1983) A theoretical analysis of transnational terrorism. Am Polit Sci Rev 77(4):36–54CrossRefGoogle Scholar
  59. Shan X, Zhuang J (2013) Cost of equity in homeland security resource allocation in the face of a strategic attacker. Risk Anal 33(6):1083–1099CrossRefGoogle Scholar
  60. Skaperdas S (1996) Contest success functions. Econ Theor 7(2):283–290CrossRefGoogle Scholar
  61. Tirman J (2006) Immigration and insecurity: post-9/11 fear in the United States. MIT Center for International Studies Audit of the Conventional Wisdom, 06–09Google Scholar
  62. Wang C, Bier VM (2011) Target-hardening decisions based on uncertain multiattribute terrorist utility. Decis Anal 8(4):286–302CrossRefGoogle Scholar
  63. Zhuang J (2010) Impacts of subsidized security on stability and total social costs of equilibrium solutions in an n-player game with errors. Eng Economist 55(2):131–149CrossRefGoogle Scholar
  64. Zhuang J, Bier VM (2007) Balancing terrorism and natural disasters-defensive strategy with endogenous attacker effort. Oper Res 55(5):976–991CrossRefGoogle Scholar
  65. Zhuang J, Bier VM (2011) Secrecy and deception at equilibrium, with applications to anti-terrorism resource allocation. Defence Peace Econ 22(1):43–61CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Division of Disaster and Safety ResearchKorea Institute of Public AdministrationSeoulRepublic of Korea
  2. 2.Department of Urban and Regional PlanningUniversity at Buffalo, The State University of New YorkBuffaloUSA
  3. 3.Regional Information ProgramSeoul National UniversitySeoulRepublic of Korea

Personalised recommendations