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Staffing models for covert counterterrorism agencies

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  • Kaplan, Edward H.

Abstract

This article presents staffing models for covert counterterrorism agencies such as the New York City Police Department, the US Federal Bureau of Investigation, Britain's Security Service or the Israeli Shin Bet. The models ask how many good guys are needed to catch the bad guys, and how should agents be deployed? Building upon the terror queue model of the detection and interdiction of terror plots by undercover agents, the staffing models developed respond to objectives such as: prevent a specified fraction of terror attacks, maximize the benefits-minus-costs of preventing attacks, staff in expectation that smart terrorists will attack with a rate that optimizes their outcomes, and allocate a fixed number of agents across groups to equalize detection rates, or prevent as many attacks as possible, or prevent as many attack casualties as possible. Numerical examples based on published data describing counterterrorism operations in the United States and Israel are provided throughout.

Suggested Citation

  • Kaplan, Edward H., 2013. "Staffing models for covert counterterrorism agencies," Socio-Economic Planning Sciences, Elsevier, vol. 47(1), pages 2-8.
    • Handle: RePEc:eee:soceps:v:47:y:2013:i:1:p:2-8
    DOI: 10.1016/j.seps.2012.09.006
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    References listed on IDEAS

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    1. Golany, Boaz & Kaplan, Edward H. & Marmur, Abraham & Rothblum, Uriel G., 2009. "Nature plays with dice - terrorists do not: Allocating resources to counter strategic versus probabilistic risks," European Journal of Operational Research, Elsevier, vol. 192(1), pages 198-208, January.
    2. Jonathan Feinstein & Edward Kaplan, 2011. "Counterterror intelligence operations and terror attacks," Public Choice, Springer, vol. 149(3), pages 281-295, December.
    3. J. Michael Steele, 1989. "Models for Managing Secrets," Management Science, INFORMS, vol. 35(2), pages 240-248, February.
    4. Jonathan S. Feinstein & Edward H. Kaplan, 2010. "Analysis of a Strategic Terror Organization," Journal of Conflict Resolution, Peace Science Society (International), vol. 54(2), pages 281-302, April.
    5. Edward H. Kaplan & Moshe Kress & Roberto Szechtman, 2010. "Confronting Entrenched Insurgents," Operations Research, INFORMS, vol. 58(2), pages 329-341, April.
    6. O. Garnet & A. Mandelbaum & M. Reiman, 2002. "Designing a Call Center with Impatient Customers," Manufacturing & Service Operations Management, INFORMS, vol. 4(3), pages 208-227, October.
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    Cited by:

    1. Abdulrahman ALRASSI, 2014. "Counterterrorism Efforts Of Saudi Arabia In Create Stability Of The World," SEA - Practical Application of Science, Romanian Foundation for Business Intelligence, Editorial Department, issue 5, pages 117-122, November.
    2. Alemayehu, Fikru K. & Kumbhakar, Subal C. & Landazuri Tveteraas, Sigbjørn, 2022. "Estimation of staff use efficiency: Evidence from the hospitality industry," Technological Forecasting and Social Change, Elsevier, vol. 178(C).
    3. Seidl, Andrea & Kaplan, Edward H. & Caulkins, Jonathan P. & Wrzaczek, Stefan & Feichtinger, Gustav, 2016. "Optimal control of a terror queue," European Journal of Operational Research, Elsevier, vol. 248(1), pages 246-256.
    4. Liu, Zhongyi & Liu, Jingchen & Zhai, Xin & Wang, Guanying, 2019. "Police staffing and workload assignment in law enforcement using multi-server queueing models," European Journal of Operational Research, Elsevier, vol. 276(2), pages 614-625.
    5. Stefan Wrzaczek & Edward H. Kaplan & Jonathan P. Caulkins & Andrea Seidl & Gustav Feichtinger, 2017. "Differential Terror Queue Games," Dynamic Games and Applications, Springer, vol. 7(4), pages 578-593, December.

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