Multipolar Security Cooperation Planning: A Multiobjective, Adversarial-Risk-Analysis Approach

William N. Caballero (), Ethan Gharst (), David Banks () and Jeffery D. Weir ()
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William N. Caballero: U.S. Air Force Academy, Colorado Springs, Colorado 80840
Ethan Gharst: U.S. Air Force Academy, Colorado Springs, Colorado 80840
David Banks: Duke University, Durham, North Carolina 27708
Jeffery D. Weir: Air Force Institute of Technology, Wright-Patterson Air Force Base, Ohio 45433

Decision Analysis, 2023, vol. 20, issue 1, 16-39

Abstract: In an increasingly competitive environment, defense organizations are met with more difficult decisions than in years past. This problem is especially apparent in security cooperation, that is, defense diplomacy, conducted by the United States. Both the United States and its competitors offer military assistance to third-party nations who, in turn, select an offer based on their own self-interest. Unfortunately, current security cooperation planning practices adopt an ad hoc approach to such problems. Therefore, we set forth herein a decision-analytic-planning framework by (1) provisioning a generic utility model for security cooperation planning applicable to myriad stakeholders and (2) developing a Bayesian solution that allows the stakeholder to select an action that maximizes their expected utility. This combination of value-focused thinking and adversarial risk analysis improves upon standard U.S. defense practices; it tractably encodes planning assumptions and more comprehensively considers the relevant uncertainties. The efficacy of this planning approach is illustrated on a notional U.S. Air Force case study in which a host nation must choose between security assistance from the United States or a competing nation.

Keywords: decision analysis; adversarial risk analysis; public-sector operations research; diplomacy; international relations (search for similar items in EconPapers)
Date: 2023
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