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Droning On: Explaining the Proliferation of Unmanned Aerial Vehicles

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  • Fuhrmann, Matthew
  • Horowitz, Michael C.

Abstract

Unmanned Aerial Vehicles (UAVs), more popularly known as “drones,†have become emblematic of twenty-first century military technologies but scholars have yet to convincingly explain the drivers of UAV proliferation. Using the first systematic data set of UAV proliferation, this research note examines the spread of UAVs in the context of scholarly debates about interests versus capacity in explaining policy adoption. The results yield important insights for both IR scholarship and the policy-making community. While countries that experience security threats—including territorial disputes and terrorism—are more likely to seek UAVs, drone proliferation is not simply a function of the threat environment. We find evidence that democracies and autocracies are more likely than mixed regimes to develop armed UAV programs, and suggest that autocracies and democracies have their own unique incentives to acquire this technology. Moreover, supply-side factors play a role in the UAV proliferation process: a state's technological capacity is a strong predictor of whether it will obtain the most sophisticated UAVs. The theories and evidence we present challenge emerging views about UAV proliferation and shed useful light on how and why drones spread.

Suggested Citation

  • Fuhrmann, Matthew & Horowitz, Michael C., 2017. "Droning On: Explaining the Proliferation of Unmanned Aerial Vehicles," International Organization, Cambridge University Press, vol. 71(2), pages 397-418, April.
  • Handle: RePEc:cup:intorg:v:71:y:2017:i:02:p:397-418_00
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    Cited by:

    1. Carsten Christensen & John Salmon, 2022. "An agent-based modeling approach for simulating the impact of small unmanned aircraft systems on future battlefields," The Journal of Defense Modeling and Simulation, , vol. 19(3), pages 481-500, July.
    2. Michael Horowitz & Joshua A Schwartz & Matthew Fuhrmann, 2022. "Who’s prone to drone? A global time-series analysis of armed uninhabited aerial vehicle proliferation," Conflict Management and Peace Science, Peace Science Society (International), vol. 39(2), pages 119-142, March.
    3. Liles, Joseph M. & Robbins, Matthew J. & Lunday, Brian J., 2023. "Improving defensive air battle management by solving a stochastic dynamic assignment problem via approximate dynamic programming," European Journal of Operational Research, Elsevier, vol. 305(3), pages 1435-1449.

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