- Israel J. Udoh1, Alabi, Oluwadamilare Ikechukwu2, Oluranti Janet Faleye3
- DOI: 10.5281/zenodo.15487252
- SSR Journal of Multidisciplinary (SSRJM)
The study, “Effects of Prioritization of Counterterrorism (CT) Related Budgets: A Budgetary Allocation Queueing Fairness (BAQF) Model”, explores the inefficiencies and socio-economic consequences of prioritizing CT budgets over other critical sectors. It introduces the BAQF model, which employs queueing theory to analyze budget allocation as a single-server system with priority levels. The model incorporates the effects of “terrorpreneurial activities” -fabricated or exaggerated terrorism threats, and false-flag operations, which distort resource allocation by inflating CT budget demands. Assumptions include limited government detection capabilities, finite budgets, and the socio-economic costs of misallocation. Key findings reveal that over-prioritization of CT budgets exacerbates socio-economic inequalities, neglects essential sectors like education, agriculture, and healthcare, and perpetuates a cycle of insecurity. Misallocation incentivizes fabricated threats, creating a self-sustaining “market for fear”. The study aligns with theories such as Maslow’s Hierarchy of Needs, Rational Choice Theory, and Broken Windows Theory, emphasizing the importance of addressing root causes of instability – poverty, unemployment, illiteracy and inequality, rather than over-relying on punitive measures. Case studies, including post-9/11 United State CT spending and Nigeria’s Boko Haram insurgency, demonstrate the adverse effects of disproportionate security spending, such as corruption and inefficiency. The study concludes that balancing resource allocation between CT and socio-economic sectors is critical. It proposes strategies to improve threat detection, mitigate fabricated threats, and promote fairness in budget allocation to prevent long-term socio-economic instability and radicalization. Simulations are recommended to optimize the trade-off between efficiency and fairness in resource distribution.