Qualitative Comparative Analysis of 30 Insurgencies, 1978–2008

Paul, Christopher; Clarke, Colin P.; Grill, Beth

doi:10.5711/1082598317219

Cited by 3 publications

(2 citation statements)

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“…The operational validity of such models is therefore limited to extracting characterizing trends in their behavior. More importantly, the contributions of these efforts are that they provide similar empirical correlates as Paul et al 26 and stylized facts that enable to test behavior of computational models against real-world behavior.…”

Section: Analytical Modelsmentioning

confidence: 95%

“…24 Evidence demonstrates that large COIN interventions yield more failures than success stories; 25 these failings have been attributed to the enemy-centric focus of COIN. Paul et al 26 demonstrated that the ''crush them'' tactic against insurgencies was ineffective 23 out of 33 times. In their analysis of 71 insurgencies, they assess 24 concepts of COIN.…”

Section: Insurgency Conflictsmentioning

confidence: 99%

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Promises and pitfalls of computational modelling for insurgency conflicts

Zwet

Barros

Engers

et al. 2022

Journal of Defense Modeling & Simulation

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Insurgency conflicts pose significant challenges to societies globally. The increase of insurgency conflicts creates a need to understand how insurgencies arise, and to identify societal drivers of insurgencies or effective strategies to counter them. In this paper, we analyze the contributions of computational modeling methods for the analysis of insurgent conflicts. We formalize a specific literature-based analysis framework using the identified key factors and drivers, which enables the evaluation of specific models in this domain. Through a systematic literature search, we identify 64 computational models to apply our framework. We highlight the development and contributions of various methodologies through an in-depth analysis of 13 high-quality models. The evaluation of these computational models revealed promising directions and future topics to design specific simulation models for all identified factors. In addition, our analysis revealed specific pitfalls concerning validity issues for each of the modeling methods.

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Section: Analytical Modelsmentioning

confidence: 95%

Section: Insurgency Conflictsmentioning

confidence: 99%