Despite over 20 years of research during the Global War on Terror, fundamental questions on the root causes and dynamics of non-state actors remain. This dissertation seeks to understand the lifecycle of violence and instability of non-state actors. To do this, it divides the lifecycle into two classes of problems: The first class of problems includes individuals or disconnected small groups. This class's violence represents a risk to individuals but is unlikely to threaten the state and operates in non-conflict zones. The second class of problems includes larger and more organized non-state actors who can represent a mid-to-high risk to state actors. These non-state actors also can operate within or even create conflict zones. This dissertation offers a novel hypothesis for each class of problems, identifying the root causes of that class. The terror contagion hypothesis asserts that violent radicalization leading to terrorism is a form of social contagion. The emerging-state actor hypothesis asserts that the relative legitimacy between state and non-state actors, along with other contingent factors, can help understand the rise of clandestine terror networks into insurgencies and even into emerging-state actors, which threaten the state itself. Key propositions from data and literature develop each hypothesis into a system structure. A computational simulation is developed from this system structure to test contingent values of propositions using military standards. The simulation models diplomatic, military, information, and economic interventions to understand dynamic reactions across political, military, economic, social, information, and infrastructure aspects (DIME-PMESII). Additionally, contingency analysis sorts propositions into strong, moderate, and weak categories, leading to insights and policy analysis. Key discoveries from this simulation begin with the insight that reducing violence and instability occurs on multidimensional terrains, of which the physical terrain is the least important. Additionally, the perceived grievance of non-state actors is fundamental to both classes of problems. Perceived grievance determines the system's carrying capacity for violence. Therefore, containment and intervention policies that do not address grievance can become like pulling weeds without removing roots or cutting off access to groundwater. What matters more than physical terrain is the human terrain, either of high-risk populations (first class) or ethnographic groups (second class), and their perception of legitimacy to the state and non-state actors competing across this landscape. Finally, if grievance creates the carrying capacity, the relative rate-of-change in legitimacy between state and non-state actors are the above-ground conditions, determining the weeds' growth rate. From these insights, one can build further policy analysis, evaluating popular and novel strategies to counter violence and instability. For the first class of problems, a policy based on cutting the feedback of social contagion performs best in simulated worst-case scenarios when combined with focused deterrence and grievance reduction. In the second class of problems – a two-phase approach combines legitimacy-building activities and small military support to local actors. Both policy portfolio suggestions are subjected to falsification tests to ensure we do not misattribute the source of policy benefit. Additionally, this project provides new publicly available resources, including the simulations described and a dataset of over 4,500 terror incidents categorized by violent ideology and radicalization type. Supplementary materials in two addenda contain complete model documentation, including confidence-building tests on both simulations.

Creator

• Clancy, Timothy

Contributors

• Addison, W. A. Bland
• Saeed, Khalid
• Pavlov, Oleg V

Degree

• PhD

Unit

• Social Science & Policy Studies

Publisher

• Worcester Polytechnic Institute

Identifier

• etd-78146

Keyword

• conflict
• simulations
• radicalization
• terrorism
• insurgency
• system dynamics

Advisor

• Saeed, Khalid
• Pavlov, Oleg V
• Addison, W. A. Bland

Orcid

• https://orcid.org/0000-0003-4508-8299

Defense date

• 2022-04-20

Year

• 2022

Date created

• 2022-09-26

Resource type

• Dissertation

Rights statement

• In Copyright

License

• Creative Commons BY-NC Attribution-NonCommercial 4.0 International

Last modified

• 2022-12-23