Date of Conferral
2017
Degree
Ph.D.
School
Public Policy and Administration
Advisor
Eliesh Lane
Abstract
Little is known about how effectively federal agencies share terrorism intelligence with state and local governments through fusion centers. As a result, there is a risk that local governments do not receive critical intelligence that would allow them to collaboratively prevent catastrophic terrorist attacks. Using Dawes' interagency information sharing model, the purpose of this exploratory case study was to evaluate how effectively federal agencies share terrorism intelligence with fusion centers. Data were collected through interviews with 25 senior leaders, federal agents deployed to fusion centers, and intelligence analysts in 5 fusion centers on the East Coast. These data were inductively coded and then subjected to a thematic analysis procedure. Findings indicated that, among these leaders, information sharing was hindered by both technology and inter-organizational relationships between the fusion centers and federal agencies. Participants also noted that obstacles to information sharing regarding classified data has not been sufficiently mitigated. Dawes' interagency information-sharing theory was found to be explanatory regarding intelligence sharing activities. Implications for positive social change include recommendations to the Department of Homeland Security to utilize Dawes' work on information sharing in order to alleviate the tension between federal and local agencies and remove obstacles, particularly related to classified intelligence related to counterterrorism. Doing so can be useful in developing policy recommendations to improve the dynamics between federal and local agencies, thereby allowing critical information to be shared with state and local governments in a proactive manner that may better protect communities.
Recommended Citation
Gardner, Jeffrey V., "A Duty to Share: The Opportunities and Obstacles of Federal Counterterrorism Intelligence Sharing with Nonfederal Fusion Centers" (2017). Walden Dissertations and Doctoral Studies. 3770.
https://scholarworks.waldenu.edu/dissertations/3770