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‘Led by Intelligence': A Scoping Review on the Experimental Evaluation of Intelligence-Led Policing

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  • Robin Khalfa
  • Wim Hardyns

Abstract

Intelligence-led policing (ILP) was introduced in the 1990s as a proactive approach to policing, but to date, there is a lack of studies that have synthesized and summarized the central characteristics and insights of (quasi-)experimental studies related to ILP. This study aims to address this gap by synthesizing and characterizing the central characteristics of 38 quasi-experimental and experimental studies related to ILP. In this study, a scoping review is conducted on different quasi-experimental and experimental studies that relate to the framework of ILP. It was found that most studies within the domain of ILP focus on testing the crime reduction effects of using spatio-temporal crime intelligence to deploy police resources more efficiently and effectively. However, some studies have combined different types of crime intelligence or used solely offender-related intelligence. Several statistical-methodological challenges were also identified that should be considered when designing experimental research within the domain of ILP. Additionally, most studies focused solely on measuring crime reduction, with few focusing on secondary effects of interventions. The review concludes that future evaluation studies should consider evaluating the use of different types of crime intelligence and establish specific, objective, and realistic criteria for measuring specific performance measures such as crime disruption. Future experimental research within the domain of ILP should consider applying the 3-i model, evaluating each leg of ILP thoroughly. The limitations of the study are also discussed. This review provides valuable insights for future research and development of ILP-related approaches.

Suggested Citation

  • Robin Khalfa & Wim Hardyns, 2024. "‘Led by Intelligence': A Scoping Review on the Experimental Evaluation of Intelligence-Led Policing," Evaluation Review, , vol. 48(5), pages 797-847, October.
  • Handle: RePEc:sae:evarev:v:48:y:2024:i:5:p:797-847
    DOI: 10.1177/0193841X231204588
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    References listed on IDEAS

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    1. Carter, Jeremy G. & Phillips, Scott W. & Gayadeen, S. Marlon, 2014. "Implementing Intelligence-Led Policing: An Application of Loose-Coupling Theory," Journal of Criminal Justice, Elsevier, vol. 42(6), pages 433-442.
    2. Giovanni Mastrobuoni, 2020. "Crime is Terribly Revealing: Information Technology and Police Productivity," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 87(6), pages 2727-2753.
    3. Anthony Braga & Andrew Papachristos & David Hureau, 2012. "Hot spots policing effects on crime," Campbell Systematic Reviews, John Wiley & Sons, vol. 8(1), pages 1-96.
    4. Andrei O. J. Kwok & Motoki Watabe & Pervaiz K. Ahmed, 2021. "Designing a Laboratory-Based Behavioral Experiment," Springer Books, in: Augmenting Employee Trust and Cooperation, chapter 0, pages 43-53, Springer.
    5. Sobel, Michael E., 2006. "What Do Randomized Studies of Housing Mobility Demonstrate?: Causal Inference in the Face of Interference," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 1398-1407, December.
    6. Kimberly S. Przeszlowski & Vaughn J. Crichlow, 2018. "An Exploratory Assessment of Community-Oriented Policing Implementation, Social Disorganization and Crime in America," Social Sciences, MDPI, vol. 7(3), pages 1-16, February.
    7. Paul M. Collier, 2006. "Policing and the Intelligent Application of Knowledge," Public Money & Management, Taylor & Francis Journals, vol. 26(2), pages 109-116, April.
    8. G. O. Mohler & M. B. Short & Sean Malinowski & Mark Johnson & G. E. Tita & Andrea L. Bertozzi & P. J. Brantingham, 2015. "Randomized Controlled Field Trials of Predictive Policing," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 110(512), pages 1399-1411, December.
    9. Carter, Jeremy G. & Mohler, George & Raje, Rajeev & Chowdhury, Nahida & Pandey, Saurabh, 2021. "The Indianapolis harmspot policing experiment," Journal of Criminal Justice, Elsevier, vol. 74(C).
    Full references (including those not matched with items on IDEAS)

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