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Please use this identifier to cite or link to this item: https://dspace.lboro.ac.uk/2134/27001

Title: Influencing operational policing strategy by predictive service analytics
Authors: Jackson, Lisa M.
Stoneman, Melanie-Jane
Callaghan, Heather
Zhang, Hanjing
Latsou, Christina
Dunnett, Sarah J.
Mao, Lei
Issue Date: 2017
Publisher: University of Hawaii at Manoa © The Authors
Citation: JACKSON, L.M. ... et al, 2017. Influencing operational policing strategy by predictive service analytics. Hawaii International Conference on System Sciences (HICSS-51), Hawaii, 3rd-6th January 2018.
Abstract: Everyday there are growing pressures to ensure that services are delivered efficiently, with high levels of quality and with acceptability of regulatory standards. For the Police Force, their service requirement is to the public, with the police officer presence being the most visible product of this criminal justice provision. Using historical data from over 10 years of operation, this research demonstrates the benefits of using data mining methods for knowledge discovery in regards to the crime and incident related elements which impact on the Police Force service provision. In the UK, a Force operates over a designated region (macro-level), which is further subdivided into Beats (micro-level). This research also demonstrates differences between the outputs of micro-level and macro-level analytics, where the lower level analysis enables adaptation of the operational Policing strategy. The evidence base provided through the analysis supports decisions regarding further investigations into the capability of flexible neighbourhood policing practices; alongside wider operations i.e. optimal officer training times.
Description: This conference paper is closed access until after the conference has taken place.
Version: Accepted for publication
URI: https://dspace.lboro.ac.uk/2134/27001
Publisher Link: http://hicss.hawaii.edu/
Appears in Collections:Closed Access (Aeronautical and Automotive Engineering)

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