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Influencing operational policing strategy by predictive service analytics

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conference contribution
posted on 19.10.2017 by Lisa Jackson, Melanie-Jane Stoneman, Heather Callaghan, Hanjing Zhang, Christina Latsou, Sarah Dunnett, Lei Mao
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.

History

School

  • Aeronautical, Automotive, Chemical and Materials Engineering

Department

  • Aeronautical and Automotive Engineering

Published in

Hawaii International Conference on System Science

Citation

JACKSON, L.M. ... et al, 2017. Influencing operational policing strategy by predictive service analytics. Presented at the Hawaii International Conference on System Sciences (HICSS-51), Hawaii, 3rd-6th January 2018.

Publisher

University of Hawaii at Manoa © The Authors

Version

AM (Accepted Manuscript)

Publisher statement

This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/

Acceptance date

22/09/2017

Publication date

2017

Notes

This is a conference paper.

Publisher version

Language

en

Location

Hawaii

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