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Coping with the Opportunities and Challenges of Smart Policing: A Research Model

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Electronic Government (EGOV 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13391))

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Abstract

The paper aims to examine how police managers cope with the threats and opportunities associated with the implementation of smart policing applications. Smart policing has reshaped the practices of police managers by offering opportunities to improve decisions with data-driven approaches. These new approaches change the traditional ways in which police managers exercise discretion. Using the theoretical lens of coping theory, we develop the foundations for a research model to explain how smart policing stimulates problem-focused and emotion-focused strategies depending on managers’ perceptions of control and discretion. Future empirical studies using the model can inform more broadly on our understanding of how public sector employees respond to data-driven technologies and automated decision-making.

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Author information

Authors and Affiliations

  1. Queen Mary University of London, London, UK

    Muhammad Afzal & Panos Panagiotopoulos

Authors
  1. Muhammad Afzal
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  2. Panos Panagiotopoulos
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Corresponding author

Correspondence to Muhammad Afzal .

Editor information

Editors and Affiliations

  1. Delft University of Technology, Delft, The Netherlands

    Marijn Janssen

  2. Corvinus University of Budapest, Budapest, Hungary

    Csaba Csáki

  3. Linköping University, Linköping, Sweden

    Ida Lindgren

  4. University of the Aegean, Samos, Greece

    Euripidis Loukis

  5. Linköping University, Linköping, Sweden

    Ulf Melin

  6. Danube University Krems, Krems an der Donau, Austria

    Gabriela Viale Pereira

  7. University of Granada, Granada, Spain

    Manuel Pedro Rodríguez Bolívar

  8. University of Macedonia, Thessaloniki, Greece

    Efthimios Tambouris

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Afzal, M., Panagiotopoulos, P. (2022). Coping with the Opportunities and Challenges of Smart Policing: A Research Model. In: Janssen, M., et al. Electronic Government. EGOV 2022. Lecture Notes in Computer Science, vol 13391. Springer, Cham. https://doi.org/10.1007/978-3-031-15086-9_30

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  • DOI: https://doi.org/10.1007/978-3-031-15086-9_30

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-15085-2

  • Online ISBN: 978-3-031-15086-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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