IDEAS home Printed from https://ideas.repec.org/a/gam/jsoctx/v12y2022i6p156-d962607.html
   My bibliography  Save this article

Incorporating Survey Perceptions of Public Safety and Security Variables in Crime Rate Analyses for the Visegrád Group (V4) Countries of Central Europe

Author

Listed:
  • Usman Ghani

    (Department for Regional Sciences and Public Policy, Széchenyi István University, 9026 Gyor, Hungary)

  • Peter Toth

    (Department for Regional Sciences and Public Policy, Széchenyi István University, 9026 Gyor, Hungary)

  • Dávid Fekete

    (Department for Regional Sciences and Public Policy, Széchenyi István University, 9026 Gyor, Hungary)

Abstract

Public governance has evolved in terms of safety and security management, incorporating digital innovation and smart-analytics-based tools to visualize abundant data collections. Urban safety and security are vital social problems that have many branches to be solved, simplified, and improved. Currently, we can see that data-driven insights have often been incorporated into planning, forecasting, and fighting such challenges. The literature has extensively indicated several aspects of solving urban safety problems, i.e., social, technological, administrative, urban, and societal. We have a keen interest in the data analysis and smart analytics options that can be deployed to enhance the presentation, promotional analysis, planning, forecasting, and fighting of these problems. For this, we chose to focus on crime statistics and public surveys regarding victimization and perceptions of crime. As we found through a review, many studies have indicated the vitality of crime rates but not public perceptions in decision-making and planning regarding security. There is always a need for the integration of widespread data insights into unified analyses. This study aimed to answer (1) how effectively we can utilize the crime rates and statistics, and incorporate community perceptions and (2) how promising these two ways of seeing the same phenomena are. For the data analysis, we chose four neighboring countries in Central Europe. We selected CECs, i.e., Hungary, Poland, Czech Republic, and Slovakia, known collectively as the Visegrád Group or V4. The data resources were administrative police statistics and ESS (European Social Survey) statistical datasets. The choice of this region helped us reduce variability in regional dynamics, regime changes, and social control practices.

Suggested Citation

  • Usman Ghani & Peter Toth & Dávid Fekete, 2022. "Incorporating Survey Perceptions of Public Safety and Security Variables in Crime Rate Analyses for the Visegrád Group (V4) Countries of Central Europe," Societies, MDPI, vol. 12(6), pages 1-19, November.
    • Handle: RePEc:gam:jsoctx:v:12:y:2022:i:6:p:156-:d:962607
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2075-4698/12/6/156/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2075-4698/12/6/156/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Altindag, Duha T., 2012. "Crime and unemployment: Evidence from Europe," International Review of Law and Economics, Elsevier, vol. 32(1), pages 145-157.
    2. Simon Christopher Moore, 2006. "The value of reducing fear: an analysis using the European Social Survey," Applied Economics, Taylor & Francis Journals, vol. 38(1), pages 115-117.
    3. Curtis, John, 2012. "The Environment Review 2012," Research Series, Economic and Social Research Institute (ESRI), number RS26.
    4. Butot, Vivien & Bayerl, Petra Saskia & Jacobs, Gabriele & de Haan, Freek, 2020. "Citizen repertoires of smart urban safety: Perspectives from Rotterdam, the Netherlands," Technological Forecasting and Social Change, Elsevier, vol. 158(C).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Usman Ghani & Peter Toth & Fekete David, 2023. "Predictive Choropleth Maps Using ARIMA Time Series Forecasting for Crime Rates in Visegrád Group Countries," Sustainability, MDPI, vol. 15(10), pages 1-15, May.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Iddisah Sulemana, 2015. "The Effect of Fear of Crime and Crime Victimization on Subjective Well-Being in Africa," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 121(3), pages 849-872, April.
    2. François, Abel & Magni-Berton, Raul & Weill, Laurent, 2014. "Abortion and crime: Cross-country evidence from Europe," International Review of Law and Economics, Elsevier, vol. 40(C), pages 24-35.
    3. Meloni, Osvaldo, 2014. "Does poverty relief spending reduce crime? Evidence from Argentina," International Review of Law and Economics, Elsevier, vol. 39(C), pages 28-38.
    4. Divya Sadana, 2020. "Effects of Early Childhood Exposure to Pollution on Crime: Evidence from 1970 Clean Air Act," 2020 Papers psa1864, Job Market Papers.
    5. Stéphane Mahuteau & Rong Zhu, 2016. "Crime Victimisation and Subjective Well‐Being: Panel Evidence From Australia," Health Economics, John Wiley & Sons, Ltd., vol. 25(11), pages 1448-1463, November.
    6. Siwach, Garima, 2018. "Unemployment shocks for individuals on the margin: Exploring recidivism effects," Labour Economics, Elsevier, vol. 52(C), pages 231-244.
    7. Andrei N. Ershov & Aleksandra A. Salatova*, 2018. "Unemployment and the Unemployed in Russia: Features, Structure, Dynamics from 2000 to 2016," The Journal of Social Sciences Research, Academic Research Publishing Group, vol. 4, pages 48-53, 11-2018.
    8. Divya Sadana, 2023. "Effects of Early Childhood Exposure to Pollution on Crime: Evidence from 1970 Clean Air Act," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 84(1), pages 279-312, January.
    9. Usman Ghani & Peter Toth & Fekete David, 2023. "Predictive Choropleth Maps Using ARIMA Time Series Forecasting for Crime Rates in Visegrád Group Countries," Sustainability, MDPI, vol. 15(10), pages 1-15, May.
    10. Christopher L Ambrey & Christopher M Fleming & Matthew Manning, 2013. "The life satisfaction approach to estimating the cost of crime: An individual's willingness-to-pay for crime reduction," Discussion Papers in Economics economics:201301, Griffith University, Department of Accounting, Finance and Economics.
    11. Troy Lorde & Mahalia Jackman & Simon Naitram & Shane Lowe, 2016. "Does crime depend on the “state” of economic misery?," International Journal of Social Economics, Emerald Group Publishing Limited, vol. 43(11), pages 1124-1134, November.
    12. Clément, Matthieu & Piaser, Lucie, 2021. "Do inequalities predict fear of crime? Empirical evidence from Mexico," World Development, Elsevier, vol. 140(C).
    13. Audi, Marc & Poulin, Marc & Ali, Amjad, 2023. "Determinants of Human Wellbeing and its Prospect Under the Role of Financial Inclusion in South Asian Countries," MPRA Paper 120119, University Library of Munich, Germany.
    14. Adriana Villamarin Garcia, 2011. "Prevenir y calcular una estimacion de los costos de la violencia homicida en Colombia," Documentos de CERAC 9108, CERAC -Centro de Recursos para el Análisis de Conflictos.
    15. Woei-Chyuan Wong & Adilah Azhari & Nur Adiana Hiau Abdullah & Chee Yin Yip, 2019. "Estimating the impact of crime risk on housing prices in Malaysia," International Journal of Housing Markets and Analysis, Emerald Group Publishing Limited, vol. 13(5), pages 769-789, November.
    16. Luigi M. Solivetti, 2018. "Immigration, socio-economic conditions and crime: a cross-sectional versus cross-sectional time-series perspective," Quality & Quantity: International Journal of Methodology, Springer, vol. 52(4), pages 1779-1805, July.
    17. Jawadi, Fredj & Mallick, Sushanta K. & Idi Cheffou, Abdoulkarim & Augustine, Anish, 2021. "Does higher unemployment lead to greater criminality? Revisiting the debate over the business cycle," Journal of Economic Behavior & Organization, Elsevier, vol. 182(C), pages 448-471.
    18. Amedeo Argentiero & Bruno Chiarini & Elisabetta Marzano, 2015. "Tax Evasion and Economic Crime. Empirical Evidence for Italy," CESifo Working Paper Series 5497, CESifo.
    19. Ahmed Tukur Umar & Moh’d Shahwahid Hajj Othman, 2017. "Causes and consequences of crude oil pipeline vandalism in the Niger delta region of Nigeria: A confirmatory factor analysis approach," Cogent Economics & Finance, Taylor & Francis Journals, vol. 5(1), pages 1353199-135, January.
    20. Fan Meng & Peng Nie & Alfonso Sousa-Poza, 2023. "The intangible costs of overweight and obesity in Germany," Health Economics Review, Springer, vol. 13(1), pages 1-10, December.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsoctx:v:12:y:2022:i:6:p:156-:d:962607. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.