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Expert model of risk assessment for the selected components of smart city concept: From safe time to pandemics as COVID-19

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  • Gavurova, Beata
  • Kelemen, Miroslav
  • Polishchuk, Volodymyr

Abstract

The purpose of the paper is to create an information, fuzzy risk assessment model to support the decision-making of Municipality management for the establishment and management of measures in the safe mode (regular) of City, emergency and disaster situations, in the selected components of Smart City concept. Research on this topic was motivated by the need for support, especially in emergency situations, such as the COVID-19 pandemic. It is proposed that the evaluation be carried out at local level within the framework of the Smart City concept and selected components integrated into the entity, including the Smart Security, Smart Healthcare, and Smart Environment components supported by the Smart WebGIS subsystem. The model also assesses proposed solutions for self-government financing to ensure the acceptable risk, and economic impact of decisions on the city budget within the Smart Budget aspects of selected components. Decision-making is based on intellectual analysis, processing of fuzzy data and use of fuzzy inference. The output of the model is the assessment of the risk of the municipality subsystems, taking into account the threshold for the functioning of the municipality subsystems, the linguistic interpretation of the level of risk and the acceptability of the tolerable risk resource. The model algorithm was used to create a web application to support the Municipal management for the above-mentioned agenda, from safe time to pandemics.

Suggested Citation

  • Gavurova, Beata & Kelemen, Miroslav & Polishchuk, Volodymyr, 2022. "Expert model of risk assessment for the selected components of smart city concept: From safe time to pandemics as COVID-19," Socio-Economic Planning Sciences, Elsevier, vol. 82(PB).
    • Handle: RePEc:eee:soceps:v:82:y:2022:i:pb:s0038012122000313
    DOI: 10.1016/j.seps.2022.101253
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    References listed on IDEAS

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    1. Zbyslaw Dobrowolski, 2020. "After COVID-19. Reorientation of crisis management in crisis," Entrepreneurship and Sustainability Issues, VsI Entrepreneurship and Sustainability Center, vol. 8(2), pages 799-810, December.
    2. Chiehyeon Lim & Paul P. Maglio, 2018. "Data-Driven Understanding of Smart Service Systems Through Text Mining," Service Science, INFORMS, vol. 10(2), pages 154-180, June.
    3. Volodymyr Polishchuk & Miroslav Kelemen & Beáta Gavurová & Costas Varotsos & Rudolf Andoga & Martin Gera & John Christodoulakis & Radovan Soušek & Jaroslaw Kozuba & Peter Blišťan & Stanislav Szabo, 2019. "A Fuzzy Model of Risk Assessment for Environmental Start-Up Projects in the Air Transport Sector," IJERPH, MDPI, vol. 16(19), pages 1-19, September.
    4. Jill Juergensen & José Guimón & Rajneesh Narula, 2020. "European SMEs amidst the COVID-19 crisis: assessing impact and policy responses," Economia e Politica Industriale: Journal of Industrial and Business Economics, Springer;Associazione Amici di Economia e Politica Industriale, vol. 47(3), pages 499-510, September.
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    Cited by:

    1. Borges, Ana & Carvalho, Mariana & Maia, Miguel & Guimarães, Miguel & Carneiro, Davide, 2023. "Predicting and explaining absenteeism risk in hospital patients before and during COVID-19," Socio-Economic Planning Sciences, Elsevier, vol. 87(PB).
    2. Zhai, Wei, 2023. "Risk assessment of China's foreign direct investment in "One Belt, One Road": Taking the green finance as a research perspective," Socio-Economic Planning Sciences, Elsevier, vol. 87(PB).
    3. Pamučar, Dragan & Durán-Romero, Gemma & Yazdani, Morteza & López, Ana M., 2023. "A decision analysis model for smart mobility system development under circular economy approach," Socio-Economic Planning Sciences, Elsevier, vol. 86(C).

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