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Criteria for Smart City Identification: A Systematic Literature Review

Author

Listed:
  • Oleg Dashkevych

    (Department of Natural Resources and Environment Management, Faculty of Social Sciences, University of Haifa, 199 Aba Khoushy Ave., Mt. Carmel, Haifa 3498838, Israel)

  • Boris A. Portnov

    (Department of Natural Resources and Environment Management, Faculty of Social Sciences, University of Haifa, 199 Aba Khoushy Ave., Mt. Carmel, Haifa 3498838, Israel)

Abstract

The transition towards greater smartness is an emerging trend in the development of modern cities. This transition manifests itself in the widespread adoption of information and communication technologies (ICTs), cloud computing, Internet of Things (IoT), and other technological tools aimed at improving the level of city smartness. Although numerous studies have focused on the smart city (SC) phenomenon, knowledge about empirical criteria that can be used to define a city as “smart” and to measure the degree of a city’s “smartness” remains limited. The present study aims to bridge this knowledge gap by a systematic literature review of recent studies, in which various empirical criteria are used for SC identification. The study helps to identify a total of 48 SC identification metrics, which are further split into three main categories—smart digital technology, living conditions, and environmental (ecological) sustainability. Among these groups of criteria, the “smart digital technology” group of metrics appears to be the most popular, while criteria pertinent to “ecological sustainability” are applied considerably less often. As the study also reveals, only about half of the criteria used by empirical studies for SC identification actually relate to urban residents’ needs, with the rest being general technological measures. Therefore, for a balanced SC assessment, we suggest a ranking system based on the nine most important metrics, which equally represent all the main aspects of the SC phenomenon while placing an emphasis on the improvement of the quality of life of local residents. The proposed system is applied to several major cities across the globe to demonstrate its use and usefulness.

Suggested Citation

  • Oleg Dashkevych & Boris A. Portnov, 2022. "Criteria for Smart City Identification: A Systematic Literature Review," Sustainability, MDPI, vol. 14(8), pages 1-34, April.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:8:p:4448-:d:789578
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    References listed on IDEAS

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    Cited by:

    1. Dashkevych, Oleg & Portnov, Boris A., 2023. "Human-centric, sustainability-driven approach to ranking smart cities worldwide," Technology in Society, Elsevier, vol. 74(C).
    2. Alper Ozpinar, 2023. "A Hyper-Integrated Mobility as a Service (MaaS) to Gamification and Carbon Market Enterprise Architecture Framework for Sustainable Environment," Energies, MDPI, vol. 16(5), pages 1-22, March.
    3. Inese Mavlutova & Dzintra Atstaja & Janis Grasis & Jekaterina Kuzmina & Inga Uvarova & Dagnija Roga, 2023. "Urban Transportation Concept and Sustainable Urban Mobility in Smart Cities: A Review," Energies, MDPI, vol. 16(8), pages 1-16, April.
    4. Jakobsen, Kine & Mikalsen, Marius & Lilleng, Grethe, 2023. "A literature review of smart technology domains with implications for research on smart rural communities," Technology in Society, Elsevier, vol. 75(C).
    5. Dashkevych, Oleg & Portnov, Boris A., 2024. "How can generative AI help in different parts of research? An experiment study on smart cities’ definitions and characteristics," Technology in Society, Elsevier, vol. 77(C).

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