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Measuring urban digitalization using cognitive mapping and the best worst method (BWM)

Author

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  • Vieira, Fabiana C.
  • Ferreira, Fernando A.F.
  • Govindan, Kannan
  • Ferreira, Neuza C.M.Q.F.
  • Banaitis, Audrius

Abstract

Rapid population growth and urbanization have a strong impact on individuals’ well-being. These trends are currently important topics in city management. As a significant driver of digitalization, technological development has been found to have great potential as a mitigator of a wide range of issues that cities face. To ensure the available technologies are being correctly used, municipalities need to measure their degree of digitalization. This assessment is also important to improve city officials’ understanding of areas that need interventions so that cities can be managed better and provide their residents with a better quality of life. This study applies the baseline principles of the multiple-criteria decision analysis (MCDA) approach to develop a decision-support system that facilitates urban digitalization evaluations. The results rely on insights provided by a panel of experts in this area, who used cognitive mapping and the best worst method (BWM) to identify important evaluation criteria within urban digitalization and to analyze their cause-and-effect relationships. The final outcomes were validated by the panel members and representatives of the Associação Nacional de Municípios Portugueses (i.e., National Association of Portuguese Municipalities) and the Agência National de Inovação (i.e., National Innovation Agency). These specialists confirmed that the evaluation system developed facilitates city differentiation in key areas of urban digitalization. The advantages and limitations of the proposed procedures are also discussed.

Suggested Citation

  • Vieira, Fabiana C. & Ferreira, Fernando A.F. & Govindan, Kannan & Ferreira, Neuza C.M.Q.F. & Banaitis, Audrius, 2022. "Measuring urban digitalization using cognitive mapping and the best worst method (BWM)," Technology in Society, Elsevier, vol. 71(C).
    • Handle: RePEc:eee:teinso:v:71:y:2022:i:c:s0160791x2200272x
    DOI: 10.1016/j.techsoc.2022.102131
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    References listed on IDEAS

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    Cited by:

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    2. Siliang Guo & Yanhua Diao & Junliang Du, 2022. "Coupling Coordination Measurement and Evaluation of Urban Digitalization and Green Development in China," IJERPH, MDPI, vol. 19(22), pages 1-32, November.
    3. Wenjing Xu & Seyyed Ahmad Edalatpanah & Ali Sorourkhah, 2023. "Solving the Problem of Reducing the Audiences’ Favor toward an Educational Institution by Using a Combination of Hard and Soft Operations Research Approaches," Mathematics, MDPI, vol. 11(18), pages 1-21, September.
    4. Correia, Inês C. & Ferreira, Fernando A.F. & Zopounidis, Constantin & Ferreira, Neuza C.M.Q.F., 2024. "Urban expansion effects on real estate ecosystems: Identification and neutrosophic analysis of causal dynamics," Socio-Economic Planning Sciences, Elsevier, vol. 93(C).

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