An expanded conceptualization of 'smart' cities: adding value with fuzzy cognitive maps

• Autor(a) principal: Miguel, B. P.
• Data de Publicação: 2019
• Outros Autores: Ferreira, F. A. F., Banaitis, A., Banaitienė, N., Meidute-Kavaliauskiene, I., Falcão, P. F.
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/10071/17643
• topic: Smart; Smart city; Smart economy; Smart environment; Smart governance; Smart mobility; Cause-and-effect dynamics; Fuzzy cognitive mapping

The world’s rapidly growing population is an issue to be taken seriously. Its consequences could be dramatic if the required steps are not taken. Concerns about this problem have led to the creation of “smart” cities, which promote improvements in citizens’ quality of life through a combination of new technologies and environmentally sustainable practices. For these cities to be truly “smart”, they need to be evaluated in order to understand the areas in which interventions are necessary to make these cities economically stable and environmentally sustainable. In this regard, various studies have sought to understand which indicators should be considered in assessments of smart cities and how this process should be conducted. Thus far, however, researchers have found that using “loose” indicators, which measure only some areas of these cities, is insufficient. That said, this study proposes the use of fuzzy cognitive maps to analyze the dynamics behind smart cities’ components. Grounded in intensive group meetings with a panel of experts in different dimensions of these cities, the method applied produced a well-informed, process-oriented framework that contains the characteristics and components that should be assessed in this type of city. Specifically, after a fuzzy cognitive map was constructed based on the direct involvement of the expert participants, six main clusters were extracted as key components in the development of smart cities. These clusters were: people; planning and environments; technology; infrastructure and materials; services; and transportation and mobility. The results also facilitate an improved understanding of smart cities’ cause-and-effect relationships and better strategic planning by urban planners and city administrators. The implications, advantages, and limitations of the proposed framework are also presented.