Abstract
The world’s population has grown rapidly. Thus, new challenges have arisen in terms of people’s quality of life, natural resources renewal, and urban environment sustainability. The smart city concept was developed to deal with these challenges by incorporating new technologies in order to find solutions that preserve cities’ environment while promoting their residents’ wellbeing. However, for cities to be truly “smart”, they should be evaluated, and, to that end, determinants that facilitate their creation need to be identified. This study thus sought to combine cognitive mapping and the system dynamics approach to find which factors foster smart city success, as well as the cause-and-effect relationships among these determinants. In two groupwork sessions, a panel of experts identified a wide range of smart city determinants and analyzed the dynamics of their relationships. The results were validated by the panel members and senior representatives of Cascais and Évora City Councils, Portugal, who confirmed that the analysis system developed provides a deeper understanding of this research context. The advantages and limitations of the proposed framework are also discussed.
Highlights
Over time, the need to convert urban areas into smart cities has become an increasingly pressing concern for all governments because these cities can have positive impacts on transportation systems, the environment, the economy, and residents
The main limitations found in previous studies on this topic were: (1) the unclear way in which smart city determinants have been identified; and (2) no research that has conducted analyses of the dynamics between determinants
The present study proposed a decision-support model based on cognitive mapping techniques, which facilitated the aggregation of determinants from the most varied areas of smart cities
Summary
The need to convert urban areas into smart cities has become an increasingly pressing concern for all governments because these cities can have positive impacts on transportation systems, the environment, the economy, and residents. Smart cities require citizens to become involved so that a relationship develops between infrastructure and residents, workers, or visitors (Castanho et al, 2021) These strategies culminate in and translate into a strategic vision of sustainability and environmental protection that pays attention to the limited nature of natural resources increasingly under pressure. The applied method took a constructivist stance, and it used the strategic options development and analysis (SODA) method ology (Ackermann and Eden, 2001), which is based on cognitive map ping. The latter tool structures complex problems and facilitated the identification of smart city determinants based on the values, experience, and knowledge of an expert panel. Section five con cludes the paper by highlighting the main contributions to theory and practice and offering suggestions for future research
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