AN EXPANDED CONCEPTUALIZATION OF “SMART” CITIES: ADDING VALUE WITH FUZZY COGNITIVE MAPS
The world’s population continues to increase rapidly, and, within the next 30 years, more than half of all people will choose to live in large urban centers (Faria et al., 2018). This has led to a number of problems, such as congested people and transportation traffic and increased pollution that produces climate change. The concept of “smart” cities has emerged as a way to deal with these issues, in which these cities are defined as an ecosystem that seeks to improve citizens’ quality of life through a combination of technology, sustainability, and physical infrastructures (Estrada et al., 2018). Smart cities have to use new technologies ranging from the Internet of Things (IoT), which facilitates connections between everything, to home automation (i.e., the ease with which
citizens can manage daily routines through their homes).
Jméno a příjmení autora:
Bárbara P. Miguel, Fernando A. F. Ferreira, Audrius Banaitis, Nerija Banaitienė, Ieva Meidutė-Kavaliauskienė, Pedro F. Falcão
Smart, smart city, smart economy, smart environment, smart governance, smart mobility, cause-and-effect dynamics, fuzzy cognitive mapping
DOI (& full text):
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…více
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.