| Title | Ranking cities based on their smartness level using MADM methods |
|---|---|
| ID_Doc | 41333 |
| Authors | Mokarrari, KR; Torabi, SA |
| Title | Ranking cities based on their smartness level using MADM methods |
| Year | 2021 |
| Published | |
| Abstract | Urbanization and its consequent problems are urging cities to become smarter. Developing smart cities calls for a suitable while comprehensive assessment framework to assist city planners and decision-makers to suggest future directions for cities on how to become smarter by evaluating the smartness of cities. In this regard, this study follows two primary purposes. First, we investigate the concept of "smart city" and its pillars. Second, we develop a smartness assessment framework by considering both subjective and objective criteria and employing six effective multi-attribute decision making (MADM) methods. A linear assignment model is formulated to find an aggregated ranking vector using the ranking vectors obtained from these MADM methods. Then, as a case study, five out of the most important cities in Iran are compared and evaluated by adopting the proposed framework. Furthermore, different scenarios are introduced to investigate the sensitivity of results to the distribution of the importance weights amongst criteria. The results demonstrate the significance of the governmental, economic, and environmental indicators in evaluating the smartness of cities. Moreover, Tehran, the capital city of Iran, obtains the best ranking in all the methods and weighting scenarios, while Tabriz has the worst ranking among the cities under study. |
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