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Revealing the smartness level of cities via a cutting-edge integrated multi-criteria framework
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DOI：10.1080/12265934.2026.2657014.png)
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Abstract
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What factors make cities ‘smart’ and how they should be ranked in terms of smartness have been essential focuses of smart city research. Valid and reliable answers to this question can be achieved by creating valid and reliable criterion sets, supporting them with high-quality empirical studies, and enriching them with local contributions from diverse countries and cities. This study develops a new set of criteria for ranking the smart cities and establishes a context-specific, evidence-based framework by evaluating implemented projects. The approach incorporates both objective and subjective data, utilizing the WENSLO and BWM methods to determine the weights of criteria and the AROMAN method for ranking alternatives in smart cities. The results indicate that ‘environment and health monitoring’ has the highest priority and that the importance of environmental sustainability coincides with many studies in the literature. Although the priority rankings of the criteria ‘mobility and transportation’ and ‘energy and utilities’ are supported by previous studies, significant inter-study deviations show up in these criteria. The study also reveal that non-metropolitan cities implementing smart city projects are ranked higher, showing that concrete projects, rather than population density, are decisive in the ranking of smart cities. The results imply that more importance should be given to cities' project performances on their way to becoming smart and that not only their demographic size or geographical location, but also smartprojects are vital determining factors. Based on the Turkish sample, the study contributes to the smart city ranking process by providing project-based insights towards becoming smart, offering a more realistic, scientifically backed ranking system.
Developes a new set of criteria for smart cities.
Offers an MCDM model including WENSLO, BWM, and AROMAN methods for analysis.
Evaluates Turkish smart city candidates to show the model’s applicability.
The driver ‘environment and health monitoring’ has the highest priority.
Keywords:
Smart cities
smart city evaluation
urbanization
MCDM
AROMAN
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