Journal of Sustainable Urban & Regional Development Studies (JSURDS)

Abstract Background and Objective: The smart city, as a modern approach to urban management, aims to enhance quality of life, service efficiency, and sustainable development through advanced information technologies, citizen participation, and data-driven decision-making. This study evaluates and ranks the neighborhoods of Tehran's District 6 based on the development level of smart city indicators.
Methodology: The research is applied in nature and employs a descriptive-analytical method. Initially, smart city indicators were identified through a review of theoretical sources, followed by the development of a specialized questionnaire based on the COCOSO model. Field data were collected from 30 urban planning experts, including university professors and municipal officials, using snowball sampling. The Shannon entropy method was used to determine the weight of each indicator, and the COCOSO decision-making model was applied to rank the neighborhoods.
Results and Findings: Results indicate that Neighborhood 4, with a score of 5.442, ranks first, followed by Neighborhood 5 (5.411) and Neighborhood 6 (5.118) in second and third places, respectively. Neighborhoods 3, 1, and 2 rank fourth to sixth with scores of 4.099, 3.322, and 1.447, respectively. The findings suggest that balanced smart city development in this district requires targeted policymaking, enhanced digital infrastructure, and leveraging local capacities in each neighborhood.
Conclusion: These results highlight that utilizing local advantages, particularly in lower-performing neighborhoods, can significantly contribute to improving smart city indicators and reducing spatial inequalities.

Abstract Background and Objective: With the rapid pace of urbanization and its associated environmental challenges, novel approaches such as the smart sustainable city and green infrastructure have become essential. However, the gap between theory and practice, particularly regarding the prioritization of interventions, persists. This study was conducted with the objective of analyzing the impact of green infrastructure on the realization of a smart sustainable city and providing a data-driven framework for spatial prioritization in the metropolis of Karaj.
Methodology: This is an applied study employing a descriptive-analytical method. Initially, 24 key variables were identified and distributed to 30 experts via a questionnaire. Subsequently, using a hybrid approach, the Cross-Impact Matrix Multiplication Applied to Classification (MICMAC) technique was utilized to identify key drivers, and the Combined Compromise Solution (CoCoSo) method was employed to rank the readiness of the 11 urban districts of Karaj.
Results and Findings: The results indicated that seven drivers, including "permeable surfaces," "ecological corridors," "investment," and "integrated governance," are the most powerful factors influencing the system. Furthermore, the CoCoSo analysis identified District 5 as the most suitable area for initiating projects. The findings emphasize that a successful transition to a smart sustainable city requires an integrated strategy that simultaneously focuses on physical infrastructure, governance factors, and economic incentives, and that policies must be formulated based on spatial priorities. Ultimately, this study shows that the realization of a smart sustainable city in Karaj is only possible through an integrated strategy that incorporates the key physical, governance, and economic drivers within specific spatial priorities.