Evaluation and Ranking of Neighborhoods in Tehran's District 6 Based on the Development of Smart City Indicators and Factors Influencing Their Enhancement

Document Type : Origional Article

Authors

1 Professor, Department of Geography & Rural Planning, Faculty of Planning and Environmental Sciences, University of Tabriz, Tabriz, Iran.

2 Ph.d student. Department of Geography and Urban Planning, Mohaghegh Ardabili University, Ardabil, Iran.

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.

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Articles in Press, Accepted Manuscript
Available Online from 22 November 2025

  • Receive Date 08 April 2025
  • Revise Date 19 May 2025
  • Accept Date 29 May 2025
  • First Publish Date 30 June 2025
  • Publish Date 22 November 2025