Strategic classification of smart city strategies in developing countries
Smart cities represent the forefront of combining technological innovation with urban management to enhance the quality of life and sustainability of urban environments. While existing studies have focused on individual smart city evaluations, there is a notable gap in systematic classification appr...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-01-01
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| Series: | Engineering Science and Technology, an International Journal |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2215098624003227 |
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| author | Mesut Samasti Emre Cakmak Alper Ozpinar |
| author_facet | Mesut Samasti Emre Cakmak Alper Ozpinar |
| author_sort | Mesut Samasti |
| collection | DOAJ |
| description | Smart cities represent the forefront of combining technological innovation with urban management to enhance the quality of life and sustainability of urban environments. While existing studies have focused on individual smart city evaluations, there is a notable gap in systematic classification approaches that can handle uncertain and incomplete data in developing countries. As urban populations continue to grow, the strategic integration of smart technologies in city planning and management becomes crucial, necessitating more sophisticated evaluation methodologies. These technologies offer promising solutions to urban challenges by improving efficiency, economic growth, and citizen engagement. This research addresses this gap by proposing a novel framework that combines Interval Valued Neutrosophic Sets (IVNS) with the EDAS Method, specifically designed to handle the complexities and uncertainties inherent in developing country contexts.The study extensively reviews existing literature and methodologies applied in similar contexts, identifying key limitations in current approaches and building a robust framework that incorporates both new and established criteria. Through the systematic application of IVNS-EDAS methodology across multiple urban environments, this study develops a comprehensive classification system that accounts for both quantitative metrics and qualitative assessments of smart city capabilities. The results showcase a dynamic classification framework that effectively handles data uncertainty while providing clear, actionable insights for urban planners and policymakers. The paper concludes by validating the effectiveness of the proposed approach through a detailed computational study involving diverse stakeholders, confirming its applicability and utility in refining smart city strategies globally, particularly in developing country contexts where data reliability and completeness may be challenging.The study provides specific policy guidelines for each city classification, offering policymakers a structured framework for resource allocation and strategic planning, ranging from foundational infrastructure development in emerging cities to advanced technology integration in metropolitan areas. |
| format | Article |
| id | doaj-art-0ff5591d38b84f41a38fdfb58f331ca8 |
| institution | Kabale University |
| issn | 2215-0986 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Engineering Science and Technology, an International Journal |
| spelling | doaj-art-0ff5591d38b84f41a38fdfb58f331ca82025-01-09T06:14:04ZengElsevierEngineering Science and Technology, an International Journal2215-09862025-01-0161101936Strategic classification of smart city strategies in developing countriesMesut Samasti0Emre Cakmak1Alper Ozpinar2TUBITAK TUSSIDE, Barış Koşuyolu Caddesi Dr. Zeki Acar Cad., No:1, 41400 Gebze/Kocaeli, TurkeyIstinye University, Industrial Engineering Department, Istanbul, Turkey; Corresponding author.İbn Haldun University, Istanbul TurkeySmart cities represent the forefront of combining technological innovation with urban management to enhance the quality of life and sustainability of urban environments. While existing studies have focused on individual smart city evaluations, there is a notable gap in systematic classification approaches that can handle uncertain and incomplete data in developing countries. As urban populations continue to grow, the strategic integration of smart technologies in city planning and management becomes crucial, necessitating more sophisticated evaluation methodologies. These technologies offer promising solutions to urban challenges by improving efficiency, economic growth, and citizen engagement. This research addresses this gap by proposing a novel framework that combines Interval Valued Neutrosophic Sets (IVNS) with the EDAS Method, specifically designed to handle the complexities and uncertainties inherent in developing country contexts.The study extensively reviews existing literature and methodologies applied in similar contexts, identifying key limitations in current approaches and building a robust framework that incorporates both new and established criteria. Through the systematic application of IVNS-EDAS methodology across multiple urban environments, this study develops a comprehensive classification system that accounts for both quantitative metrics and qualitative assessments of smart city capabilities. The results showcase a dynamic classification framework that effectively handles data uncertainty while providing clear, actionable insights for urban planners and policymakers. The paper concludes by validating the effectiveness of the proposed approach through a detailed computational study involving diverse stakeholders, confirming its applicability and utility in refining smart city strategies globally, particularly in developing country contexts where data reliability and completeness may be challenging.The study provides specific policy guidelines for each city classification, offering policymakers a structured framework for resource allocation and strategic planning, ranging from foundational infrastructure development in emerging cities to advanced technology integration in metropolitan areas.http://www.sciencedirect.com/science/article/pii/S2215098624003227Sustainable Urban DevelopmentSmart City StrategiesSmart City ClassificationInterval Valued Fuzzy EDAS |
| spellingShingle | Mesut Samasti Emre Cakmak Alper Ozpinar Strategic classification of smart city strategies in developing countries Engineering Science and Technology, an International Journal Sustainable Urban Development Smart City Strategies Smart City Classification Interval Valued Fuzzy EDAS |
| title | Strategic classification of smart city strategies in developing countries |
| title_full | Strategic classification of smart city strategies in developing countries |
| title_fullStr | Strategic classification of smart city strategies in developing countries |
| title_full_unstemmed | Strategic classification of smart city strategies in developing countries |
| title_short | Strategic classification of smart city strategies in developing countries |
| title_sort | strategic classification of smart city strategies in developing countries |
| topic | Sustainable Urban Development Smart City Strategies Smart City Classification Interval Valued Fuzzy EDAS |
| url | http://www.sciencedirect.com/science/article/pii/S2215098624003227 |
| work_keys_str_mv | AT mesutsamasti strategicclassificationofsmartcitystrategiesindevelopingcountries AT emrecakmak strategicclassificationofsmartcitystrategiesindevelopingcountries AT alperozpinar strategicclassificationofsmartcitystrategiesindevelopingcountries |