Search citation statements
Paper Sections
Citation Types
Year Published
Publication Types
Relationship
Authors
Journals
The aim of the paper was to identify which European capitals are sustainable and smart, why, and what influences the ranking. The main research hypothesis was to indicate that cities in the ‘old’ E.U. countries (richer and with higher levels of economic development) are more sustainable and smart. Furthermore, sustainable smart cities, by definition, through the use of advanced and modern management tools and technological support, should contribute to community resilience. Sustainable energy plays a significant role in the measurement system. The study’s results showed the differences that exist across countries, as well as the leaders in each smart category and area. This is interesting and new; from a research point of view, there has been no study based on OECD research and data confronting and correlating the range of data with indicators found in the literature. The study results show that the concept of a smart city is comprehensive and that it is necessary to analyze in depth the various sub-categories included in the measurement and assessment of smartness offered by different indicators. This is because it turns out that an overall score and ranking do not always mean that a city is smart in every area and every element included in smart. Statistical methods and literature analysis are used for the study. The results represent a novel development and contribution to the science discipline and can be the basis for further scientific exploration in this area. The research gap and challenge indicate whether there is a link and correlation between the use of sustainable energy in E.U. countries and the implementation of smart concepts in European capitals in the context of the division into ‘new’ and ‘old’ E.U. capitals. An important element is the verification of the thesis that ‘old’ capitals are more advanced in the implementation of smart cities and make greater use of sustainable energy to meet social and economic needs. The thesis has been partly falsified and confirmed negatively; the results are not obvious. It means that the ‘new’ E.U. countries are very skillful in using financial, organizational, and common development policy opportunities to make their cities modern, intelligent, and friendly to their inhabitants.
The aim of the paper was to identify which European capitals are sustainable and smart, why, and what influences the ranking. The main research hypothesis was to indicate that cities in the ‘old’ E.U. countries (richer and with higher levels of economic development) are more sustainable and smart. Furthermore, sustainable smart cities, by definition, through the use of advanced and modern management tools and technological support, should contribute to community resilience. Sustainable energy plays a significant role in the measurement system. The study’s results showed the differences that exist across countries, as well as the leaders in each smart category and area. This is interesting and new; from a research point of view, there has been no study based on OECD research and data confronting and correlating the range of data with indicators found in the literature. The study results show that the concept of a smart city is comprehensive and that it is necessary to analyze in depth the various sub-categories included in the measurement and assessment of smartness offered by different indicators. This is because it turns out that an overall score and ranking do not always mean that a city is smart in every area and every element included in smart. Statistical methods and literature analysis are used for the study. The results represent a novel development and contribution to the science discipline and can be the basis for further scientific exploration in this area. The research gap and challenge indicate whether there is a link and correlation between the use of sustainable energy in E.U. countries and the implementation of smart concepts in European capitals in the context of the division into ‘new’ and ‘old’ E.U. capitals. An important element is the verification of the thesis that ‘old’ capitals are more advanced in the implementation of smart cities and make greater use of sustainable energy to meet social and economic needs. The thesis has been partly falsified and confirmed negatively; the results are not obvious. It means that the ‘new’ E.U. countries are very skillful in using financial, organizational, and common development policy opportunities to make their cities modern, intelligent, and friendly to their inhabitants.
In an era marked by rapid technological progress, the pivotal role of Artificial Intelligence (AI) is increasingly evident across various sectors, including local governments. These governmental bodies are progressively leveraging AI technologies to enhance service delivery to their communities, ranging from simple task automation to more complex engineering endeavours. As more local governments adopt AI, it is imperative to understand the functions, implications, and consequences of these advanced technologies. Despite the growing importance of this domain, a significant gap persists within the scholarly discourse. This study aims to bridge this void by exploring the applications of AI technologies within the context of local government service provision. Through this inquiry, it seeks to generate best practice lessons for local government and smart city initiatives. By conducting a comprehensive review of grey literature, we analysed 262 real-world AI implementations across 170 local governments worldwide. The findings underscore several key points: (a) there has been a consistent upward trajectory in the adoption of AI by local governments over the last decade; (b) local governments from China, the US, and the UK are at the forefront of AI adoption; (c) among local government AI technologies, natural language processing and robotic process automation emerge as the most prevalent ones; (d) local governments primarily deploy AI across 28 distinct services; and (e) information management, back-office work, and transportation and traffic management are leading domains in terms of AI adoption. This study enriches the existing body of knowledge by providing an overview of current AI applications within the sphere of local governance. It offers valuable insights for local government and smart city policymakers and decision-makers considering the adoption, expansion, or refinement of AI technologies in urban service provision. Additionally, it highlights the importance of using these insights to guide the successful integration and optimisation of AI in future local government and smart city projects, ensuring they meet the evolving needs of communities.
The convergence of artificial intelligence (AI) and environmental science offers a promising avenue for addressing the pressing challenges of sustainability. This bibliometric analysis explores the synergistic potential of these fields to advance sustainability goals, focusing on how AI can enhance environmental monitoring, resource management, and policy development. By examining a comprehensive collection of studies, the analysis highlights the critical role of AI-driven approaches in optimizing energy usage, reducing waste, and promoting sustainable practices across various sectors. However, the integration of AI into environmental science also presents significant challenges, including ethical considerations, data privacy concerns, and the need for interdisciplinary collaboration. This study underscores the importance of leveraging AI to foster a resilient and sustainable future, emphasizing collaborative efforts among scientists, technologists, and policymakers.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.