Meng Cai, Travis Decaminada, Yingjie Li, Noah J. Durst, Eva Kassens-Noor, Mark Wilson
{"title":"Linking smart cities and SDGs through descriptive analysis of US municipalities","authors":"Meng Cai, Travis Decaminada, Yingjie Li, Noah J. Durst, Eva Kassens-Noor, Mark Wilson","doi":"10.1038/s44284-024-00192-9","DOIUrl":null,"url":null,"abstract":"Transforming cities and communities into ‘smart cities’ holds great potential to advance sustainable development goals (SDGs), but where smart initiatives are taking place, and how they link to local SDGs and performance remain unknown. Here we analyze the official websites of US municipalities and identified 397 smart cities. Although our findings do not establish causality, we observed distinct disparities between smart and non-smart cities in educational attainment (SDG 4.3), internet access (SDG 9.c), income inequality (SDG 10.4) and sustainable transportation (SDG 11.2), based on comparisons of American Community Survey data. This study looks at all municipalities in the United States to identify smart cities and their links to SDGs. Through text-mining and manual verification, it identifies 397 smart cities with specific disparities between smart and non-smart cities in several SDGs.","PeriodicalId":501700,"journal":{"name":"Nature Cities","volume":"2 2","pages":"144-148"},"PeriodicalIF":0.0000,"publicationDate":"2025-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nature Cities","FirstCategoryId":"1085","ListUrlMain":"https://www.nature.com/articles/s44284-024-00192-9","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Transforming cities and communities into ‘smart cities’ holds great potential to advance sustainable development goals (SDGs), but where smart initiatives are taking place, and how they link to local SDGs and performance remain unknown. Here we analyze the official websites of US municipalities and identified 397 smart cities. Although our findings do not establish causality, we observed distinct disparities between smart and non-smart cities in educational attainment (SDG 4.3), internet access (SDG 9.c), income inequality (SDG 10.4) and sustainable transportation (SDG 11.2), based on comparisons of American Community Survey data. This study looks at all municipalities in the United States to identify smart cities and their links to SDGs. Through text-mining and manual verification, it identifies 397 smart cities with specific disparities between smart and non-smart cities in several SDGs.