{"title":"规划的偏好异质性,住房和城市绿地的案例","authors":"Jianfei Li, Ioulia.V. Ossokina, Theo.A. Arentze","doi":"10.1016/j.cities.2025.106344","DOIUrl":null,"url":null,"abstract":"<div><div>Developing urban green space (UGS) is a widely considered way to mitigate negative effects of climate change and improve the quality of living environments in cities. Since UGS has to compete with other land-use demands, land-use models offer a valuable tool to optimize the spatial allocation of UGS. Current methods to empirically estimate the land-use models, however, do not take into account preference heterogeneity that may exist in a population. In this paper, we apply a latent class model on data from a stated choice experiment to estimate housing preferences related to locational characteristics. Three classes that differ in the utilities attached to accessibility, green and price characteristics of a housing location emerge. The estimates are used to specify a housing land-use allocation model that represents the preferences of the different classes. The result of an application to a housing area development problem shows that taking the preference heterogeneity into account can increase the total housing utility value for residents significantly.</div></div>","PeriodicalId":48405,"journal":{"name":"Cities","volume":"167 ","pages":"Article 106344"},"PeriodicalIF":6.6000,"publicationDate":"2025-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Planning for preference heterogeneity, the case of housing and urban green space\",\"authors\":\"Jianfei Li, Ioulia.V. Ossokina, Theo.A. Arentze\",\"doi\":\"10.1016/j.cities.2025.106344\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Developing urban green space (UGS) is a widely considered way to mitigate negative effects of climate change and improve the quality of living environments in cities. Since UGS has to compete with other land-use demands, land-use models offer a valuable tool to optimize the spatial allocation of UGS. Current methods to empirically estimate the land-use models, however, do not take into account preference heterogeneity that may exist in a population. In this paper, we apply a latent class model on data from a stated choice experiment to estimate housing preferences related to locational characteristics. Three classes that differ in the utilities attached to accessibility, green and price characteristics of a housing location emerge. The estimates are used to specify a housing land-use allocation model that represents the preferences of the different classes. The result of an application to a housing area development problem shows that taking the preference heterogeneity into account can increase the total housing utility value for residents significantly.</div></div>\",\"PeriodicalId\":48405,\"journal\":{\"name\":\"Cities\",\"volume\":\"167 \",\"pages\":\"Article 106344\"},\"PeriodicalIF\":6.6000,\"publicationDate\":\"2025-08-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Cities\",\"FirstCategoryId\":\"96\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0264275125006456\",\"RegionNum\":1,\"RegionCategory\":\"经济学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"URBAN STUDIES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cities","FirstCategoryId":"96","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0264275125006456","RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"URBAN STUDIES","Score":null,"Total":0}
Planning for preference heterogeneity, the case of housing and urban green space
Developing urban green space (UGS) is a widely considered way to mitigate negative effects of climate change and improve the quality of living environments in cities. Since UGS has to compete with other land-use demands, land-use models offer a valuable tool to optimize the spatial allocation of UGS. Current methods to empirically estimate the land-use models, however, do not take into account preference heterogeneity that may exist in a population. In this paper, we apply a latent class model on data from a stated choice experiment to estimate housing preferences related to locational characteristics. Three classes that differ in the utilities attached to accessibility, green and price characteristics of a housing location emerge. The estimates are used to specify a housing land-use allocation model that represents the preferences of the different classes. The result of an application to a housing area development problem shows that taking the preference heterogeneity into account can increase the total housing utility value for residents significantly.
期刊介绍:
Cities offers a comprehensive range of articles on all aspects of urban policy. It provides an international and interdisciplinary platform for the exchange of ideas and information between urban planners and policy makers from national and local government, non-government organizations, academia and consultancy. The primary aims of the journal are to analyse and assess past and present urban development and management as a reflection of effective, ineffective and non-existent planning policies; and the promotion of the implementation of appropriate urban policies in both the developed and the developing world.