The subject of place attachment represents a field of study very relevant in urban sociology and in other social sciences, such as environmental psychology. The relationship that individuals have with their own significant places promotes the creation of an emotional bond. This article presents the results of the first wave of an Italian national panel survey (ITA.LI - Italian Lives) on a representative sample of 8776 individuals. An exploratory analysis has been set organizing the variables based on a tripartite level: a macro level (geographical area and size urban area of the municipality of residence), a meso level (linked to the neighborhood of residence) and a micro level (individual characteristics). The multiple regression models offer a much broader overview on the understanding of place attachment predictors, showing how a tripartite setup of variables allows an increasingly explanatory capacity. Finally, among the types of variables included in the models, the predictors belonging to the meso level (neighborhood satisfaction, perceived urban safety, housing satisfaction) appear to be associated significantly more intensely with the dependent variable than with territorial or individual characteristics.
Bottini, L. (2023). The role of neighborhood quality in predicting place attachment: Results from ITA.LI, a newly established nationwide Italian panel survey. CITIES, 143(December 2023) [10.1016/j.cities.2023.104632].
The role of neighborhood quality in predicting place attachment: Results from ITA.LI, a newly established nationwide Italian panel survey
Bottini, L
2023
Abstract
The subject of place attachment represents a field of study very relevant in urban sociology and in other social sciences, such as environmental psychology. The relationship that individuals have with their own significant places promotes the creation of an emotional bond. This article presents the results of the first wave of an Italian national panel survey (ITA.LI - Italian Lives) on a representative sample of 8776 individuals. An exploratory analysis has been set organizing the variables based on a tripartite level: a macro level (geographical area and size urban area of the municipality of residence), a meso level (linked to the neighborhood of residence) and a micro level (individual characteristics). The multiple regression models offer a much broader overview on the understanding of place attachment predictors, showing how a tripartite setup of variables allows an increasingly explanatory capacity. Finally, among the types of variables included in the models, the predictors belonging to the meso level (neighborhood satisfaction, perceived urban safety, housing satisfaction) appear to be associated significantly more intensely with the dependent variable than with territorial or individual characteristics.File | Dimensione | Formato | |
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