Integration is a multidimensional process, which can take place in different ways and at different times in relation to each of the single economic, social, cultural, and political dimensions. Hence, examining every single dimension is important as well as building composite indexes simultaneously inclusive of all dimensions in order to obtain a complete description of a complex phenomenon and to convey a coherent set of information. In this paper, we aim at building an immigrant integration composite indicator (IICI), able to measure the different aspects related to integration such as employment, education, social inclusion, active citizenship, and on the basis of which to simultaneously classify territorial areas such as European regions. For this application, the data collected in 274 European regions from the European Social Survey (ESS), Round 8, on immigration have been used.

Construction of an Immigrant Integration Composite Indicator through the Partial Least Squares Structural Equation Model K-Means / Tomaselli, Venera; Fordellone, Mario; Vichi, Maurizio. - (2020), pp. 353-366. - STUDIES IN CLASSIFICATION, DATA ANALYSIS, AND KNOWLEDGE ORGANIZATION. [10.1007/978-3-030-51222-4_28].

Construction of an Immigrant Integration Composite Indicator through the Partial Least Squares Structural Equation Model K-Means

Tomaselli, Venera;Fordellone, Mario;Vichi, Maurizio
2020

Abstract

Integration is a multidimensional process, which can take place in different ways and at different times in relation to each of the single economic, social, cultural, and political dimensions. Hence, examining every single dimension is important as well as building composite indexes simultaneously inclusive of all dimensions in order to obtain a complete description of a complex phenomenon and to convey a coherent set of information. In this paper, we aim at building an immigrant integration composite indicator (IICI), able to measure the different aspects related to integration such as employment, education, social inclusion, active citizenship, and on the basis of which to simultaneously classify territorial areas such as European regions. For this application, the data collected in 274 European regions from the European Social Survey (ESS), Round 8, on immigration have been used.
2020
Data Science and Social Research II
978-3-030-51221-7
978-3-030-51222-4
Immigrant integration, Composite indicator, Structural equation modeling, Partial least squares
02 Pubblicazione su volume::02a Capitolo o Articolo
Construction of an Immigrant Integration Composite Indicator through the Partial Least Squares Structural Equation Model K-Means / Tomaselli, Venera; Fordellone, Mario; Vichi, Maurizio. - (2020), pp. 353-366. - STUDIES IN CLASSIFICATION, DATA ANALYSIS, AND KNOWLEDGE ORGANIZATION. [10.1007/978-3-030-51222-4_28].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1463154
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