Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/113915
Title: Analyzing the main determinants for being an immigrant in Cuenca (Ecuador) based on a fuzzy clustering approach
Authors: Martín Hernández, Juan Carlos 
Bustamante Sánchez, Natalia Soledad
Indelicato, Alessandro 
UNESCO Clasification: 5302 Econometría
520301 Movilidad y migraciones interiores
Keywords: Fuzzy Logic
Fuzzy-Hybrid Cluster
Immigrants
Topsis
Triangular Fuzzy Numbers
Issue Date: 2022
Journal: Axioms 
Abstract: The study aims to analyze the determinants for being an immigrant in Cuenca (Ecuador). Our analysis is based on the answers given to a scale formed by 30 items included in a questionnaire administered to a representative sample of 369 immigrants. A fuzzy hybrid multi-criteria decisionmaking method, TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution), is used to analyze whether immigrants are more or less exigent regarding the items included in the scale to reside in Cuenca. Then, a fuzzy clustering method is applied to analyze the differences observed in the main determinants observed over a number of traits according to their similarities to three obtained profiles: (1) extreme exigent immigrants; (2) extreme unneedful immigrants; and (3) intermediate exigent immigrants. Results show that items such as access to internet and benefits for retirees were highly valued by some immigrants. In addition, the authors found that information channels, reasons for immigrating, house location, main transport mode, income and main income source are the main determinants that differentiate whether the immigrants in Cuenca (Ecuador) are more or less demanding with respect to the exigency scale developed in the study. The main contributions to the body of knowledge, the policy implications and lines for future research are finally discussed.
URI: http://hdl.handle.net/10553/113915
ISSN: 2075-1680
DOI: 10.3390/axioms11020074
Source: Axioms [EISSN 2075-1680], v. 11 (2), 74, (Febrero 2022)
Appears in Collections:Artículos
Adobe PDF (2,46 MB)
Unknown (518,44 kB)
Unknown (518,44 kB)
Show full item record

SCOPUSTM   
Citations

5
checked on Nov 17, 2024

WEB OF SCIENCETM
Citations

4
checked on Nov 17, 2024

Page view(s)

88
checked on Oct 5, 2024

Download(s)

228
checked on Oct 5, 2024

Google ScholarTM

Check

Altmetric


Share



Export metadata



Items in accedaCRIS are protected by copyright, with all rights reserved, unless otherwise indicated.