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Beneficiaries of Social Disability Pension in Small Municipalities in the Northern Region of Portugal: Application of Cluster Analysis in the Identification of Potential Causes

2022-06-18Journal article Restricted access
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dc.contributor.authorTorres, Cristina
dc.contributor.authorVieira, Isabel
dc.contributor.authorLopes, Isabel Cristina
dc.contributor.authorMonteiro, Rui
dc.contributor.authorFerreira, Carla
dc.contributor.authorBem-Haja, Inês
dc.date.accessioned2023-01-27T08:26:39Z
dc.date.available2023-01-27T08:26:39Z
dc.date.issued2022-06-18
dc.description.abstractThis study is focused on the northern region of Portugal and addresses the number of road accidents with casualties and the number of beneficiaries of the social disability pension. Municipalities with low population density are mostly located in the hinterland. The phenomenon of population aging entails the problem of people who are unable to work and become beneficiaries of the social disability pension. The hierarchical clustering method applied in this paper characterizes 46 municipalities in northern Portugal with a population of less than 20,000 inhabitants – designated small – according to economic activity, rate of road accidents with casualties and disability pensioners. These municipalities were divided into two homogeneous groups or clusters. It was possible to identify that Cluster 1 comprises the innermost municipalities featuring few road accidents with casualties, not many disability pensioners, and a small number of companies compared to Cluster 2. This study can contribute to helping local governments’ decision-making process to improve the economic activity, reduce the region’s human desertification, and improve municipal road conditions.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.doi10.1007/978-3-031-09360-9_18pt_PT
dc.identifier.urihttp://hdl.handle.net/10400.22/21926
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherSpringer, Champt_PT
dc.relationCenter of Organizational and Social Studies of Polytechnic of Porto
dc.relation.ispartofseriesLecture Notes in Mechanical Engineering;
dc.relation.publisherversionhttps://link.springer.com/chapter/10.1007/978-3-031-09360-9_18pt_PT
dc.subjectBeneficiaries of social disability pensionpt_PT
dc.subjectSmall municipalitiespt_PT
dc.subjectNorthern region of Portugalpt_PT
dc.subjectCluster analysispt_PT
dc.subjectHierarchical methodpt_PT
dc.titleBeneficiaries of Social Disability Pension in Small Municipalities in the Northern Region of Portugal: Application of Cluster Analysis in the Identification of Potential Causespt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.awardTitleCenter of Organizational and Social Studies of Polytechnic of Porto
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F05422%2F2020/PT
oaire.citation.endPage219pt_PT
oaire.citation.startPage209pt_PT
oaire.citation.titleInnovations in Industrial Engineering II. ICIENG 2022pt_PT
oaire.fundingStream6817 - DCRRNI ID
person.familyNamePereira Torres
person.familyNameVieira
person.familyNameLopes
person.givenNameCristina
person.givenNameIsabel
person.givenNameIsabel Cristina
person.identifier2277025
person.identifier.ciencia-id111C-A2B8-EBB4
person.identifier.ciencia-id7312-2D3B-F677
person.identifier.ciencia-idBC14-DF88-AEBC
person.identifier.orcid0000-0002-8644-2381
person.identifier.orcid0000-0002-2943-7578
person.identifier.orcid0000-0002-4833-470X
person.identifier.ridA-7445-2017
person.identifier.ridL-7458-2017
person.identifier.scopus-author-id57212003105
person.identifier.scopus-author-id35204338400
person.identifier.scopus-author-id36185835200
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsrestrictedAccesspt_PT
rcaap.typearticlept_PT
relation.isAuthorOfPublication7ff54c60-dca4-47c1-8c5a-6fd3f7d727e0
relation.isAuthorOfPublication537ed579-f575-4d2b-814e-ae6b7a824572
relation.isAuthorOfPublication70af5a18-432a-4ef9-862d-c5a79581c255
relation.isAuthorOfPublication.latestForDiscovery70af5a18-432a-4ef9-862d-c5a79581c255
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