Using multiple correspondence analysis to determine recommended professional profiles for Smart Cities projects

The absence of clearly defined professional profiles for Smart City engineers and technicians motivated this study, which aims to identify their key functions and skill requirements. An international survey was conducted among relevant stakeholders involved in Smart City projects to shape those two...

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Detalles Bibliográficos
Autores: López Baldominos, Inés, Pospelova, Vera, Caballé Cervigón, Nuria, Fernández Sanz, Luis
Tipo de recurso: artículo
Fecha de publicación:2026
País:España
Institución:Universidad Complutense de Madrid (UCM)
Repositorio:Docta Complutense
Idioma:inglés
OAI Identifier:oai:docta.ucm.es:20.500.14352/133882
Acceso en línea:https://hdl.handle.net/20.500.14352/133882
Access Level:acceso abierto
Palabra clave:Engineers
ESCO
Multiple correspondence analysis
Multivariate data analysis
Professional profiles
Smart cities
Technicians
Estadística aplicada
Informática (Informática)
1209.03 Análisis de Datos
1209.09 Análisis Multivariante
1203.17 Informática
id ES_5b8bfda7552ceafdf2b73fb83a074023
oai_identifier_str oai:docta.ucm.es:20.500.14352/133882
network_acronym_str ES
network_name_str España
repository_id_str
spelling Using multiple correspondence analysis to determine recommended professional profiles for Smart Cities projectsLópez Baldominos, InésPospelova, VeraCaballé Cervigón, NuriaFernández Sanz, LuisEngineersESCOMultiple correspondence analysisMultivariate data analysisProfessional profilesSmart citiesTechniciansEstadística aplicadaInformática (Informática)1209.03 Análisis de Datos1209.09 Análisis Multivariante1203.17 InformáticaThe absence of clearly defined professional profiles for Smart City engineers and technicians motivated this study, which aims to identify their key functions and skill requirements. An international survey was conducted among relevant stakeholders involved in Smart City projects to shape those two profiles. The collected data were analysed through descriptive statistics and Multiple Correspondence Analysis (MCA), allowing the identification of functional domains that are essential for both roles, while also revealing distinctive patterns between them. The findings show that, although engineers and technicians share core technical competencies, engineers place comparatively greater emphasis on soft and green skills. Overall, the study provides an evidence-based characterisation of Smart City professional profiles, contributing to the refinement of European qualification and skills frameworks.PeerJUniversidad Complutense de Madrid20262026-01-0120262026-01-01journal articlehttp://purl.org/coar/resource_type/c_6501info:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/20.500.14352/133882reponame:Docta Complutenseinstname:Universidad Complutense de Madrid (UCM)Inglésengopen accesshttp://purl.org/coar/access_right/c_abf2Attribution 4.0 Internationalhttp://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessoai:docta.ucm.es:20.500.14352/1338822026-06-02T12:44:21Z
dc.title.none.fl_str_mv Using multiple correspondence analysis to determine recommended professional profiles for Smart Cities projects
title Using multiple correspondence analysis to determine recommended professional profiles for Smart Cities projects
spellingShingle Using multiple correspondence analysis to determine recommended professional profiles for Smart Cities projects
López Baldominos, Inés
Engineers
ESCO
Multiple correspondence analysis
Multivariate data analysis
Professional profiles
Smart cities
Technicians
Estadística aplicada
Informática (Informática)
1209.03 Análisis de Datos
1209.09 Análisis Multivariante
1203.17 Informática
title_short Using multiple correspondence analysis to determine recommended professional profiles for Smart Cities projects
title_full Using multiple correspondence analysis to determine recommended professional profiles for Smart Cities projects
title_fullStr Using multiple correspondence analysis to determine recommended professional profiles for Smart Cities projects
title_full_unstemmed Using multiple correspondence analysis to determine recommended professional profiles for Smart Cities projects
title_sort Using multiple correspondence analysis to determine recommended professional profiles for Smart Cities projects
dc.creator.none.fl_str_mv López Baldominos, Inés
Pospelova, Vera
Caballé Cervigón, Nuria
Fernández Sanz, Luis
author López Baldominos, Inés
author_facet López Baldominos, Inés
Pospelova, Vera
Caballé Cervigón, Nuria
Fernández Sanz, Luis
author_role author
author2 Pospelova, Vera
Caballé Cervigón, Nuria
Fernández Sanz, Luis
author2_role author
author
author
dc.contributor.none.fl_str_mv Universidad Complutense de Madrid
dc.subject.none.fl_str_mv Engineers
ESCO
Multiple correspondence analysis
Multivariate data analysis
Professional profiles
Smart cities
Technicians
Estadística aplicada
Informática (Informática)
1209.03 Análisis de Datos
1209.09 Análisis Multivariante
1203.17 Informática
topic Engineers
ESCO
Multiple correspondence analysis
Multivariate data analysis
Professional profiles
Smart cities
Technicians
Estadística aplicada
Informática (Informática)
1209.03 Análisis de Datos
1209.09 Análisis Multivariante
1203.17 Informática
description The absence of clearly defined professional profiles for Smart City engineers and technicians motivated this study, which aims to identify their key functions and skill requirements. An international survey was conducted among relevant stakeholders involved in Smart City projects to shape those two profiles. The collected data were analysed through descriptive statistics and Multiple Correspondence Analysis (MCA), allowing the identification of functional domains that are essential for both roles, while also revealing distinctive patterns between them. The findings show that, although engineers and technicians share core technical competencies, engineers place comparatively greater emphasis on soft and green skills. Overall, the study provides an evidence-based characterisation of Smart City professional profiles, contributing to the refinement of European qualification and skills frameworks.
publishDate 2026
dc.date.none.fl_str_mv 2026
2026-01-01
2026
2026-01-01
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://hdl.handle.net/20.500.14352/133882
url https://hdl.handle.net/20.500.14352/133882
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution 4.0 International
http://creativecommons.org/licenses/by/4.0/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution 4.0 International
http://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv PeerJ
publisher.none.fl_str_mv PeerJ
dc.source.none.fl_str_mv reponame:Docta Complutense
instname:Universidad Complutense de Madrid (UCM)
instname_str Universidad Complutense de Madrid (UCM)
reponame_str Docta Complutense
collection Docta Complutense
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,812455

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