The Pathmox approach for PLS path modeling: discovering which constructs differentiate segments

This is the peer reviewed version of the following article: Giuseppe Lamberti, Aluja, T., G. S. The Pathmox approach for PLS path modeling: discovering which constructs differentiate segments. "Applied stochastic models in business and industry", Novembre 2017, vol. 33, núm. 6, p. 674-689,...

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Autores: Lamberti, Giuseppe, Aluja Banet, Tomàs|||0000-0003-3096-0339, Sanchez Trujillo, Gaston
Tipo de recurso: artículo
Fecha de publicación:2017
País:España
Institución:Universitat Politècnica de Catalunya (UPC)
Repositorio:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglés
OAI Identifier:oai:upcommons.upc.edu:2117/116172
Acceso en línea:https://hdl.handle.net/2117/116172
https://dx.doi.org/10.1002/asmb.2270
Access Level:acceso abierto
Palabra clave:Mathematical statistics
Numerical analysis--Simulation methods
Fisher F
heterogeneity
models comparison
Partial least squares path modeling
Pathmox
segmentation
Anàlisi numèrica
Estadística matemàtica
Classificació AMS::65 Numerical analysis::65C Probabilistic methods, simulation and stochastic differential equations
Classificació AMS::62 Statistics::62D05 Sampling theory, sample surveys
Àrees temàtiques de la UPC::Matemàtiques i estadística::Probabilitat
Àrees temàtiques de la UPC::Matemàtiques i estadística::Estadística matemàtica
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spelling The Pathmox approach for PLS path modeling: discovering which constructs differentiate segmentsLamberti, GiuseppeAluja Banet, Tomàs|||0000-0003-3096-0339Sanchez Trujillo, GastonMathematical statisticsNumerical analysis--Simulation methodsFisher Fheterogeneitymodels comparisonPartial least squares path modelingPathmoxsegmentationAnàlisi numèricaEstadística matemàticaClassificació AMS::65 Numerical analysis::65C Probabilistic methods, simulation and stochastic differential equationsClassificació AMS::62 Statistics::62D05 Sampling theory, sample surveysÀrees temàtiques de la UPC::Matemàtiques i estadística::ProbabilitatÀrees temàtiques de la UPC::Matemàtiques i estadística::Estadística matemàticaThis is the peer reviewed version of the following article: Giuseppe Lamberti, Aluja, T., G. S. The Pathmox approach for PLS path modeling: discovering which constructs differentiate segments. "Applied stochastic models in business and industry", Novembre 2017, vol. 33, núm. 6, p. 674-689, which has been published in final form at http://onlinelibrary.wiley.com/doi/10.1002/asmb.2270/pdf. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.The problem of heterogeneity represents a very important issue in the decision-making process. Furthermore, it has become common practice in the context of marketing research to assume that different population parameters are possible depending on sociodemographic and psycho-demographic variables such as age, gender, and social status. In recent decades, numerous approaches have been proposed with the aim of involving heterogeneity in the parameter estimation procedures. In partial least squares path modeling, the common practice consists of achieving a global measurement of the differences arising from heterogeneity. This leaves the analyst with the important task of detecting, a posteriori, which are the causal relationships (ie, path coefficients) that produce changes in the model. This is the case in Pathmox analysis, which solves the heterogeneity problem by building a binary tree to detect those segments of population that cause the heterogeneity. In this article, we propose extending the same Pathmox methodology to asses which particular endogenous equation of the structural model and which path coefficients are responsible of the difference.Peer Reviewed20172017-11-0120182018-04-11journal articlehttp://purl.org/coar/resource_type/c_6501AMhttp://purl.org/coar/version/c_ab4af688f83e57aainfo:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/2117/116172https://dx.doi.org/10.1002/asmb.2270reponame:UPCommons. Portal del coneixement obert de la UPCinstname:Universitat Politècnica de Catalunya (UPC)Inglésengopen accesshttp://purl.org/coar/access_right/c_abf2info:eu-repo/semantics/openAccessoai:upcommons.upc.edu:2117/1161722026-05-27T15:37:01Z
dc.title.none.fl_str_mv The Pathmox approach for PLS path modeling: discovering which constructs differentiate segments
title The Pathmox approach for PLS path modeling: discovering which constructs differentiate segments
spellingShingle The Pathmox approach for PLS path modeling: discovering which constructs differentiate segments
Lamberti, Giuseppe
Mathematical statistics
Numerical analysis--Simulation methods
Fisher F
heterogeneity
models comparison
Partial least squares path modeling
Pathmox
segmentation
Anàlisi numèrica
Estadística matemàtica
Classificació AMS::65 Numerical analysis::65C Probabilistic methods, simulation and stochastic differential equations
Classificació AMS::62 Statistics::62D05 Sampling theory, sample surveys
Àrees temàtiques de la UPC::Matemàtiques i estadística::Probabilitat
Àrees temàtiques de la UPC::Matemàtiques i estadística::Estadística matemàtica
title_short The Pathmox approach for PLS path modeling: discovering which constructs differentiate segments
title_full The Pathmox approach for PLS path modeling: discovering which constructs differentiate segments
title_fullStr The Pathmox approach for PLS path modeling: discovering which constructs differentiate segments
title_full_unstemmed The Pathmox approach for PLS path modeling: discovering which constructs differentiate segments
title_sort The Pathmox approach for PLS path modeling: discovering which constructs differentiate segments
dc.creator.none.fl_str_mv Lamberti, Giuseppe
Aluja Banet, Tomàs|||0000-0003-3096-0339
Sanchez Trujillo, Gaston
author Lamberti, Giuseppe
author_facet Lamberti, Giuseppe
Aluja Banet, Tomàs|||0000-0003-3096-0339
Sanchez Trujillo, Gaston
author_role author
author2 Aluja Banet, Tomàs|||0000-0003-3096-0339
Sanchez Trujillo, Gaston
author2_role author
author
dc.subject.none.fl_str_mv Mathematical statistics
Numerical analysis--Simulation methods
Fisher F
heterogeneity
models comparison
Partial least squares path modeling
Pathmox
segmentation
Anàlisi numèrica
Estadística matemàtica
Classificació AMS::65 Numerical analysis::65C Probabilistic methods, simulation and stochastic differential equations
Classificació AMS::62 Statistics::62D05 Sampling theory, sample surveys
Àrees temàtiques de la UPC::Matemàtiques i estadística::Probabilitat
Àrees temàtiques de la UPC::Matemàtiques i estadística::Estadística matemàtica
topic Mathematical statistics
Numerical analysis--Simulation methods
Fisher F
heterogeneity
models comparison
Partial least squares path modeling
Pathmox
segmentation
Anàlisi numèrica
Estadística matemàtica
Classificació AMS::65 Numerical analysis::65C Probabilistic methods, simulation and stochastic differential equations
Classificació AMS::62 Statistics::62D05 Sampling theory, sample surveys
Àrees temàtiques de la UPC::Matemàtiques i estadística::Probabilitat
Àrees temàtiques de la UPC::Matemàtiques i estadística::Estadística matemàtica
description This is the peer reviewed version of the following article: Giuseppe Lamberti, Aluja, T., G. S. The Pathmox approach for PLS path modeling: discovering which constructs differentiate segments. "Applied stochastic models in business and industry", Novembre 2017, vol. 33, núm. 6, p. 674-689, which has been published in final form at http://onlinelibrary.wiley.com/doi/10.1002/asmb.2270/pdf. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.
publishDate 2017
dc.date.none.fl_str_mv 2017
2017-11-01
2018
2018-04-11
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
AM
http://purl.org/coar/version/c_ab4af688f83e57aa
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://hdl.handle.net/2117/116172
https://dx.doi.org/10.1002/asmb.2270
url https://hdl.handle.net/2117/116172
https://dx.doi.org/10.1002/asmb.2270
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
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
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:UPCommons. Portal del coneixement obert de la UPC
instname:Universitat Politècnica de Catalunya (UPC)
instname_str Universitat Politècnica de Catalunya (UPC)
reponame_str UPCommons. Portal del coneixement obert de la UPC
collection UPCommons. Portal del coneixement obert de la UPC
repository.name.fl_str_mv
repository.mail.fl_str_mv
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