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dc.contributor.authorLamberti, Giuseppe
dc.contributor.authorAluja Banet, Tomàs
dc.contributor.authorSanchez, Gaston
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Estadística i Investigació Operativa
dc.identifier.citationGiuseppe Lamberti, Aluja, T., Sanchez, G. The Pathmox approach for PLS path modeling segmentation. "Applied stochastic models in business and industry", Agost 2016, vol. 32, núm. 4, p. 453-468.
dc.descriptionThis is the peer reviewed version of the following article: Giuseppe Lamberti, Aluja, T., Sanchez, G. The Pathmox approach for PLS path modeling segmentation. "Applied stochastic models in business and industry", Agost 2016, vol. 32, núm. 4, p. 453-468, which has been published in final form at DOI: 10.1002/asmb.2168. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.
dc.description.abstractModeling has often failed to meet expectations, mostly because of the difficulty of comprehending relationships within phenomena and expressing them in mathematical models. Reality is frequently too complex to be reflected in a single model. This is often the case of marketing research, where variables relating to socioeconomics or psychographics constitute potential sources of heterogeneity. In such cases, the assumption of ‘one model fits all’ is unrealistic and may lead to inaccurate decisions. Thus, heterogeneity is a major issue in modeling. Once a model has been fitted to a complete data set that fulfills all validation criteria, it is difficult to establish whether it is valid for the whole population or it is merely an average artifact from several sub-populations. The purpose of this paper is to present the Pathmox approach to deal with heterogeneity in partial least squares path modeling. The idea behind Pathmox is to build a tree of path models that have look-alike structure as a binary decision tree, with different models for each of its nodes. The split criterion consists of an F statistic comparing two structural models. In order to ensure the suitability of the split criterion, a simulation study was conducted. Finally, we have applied Pathmox to a survey that measured Satisfaction among Spanish mobile phone operators. Results suggest that the Pathmox approach performs adequately in detecting partial least squares path modeling heterogeneity. Copyright © 2016 John Wiley & Sons, Ltd.
dc.format.extent16 p.
dc.subjectÀrees temàtiques de la UPC::Matemàtiques i estadística::Estadística matemàtica::Anàlisi multivariant
dc.subjectÀrees temàtiques de la UPC::Matemàtiques i estadística::Estadística matemàtica::Mètodes estadístics
dc.subject.lcshMultivariate analysis
dc.subject.lcshStochastic processes
dc.subject.otherpartial least squares path modeling
dc.subject.othermodel comparison
dc.subject.othersegmentation trees
dc.titleThe Pathmox approach for PLS path modeling segmentation
dc.subject.lemacAnàlisi multivariable
dc.subject.lemacProcessos estocàstics
dc.contributor.groupUniversitat Politècnica de Catalunya. LIAM - Laboratori de Modelització i Anàlisi de la Informació
dc.description.peerreviewedPeer Reviewed
dc.subject.amsClassificació AMS::62 Statistics::62H Multivariate analysis
dc.subject.amsClassificació AMS::60 Probability theory and stochastic processes::60H Stochastic analysis
dc.rights.accessOpen Access
dc.description.versionPostprint (author's final draft)
local.citation.authorLamberti, Giuseppe; Aluja, T.; Sanchez, G.
local.citation.publicationNameApplied stochastic models in business and industry

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