Identificador persistente para citar o vincular este elemento: http://hdl.handle.net/10553/55071
Campo DC Valoridioma
dc.contributor.authorGómez-Déniz, E.en_US
dc.contributor.authorPérez-Rodríguez, J. V.en_US
dc.date.accessioned2019-02-18T16:23:42Z-
dc.date.available2019-02-18T16:23:42Z-
dc.date.issued2019en_US
dc.identifier.issn0160-7383en_US
dc.identifier.urihttp://hdl.handle.net/10553/55071-
dc.description.abstractEmpirically, the length of stay by tourists at their destination usually presents bimodality, overdispersion and non-zero observations, and classical distributions do not seem to fit this type of data very appropriately. In this paper, we introduce two distributions which accommodate bimodality. One is a flexible discrete distribution which can be applied to both bimodal and unimodal data sets. The second distribution is an infinite mixture model that accounts for unobserved heterogeneity in the mean parameter, thus reflecting the heterogeneous preferences of tourists. Both models are suitable for the inclusion of covariates. Our empirical results show that each of these models is suitable and provides a reasonably good fit. Of the two, the infinite mixture model is preferred.
dc.languagespaen_US
dc.publisher0160-7383
dc.relation.ispartofAnnals of Tourism Researchen_US
dc.sourceAnnals of Tourism Research[ISSN 0160-7383],v. 75, p. 131-151en_US
dc.subject.otherAutoregressive Conditional Duration
dc.subject.otherOf-Stay
dc.subject.otherDestinations
dc.subject.otherDeterminants
dc.subject.otherVacation
dc.titleModelling bimodality of length of tourist stayen_US
dc.typeinfo:eu-repo/semantics/Articleen_US
dc.typeArticleen_US
dc.identifier.doi10.1016/j.annals.2019.01.006
dc.identifier.scopus85060302907
dc.identifier.isi000474679500011
dc.contributor.authorscopusid15724912000
dc.contributor.authorscopusid56216749800
dc.description.lastpage151-
dc.description.firstpage131-
dc.relation.volume75-
dc.type2Artículoen_US
dc.contributor.daisngid610603
dc.contributor.daisngid1615612
dc.contributor.wosstandardWOS:Gomez-Deniz, E
dc.contributor.wosstandardWOS:Perez-Rodriguez, JV
dc.date.coverdateMarzo 2019
dc.identifier.ulpgces
dc.description.sjr2,228
dc.description.jcr5908,0
dc.description.sjrqQ1
dc.description.jcrqQ1
dc.description.ssciSSCI
dc.description.erihplusERIH PLUS
item.fulltextSin texto completo-
item.grantfulltextnone-
crisitem.author.deptGIR TIDES- Técnicas estadísticas bayesianas y de decisión en la economía y empresa-
crisitem.author.deptIU de Turismo y Desarrollo Económico Sostenible-
crisitem.author.deptDepartamento de Métodos Cuantitativos en Economía y Gestión-
crisitem.author.deptGIR Finanzas Cuantitativas y Computacionales-
crisitem.author.deptDepartamento de Métodos Cuantitativos en Economía y Gestión-
crisitem.author.orcid0000-0002-5072-7908-
crisitem.author.orcid0000-0002-6738-9191-
crisitem.author.parentorgIU de Turismo y Desarrollo Económico Sostenible-
crisitem.author.parentorgDepartamento de Métodos Cuantitativos en Economía y Gestión-
crisitem.author.fullNameGómez Déniz, Emilio-
crisitem.author.fullNamePérez Rodríguez, Jorge Vicente-
Colección:Artículos
Vista resumida

Google ScholarTM

Verifica


Comparte



Exporta metadatos



Los elementos en ULPGC accedaCRIS están protegidos por derechos de autor con todos los derechos reservados, a menos que se indique lo contrario.