Identificador persistente para citar o vincular este elemento: http://hdl.handle.net/10553/46360
Título: Modelling mode choice for freight transport using advanced choice experiments
Autores/as: Arencibia Perez, Ana Isabel 
Feo Valero, María
García Menéndez, Leandro
Román García, Concepción 
Clasificación UNESCO: 531212 Transportes y comunicaciones
Palabras clave: Transportes frigoríficos
Logística
Fecha de publicación: 2015
Editor/a: 0965-8564
Publicación seriada: Transportation Research Part A: Policy and Practice 
Resumen: In this paper we use advanced choice modelling techniques to analyse demand for freight transport in a context of modal choice. To this end, a stated preference (SP) survey was conducted in order to estimate freight shipper preferences for the main attributes that define the service offered by the different transport modes. From a methodological point of view, we focus on two critical issues in the construction of efficient choice experiments. Firstly, in obtaining good quality prior information about the parameters; and secondly, in the improved quality of the experimental data by tailoring a specific efficient design for every respondent in the sample.With these data, different mixed logit models incorporating panel correlation effects and accounting for systematic and random taste heterogeneity are estimated. For the best model specification we obtain the willingness to pay for improving the level of service and the elasticity of the choice probabilities for the different attributes. Our model provide interesting results that can be used to analyse the potential diversion of traffic from road (the current option) to alternative modes, rail or maritime, as well as to help in the obtaining of the modal distribution of commercial traffic between Spain and the European Union, currently passing through the Pyrenees.
URI: http://hdl.handle.net/10553/46360
ISSN: 0965-8564
DOI: 10.1016/j.tra.2015.03.027
Fuente: Transportation Research Part A: Policy and Practice[ISSN 0965-8564],v. 75, p. 252-267
Colección:Artículos
Vista completa

Citas SCOPUSTM   

86
actualizado el 08-sep-2024

Citas de WEB OF SCIENCETM
Citations

70
actualizado el 08-sep-2024

Visitas

92
actualizado el 04-may-2024

Google ScholarTM

Verifica

Altmetric


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.