Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/112169
Title: Values of travel time for recreational trips under different behavioural rules
Authors: González, Rosa Marina
Román García, Concepción 
Marrero, Ángel Simón
UNESCO Clasification: 531290 Economía sectorial: turismo
Keywords: Discrete choice models
Random regret minimization
Random utility maximization
Revealed preferences
Value of time
Issue Date: 2021
Project: Design of a Sustainable Mobility Plan for visitors to the Teide National Park and Evaluation of the Implementation of ‘Cycle’ Lanes in Tenerife
Journal: Sustainability (Switzerland) 
Abstract: In this study, discrete choice models that combine different behavioural rules are estimated to study the visitors’ preferences in relation to their travel mode choices to access a national park. Using a revealed preference survey conducted on visitors of Teide National Park (Tenerife, Spain), we present a hybrid model specification—with random parameters—in which we assume that some attributes are evaluated by the individuals under conventional random utility maximization (RUM) rules, whereas others are evaluated under random regret minimization (RRM) rules. We then compare the results obtained using exclusively a conventional RUM approach to those obtained using both RUM and RRM approaches, derive monetary valuations of the different components of travel time and calculate direct elasticity measures. Our results provide useful instruments to evaluate policies that promote the use of more sustainable modes of transport in natural sites. Such policies should be considered as priorities in many national parks, where negative transport externalities such as traffic congestion, pollution, noise and accidents are causing problems that jeopardize not only the sustainability of the sites, but also the quality of the visit.
URI: http://hdl.handle.net/10553/112169
ISSN: 2071-1050
DOI: 10.3390/su13126831
Source: Sustainability (Switzerland) [ISSN 2071-1050], v. 13(12), 6831, (Junio 2021)
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