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Abstract
The value of travel time is one of the most important factors in recreation demand models. Traditionally, the most common approach for its calculation has been the use of different proportions of the wage rate; however, criticisms of this method abound because in a recreational trip the relevant measure is the opportunity cost of leisure time rather than work time. In this paper, we adopt a novel approach in the literature using discrete choice models based on short-term decisions and independent of the labor market. We obtain the value of travel time through the trade-off between time and money considered by the tourist visitors when choosing the transport mode and we present the first calculation of the recreational value of the Teide National Park. Specifically, using a Revealed Preference survey of 801 park visitors, we estimate Mixed Logit models accounting for random preference heterogeneity, derive travel time values and incorporate them into a Zonal Travel Cost Method. This approach allows us to estimate different time values depending on transport mode and stage of the trip and shows that the use of discrete choice models instead of the wage rate approach has a strong impact on the recreational value calculated.
Acknowledgments
The authors acknowledge the financial support provided by the Fundación Obra Social CajaCanarias granted for the project entitled “Design of a Sustainable Mobility Plan for visitors to the Teide National Park and Evaluation of the implementation of ‘cycle’ lanes in Tenerife” from which the data has been extracted for this work and by the Agencia Canaria de Investigación, Innovación y Sociedad de la Información through its doctoral thesis support program. We are also grateful to José Juan Cáceres, Julio Angel Afonso, Alfredo Jesús Ramírez and Josué Barrera for their valuable contributions to this work.
Disclosure statement
No potential conflict of interest was reported by the authors.
Notes
1 For a theoretical review of time allocation models see González (Citation1997) and, more recently, Jara-Díaz and Rosales-Salas (Citation2017)
2 Resident visitors have a completely different behavior which requires a different analysis from the one proposed here. They visit more frequently and do not make a choice between transport modes because they access the TNP in their own vehicles and tend visit the park in specific seasons (snow and flowering seasons).
3 Data extracted from “Anuario de Estadística”, Instituto Nacional de Estadística (INE), and “Memorias de la Red de Parques Nacionales”, Ministerio de Agricultura y Pesca, Alimentación y Medioambiente.
4 The high car use compared with public transportation has also been found in other studies on the island: specifically, among university students (González, Marrero, & Cherchi, Citation2017).
5 The differences in the positions of tourists and TNP visitors of different nationalities are due to the fact that tourists from the UK are least likely to go on excursions on the island (26%), while the Germans and Spanish do so the most, with rates of 82% and 78% respectively (“Inbound Tourism Survey”, Tenerife Council Database).
6 The proportions used replicate the information provided by the TNP authorities and the Tenerife Island Council Database.
7 Taxis were excluded since they represented a small fraction of users (0.12%) and their inclusion in the analysis would lead to misleading estimations.
8 “Captives” are visitors who used a tourist bus as a transport mode and whose travel package already included the excursion to the TNP, and who therefore did not make a choice.
9 This is because the majority of drivers were men; hence their overrepresentation.
10 http://www.tenerife.es/bancodatos/
11 Tenerife Council Database, “Tourist who go on excursions”, http://www.tenerife.es/bancodatos/
12 It should be noted that the choke prices in the semi-log dependent and double-log models are infinite, so we choose the price that reduces the visitors for each zone to 1000.
13 In Appendix 2, a simple MATLAB code is provided to replicate the consumer surplus and the consumer surplus per visit of each zone.
14 Source: DGT, "Car fleet dataset by fuel type and region (2015)".
15 The method was applied through the “mi impute pmm” command in STATA 14.
16 The RP survey used in the research project to which this investigation belongs includes more questions. Here we only present the questions that have been used in the estimated models of the present work.
Additional information
Notes on contributors
Rosa Marina González
Rosa Marina González is Associate Professor in Economics at the University of La Laguna (Spain). Her main research interest is in the field of Transport Economics, in particular Discrete Choice Modeling and Willingness to Pay. She is the director of the Chair “Economy and Mobility” (ULL-Fundación Caja Canarias-Cabildo de Tenerife).
Ángel S. Marrero
Ángel S. Marrero is a PhD candidate in the University of La Laguna (Spain) specialized in transport economics, discrete choice modeling, poverty and inequality.
Manuel Navarro-Ibáñez
Manuel Navarro Ibañez is Full Professor at the Departament of Economics, Account and Finances at the University of La Laguna (Spain). He has authored or coauthored thab 40 peer-reviewed papers in the fiel of tourism and economics.