Transport infrastructures, environment impacts and tourists' welfare: a choice experiment to elicit tourist preferences in Siena–Italy

Abstract

Transport infrastructures have been investigated as drivers of tourist demand. Specific attention has been devoted to air transport infrastructure and services. However, the literature on this issue is scanty. Moreover, few studies focus on ex-ante valuation of tourists' preferences for mobility systems. This study contributes to this literature by presenting a case study on the re-organization of the mobility system to access the city of Siena, Italy. A choice experiment is carried out to elicit tourists' preferences for distance, time, cost, travel mode, along with the environmental impact of infrastructure. The latter factor turns out to be particularly relevant in explaining tourists' choices and welfare. Furthermore, the results appear to be robust and not significantly dependent on design settings (specifically the number of alternatives). While these results only refer to a single case study, they seem to suggest that new transportation facilities do not necessarily cause an increase in tourism flows.

Keywords:

• choice experiment
• tourist preferences
• environmental impact
• transport infrastructures
• air transportation

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1. The special report of the European Court of Auditors (2014) found that EU funding was provided in many cases to airports in close proximity to each other. This produced poor value for money and over capacity. The Court also observes that seven of the airports examined are not profitable.

2. A detailed document may be found on the web: http://www.comitatoampugnano.it/numeri_progetto.html.

3. Flyvbjerg, Skamris Holm, and Buhl (2005) carried out an analysis of traffic forecasts in rail infrastructure projects. Their sample comprised 210 projects in 14 countries. They evidenced that in the 90% of cases forecasters generally overestimated the demand for transportation.

4. It is worth noting that the literature on tourism and sustainability is continuously increasing. See, for example, Da Costa and Carvalho (2011) for food chain sustainability; Gössling et al. (2005) for analysis of eco-efficiency aspects; Gössling et al. (2012) for the impacts of climate change on tourist demand; Patterson, Niccolucci, and Bastianoni (2007) for the ecological footprint.

5. For a detailed survey of the literature, see De Dios Ortuzar and Willumsen (2011).

6. A more profound description of the context is available in Bimonte, Ferrini, and Grilli (2014).

7. Different strategies for capturing the relationship between distance and time were tested, but the constrained design offered the best D-error performance.

8. Considering how the questionnaire was administered, the non-response rate was very moderate. Less than 30 respondents declined to take part in the survey.

9. The distance to Pisa is higher than 80 km, but by road and rail network it is possible to access Siena in roughly 100 minutes.

10. Ideally, we could have used a pivot experimental design built on each respondent actual travel characteristics but this would have required a Computerized Personal Interview.

11. The non-linearity of the attribute cost has been tested following the procedure in Marcucci and Gatta (2014).

12. Results are available upon request.

13. Results are available upon request.

14. This ratio can be interpreted as a marginal rate of substitution.

15. As the cost is the only random term, the WTP is not a function of two mixing distributions as in other mixed logit studies. In these cases the reader should refer to Train (2003), Greene, Hensher, and Rose (2005) and Daly, Hess, and Train (2011).