This paper analyses the effect of access and egress time to train stations and airports on modal competition in the Madrid-Barcelona corridor, (Spain), where a new high speed train started to operate in the year 2008. The analysis is based on the estimation of a Nested Logit model that uses a mixed revealed/stated preference data set that provides information on travellers’ behaviour in the available modes. We obtained the value of the different components of the travel time, as well as the willingness to pay for other service attributes. We then analysed demand response to different policies that consider variation in access time to train stations and airports and other attributes. The results highlight the important role that access time to terminals may play in terms of modal competition between rail and plane for interurban travel passengers.
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Martín and Nombela (2007) analysed that, after the investments in HST in Spain, the interurban market shares for railways will rise from 8.9% in 2000 to 22.8% in 2010. They concluded that, in a 10-year period, the share of railways in total interurban transport demand in Spain could increase almost threefold.
It is well known that accessibility measures usually encapsulate abstract concepts such as spatial interaction and utility. These constructs are usually more important than others such as location or proximity. However, in this paper, accessibility will only be addressed by the access times to terminals–airports and train stations, as a way to proxy this concept in our empirical paper. Of course, we are aware that other sophisticated measures could also be proposed. Reggiani (1998) presented a good summary of the measures and indicators that could be considered proxies to analyse accessibility.
It is important to point out that the new HST will reduce the in-vehicle travel time for the train by approximately 50%.
This variable was used in the specification of the model, as we will see below.
This method is known in the literature as the Bradley and Daly nested logit trick.
It was not included in the final model.
Ben-Akiva ME, Morikawa T (1990) Estimation of travel demand models from multiple data sources. Proceedings of the 11th International Symposium on Transportation and Traffic Theory, Yokohama
Bradley MA, Daly AJ (1997) Estimation of logit choice models using mixed stated preference and revealed preference information. In: Stopher PR, Lee-Gosselin M (eds) Understanding travel behavior in an era of change. Pergamon, Oxford, pp 209–232
Cherchi E, Ortúzar JD (2004) On fitting mode-specific constants in the presence of new options in RP/SP models. Transp Res 40A:1–18
Domencich TA, McFadden D (1975) Urban Travel Demand. A Behavioural Analysis. North Holland, Amsterdam
Givoni M, Rietveld P (2007) The access journey to the railway station and its role in passengers’ satisfaction with rail travel. Transp Policy 14(5):357–365
Hensher DA (2003) Revealing differences in willingness to pay due to the dimensionality of stated choice designs: an initial assessment. Design of Designs Report #1, Institute of Transport Studies, The University of Sydney
Jara-Díaz SR (1998) Time and income in travel choice: towards a microeconomic activity-based theoretical framework. In: Garling T, Laitila T, Westin K (eds) Theoretical foundations of travel choice modeling. Elsevier Science, New York, pp 51–74
Jara-Díaz SR, Farah M (1987) Transport demand and users’ benefits with fixed income: the goods/leisure trade-off revisited. Transp Res 21B:165–170
Louviere JJ, Hensher DA, Swait JD (2000) Stated choice methods: analysis and application. Cambridge University Press, Cambridge
Martens K (2004) The bicycle as a feedering mode: experiences from three European countries. Transp Res D 9:281–294
Martín JC, Nombela G (2007) Microeconomic impacts of investments in high speed trains in Spain. Ann Reg Sci 41(3):715–733
McFadden D (1981) Econometric models of probabilistic choice. In: Manski C, Mcfadden D (eds) Structural analysis of discrete choice data with econometric applications. MIT Press, Cambridge, pp 198–272
Ortúzar JD, Willumsen LG (2001) Modelling Transport, 3rd edn. Wiley, Chichester
Reggiani A (1998) Accessibility, trade and location behaviour: an introduction. In: Reggiani A (ed) Accessibility. Trade and Location Behaviour. Ashgate, Aldershot, pp 1–16
Rietveld P (2000) The accessibility of railway stations: the role of the bicycle in The Netherlands. Transp Res D 5:71–75
Wardman M, Tyler J (2000) Rail network accessibility and the demand for inter-urban rail travel. Transp Rev 20(1):3–24
Williams HCWL (1977) On the formation of travel demand models and economic evaluation measures of user benefit. Environ Plan 9A:167–219
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Román, C., Martín, J.C. Special Issue on New Frontiers in Accessibility Modelling: The Effect of Access Time on Modal Competition for Interurban Trips: The Case of the Madrid-Barcelona Corridor in Spain. Netw Spat Econ 11, 661–675 (2011). https://doi.org/10.1007/s11067-011-9158-7
- Access time
- Intermodal competition
- Mixed RP/SP data