Quantifying travellers' willingness to pay for the Harbour Tunnel in Copenhagen
A stated choice study
ResearchPublished Mar 20, 2018
This study uses a stated choice experiment to quantify travellers' willingness to pay for a tolled tunnel in Copenhagen. Discrete choice models are used to quantify travellers' value of travel time savings. The discrete choice models take account of systematic heterogeneity in terms of traveller and trip characteristics and random heterogeneity.
A stated choice study
ResearchPublished Mar 20, 2018
This study quantifies the willingness of car and light van travellers to pay to use a proposed new tolled tunnel to travel across the harbour in central Copenhagen. The crucial issue in predicting whether drivers will choose to pay the toll is to understand the 'value of time' (VTT) of each driver; that is, the value that each is willing to pay to save a minute of his or her time (and that of the passengers, if any) and whether they have a bias against tolls. To fulfil the research purpose, a stated choice (SC) experiment was undertaken with 3,688 travellers in cars and vans travelling in the relevant corridor. Discrete choice models (DCM) were then developed to quantify travellers' VTTs. We found that DCMs with multiplicative error structures gave a better fit to the data and more reasonable estimates for VTT and travellers with higher incomes and those who made longer journeys placed higher value on travel time savings. We observe significant random heterogeneity in the value of free flow and congested travel times for commute and other travel, in addition to systematic variation by income, trip length and other measured socio-economic covariates. In contrast to other work, we find little evidence of reference dependence in the survey responses or that the survey recruitment methodology impacted the resulting VTTs. We find that respondents reacted more negatively to tolls than other driving costs, but not significantly so.
This study was commissioned the Danish Road Directorate. RAND Europe was responsible for the survey design and model analysis.
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