Toll product preferences and implications for alternative payment options and going cashless

There has been a great deal of research on deriving estimates of the value of travel time savings (VTTS) as a way of converting travel time benefits of toll roads relative to free routes into monetary units, the major user benefit in the development of forecasts of traffic and hence revenue streams. By contrast there has been almost no consideration given to identifying the role that various tollroad products play in establishing preferences for toll routes over non-tolled routes. Increasingly tollroads give users the option to pay by cash at a toll booth, by electronic tolling or by a pre- or post-paid debit and credit account system involving vehicle identification. The efficiency gained by electronic tolling for both the users and the operator have resulted in moves in many jurisdictions to eliminate cash collection entirely (or not introduce it when introducing a new tolled road facility), and to introduce a range of pre- and post-payment options. This has been accompanied by a growing move to distance-based charging in some contexts which is more cumbersome to structure with a cash option. This paper investigates current and potential travellers’ preferences for a range of toll products and how much individual’s are willing to pay for very specific toll products. Data from a stated choice experiment is used in a mixed logit model to establish the role that toll products play in the context of offered times and costs of alternative routes, in choosing between alternative ways of paying for the use of tolled routes.

Can value capture work in a car dependent city? Willingness to pay for transit access in Perth,Western Australia

This paper investigates the impact of transit on urban land markets in the highly car dependent corridors of Perth with a focus on where new fast rail transit services have recently been built. It determines people’s willingness to pay for transit access within different pedestrian catchments for each of the corridors based on hedonic price modelling using land value data on over 460,000 households. The case study uses cross sectional and panel data hedonic price modelling methodology for the calculation of willingness to pay for transit. It finds that land market increases of up to 40% can be achieved, and is particularly relevant to car dependent cities looking to capture the financial and economic value created to build transit extensions or entirely new systems, thus making a strong case for value capture funding of transit projects into car dependent suburbs and the potential for density increases near stations.     

Willingness to pay for improving service quality in a multimodal area

Travellers use the installations at multimodal areas to transfer from one mode of transport to another. In many cases these installations are called interchanges. This article characterises the users of transport interchanges to determine the fundamental attributes which they most value when they pass through the area. A Stated Choice survey is designed and administered and Mixed Logit models are estimated to calculate willingness to pay levels for three main attributes: transfer time, the quality of the available information and the services provided in the area. Travellers place most value on the quality of the information they receive and the available services rather than on transfer time, which contradicts the widely held opinion of experts in the field. This opens up new possibilities in the design of modern interchanges which should concentrate more on being welcoming areas with many information points rather than being based around minimising transfer times.     

Estimating the willingness to pay and value of risk reduction for car occupants in the road environment

In recent years there has been a re-focus on the valuation of a statistical life from the ex post or human capital method to an ex ante willingness to pay (WTP) approach. This is in part a recognition that we may have been undervaluing the cost of fatalities and injuries to society associated with crashes, but also a strong belief in the need to focus on establishing the amount, ex ante, that individuals are willing to pay to reduce the risk of exposure to circumstances that might lead to death or degree of injury on the road network. This study has developed a framework in which to identify the degree of preference heterogeneity in willingness to pay by individuals who are drivers or passengers in cars to avoid being killed or injured. A stated choice experiment approach is developed. The empirical setting is a choice of route for a particular trip that a sample of individuals periodically undertakes in Australia. The particular trip is described in enough detail to provide the respondent with a familiar market environment, providing all the relevant background information required for making a decision. Mixed logit models are estimated to obtain the marginal (dis)utilities associated with each influence on the choice amongst the attribute packages offered in the stated choice scenarios. These estimates are used to obtain the WTP distributions for fatality and injury avoidance, which are then aggregated to obtain estimates of the value of risk reduction (VRR), of which the fatality class is also known as the value of a statistical life (VSL).     

The Signs of the Times: Imposing a Globally Signed Condition on Willingness to Pay Distributions

A feature of recent developments in choice models that enable estimation of the distribution of willingness to pay (WTP) is that the sign of the distribution can change over the range. Behaviourally this often makes little sense for attributes such as travel time on non-discretionary travel, despite a growing recognition of positive utility over some travel time ranges. This can in part be attributed to the analytical distribution that is selected (except the cumbersome lognormal), many of which are unconstrained over the full range. Although a number of analysts have imposed constraints on various distributions for random parameters that can satisfy the single-sign condition, these restrictions are, with rare exception, only satisfied for the mean and the standard deviation estimates of a random parameter. When heterogeneity around the mean and/or heteroscedasticity around the standard deviation is allowed for, however, the constraint condition is often not satisfied. Given the popularity of distributions other than the lognormal, in order to satisfy the sign condition under the most general form of parameterisation, we need to impose a global sign condition. In this paper we show how this might be achieved in the context of the valuation of travel time savings for car commuters choosing amongst an offered set of route-specific travel times and costs. We illustrate the impact of the constraint under a globally constrained Rayleigh distribution for total travel time parameterisation, contrasting the evidence with a multinomial logit model and a range of other distributional assumptions within the mixed logit framework. Discussions with Bill Greene, John Rose, Ken Train and especially Juan de Dios Ortuzar have been invaluable as have the comments of referees.     

Passengers’ willingness to pay for airport ground access time savings

There are cases when passengers are willing to pay a premium to reduce the travel time, in particular when the trip has to be made. This paper aims to provide insight into factors that determine passengers’ willingness to pay to reduce travel time for their ground access to an airport. A methodology is developed that comprises two steps: the identification of the passengers with zero willingness to pay and from the rest the estimation of the additional price they are willing to pay to reduce their travel time. For the first step a Probit model was formulated and for the second a linear regression model. To this purpose, data has been collected employing stated preference from passengers at the Athens International Airport. It has been found that a high percentage of passengers have zero willingness to pay, and of the remaining ones those using public transport have a significant willingness to pay to reduce access travel time. The methodology and the models are structured in such a way that their transferability to any airport environment is possible, thus providing a useful tool for decisions relating to airport ground access measures.     

Are consumers willing to pay to let cars drive for them? Analyzing response to autonomous vehicles

Autonomous vehicles use sensing and communication technologies to navigate safely and efficiently with little or no input from the driver. These driverless technologies will create an unprecedented revolution in how people move, and policymakers will need appropriate tools to plan for and analyze the large impacts of novel navigation systems. In this paper we derive semiparametric estimates of the willingness to pay for automation. We use data from a nationwide online panel of 1260 individuals who answered a vehicle-purchase discrete choice experiment focused on energy efficiency and autonomous features. Several models were estimated with the choice microdata, including a conditional logit with deterministic consumer heterogeneity, a parametric random parameter logit, and a semiparametric random parameter logit. We draw three key results from our analysis. First, we find that the average household is willing to pay a significant amount for automation: about $3500 for partial automation and $4900 for full automation. Second, we estimate substantial heterogeneity in preferences for automation, where a significant share of the sample is willing to pay above $10,000 for full automation technology while many are not willing to pay any positive amount for the technology. Third, our semiparametric random parameter logit estimates suggest that the demand for automation is split approximately evenly between high, modest and no demand, highlighting the importance of modeling flexible preferences for emerging vehicle technology.     

The accuracy of proxy responses in a stated choice setting: A re-examination and some controversial conclusions

Data is typically gathered from an individual respondent who represents the group or the household. This individual is often identified as the “primary decision maker” and is asked to provide responses as a proxy for the group given that the cost of interviewing each member individually is impractical and/or expensive. The collection of joint preferences is rarely undertaken, with the use of proxy responses not uncommon in travel behaviour research. Under such a framework, there exists an assumption that the primary decision maker has perfect knowledge of other group member preferences, and bargaining behaviour, and is able to synthesise this information when providing a response on their behalf. The validity of such an assumption however remains an open question, with recent research calling the reliability of proxy responses into account (Bateman and Munro, 2009). In this paper, using three models estimated in willingness to pay space, we examine the accuracy of proxy responses in a stated choice experiment. We find that there is overlap between a proxy response and the own preferences of the individual providing the proxy choice, but while the proxy responses fail to represent the full preference heterogeneity that exists in the actual choices made by individuals, the proxy responses in aggregate provide a suitable replacement for actual data, subject to a number of caveats.     

Not bored yet - Revisiting respondent fatigue in stated choice experiments

Stated choice surveys are used extensively in the study of choice behaviour across many different areas of research, notably in transport. One of their main characteristics in comparison with most types of revealed preference (RP) surveys is the ability to capture behaviour by the same respondent under varying choice scenarios. While this ability to capture multiple choices is generally seen as an advantage, there is a certain amount of unease about survey length. The precise definition about what constitutes a large number of choice tasks however varies across disciplines, and it is not uncommon to see surveys with up to twenty tasks per respondent in some areas. The argument against this practice has always been one of reducing respondent engagement, which could be interpreted as a result of fatigue or boredom, with frequent reference to the findings of Bradley and Daly (1994) who showed a significant drop in utility scale, i.e. an increase in error, as a respondent moved from one choice experiment to the next, an effect they related to respondent fatigue. While the work by Bradley and Daly has become a standard reference in this context, it should be recognised that not only was the fatigue part of the work based on a single dataset, but the state-of-the-art and the state-of-practice in stated choice survey design and implementation has moved on significantly since their study. In this paper, we review other literature and present a more comprehensive study investigating evidence of respondent fatigue across a larger number of different surveys. Using a comprehensive testing framework employing both Logit and mixed Logit structures, we provide strong evidence that the concerns about fatigue in the literature are possibly overstated, with no clear decreasing trend in scale across choice tasks in any of our studies. For the data sets tested, we find that accommodating any scale heterogeneity has little or no impact on substantive model results, that the role of constants generally decreases as the survey progresses, and that there is evidence of significant attribute level (as opposed to scale) heterogeneity across choice tasks.     

Hypothetical bias in Stated Choice Experiments: Is it a problem? And if so,how do we deal with it?

The extent to which Stated Choice (SC) experiments suffer from hypothetical bias continues to be a controversial topic in the literature. This research provides further evidence in this debate by examining the existence of hypothetical bias in a transport-related SC experiment. Data for this research were sourced from a University of Sydney study exploring the effect of exposure-based charging on motorist behaviour. The sample included 148 Sydney motorists who were recruited to take part in the 10-week GPS driving field study (Revealed Preference/RP data). In addition, participants were also required to complete an SC survey which was designed to mimic the RP decision context in order to capture what participants indicated they would do as opposed to what participants actually did in reaction to the charging regime.The current state of practice for measuring hypothetical bias in the literature is to compare aggregate differences in model outcomes using SC and RP data sources. Aggregate analysis is limited in its scope and does not allow for the calculation of the prevalence of hypothetical bias (i.e., how many participants are affected by hypothetical bias). This research is uniquely structured to allow for individual categorisation of hypothetical bias by comparing SC and RP data from the same sample for the direct purpose of investigating the prevalence of hypothetical bias. Furthermore, the extent to which mitigation techniques (cheap talk and certainty scales) influence hypothetical bias is also explored. The findings from this research show that the SC model estimates are prone to hypothetical bias and that the mitigation techniques have potential to compensate for this inherent bias.