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.     

Intention and willingness to pay for green freight transportation: An empirical examination

The objective of this paper is to explore what motivates consumer intention and willingness to pay for green transportation. The model is based on the theory of planned behavior and explains the relationship between consumer attitude, perceived behavioral control and peer pressure on intention and willingness to pay for a t-shirt that was transported using energy efficient fuel. Data from a survey of U.S. consumers is analyzed. Results suggest consumer attitude and peer pressure are positively associated with intention which is positively associated with willingness to pay. High levels of consumer attitude, perceived behavioral control and intention suggest a positive outlook for organizations investing in green transportation initiatives. Results also suggest a need for organizations and government to market and educate consumers and citizens about the positive implications of green transportation and using energy efficient fuel.     

Rural environment stakeholders and policy making: Willingness to pay to reduce road transportation pollution impact in the Western Pyrenees

In spite of the strategic national and regional development importance of transportation infrastructures, road transportation is one of the major sources of externalities worldwide. Using data collected from 900 residents living in 14 rural towns near the roads crossing the Spanish Pyrenees, we model citizens’ willingness-to-pay (WTP) to reduce noise and air pollution. We collect the data adopting a contingent valuation method (CVM) design and we analyze the data employing a Zero-Inflated Ordered Probit (ZIOP) model, which allows us to account for an excessive number of zero observations. Our results are in contrast with previous studies’ results with regard to environmental attitudes and socio-economic profiles of residents. Our findings indicate that the stakeholders living near major roads have higher incentives to offset environmental costs. Also, younger, better educated, and more environmentally-aware citizens are willing to pay more to reduce externalities, as they are influenced by their values and environmentally friendly sub-culture, possibly fostered during the past 30 years of green movement worldwide campaigning.     

Using spike model to reduce traffic congestion and improve public transportation in Malaysia

In this study, passengers’ willingness to pay (WTP) for and willingness to accept (WTA) improved public transportation and shift to public transportation in Malaysia were examined. Specifically, this study aimed to determine the factors or transport attributes that affect passenger WTA and WTP to shift to public transportation. The adopted methodology was based on a contingent valuation (CV) survey, which was conducted on a representative sample of a cross section in residents of Kajang, in Malaysia. This CV primary survey elicited the demand of passengers for improved public transportation. The spike model was adopted to avoid estimation errors caused by a large percentage of respondents who were unwilling to pay and accept at all. The estimation results showed that the best reduction rate for both travel time and cost was 45% among other amounts that range from 15% to 75%. The best parking cost increment was US$0.30 and the average WTP is US$0.68.     

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.

Social inclusivity through public transportation: a strategic approach to improve quality of life in developing countries

Welfare services such as healthcare and education are commonly recognised as determinants of physical quality of life indices during the early phases of development in the third world. In order to benefit from these services, it is important that the general public have the mobility means to access welfare provision centres. However, very low vehicle ownership under the conditions of low per‐capita incomes and large shares of population living in deep rural areas prevent the masses from accessing such services, thereby retarding the process of social development, which is reflected in the very poor physical quality of life indices in low‐income countries. Public transportation could offer a viable and affordable solution to this apparent ambivalence. It could permit mobility for poor masses in spite of low per‐capita vehicle ownership enabled by the national income levels. The present research demonstrates this strategic niche through an econometric examination of the evolution of the physical quality of life indices such as maternal mortality, infant mortality and literacy as against the healthcare, education and affordable mobility proxies in post‐independent Sri Lanka. The country, which was then referred to as Ceylon, is often cited as a rare example of achieving social inclusion and reduced marginalisation and thereby a high social welfare standing, in spite of relatively poor per‐capita income levels. Copyright © 2015 John Wiley & Sons, Ltd.     

Consumer preferences and willingness to pay for advanced vehicle technology options and fuel types

The automotive industry is witnessing a revolution with the advent of advanced vehicular technologies, smart vehicle options, and fuel alternatives. However, there is very limited research on consumer preferences for such advanced vehicular technologies. The deployment and penetration of advanced vehicular technologies in the marketplace, and planning for possible market adoption scenarios, calls for the collection and analysis of consumer preference data related to these emerging technologies. This study aims to address this need, offering a detailed analysis of consumer preference for alternative fuel types and technology options using data collected in stated choice experiments conducted on a sample of consumers from six metropolitan cities in South Korea. The results indicate that there is considerable heterogeneity in consumer preferences for various smart technology options such as wireless internet, vehicle connectivity, and voice command features, but relatively less heterogeneity in the preference for smart vehicle applications such as real-time traveler information on parking and traffic conditions.     

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).     

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.     

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.     

On finite sample performance of confidence intervals methods for willingness to pay measures

This paper systematically compares finite sample performances of methods to build confidence intervals for willingness to pay measures in a choice modeling context. It contributes to the field by also considering methods developed in other research fields. Various scenarios are evaluated under an extensive Monte Carlo study. Results show that the commonly used Delta method, producing symmetric intervals around the point estimate, often fails to account for skewness in the estimated willingness to pay distribution. Both the Fieller method and the likelihood ratio test inversion method produce more realistic confidence intervals for small samples. Some bootstrap methods also perform reasonably well, in terms of effective coverage. Finally, empirical data are used to illustrate an application of the methods considered.     

Willingness to accept longer commutes for better salaries: Understanding the differences within and between couples

This paper reports on an analysis aiming to understand differences across individual people in their willingness to accept increased commuting time in return for higher salary, using Hierarchical Bayes (HB) analysis of a dataset collected in Sweden. We find that socio-demographic and attitudinal differences are significant in explaining the variations in values of time for individuals, in particular income, who drives when carpooling and hours worked per week. Additionally we also examine the values of individuals when their choices also impact on the salary and commute of their partner, finding that incomes, income differentials, driving behaviour when carpooling, division of housework and car user decisions significantly explain the values assigned to others and variations in an individual’s own values once their partner is affected. The overall richness of the results reflect the benefits that posterior analysis can bring, and highlight the computational efficiency of Bayesian methods in producing such conditionals at an individual level.     

城市公共交通发展的动力机制研究

城市公共交通发展动力涵盖政府的主导作用、公交运营企业的主动力、公众的支持力以及营销传播的助动力等"四方力量",四方力量的协同推动城市公共交通系统快速发展。首先对城市公共交通发展的动力机制进行分析,研究快速发展面临的困境以及进行公共交通系统动力协调的必要性;然后提出强化政府主导作用的"4P"发展策略、激发公交运营企业主动力的品牌服务策略、拓展公众支持力的乘客关系管理策略、发挥营销传播助动力的促销策略等公共交通协同发展策略;由此增强公共交通竞争力,提高公交出行方式分担率,推动城市可持续发展。     

A cognitive framework to plan for the future of transportation

ABSTRACT

Automated, connected, electrified, and shared mobility will be cornerstones of the transportation future. Research to quantify the potential benefits and drawbacks of practice, and to identify barriers to adoption, is the first step in any strategic plan for their adoption. However, uncertainties, complexity, interdependence, and the multidisciplinary nature of emerging transportation technologies make it difficult to organize and identify focused research. The contribution of this work is a cognitive framework to help planners and policymakers organize broad topics, reveal challenges, discover ideas for solutions, quantify potential impacts, and identify implications to guide preparation strategies. The authors provide example cognitive frameworks for connected, automated, and electrified vehicles.