Parameter transfer of common-metric attributes in choice analysis: implications for willingness to pay

There is a growing literature that promotes the presence of a mix of compensatory and semi-compensatory processing strategies in the way that individuals evaluate packages of attributes in real or hypothetical markets, and make choices. This paper proposes a specification for the utility form in a choice model to test if, given a pair of attributes with a common-metric (e.g., components of travel time or cost), the attribute with the dominating level defines the marginal (dis)utility that is assigned to both attributes. We refer to this processing strategy as a parameter transfer rule. We use a stated choice data set, in the context of car driving individuals choosing between tolled and non-tolled routes, to estimate a mixed logit model which incorporates the presence of the parameter transfer rule and the conventional fully compensatory rule, both existing up to a probability. We find that if this parameter transfer heuristic is part of the mix, the WTP is more than 30% higher, on average, than when only a fully compensatory rule is imposed. We also contrast the parameter transfer rule with other semi-compensatory heuristics which have been investigated in other papers, and show that the finding adds further support to the accumulating evidence that a semi-compensatory attribute processing rules tend to result in higher mean WTP estimates compared to the fully compensatory attribute processing rule.     

Aggregation of common-metric attributes in preference revelation and implications for willingness to pay

There is a growing interest in process heterogeneity in the way that individuals evaluate packages of attributes in real or hypothetical markets and make choices. We consider the role of the relative magnitude of pairs of attributes that are defined on a common metric (e.g., minutes or dollars), to look at the extent to which attributes might be added in preference revelation, in contrast to the commonly adopted single rule of compensatory behaviour. The focus is on a choice model specification that allows for different treatments of pairs of attributes across a sample, in contrast to studies that impose a single rule on all observations, and that does not require supplementary information on whether specific individuals claimed to have added up attributes; rather we structure a non-linear utility function that permits a probabilistic aggregation of each attribute. We translate this into a willingness to pay for travel time-savings for car commuters, in the context of tolling roads in Sydney, and contrast it with the results from the additive model, and a model where self-stated attribute processing information is taken into account. The empirical evidence suggests that mean willingness to pay increases when the addition rule is accounted for. This is a potentially important message for environmental applications where two or more attributes have a common metric.     

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).     

An investigation of commuting trip timing and mode choice in the Greater Toronto Area: Application of a joint discrete-continuous model

The trip timing and mode choice are two critical decisions of individual commuters mostly define peak period traffic congestion in urban areas. Due to the increasing evidence in many North American cities that the duration of the congested peak travelling periods is expanding (peak spreading), it becomes necessary and natural to investigate these two commuting decisions jointly. In addition to being considered jointly with mode choice decisions, trip timing must also be modelled as a continuous variable in order to precisely capture peak spreading trends in a policy sensitive transportation demand model. However, in the literature to date, these two fundamental decisions have largely been treated separately or in some cases as integrated discrete decisions for joint investigation. In this paper, a discrete-continuous econometric model is used to investigate the joint decisions of trip timing and mode choice for commuting trips in the Greater Toronto Area (GTA). The joint model, with a multinomial logit model for mode choice and a continuous time hazard model for trip timing, allows for unrestricted correlation between the unobserved factors influencing these two decisions. Models are estimated by occupation groups using 2001 travel survey data for the GTA. Across all occupation groups, strong correlations between unobserved factors influencing mode choice and trip timing are found. Furthermore, the estimated model proves that it sufficiently captures the peak spreading phenomenon and is capable of being applied within the activity-based travel demand model framework.     

Biased standard error estimations in transport model calibration due to heteroscedasticity arising from the variability of linear data projection

Reliable transport models calibrated from accurate traffic data are crucial for predicating transportation system performance and ensuring better traffic planning. However, due to the impracticability of collecting data from an entire population, methods of data inference such as the linear data projection are commonly adopted. A recent study has shown that systematic bias may be embedded in the parameters calibrated due to linearly projected data that do not account for scaling factor variability. Adjustment factors for reducing such biases in the calibrated parameters have been proposed for a generalized multivariate polynomial model. However, the effects of linear data projection on the dispersion of and confidence in the adjusted parameters have not been explored. Without appropriate statistics examining the statistical significance of the adjusted model, their validity in applications remains unknown and dubious. This study reveals that heteroscedasticity is inherently introduced by data projection with a varying scaling factor. Parameter standard errors that are estimated by linearly projected data without any appropriate treatments for non-homoscedasticity are definitely biased, and possibly above or below their true values. To ensure valid statistical tests of significance and prevent exposure to uninformed and unnecessary risk in applications, a generic analytical distribution-free (ADF) method and an equivalent scaling factor (ESF) method are proposed to adjust the parameter standard errors for a generalized multivariate polynomial model, based on the reported residual sum of squares. The ESF method transforms a transport model into a linear function of the scaling factor before calibration, which provides an alternative solution path for achieving unbiased parameter estimations. Simulation results demonstrate the robustness of the ESF method compared with the ADF method at high model nonlinearity. Case studies are conducted to illustrate the applicability of the ESF method for the parameter standard error estimations of six Macroscopic Bureau of Public Road functions, which are calibrated using real-world global positioning system data obtained from Hong Kong.     

Shopping trip mode choice of older adults: an application of activity space and hybrid choice models in understanding the effects of built environment and personal goals

Transportation - Rapid growth of the older population worldwide, coupled with their overreliance on automobile and its negative consequences for the environment and for their wellbeing, has...     

Incorporating equity as part of the wider impacts in transport infrastructure assessment: an application of the SUMINI approach

The state of the art in appraisal of transport infrastructure (particularly for developed countries) is moving towards inclusivity of a set of wider impacts than has traditionally been the case. In appraisal frameworks generally Multi-Criteria Analysis (MCA), features as either an alternative to, or complementary with, Cost Benefit Analysis (CBA) particularly when assessing a wider set of distributional and other impacts. In that respect it goes some way towards addressing an identified weakness in conventional CBA. This paper proposes a new method to incorporate the wider impacts into the appraisal framework (SUMINI) based upon a composite indicator and MCA. The method is illustrated for a particular example of the wider set of impacts, i.e. equity, through the ex-post assessment of two large EU transport infrastructure (TEN-T) case studies. The results suggest that SUMINI assesses equity impacts well and the case studies highlight the flexibility of the approach in reflecting different policy or project objectives. The research concludes that this method should not be viewed as being in competition with traditional CBA, but that it could be an easily adopted and complementary approach. The value in the research is in providing a new and significant methodological advance to the historically difficult question of how to evaluate equity and other wider impacts. The research is of strong international significance due to the publication of the TEN-Ts review by the European Commission, as well as the transnational nature of large scale interurban transport schemes, the involvement of national and transnational stakeholder groups in the approval and funding of those schemes, the large numbers of population potentially subject to equity and other wider impacts and the degree of variation in the regional objectives and priorities for transport decision makers.     

Variation in cost overruns of transportation projects: an econometric meta-regression analysis of studies reported in the literature

Transportation - This paper uses an econometric meta-regression analysis framework to examine how the mean percentage cost overruns (MPCOs) of transportation projects reported in the literature...     

Estimating the value of risk reductions for car drivers when pedestrians are involved: a case study in Spain

We estimated the benefits associated with reducing fatal and severe injuries from traffic accidents using a stated choice experiment where choice situations were generated through a statistically efficient design. Specifically, the risk variables were defined as the expected annual number of vehicle car-users that suffered their death or were severely injured in a traffic accident. In addition, and differing from previous research, the number of pedestrians that died or were severely injured in traffic accidents per year was also included as a risk attribute in the choice experiment, to attempt at measuring drivers’ willingness to pay to reduce the risk of hitting pedestrians in a crash. The empirical setting was a choice of route for a particular trip that a sample of car drivers periodically undertakes in Tenerife, Spain. Models were estimated accounting for random taste heterogeneity and pseudo-panel data correlation. The median of the distribution of simulated parameters was used to obtain a representative measure for the monetary valuation of risk reductions. We found that the ratio between the values of reducing the risk of suffering a serious injury and that of reducing a fatality was approximately 18 %. Further, and quite novel, we also found that the value of reducing a pedestrian fatality was 39 % of the value of reducing a car occupant fatality.     

All minutes are not equal: travel time and the effects of congestion on commute satisfaction in Canadian cities

Despite decades of research, it is unclear under which circumstances travel is most onerous. While studies have found that some individuals derive positive utility from aspects of commuting, others have shown that traffic congestion can entail important time, monetary, and mental stress costs. Moreover, responses to traffic congestion-related stressors differs by individual characteristics. In response, this research captures how exposure to traffic congestion events, the duration of this exposure, and individual trait susceptibility to congestion affect the utility of commuting. Working through the lens of individual satisfaction with the duration of their commute, we show that not every minute of travel is valued the same by car commuters in Canadian cities. Results suggest a complex relationship between travel time, congestion, and individual predisposition to congestion-related stress. While improvements in travel time matter for increasing commute satisfaction, it is reductions in travel in congested conditions that matter most, particularly among those susceptible to congestion-related stressors.     

Modal split models based on car availability: the application of such models in studies of medium sized towns

This paper discusses the need for a new approach to urban transportation modelling in recognition that at least in medium sized towns the choice of model is largely dominated by car availability.     

The limits of partial life cycle assessment studies in road construction practices: A case study on the use of hydrated lime in Hot Mix Asphalt

Extensive published literature shows that hydrated lime improves Hot Mix Asphalt (HMA) durability. Its impact on the environmental impact of HMA has not been investigated. This paper presents a comparative Life Cycle Assessment (LCA) for the use of HMA without hydrated lime (classical HMA) and with hydrated lime (modified HMA) for the lifetime of a highway. System boundaries cover the life cycle from cradle-to-grave, meaning extraction of raw materials to end of life of the road. The main assumptions were: 1. Lifetime of the road 50 years; 2. Classical HMA with a life span of 10 years, maintenance operations every 10 years; 3. Modified HMA with an increase in the life span by 25%, maintenance operations every 12.5 years. For the lifetime of the road, modified HMA has the lowest environmental footprint compared to classical HMA with the following benefits: 43% less primary total energy consumption resulting in 23% lower emissions of greenhouse gases. Partial LCAs focusing only on the construction and/or maintenance phase should be used with caution since they could lead to wrong decisions if the durability and the maintenance scenarios differ. Sustainable construction technologies should not only consider environmental impact as quantified by LCA, but also economic and social impacts as well. Avoiding maintenance steps means less road works, fewer traffic jams and hence less CO₂ emissions.     

开启品牌营销序幕中大破解淡季局面

长期以来,客车市场已经形成一个人尽皆知的潜规则:进入2月份,就意味着进入令人难熬的销售淡季.令人瞩目的是,中大汽车自进入2月份以来,各项指标一再逆向反弹.中大汽车凭什么获得客户的青睐?凭什么走出了一个多年不变的行业宿命?     

A scenario approach to airport evaluation in remote communities: with particular reference to the Pilbara region of Australia

Coordinated development of aviation facilities and services is critical for geographically remote communities. Improvements in aviation capability can be assisted by an analytical base for determining the implications of alternative configurations of air services in terms of links to be served, airport/aerodrome investment, type of flight equipment and flight frequency. We outline a method for identifying airport supply configurations to meet air service demand to and from the Pilbara region of north-west Australia. The approach emphasises minimum levels of demand required from a community in order to justify provision of air services of a given scenario. The method is influenced by the paucity of data on demand in remote communities, and the consequent risk of relying solely on demand-side forecasts of patronage levels. It is therefore particularly useful in assessing transport systems associated with remote resource development projects which are notable for the rapidity of change which they can bring. The approach has relevance to a wide range of transport applications.     

Uncertain benefits: Application of Bayesian melding to the Alaskan Way Viaduct in Seattle

Uncertainty is inherent in major infrastructure projects, but public decision-making for such projects ignores it. We investigate the uncertainty about the future effects of tearing down the Alaskan Way Viaduct in downtown Seattle, using an integrated model of housing, jobs, land use and transportation, on outcomes including average commute times. Our methodology combines the urban simulation model UrbanSim with the regional transportation model. We assess uncertainty using Bayesian melding, yielding a full predictive distribution of average commute times on 22 different routes in 2020. Of these routes, 14 do not include the viaduct and eight do. For the 14 base routes that do not include the viaduct, the predictive distributions overlap substantially, and so there is no indication that removing the viaduct would increase commute times for these routes. For each of the eight routes that do include the viaduct, the 95% predictive interval for the difference in average travel times between the two scenarios includes zero, so there is not strong statistical support for the conclusion that removing the viaduct would lead to any increase in travel times. However, the median predicted increase is positive for each of these routes, with an average of 6 min, suggesting that there may be some measurable increase in travel time for drivers that use the viaduct as a core component of their commute.     

Cost-benefit analysis according to Sen: An application in the evaluation of transport infrastructures in France

Made compulsory in France for major transport infrastructures, cost-benefit analysis is constantly being improved to achieve the best socio-economic evaluation possible. According to the philosopher and economist Amartya Sen, this analysis should meet two requirements: one ethical, the other democratic. We will examine the evaluation procedure in France and highlight the gap between its officially more democratic character and its still insufficiently ethical character, from the viewpoint of this dual requirement.     

Strategies to achieve deep reductions in metropolitan transportation GHG emissions: the case of Philadelphia

ABSTRACT

This paper investigates strategies that could achieve an 80% reduction in transportation emissions from current levels by 2050 in the City of Philadelphia. The baseline daily lifecycle emissions generated by road transportation in the Greater Philadelphia Region in 2012 were quantified using trip information from the 2012 Household Travel Survey (HTS). Emissions were projected to the year 2050 accounting for population growth and trends in vehicle technology for both the Greater Philadelphia Region and the City of Philadelphia. The impacts of vehicle technology and shifts in travel modes on greenhouse gas (GHG) emissions in 2050 were quantified using a scenario approach. The analysis of 12 different scenarios suggests that 80% reduction in emissions is technically feasible through a combination of active transportation, cleaner fuels for public transit vehicles, and a significant market penetration of battery-electric vehicles. The additional electricity demand associated with greater use of electric vehicles could amount to 10.8 TWh/year. The use of plug-in hybrid electric vehicles (PHEV) shows promising results due to high reductions in GHG emissions at a potentially manageable cost.     

Refocusing the Modelling of Freight Distribution: Development of an Economic-Based Framework to Evaluate Supply Chain Behaviour in Response to Congestion Charging

The distribution of freight is a major contributor to the levels of traffic congestion in cities. However it is much neglected in the research and planning activities of government, where the focus is disproportionately on passenger vehicle movements. Despite the recent recognition of the contribution of freight transportation to the performance of urban areas under the rubric of city logistics, we see a void in the study of how the stakeholders in the supply chain might cooperate through participation in distribution networks, to reduce the costs associated with traffic congestion. Given that transport costs are typically over 45 of all distribution costs, with congestion a major contributor in the urban setting, the importance of establishing ways in which supply chain partnerships might cooperate to reduce levels of freight vehicle movements has much merit. This paper sets out a framework to investigate how agents in a retail supply chain might interact more effectively to reduce the costs of urban freight distribution. We propose an interactive agency choice method as a way of formalising a framework for studying the preferences of participants in the supply chain to support specific policy initiatives. Such a framework is a powerful way of investigating the behavioural response of each agent to many policies, including congestion pricing, as a way of improving the efficient flow of traffic in cities.     

Eliminating barriers to nighttime activity participation: the case of on-demand transit in Belleville,Canada

Transportation - Demand-responsive technologies are rapidly changing the transportation landscape. The City of Belleville, Ontario has recently replaced its evening and nighttime fixed route bus...