The best of times and the worst of times: A new best–worst measure of attitudes toward public transport experiences

Attitudes play an important role in determining individual transit behaviour and the measurement of attitudes is relied on by public transit authorities’ world over. Given their role in behaviour and policy making, the accurate measurement of attitudes is of critical importance. Traditional satisfaction scales are prone to bias and on their own they are only a partial measure of attitudes. Given that satisfaction scales have been used to assist with large scale transport infrastructure investment decisions, to aid policy makers examining reactions to alternative policy changes and reform, and to measure the success of new initiatives, deriving robust satisfaction scales should be of critical importance. This paper introduces a dual version of best–worst scaling as an alternative measure of satisfaction. Best–worst scaling is free of the biases inherent in traditional response scales and is ideal for handling the comparative evaluation of large amount of attributes, particularly those which are inherently qualitative. The paper makes a further innovative contribution by proposing a model structure for the joint estimation of satisfaction and importance. Our model shows a better delineation between the attributes used to measure attitudes towards bus use and a more detailed understanding of the relationship between importance and satisfaction; enabling transport operators to better understand what counts most and assess their performance.     

I can’t believe your attitude: a joint estimation of best worst attitudes and electric vehicle choice

The number of conventionally fuelled motor vehicles in use is increasing worldwide despite warnings about finite fossil fuel and the detrimental impacts of burning such fuels. While electric vehicles, the subject of much research, generate far less emissions and offer the potential for power from renewable sources, they are yet to significantly penetrate the market. Tangible barriers such as price and vehicle range still exist, but consumer attitudes also drive behaviour. This paper examines attributes in a framework relatively new to transportation and energy policy; best–worst scaling. This method is widely considered an improvement over traditional methods of eliciting attitudes and beliefs, where respondents select attitudes they find best or worst from a set of attitudinal statements. To avoid potential endogeneity bias, we jointly model attitudes and choice for the first time with best–worst data. It is found that energy crisis, air quality and climate change concerns influence behaviour with respect to vehicle range and that travel behaviour change and forms of government incentives are needed influences on behaviour with respect to vehicle emissions. It is argued that correctly modelling attitudes reduces the error term of the vehicle choice model and provides policy makers with an improved lens for assessing behaviour. Additionally, the methods described within can easily be adapted to other policy scenarios.     

Walk score® and its potential contribution to the study of active transport and walkability: A critical and systematic review

The Walk Score® index has become increasingly applied in studies of walking and walkability. The index assesses the “walking potential” of a place through a combination of three elements: the shortest distance to a group of preselected destinations, the block length, and the intersection density around the origin. The Index links a gravity-based measure (distance accessibility), with topological accessibility (street connectivity) measured by two complementary indicators that act as penalties in the final score (linearly expanded in the range 0–100). A systematic review of Scopus® and Web of Science® was conducted with 42 journal articles eventually being evaluated. Research was primarily undertaken in North American urban geographies. Analysis of walkability using Walk Score® is inconsistent. Twenty-nine papers do not exclusively relying on Walk Score® as a single measurement of walkability and add further estimates to better capture the multiple dimensions of walkability. In 33 studies the Walk Score® was used as an independent variable, and only once as a mediating-moderating variable. In eight papers (18%) the Walk Score® was a part of a bivariate correlation model. On no occasion was it used as a dependent variable. Results tend to only partly support the validity of Walk Score®. The paper concludes that the Index is best understood as a surrogate measure of the density of the built environment of a specific neighborhood that indicates utilitarian walking potential. Implications for, and potential areas of, future research are discussed.     

Modelling journey‐to‐work fuel consumption: a case study of Bayridge subdivision

Fuel consumption is calculated using a modelling procedure for automobiles travelling on three alternative street patterns designed for a subdivision in Kingston Township, Ontario. The modelling procedure is described. The results indicate that grid and solar superblock street patterns, compared to the existing street pattern, offer small fuel savings to a tripmaker in the portion of the work trip travelled in the subdivision.     

Empirical test of a constrained choice discrete model: Mode choice in São Paulo,Brazil

This paper examines the properties and empirically tests a model of discrete choice which incorporates probabilistic choice set generation. Denominated the Parametrized Logit Captivity (PLC) model, it is a generalization of the well-known “dogit” specification. The PLC model is shown to be theoretically and empirically more flexible than the latter. Work mode choice data collected in a 1977 O/D survey in São Paulo, Brazil, is used to obtain parameter estimates, as well as to evaluate consumer reaction to a series of perturbations in travel time, travel cost and income, for both the PLC and Multinomial Logit models. Comparisons between the two specifications are made in terms of statistical fit, reasonableness of predictions and differences in predictions across models.     

Public–private partnerships: a review of economic considerations with particular reference to transportation projects

The paper sets in context some of the more recent work that has been conducted on public–private partnerships (PPPs) in the provision and operation of infrastructure. PPPs essentially involve a government or its agent signing an agreement with a private company or consortium to supply it with services with the private sector actor involved in major elements of designing, building, temporarily ‘owning’, and running the physical assets; basically they are long-term development and service contracts between government and a private partner. The paper outlines the development of economic thinking regarding the rationale behind PPPs, the extent to which unbundling is optimal and the forms that it may take, the nature of the contracts that are enacted and their renegotiation, the awarding of contracts, and matters of possible corruption. By way of focus, it also provides some indication of what empirical studies in the transportation have thrown up regarding the outcomes of PPPs.     

Environmental impacts of high-speed rail links in cost–benefit analyses: a case study of the Dutch Zuider Zee line

Since 2000 it has been formally required in the Netherlands to evaluate major infrastructure projects according to a standard manual. Here the focus is on its application to the Zuider Zee line, a possible rail link to run from the west to the north of the country, starting at Schiphol Airport and ending at the northern towns in the province of Groningen. We put a major emphasis on environmental impacts of the line, including the methods used to estimate impacts and the results. Ways to improve current practice are discussed. A major advantage has been that the environment has been put on the research and policy agenda at an early stage, although insights into the effects of rail infrastructure on the landscape and nature are limited.     

The impacts of household features on commuting carbon emissions: a case study of Xi’an,China

Transportation - This study contributes to the analysis of the household characteristics and household neighborhood ones affecting the transportation carbon dioxide emissions produced by commuters....     

Commuters’ acceptance of and behavior reactions to license plate restriction policy: A case study of Tianjin,China

License plate restriction (LPR) policies are currently being implemented in major Chinese cities with the aim of mitigating traffic congestions. Meanwhile, much controversy regarding the effectiveness of the LPR policies is arising. To better understand the impact of the LPR policies, this paper studies commuters’ acceptance of and behavior reactions to the policies after their implementation. A theoretical model was proposed as the first step, followed by a questionnaire survey that was conducted in Tianjin, China, where an LPR policy has been in place since March 2014. Car owners frequently commuting within the restricted area were sampled as respondents, and a multi-variable regression method was employed to analyze the collected survey data. The results indicate that it is necessary to promote public’s acceptance of the LPR policy, because lower acceptance will lead to more negative reactions towards the policy, which may weaken its effectiveness. Main factors affecting the level of acceptance of the policy are also found, which may serve as a reference for transportation authorities seeking to increase commuters’ acceptance of the policy. These findings are beneficial to designing and implementing LPR policies.     

“Turn on the radio,bust out a song”: the experience of driving to work

Though driving to and from work has become a prevalent experience in the lives of individuals in every metropolitan region in the US, much remains to be learned about the activity from the perspective of the drivers. To increase our understanding of the motivation for certain travel behaviors, we must first know something about what those drivers experience. The existing literature explains much, but the application of new methodologies could improve our ability to explain the willingness of individuals to choose to drive through increasingly congested road networks. The results of this study of oral histories of 12 women commuters underscore the idea that commute should be seen as a set of subjective behaviors that contradict some existing assumptions about why individuals commute.     

Evaluating the multi-scale patterns of jobs-residence balance and commuting time–cost using cellular signaling data: a case study in Shanghai

Transportation - Assessing jobs-housing balance (JHB) and commuting efficiency is crucial to urban and transport planning. However, the scale dependency problem, meaning that metrics may be biased...     

Effectiveness and costs of odor repellents in wildlife–vehicle collisions: A case study in Central Bohemia,Czech Republic

This article summarizes the results of the field tests, when the efficiency and financial costs of the chosen odor repellents to reduce mortality of animals on selected roads and railways in the Czech Republic during the years 2011–2013 were evaluated. The main objective was to determine whether by using repellents it is possible to reduce the number of animals killed and evaluate the return of financial costs that are associated with the application of the repellents. Our results showed that the odor repellents are an effective tool to reduce wildlife–vehicle collision (WVC), and thanks to their application it was possible to reduce the cost of damage to property and reduce the number of killed animals by comparing the years 2011 (without measure) and 2013 (2 years of repellent application) by 37% of the initial loss.     

From behavioral psychology to acceleration modeling: Calibration,validation, and exploration of drivers’ cognitive and safety parameters in a risk-taking environment

We investigate a utility-based approach for driver car-following behavioral modeling while analyzing different aspects of the model characteristics especially in terms of capturing different fundamental diagram regions and safety proxy indices. The adopted model came from an elementary thought where drivers associate subjective utilities for accelerations (i.e. gain in travel times) and subjective dis-utilities for decelerations (i.e. loss in travel time) with a perceived probability of being involved in rear-end collision crashes. Following the testing of the model general structure, the authors translate the corresponding behavioral psychology theory – prospect theory – into an efficient microscopic traffic modeling with more elaborate stochastic characteristics considered in a risk-taking environment.After model formulation, we explore different model disaggregate and aggregate characteristics making sure that fidelity is kept in terms of equilibrium properties. Significant effort is then dedicated to calibrating and validating the model using microscopic trajectory data. A modified genetic algorithm is adopted for this purpose while focusing on capturing inter-driver heterogeneity for each of the parameters. Using the calibration exercise as a starting point, simulation sensitivity analysis is performed to reproduce different fundamental diagram regions and to explore rear-end collisions related properties. In terms of fundamental diagram regions, the model in hand is able to capture traffic breakdowns and different instabilities in the congested region represented by flow-density data points scattering. In terms of incident related measures, the effect of heterogeneity in both psychological factors and execution/perception errors on the accidents number and their distribution is studied. Through sensitivity analysis, correlations between the crash-penalty, the negative coefficient associated with losses in speed, the positive coefficient associated with gains in speed, the driver’s uncertainty, the anticipation time and the reaction time are retrieved. The formulated model offers a better understanding of driving behavior, particularly under extreme/incident conditions.     

Area-wide travel plans—targeting strategies for greater participation in green travel initiatives: a case study of Rouse Hill Town Centre,NSW Australia

Travel planning by employers promoting more sustainable travel has delivered less car dependent behaviour for the commute in many places. Area-wide or precinct travel plans are less common but, where they exist, attempt to provide a more holistic approach through capturing synergies between employers and employees throughout a precinct. Area-based travel planning aimed at influencing employers, employees and residents are new, especially in relation to creating synergies for a single precinct that has more of an origin focus with participants travelling to diverse destinations. This paper examines various strategies that have been employed in order to achieve greener travel and to provide a self-sustaining travel planning environment. The aim of this paper is to assess the community awareness, interest and involvement with a number of green initiatives and to understand how sustainable travel planning has been absorbed by residents within a new regional centre in New South Wales, Australia. The analysis of a resident survey undertaken in 2011 distinguishes between the community awareness and their propensity to take part in each of the greener travel initiatives. The results show that a generic approach is likely to be less effective than segmenting the market so as to more directly target likely participants. Attitudes to greener travel are also highly significant and working to change them should also affect potential take up of sustainable travel initiatives. The conclusions inform the development of successful precinct based travel demand strategies both in Australia and beyond.     

Exploring the impact of walk–bike infrastructure,safety perception,and built-environment on active transportation mode choice: a random parameter model using New York City commuter data

This study estimates a random parameter (mixed) logit model for active transportation (walk and bicycle) choices for work trips in the New York City (using 2010–2011 Regional Household Travel Survey Data). We explored the effects of traffic safety, walk–bike network facilities, and land use attributes on walk and bicycle mode choice decision in the New York City for home-to-work commute. Applying the flexible econometric structure of random parameter models, we capture the heterogeneity in the decision making process and simulate scenarios considering improvement in walk–bike infrastructure such as sidewalk width and length of bike lane. Our results indicate that increasing sidewalk width, total length of bike lane, and proportion of protected bike lane will increase the likelihood of more people taking active transportation mode This suggests that the local authorities and planning agencies to invest more on building and maintaining the infrastructure for pedestrians. Further, improvement in traffic safety by reducing traffic crashes involving pedestrians and bicyclists, will increase the likelihood of taking active transportation modes. Our results also show positive correlation between number of non-motorized trips by the other family members and the likelihood to choose active transportation mode. The model would be an essential tool to estimate the impact of improving traffic safety and walk–bike infrastructure which will assist in investment decision making.