Environmental justice and hazmat transport: A spatial analysis in southern California

This paper explores whether the risk of a toxic release during transport is greater in poor and minority neighborhoods using a combination of mapping and statistical methods. Cluster analysis is used to examine the density of facilities and transport spill events as well as test for the spatial covariance between facilities and spills. Strong clustering of transport spills is evident, as well as clustering between factory sites and transport spills. A spatial model demonstrates raised rates of transport spills surrounding clusters of toxic firms. Most spills in Los Angeles occurred within 2 km of an intermodal facility. The last step of the analysis compares risk and facility clustering between neighborhoods and socio-economic groups, finding that hazmat spills during transport disproportionately occur in Latino neighborhoods in Los Angeles. The results clarify the spatial distribution of risk and nuisance from freight in urban landscapes.     

A probability analysis of some spatial interaction models

This paper derives several well-known spatial models in a framework based upon the laws of conditional probability analysis. In particular, it relates the structure of some existing models of trip distribution, elementary residential location and residential location with capacity constraints, to either the multinomial or hypergeometric probability distributions. The major changes from traditional methods for developing these models deal with the derivation and form of the objective function for each interaction model. This alternative analysis reaches a wider audience than that only familiar with entropy methods and leads to several improvements in generality. Further, when population constraints were imposed on residential location models, it was found that the model which developed naturally from the approach taken in the paper contained as a special case the model proposed by Dacey and Norcliffe and not the Wilson model.     

Transport-related CO2 effects of online and brick-and-mortar shopping: A comparison and sensitivity analysis of clothing retailing

This paper compares transport-related CO₂ emissions of online and brick-and-mortar shopping based on supply, delivery, order and travel data related to one multi-channel clothing retailer. A sensitivity analysis sheds more light on how situational factors, such as the customers’ travel distances, returns, the use of public transport modes and information behavior via different channels influence the outcome of this comparison. The results show that online retailing causes lower CO₂ emissions under many conditions. Nevertheless, the brick-and-mortar channel is more environmentally friendly when travel distances are small. The radius for which brick-and-mortar shopping has an advantage increases when returns, shifts in the use of public transport and information behavior are also considered.     

Estimation and validation of a microscopic model for spatial economic effects of transport infrastructure

The spatial economic effects in integrated land use and transport models are increasingly disaggregate and can benefit from improved knowledge into the effect of accessibility and agglomeration on the spatial behaviour of firms. This article strives to contribute to this knowledge by first analysing the influence of accessibility and agglomeration on firm behaviour with exceptionally detailed firm data for the province of South Holland in The Netherlands. Next the added value of incorporating such effects in urban simulation models is tested with two series of validation runs with a microscopic model for firm dynamics.The presented Spatial Firm-demographic Micro-simulation (SFM) model simulates transitions and events in the firm population, including firm relocations, firm growth, firm dissolution and firm formation. Accessibility is measured with proximity to infrastructure access points and logsums of business and commuting trips from a transport model. Agglomeration measures are based on theories from urban economics and integrate travel time range bands into measures for specialisation and diversification. Estimation results confirm a significant influence of accessibility and agglomeration on the choice behaviour of firms. Application of these measures prove to increase the validity of the firm-demographic simulation model to a significant but modest extend.     

Disparities in access to opportunities across neighborhoods types: a case study from the Los Angeles region

This study investigates the disparities in access to various types of opportunities in ethnic neighborhoods, as compared to wealthy white neighborhoods (the reference). Focusing on the heterogeneity within ethnic neighborhoods, I distinguish between different types of neighborhoods based on their racial/ethnic makeup and median household income. The Los Angeles region provides an interesting empirical setting because of its racial diversity and its auto-centric spatial structure. The results show that the various types of ethnic neighborhoods differ not only in spatial patterns within the region but also in terms of relative access to opportunities. Nevertheless, I find that all types of the low-income ethnic neighborhoods have higher levels of access to jobs and non-work opportunities, except for access to parks/open spaces, than do the reference neighborhoods. This holds true regardless of accessibility measures and travel modes. However, the relative access to opportunities for middle-to-high-income ethnic neighborhoods varies by accessibility measure. Considering that each accessibility measure has its own set of meanings and planning implications, diverse measures should be taken into account for policy interventions. The present study also adds further evidence of modal disparities, which are much greater than spatial disparities, in access to opportunities.

     

Transit fare differentials: A theoretical analysis

This paper compares the ridership. operator revenue, passenger-km, and consumer surplus in uniform pricing policy versus the differential fare pricing system. The comparisons are assumed that the flat fare is set equal to average differential fares. With mathematical derivation, the paper investigates some of the properties of fare differentiation and discusses characteristics of a general nature. The theoretical results have spelled out the conditions under which pricing policy may yield higher performances. A simple numerical example is used to demonstrate the sensitivity of the model. Some recommendations for setting transit pricing policy are drawn from the results.     

Identification and mapping of spatial variations in travel choices through combining structural equation modelling and latent class analysis: findings for Great Britain

Transportation - This paper exploits some latest advances in structural equation modelling and latent class analysis for identification and mapping of the spatial variations in travel choices. The...     

Efficiency of urban public transit: A meta analysis

The aim of this paper is twofold. First, to provide a statistical overview of the literature on public transit efficiency performance. Second, to statistically explain the variation in efficiency findings reported in the literature. To this end, first some key concepts of efficiency analysis will be introduced, while next the different frontier methodologies that are used in the literature will be discussed. The empirical part of this paper consists of a statistical summary of the literature as well as meta-regression analyses for different samples of the literature in order to identify key determinants of technical efficiency (TE) of public transit operators. For a broad sample of observations, we found significant and consistent effects of the type of database, region and output measurement method. For the sample of non-parametric studies we found that the type of frontier assumptions also have an impact on the efficiency ratio. Further results show that there is no statistical difference in TE ratios between parametric and non-parametric studies. Finally, we found a positive univariate relationship between the number of inputs in the estimated specification and the efficiency ratio.     

Consistency and fungibility of monetary valuations in transport: An empirical analysis of framing and mental accounting effects

Governments around the world use monetised values of transport externalities to undertake project appraisal and cost–benefit analysis. However, because different types of benefits are monetised (e.g., travel time savings, preventing statistical fatalities, reliability, etc.) the question naturally arises as to whether they are consistent. That is, whether a “dollar is a dollar” as welfare economics requires, or whether spending money in one area carries a different disutility from spending money in another area. This would equate to a violation of fungibility, which is the property of a good or a commodity whose individual units are capable of mutual substitution. The view that money is not fungible is explained in behavioural economics through theories of framing and mental accounting. This paper describes the results of a stated choice experiment designed to test the fungibility and consistency of monetary valuations in transport. From a nationally representative sample, we elicit direct values for the three pairwise trade-offs between travel time, travel cost, and safety. We then show that in the context of our analysis, any trade-offs inferred on the basis of other trade-offs, as is common practice (e.g. inferring a safety vs time trade-off on the basis of monetary valuations for time and safety), produces biased results, suggesting that the assumption of fungibility does not hold. Specifically, we find that time is valued more highly when valued directly by cost than when traded with safety, and the reverse is true for safety.     

Modelling inter-urban transport flows in Italy: A comparison between neural network analysis and logit analysis

In the present paper a modal split problem is analysed by means of two competing statistical models, the traditional logit model and the new technique for information processing, viz. the feedforward neural network model. This study aims to explore the modal split between rail and road transport modes in Italy in relation to the introduction of a new technological innovation, the new High-Speed Train. The paper is sub-divided into two major parts. The first part offers some general considerations on the use of neural networks in the light of the increasing number of empirical applications in the specific area of transport economics. The second part describes the Italian case study by using the two above mentioned statistical models. The results highlights the fact that the two adopted models, although methodologically different, are both able to provide a reasonable spatial forecasting of the phenomenon studied. In particular, the neural network model turns out to have a slightly better performance, even though there are still critical problems inherent in its application.     

Travel time ratio: the key factor of spatial reach

An important aspect of reach and accessibility is the time people are willing to spend on reaching activity places. In this paper we see the issue of travel time in an alternative way. Instead of looking at travel time separated from time spent on activities, we examine the relation between travel time and stay time. We operationalize this relation with the concept “travel time ratio”. A hypothetical framework underlying these travel time ratios is displayed. We show that for similar types of activity places the value of travel time ratio are in accordance with each other. We find large differences between trips for mandatory activities and trips for discretionary activities. The results indicate the stability of the travel time ratios. Finally, some implications for future research and policy will be mentioned. This revised version was published online in June 2006 with corrections to the Cover Date.     

The spatial dimensions of immobility in France

In travel surveys, immobility is often approached as a technical issue that needs to be dealt with in order to measure mobility more accurately. By covering mobility patterns over a full week, the 2008 French Travel Survey allows immobility to be analysed other than as a marginal and random phenomenon. For working days alone, 28.8% of the adults in the survey had experienced one or more immobility episodes. By considering the intensity of immobility, and by introducing latent variables into Structural Equation Modelling, we have been able to propose a model with reasonable explanatory power. Our findings agree with previous studies and also show that within suburban or rural areas, access to shops or the type of local residential fabric are also factors that influence the number of immobile days. In addition, our findings show that the effects of the determinants differ between categories of individuals, notably between working adults and students on the one hand, and between retired and non-working people on the other.     

The multinomial logit model revisited: A semi-parametric approach in discrete choice analysis

The multinomial logit model in discrete choice analysis is widely used in transport research. It has long been known that the Gumbel distribution forms the basis of the multinomial logit model. Although the Gumbel distribution is a good approximation in some applications such as route choice problems, it is chosen mainly for mathematical convenience. This can be restrictive in many other scenarios in practice. In this paper we show that the assumption of the Gumbel distribution can be substantially relaxed to include a large class of distributions that is stable with respect to the minimum operation. The distributions in the class allow heteroscedastic variances. We then seek a transformation that stabilizes the heteroscedastic variances. We show that this leads to a semi-parametric choice model which links the linear combination of travel-related attributes to the choice probabilities via an unknown sensitivity function. This sensitivity function reflects the degree of travelers’ sensitivity to the changes in the combined travel cost. The estimation of the semi-parametric choice model is also investigated and empirical studies are used to illustrate the developed method.     

Trip generation of vulnerable populations in three Canadian cities: a spatial ordered probit approach

This paper provides an analysis of trip generation of three vulnerable groups: single-parent families, low income households, and the elderly. It compares the mobility of these groups to that of the general population in three Canadian urban areas of Hamilton, Montreal and Toronto, based on data from large-sample metropolitan transport surveys. An ordered probit model with spatially expanded coefficients is used for the analysis. Spatial expansion shows that there are spatial mobility trends for elderly populations and low-income populations even after socio-economic attributes are accounted for. Such spatial differences are not generally found for single parent families. This novel spatial analysis provides clues as to where vulnerable populations may experience greater degrees of social exclusion. It provides information to help prioritize transportation infrastructure projects or other social programs to take into account the needs of vulnerable populations with the lowest levels of mobility.     

Changes in level of household car ownership: the role of life events and spatial context

Recent longitudinal studies of household car ownership have examined factors associated with increases and decreases in car ownership level. The contribution of this panel data analysis is to identify the predictors of different types of car ownership level change (zero to one car, one to two cars and vice versa) and demonstrate that these are quite different in nature. The study develops a large scale data set (n = 19,334), drawing on the first two waves (2009–2011) of the UK Household Longitudinal Study (UKHLS). This has enabled the generation of a comprehensive set of life event and spatial context variables. Changes to composition of households (people arriving and leaving) and to driving licence availability are the strongest predictors of car ownership level changes, followed by employment status and income changes. Households were found to be more likely to relinquish cars in association with an income reduction than they were to acquire cars in association with an income gain. This may be attributed to the economic recession of the time. The effect of having children differs according to car ownership state with it increasing the probability of acquiring a car for non-car owners and increasing the probability of relinquishing a car for two car owners. Sensitivity to spatial context is demonstrated by poorer access to public transport predicting higher probability of a non-car owning household acquiring a car and lower probability of a one-car owning household relinquishing a car. While previous panel studies have had to rely on comparatively small samples, the large scale nature of the UKHLS has provided robust and comprehensive evidence of the factors that determine different car ownership level changes.     

Significant characteristics of the urban rail renaissance in the United States: A discriminant analysis

In the rebirth of light-rail in the US, there has been little quantitative work detailing the differences between cities that have built rail transit and those that have not. In this study, 18 independent variables measuring a variety of characteristics that might promote or hinder rail transit construction are examined for 13 cities that built rail and 22 that did not, but considered it. After isolating the most significant variables, a two-group discriminant analysis generates a function from a randomly chosen set of 25 cities, and then cross-validates it on a separate set of 10. That model attempts to classify the cities into their respective groups. A model with three significant independent variables is generated that correctly classifies 33 of the 35 cities. The results indicate that cities which chose to build rail already had relatively well-used bus systems. There also appears to be an image and economic development aspect associated with rail construction.     

A cluster analysis of cyclists in Europe: common patterns,behaviours, and attitudes

Transportation - This study uses cluster analysis on a sample of regular cyclists from six European countries (the U.K., the Netherlands, Sweden, Hungary, Italy, and Spain) to shed light on common...