Do changes in neighborhood characteristics lead to changes in travel behavior? A structural equations modeling approach

Suburban sprawl has been widely criticized for its contribution to auto dependence. Numerous studies have found that residents in suburban neighborhoods drive more and walk less than their counterparts in traditional environments. However, most studies confirm only an association between the built environment and travel behavior, and have yet to establish the predominant underlying causal link: whether neighborhood design independently influences travel behavior or whether preferences for travel options affect residential choice. That is, residential self-selection may be at work. A few studies have recently addressed the influence of self-selection. However, our understanding of the causality issue is still immature. To address this issue, this study took into account individuals’ self-selection by employing a quasi-longitudinal design and by controlling for residential preferences and travel attitudes. In particular, using data collected from 547 movers currently living in four traditional neighborhoods and four suburban neighborhoods in Northern California, we developed a structural equations model to investigate the relationships among changes in the built environment, changes in auto ownership, and changes in travel behavior. The results provide some encouragement that land-use policies designed to put residents closer to destinations and provide them with alternative transportation options will actually lead to less driving and more walking.

The influence of the operational environment on efficiency of international airports

Heterogeneity must be considered in the efficiency analysis of decision‐making units; otherwise, the results will be strongly biased. This is also valid for airport management where the operational environment heavily influences efficiency. In this paper, conditional efficiency measures are applied to airports to incorporate heterogeneity in non‐parametric frontier models which are robust for outlying observations. In particular, the influence of the operational environment on airport efficiency is examined in a sample of 141 international airports. The conclusions show that the operational environment indeed matters and that privatisation, regulation, traffic transfer and the dominant carrier have a positive effect on efficiency, whereas aeronautical revenues influence it negatively. Copyright © 2014 John Wiley & Sons, Ltd.     

Analyzing the preference for non-exclusive forms of telecommuting: Modeling and policy implications

This study examines three models of the individual's preference for home- and center-based telecommuting. Issues concerning the estimation of discrete models when the alternatives are non-exclusive are discussed. Two binary logit models are presented, one on the preference to telecommute from a center versus not telecommuting from a center (adjusted ² = 0.24), and the other on the preference to telecommute from a center over telecommuting from home (adjusted ² = 0.64). A nested logit model is also estimated on the following four alternatives: preferring not to telecommute, preferring either form of telecommuting, preferring to telecommute from home, and preferring to telecommute from a center (adjusted ² = 0.35).The results of the models illustrated the importance of attitudinal measures in measuring an individual's preference to telecommute. Oblique factor scores representing workplace interaction, stress, workaholism, internal control, and commute stress were statistically significant in some or all of the models. Other explanatory variables which were found to be consistently significant were education, job suitability, and age. Most respondents preferred either to telecommute from home or were indifferent between either form of telecommuting, which raises the question as to whether there really is a sizeable market niche to be filled by telecommuting centers, and hence whether they may make a significant contribution to transportation demand reduction.     

Travel mode choice and travel satisfaction: bridging the gap between decision utility and experienced utility

Over the past decades research on travel mode choice has evolved from work that is informed by utility theory, examining the effects of objective determinants, to studies incorporating more subjective variables such as habits and attitudes. Recently, the way people perceive their travel has been analyzed with transportation-oriented scales of subjective well-being, and particularly the satisfaction with travel scale. However, studies analyzing the link between travel mode choice (i.e., decision utility) and travel satisfaction (i.e., experienced utility) are limited. In this paper we will focus on the relation between mode choice and travel satisfaction for leisure trips (with travel-related attitudes and the built environment as explanatory variables) of study participants in urban and suburban neighborhoods in the city of Ghent, Belgium. It is shown that the built environment and travel-related attitudes—both important explanatory variables of travel mode choice—and mode choice itself affect travel satisfaction. Public transit users perceive their travel most negatively, while active travel results in the highest levels of travel satisfaction. Surprisingly, suburban dwellers perceive their travel more positively than urban dwellers, for all travel modes.     

Wanting to travel,more or less: Exploring the determinants of the deficit and surfeit of personal travel

This study investigates the determinants of peoples desire to increase or decrease the amount of travel they do. We use data from 1,357 working commuters, residents of three different neighborhoods in the San Francisco Bay Area, California. The dependent variables are indicators of Relative Desired Mobility for ten categories of travel (short- and long-distance overall and by several mode- and purpose-specific categories). These variables are measured on a five-point ordinal scale ranging from much less to much more, through which the respondents indicated the amount of travel they want to do (in the category in question) compared to what they are doing now. Censored ordered probit models were developed for these variables, with explanatory variables including general travel attitudes, specific liking for travel in each of the same separate categories, objective and subjective measures of the amount currently traveled in each category, and personality, lifestyle, and socio-demographic characteristics. The results support the hypotheses that the liking for travel has a strong positive impact, and subjective qualitative assessments of mobility have a strong negative impact, on the desire to increase ones travel. Finally, a number of general types of effects on Relative Desired Mobility were identified, among them complementarity and substitution effects. The results of this study can provide policy makers and researchers with new and valuable insight into key principles that affect individual travel demand.     

Telemetric system for monitoring and automation of railroad networks

This paper describes a new method of real-time train monitoring based on the ZigBee/IEEE 802.15.4 protocol. The system consists of a mobile device embedded in the moving train which transmits parameter signals that are being measured by a base unit with the help of routers. When applied, the technique monitors and controls vehicles operating on permanent routes, making a real-time evaluation of their performance and location, and allowing an effective planning of trains. It consists of a low cost, low power consumption and safe modular technology capable of monitoring many different variables simultaneously.     

Optimizing sustainable feeder bus operation considering realistic networks and heterogeneous demand

A mathematical model is developed to optimize social and fiscal sustainable operation of a feeder bus system considering realistic network and heterogeneous demand. The objective total profit is a nonlinear, mixed integer function, which is maximized by optimizing the number of stops, headway, and fare. The stops are located which maximize the ridership. The demand elasticity for the bus service is dependent on passengers' access distance, wait time, in‐vehicle time, and fare. An optimization algorithm is developed to search for the optimal solution that maximizes the profit. The modeling approach is applied to planning a bus transit system within Woodbridge, New Jersey. Copyright © 2011 John Wiley & Sons, Ltd.     

Commuter impacts and behavior changes during a temporary freeway closure: the ‘Fix I-5’ project in Sacramento,California

One mile of Interstate 5 (I-5) in downtown Sacramento, California was closed intermittently for reconstruction (‘the Fix project’) over nine weeks in 2008. We analyze the impacts of the Fix on commuters’ travel behavior, as measured through two contemporaneous Internet-based surveys. The impacts of the Fix on traffic conditions do not appear to have been excessive: majorities in all relevant subsamples did not find conditions worse than usual, and sizable minorities actually found them to be better. Among the active changes to commute trips, the easiest options – avoiding rush hour and changing route – were the most common (adopted by 48% and 44%, respectively). Among the changes that reduced vehicle-miles traveled, increasing transit use and increasing telecommuting (TC) were the most common (each adopted by 5–6% of the relevant subsample). Binary logit models of these two choices suggest that persuading current adopters to increase their frequency of use is easier than convincing nonadopters to start TC or switch to transit. Women and those in larger households were found to be more likely to increase TC and transit use. Employer support of commute alternatives significantly influenced the adoption of both strategies.     

Quantifying the Difference Between Self-Reported and Global Positioning Systems-Measured Journey Durations: A Systematic Review

Accurate measurement of travel behaviour is vital for transport planning, modelling, public health epidemiology, and assessing the impact of travel interventions. Self-reported diaries and questionnaires are traditionally used as measurement tools; advances in Global Positioning Systems (GPS) technology allow for comparison. This review aimed to identify and report about studies comparing self-reported and GPS-measured journey durations. We systematically searched, appraised, and analysed published and unpublished articles from electronic databases, reference lists, bibliographies, and websites up to December 2012. Included studies used GPS and self-report to investigate trip duration. The average trip duration from each measure was compared and an aggregated, pooled estimate of the difference, weighted by number of trips, was calculated. We found 12 results from eight eligible studies. All studies showed self-reported journey times were greater than GPS-measured times. The difference between self-report and GPS times ranged from over-reporting of +2.2 to +13.5 minutes per journey. The aggregated, pooled estimate of the difference, weighted by number of trips, was over-report of +4.4 minutes (+28.6%). Studies comparing self-reported and GPS-measured journey duration have shown self-reported to be consistently over-reported across the study sample. Our findings suggest that when using self-reported journey behaviour, the journey durations should be treated as an over-estimation.