Transportation (TRANSPORTATION)

Publisher: Springer Verlag

Journal description

Although the transportation needs of cities and nations around the world may differ in detail there is much that is common. The benefit to be derived by sharing research findings and practical experience is therefore vast. Transportation lends itself to that vital process of information exchange by publishing carefully selected papers which advance the international fund of knowledge. Transportation focuses on issues of direct relevance to those concerned with the formulation of policy the preparation and evaluation of plans and the day-to-day operational management of transport systems. It concerns itself with the policies and systems themselves as well as with their impacts on and relationships with other aspects of the social economic and physical environment. Transportation is relevant to all parts of the world: industrialized newly industrialized or developing. The journal has no model bias and is totally apolitical. Its mission is simply to help improve the transportation of people and goods by bringing an improved understanding of the subject to the theorists practitioners and policy makers who study it.

Current impact factor: 2.36

Impact Factor Rankings

2016 Impact Factor Available summer 2017
2014 / 2015 Impact Factor 2.358
2012 Impact Factor 1.657
2011 Impact Factor 1.023
2010 Impact Factor 1.875
2009 Impact Factor 1.512
2008 Impact Factor 1.767
2007 Impact Factor 1.242
2006 Impact Factor 0.854
2005 Impact Factor 1.19
2004 Impact Factor 0.795
2003 Impact Factor 1.05
2002 Impact Factor 0.757
2001 Impact Factor 0.41
2000 Impact Factor 0.25
1999 Impact Factor 0.316
1998 Impact Factor 0.595
1997 Impact Factor 0.378
1996 Impact Factor 0.432
1995 Impact Factor 0.447
1994 Impact Factor 0.538
1993 Impact Factor 0.2
1992 Impact Factor 0.25

Impact factor over time

Impact factor

Additional details

5-year impact 2.48
Cited half-life 8.00
Immediacy index 0.29
Eigenfactor 0.00
Article influence 0.82
Website Transportation website
Other titles Transportation
ISSN 0049-4488
OCLC 1624097
Material type Periodical
Document type Journal / Magazine / Newspaper

Publisher details

Springer Verlag

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    • Author's post-print on author's personal website immediately
    • Author's post-print on any open access repository after 12 months after publication
    • Publisher's version/PDF cannot be used
    • Published source must be acknowledged
    • Must link to publisher version
    • Set phrase to accompany link to published version (see policy)
    • Articles in some journals can be made Open Access on payment of additional charge
  • Classification

Publications in this journal

  • No preview · Article · Feb 2016 · Transportation

  • No preview · Article · Jan 2016 · Transportation
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    ABSTRACT: Modeling commuters’ choice behavior in response to transportation demand management (TDM) helps in predicting the consequences of TDM policies. Although research looking at choice behavior has evolved to investigate preference heterogeneity in response to factors influencing mode choice, as far as we know, no study has considered taste variation across commuters in response to multiple TDM policies. This paper investigates the presence of systematic preference heterogeneity across commuters, in response to the TDM policies that can be explained by their socio-economic or commuting-related characteristics. Analysis is based on results of a stated preference survey developed using a Design of Experiments approach. Five policies were assessed in order to study the impact they had on how commuters chose their mode of transportation. These include increasing parking cost, increasing fuel cost, implementing cordon pricing, reducing transit time and improving access to transit facilities. For the sake of assessing both systematic and random preference heterogeneity across car commuters, a form of the Mixed Multinomial Logit (MMNL) model that identifies sources of heterogeneity and consequently makes the choice models less restrictive in considering both systematic and random preference variation across individuals was developed. The sample includes 366 individuals who regularly commute to their workplace in the city center of Tehran, Iran. The likelihood function value of this model shows a significant improvement compared to the base MNL model, using the same variables. The MMNL model shows that taste variation across the studied commuters results in differences in influences estimated for three policies: increasing parking cost, reducing transit time and improving access to transit. The analysis examines several distributions for random parameters to test the impacts of restricting distributions to allow for only normality. The results confirm the potential to improve model fit with alternative distributions.
    No preview · Article · Dec 2015 · Transportation
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    ABSTRACT: Most of the earlier activity based models (ABMs) largely relied on a tour-based modeling paradigm which explicitly predicts tour frequency and then adds details including stop frequency, order, and location of stops within each tour. The current study is part of new tour formation design framework for an ABM in which the underlying tour structure and the stop frequency within tours emerge from temporal, sequencing, and locational preferences of activities that the traveler intends to participate during the day. In order to do this, the study developed a modified rank-ordered logit (ROL) framework that is capable of modeling sequence, locations, as well as the underlying tour structure of all activity episodes simultaneously in an integrated manner. Model estimation with the household survey data, provided several important behavioral insights into underlying choices that drive tour formation. Specifically, the study uncovered pairwise ordering preferences among episodes of different activity purposes, clustering tendencies among episodes of same activity purpose, the impact of supply side activity opportunities on the location and sequence choice dimensions, and impedance effects (including distance and mode and time-of-day logsums) on location and tour break dimensions. The developed models are incorporated in the operational ABM structure adopted for three major cities (Columbus, Cleveland, and Cincinnati) in Ohio.
    No preview · Article · Dec 2015 · Transportation
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    ABSTRACT: Assuming freight trip generation as the total number of freight vehicles arriving to retail establishments, for loading/unloading purposes and within a defined time period, we experiment and compare four alternative modeling methodologies to predict freight trip generation. The aim is to achieve better freight trip generation models, thus contributing to improving the chances of correctly dimension, for example, the parking infrastructure required to accommodate demand, or estimating the freight traffic impacts at micro level. Representing the state of the practice, the first two methodologies are based on cross-classification/category analysis. The third methodology uses a generalized linear model specification, a robust alternative to ordinary least squares linear regression. The fourth methodology consists in the exploration of a dependent variable simplification using an Ordinal Logit model. The main source of data is an Establishment-based Freight Survey, which collected data from 604 retail establishments in the city of Lisbon, Portugal. The selected independent variables were the establishments’ industry category, number of employees and retail area. The analysis allowed for the conclusion that (a) variable contribution varies depending on the chosen modelling methodology, (b) there is little variability in the quality of predictions depending on the selected model, but a considerable improvement in correct predictions can be achieved by reducing the variability of the dependent variable, and (c) the proposed indicator framework is suitable to compare model predictions and might be adequately represented by subset of those applied.
    No preview · Article · Dec 2015 · Transportation
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    ABSTRACT: The use of GPS devices and smartphones has made feasible the collection of multi-day activity-travel diaries. In turn, the availability of multi-day travel diary data opens up new avenues for analyzing dynamics of individual travel behavior. This paper addresses the issue of day-to-day variability in activity-travel behavior. The study, which is the first of its kind in China, applies a unique combination of methods to analyze the degree of dissimilarity between travel days using multi-day GPS data. First, multi-dimensional sequence alignment is applied to measure the degree of dissimilarity in individual daily activity-travel sequences between pairs of travel days. Next, a series of panel effects regression models is used to estimate the effects of socio-demographics and days of the week. The models are estimated using multi-day activity-travel patterns imputed from GPS-enabled smartphone data collected in Shanghai, China. Results indicate that (1) days of the week have significant effects on day-to-day variability in activity-travel behavior with weekday activity-travel sequences being more similar and thereby different from weekend sequences; (2) the degree of dissimilarity in activity-travel sequences is strongly influenced by respondent socio-demographic profiles; (3) individuals having more control over and flexibility in their work schedule show greater intra-personal variability. Day-to-day variability in activity-travel behavior of this sample is similar to patterns observed in developed countries in some aspects but different in others. Strict international comparison study based on comparative data collection is required to further distinguish the sources of travel behavior differences between developing countries and developed countries. The paper ends with a discussion of the limitations of this study and the implications of the research findings for future research.
    No preview · Article · Nov 2015 · Transportation
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    ABSTRACT: The paper presents the results of an investigation on daily activity-travel scheduling behaviour of older people by using an advanced econometric model and a household travel survey, collected in the National Capital Region (NCR) of Canada in 2011. The activity-travel scheduling model considers a dynamic time–space constrained scheduling process. The key contribution of the paper is to reveal daily activity-travel scheduling behaviour through a comprehensive econometric framework. The resulting empirical model reveals many behavioural details. These include the role that income plays in moderating out-of-home time expenditure choices of older people. Older people in the highest and lowest income categories tend to have lower variations in time expenditure choices than those in middle-income categories. Overall, the time expenditure choices become more stable with increasing age, indicating that longer activity durations and lower activity frequency become more prevalent with increasing age. Daily activity type and location choices reveal a clear random utility-maximizing rational behaviour of older people. It is clear that increasing spatial accessibility to various activity locations is a crucial factor in defining daily out-of-home activity participation of older people. It is also clear that the diversity of out-of-home activity type choices reduces with increasing age and older people are more sensitive to auto travel time than to transit or non-motorized travel time.
    No preview · Article · Nov 2015 · Transportation
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    ABSTRACT: We provide an in-depth theoretical discussion about the differences between individual-specific latent constructs (representing attitudes, for example, but also other characteristics such as values or personality traits) and alternative-specific latent constructs (that may represent perceptions) affecting the choice-making process of individuals; we also carry out an empirical exercise to analyze their effects. This discussion is of importance, as the majority of papers considering attitudinal latent variables just take these as attributes affecting directly the utility of a certain alternative, while systematic taste variations are rarely considered and perceptions are mostly ignored. The results of our case study show that perceptions may indeed affect the decision making process and that they are able to capture a significant part of the variability that is normally explained by alternative specific constants. Furthermore, our results indicate that attitudes may be a reason for systematic taste variations, and that a proper categorization of latent variables, in accordance with underlying theory, may outperform the customary assumption of linearity.
    No preview · Article · Nov 2015 · Transportation
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    ABSTRACT: In 2015 the New York Islanders, a professional men’s ice hockey team in the National Hockey League, will relocate to an arena with more transportation options for fans. The team currently plays at Nassau Coliseum in Uniondale, Long Island, NY, with limited public transportation access. They will move 23 miles west to the Barclays Center, an arena in the heart of Brooklyn, NY, with many public transportation options. This study examined fan characteristics which may influence their likelihood of attending Islanders games at the Barclays Center, including familiarity with public transportation, frequency of game attendance, and demographic factors. An online survey of Islanders fans captured fans’ transportation behaviors when traveling to Islanders games at Nassau Coliseum and their projected frequency of attendance after the move, among other variables. Binary and ordered logistic regression models tested the significance of fan characteristics on the likelihood they attended a pre-season Islanders game held at the Barclays Center in September, 2013, and on how frequently respondents reported they will attend future games in Brooklyn. For both models, fans who use regional rail every workday, compared to those who do not, were significantly more likely to have attended the pre-season game and to report they will attend future games. Transit-use variables performed stronger in models than variables representing fans’ work locations. The results exemplify the importance of familiarity with public transportation options when making mode choice decisions, bolstering the importance of transportation demand management strategies when opening new or relocating existing large event venues.
    No preview · Article · Nov 2015 · Transportation
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    ABSTRACT: Although there is a significant body of work associating socio-demographics with activity-travel behaviors, very few prior studies have examined the relationship between changes in employment status and adaptations in activity-travel patterns. To examine this issue, this study employs data of the Puget Sound Panel Survey, comprising a total of 7135 respondents. Through descriptive analyses and a random parameters panel effects regression model, we analyze changes in the time spent on shopping between two consecutive waves of the panel differentiating between employment status transitions, after controlling for a set of socio-demographic variables and day of the week. Results indicate that while activity-travel patterns in general and shopping duration in particular are relatively stable for the groups showing no transitions in employment status, the transition groups show evidence of a reorganization of their shopping activities across the week. In addition, results of the model indicate that the relationship between change in employment status and dynamics in shopping behavior is not symmetrical.
    No preview · Article · Oct 2015 · Transportation
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    ABSTRACT: A traveler’s willingness to pay for travel time savings depends on his/her socio-economic characteristics, travel purpose, and situational factors such as time pressure under which the travel is undertaken. Earlier literature on value of time (VOT) analysis focused mostly on the first two factors but did not examine the last factor thoroughly. However, in the real world we expect that (at least in most cases) a worker would be willing to pay more during the before-work period than during the after-work period since most of the workers should reach their respective work places by a certain time while the after-work schedule in general should be more relaxed. The additional time pressure during the before-work period makes time more valuable, thus increasing VOT. In some cases, where a worker with a flexible schedule has a high-priority post-work activity with a fixed schedule (for example, tickets to a concert) the situation can be reversed. The current study aims to capture such impacts of daily activity patterns on a person’s VOT using a comprehensive trip segmentation framework that is comprised of several integrated mode and trip departure time-of-day choice models. Each of these integrated models was estimated using both Revealed Preference and Stated Preference data from a large-scale GPS-assisted Household Travel Survey undertaken in Jerusalem, Israel. The results not only confirm the long-held hypothesis about variation of VOT by socio-economic factors and trip purpose but also shed light on the variation of VOT with daily travel patterns. To our knowledge, this is the first attempt to develop a rigorous modeling framework for capturing variation of VOT as a function of the individual daily activity pattern. An additional feature of the proposed approach is that it was practically implemented within the framework of an applied activity-based model.
    No preview · Article · Oct 2015 · Transportation
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    ABSTRACT: This paper proposes a conceptual framework to model the travel mode searching and switching dynamics. The proposed approach is structurally different from existing mode choice models in the way that a non-homogeneous hidden Markov model (HMM) has been constructed and estimated to model the dynamic mode searching process. In the proposed model, each hidden state represents the latent modal preference of each traveler. The empirical application suggests that the states can be interpreted as car loving and carpool/transit loving, respectively. At each time period, transitions between the states are functions of time-varying covariates such as travel time and travel cost of the habitual modes. The level-of-service (LOS) changes are believed to have an enduring impact by shifting travelers to a different state. While longitudinal data is not readily available, the paper develops an easy-to-implement memory-recall survey to collect required process data for the empirical estimation. Bayesian estimation and Markov chain Monte Carlo (MCMC) method have been applied to implement full Bayesian inference. As demonstrated in the paper, the estimated HMM is reasonably sensitive to mode-specific LOS changes and can capture individual and system dynamics. Once applied with travel demand and/or traffic simulation models, the proposed model can describe time-dependent multimodal behavior responses to various planning/policy stimuli.
    No preview · Article · Oct 2015 · Transportation
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    ABSTRACT: While metro disruptions can have a significant impact to the travel patterns and behavior of users, research on that topic has been limited. Using Athens, Greece, as a study case, this paper combines information on traveler experiences and perceptions and attempts to model mode choice during a long-run metro service disruption. A Nested Logit (NL) approach for jointly analyzing RP/SP data is applied and compared to individual RP and SP based MNL models. Findings suggest that the propensity to shift to buses or cars in such cases depends—to a large extent—on the travelers’ available income. Also, the possibility of a flexible work schedule is negatively correlated with the choice of using a car during metro closures. Finally, the overall performance of the joint RP/SP Nested Logit model has been found to be superior to that of the joint RP/SP MNL model.
    No preview · Article · Sep 2015 · Transportation