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Highlights • A meta-analysis on railways studies was presented. • A permutation test was used for the robustness of the findings. • Location and type of service were significant to explain efficiency estimates. • Methodology applied and model characteristics were significant to efficiency scores. • Public policies based on findings were commented. Abstract Meta-analysis is a statistical method used to make a systematic review of the literature to integrate the results of a series of studies. It is increasingly adopted in social sciences but according to our best knowledge used for the first time to aggregate and contrast findings on rail transport efficiency. The experiment adopted a permutation test to evaluate the influence of variables discussed in the literature in the mean efficiency scores. The results suggest that railways located in Japan and in the US have characteristics that push them toward increasing efficiency. The passenger rail systems reached significantly higher estimates than conventional cargo systems. Estimates from parametric and nonparametric models showed significant difference, while from nonparametric models including Data Envelopment Analysis (DEA) and from Network DEA did not. The number of variables and the ratio between the number of decision making units and the number of variables employed significantly influenced the scores. Unexpectedly, different data structures did not. Validation methods are presented. Public policies based on the empirical results are commented. [ABSTRACT FROM AUTHOR]

In this study, we analyse the impact of port infrastructure on trade by estimating a gravity equation for exports (imports) of Brazilian states towards (from) all main Brazil’s trading partners. In particular, we consider exports (imports) of the 27 Brazilian states towards (from) 30 of Brazil’s most important trading partners over the period 2009–2012. By estimating a set of gravity equations with the Poisson pseudo-maximum likelihood estimator, we find that an increase in port infrastructure (as proxied by the piers extension in each Brazilian state normalized by that state’s area) is associated to large increases in Brazilian exports, while the impact on imports is more mixed and generally lower. Our results are robust to controlling for a series of state and country fixed effects. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Public transport networks (PTN) are subject to recurring service disruptions. Most studies of the robustness of PTN have focused on network topology and considered vulnerability in terms of connectivity reliability. While these studies provide insights on general design principles, there is lack of knowledge concerning the effectiveness of different strategies to reduce the impacts of disruptions. This paper proposes and demonstrates a methodology for evaluating the effectiveness of a strategic increase in capacity on alternative PTN links to mitigate the impact of unexpected network disruptions. The evaluation approach consists of two stages: identifying a set of important links and then for each identified important link, a set of capacity enhancement schemes is evaluated. The proposed method integrates stochastic supply and demand models, dynamic route choice and limited operational capacity. This dynamic agent-based modelling of network performance enables to capture cascading network effects as well as the adaptive redistribution of passenger flows. An application for the rapid PTN of Stockholm, Sweden, demonstrates how the proposed method could be applied to sequentially designed scenarios based on their performance indicators. The method presented in this paper could support policy makers and operators in prioritizing measures to increase network robustness by improving system capacity to absorb unexpected disruptions. [ABSTRACT FROM AUTHOR]

The effect of corruption on airport productive efficiency is analyzed using an unbalanced panel data of major European airports from 2003 to 2009. We first compute the residual (or net) variable factor productivity using the multilateral index number method and then apply robust cluster random effects model in order to evaluate the importance of corruption. We find strong evidence that corruption has negative impacts on airport operating efficiency; and the effects depend on the ownership form of the airport. The results suggest that airports under mixed public–private ownership with private majority achieve lower levels of efficiency when located in more corrupt countries. They even operate less efficiently than fully and/or majority government owned airports in high corruption environment. We control for economic regulation, competition level and other airports’ characteristics. Our empirical results survive several robustness checks including different control variables, three alternative corruption measures: International Country Risk Guide (ICRG) corruption index, Corruption Perception Index (CPI) and Control of Corruption Index (CCI). The empirical findings have important policy implications for management and ownership structuring of airports operating in countries that suffer from higher levels of corruption. [ABSTRACT FROM AUTHOR]

Highlights: [•] Barriers limit robust US high-speed rail (HSR) environmental assessment. [•] Five challenges must be addressed to improve the environmental assessment of HSR. [•] HSR assessment should consider complementary configurations with air. [•] Environmental research objectives are siloed across academics and practitioners. [•] Multi-modal long-distance mobility visions and research support are needed. [Copyright &y& Elsevier]

Abstract: This paper studies changes in people’s travel mode use from oneyear to the next. It is informed by three distinct discourses: travel behaviour change, the mobility biographies approach, and cohort analysis. The data used is the German Mobility Panel (GMP) 1994–2008 in which households and their members are asked three times in three subsequent years to report the trips they made over a week. The changes reported are regressed to key events over the life course, cohort effects and period effects, while various sociodemographic and spatial attributes are controlled. Due to the non-independent nature of panel observations, a cluster-robust regression approach is used. The findings suggest that behind the aggregate stability in travel mode use over time there is much change ‘under the surface’, induced by life course changes, individual and household sociodemographic, and spatial context. The changes found induced by life course related key events favour the notion of mobility biographies. However, taken over all key events seem to be relatively loosely associated with mode use changes. Nonetheless, various significant effects of baseline variables suggest that mode use may change even in the absence of a key event. [Copyright &y& Elsevier]

Abstract: Local, county and state level transit agencies with large fleets of buses and limited budgets seek a robust fund allocation mechanism to maintain service standards. However, equitable and optimal fund allocation for purchasing, operating and maintaining a transit fleet is a complex process. In this study, we develop an optimization model for allocation of funds among different fleet improvement programs within budget constraints over the planning period. This is achieved by minimizing the net present cost (NPC) of the investment within the constraint of a minimum level of fleet quality expressed as a surrogate of the remaining life of the fleet. Integer programming is used to solve the formulated optimization problem using branch and bound algorithm. The model formulation and application are demonstrated with a real world case study of transit agencies. It is observed that minimizing NPC provides a realistic way to allocate resources between different program options among different transit agencies while maintaining a desired quality level. The proposed model is generalized and can be used as a resource allocation tool for transit fleet management by any transit agency. [Copyright &y& Elsevier]

Abstract: There is a growing awareness that road networks, are becoming more and more vulnerable to unforeseen disturbances like incidents and that measures need to be taken in order to make road networks more robust. In order to do this the following questions need to be addressed: How is robustness defined? Against which disturbances should the network be made robust? Which factors determine the robustness of a road network? What is the relationship between robustness, travel times and travel time reliability? Which indicators can be used to quantify robustness? How can these indicators be computed? This paper addresses these questions by developing a consistent framework for robustness in which a definition, terms related to robustness, indicators and an evaluation method are included. By doing this, policy makers and transportation analyst are offered a framework to discuss issues that are related to road network robustness and vulnerability which goes beyond the disconnected definitions, indicators and evaluation methods used so far in literature. Furthermore, the evaluation method that is presented for evaluating the robustness of the road network against short term variations in supply (like incidents) contributes to the problem of designing robust road networks because it has a relatively short computation time and it takes spillback effects and alternative routes into account. [Copyright &y& Elsevier]

Abstract: A wide range of relatively short-term disruptive events such as partial flooding, visibility reductions, traction hazards due to weather, and pavement deterioration occur on transportation networks on a daily basis. Despite being relatively minor when compared to catastrophes, these events still have profound impacts on traffic flow. To date there has been very little distinction drawn between different types of network-disruption studies and how the methodological approaches used in those studies differ depending on the specific research objectives and on the disruption scenarios being modeled. In this paper, we advance a methodological approach that employs different link-based capacity-disruption values for identifying and ranking the most critical links and quantifying network robustness in a transportation network. We demonstrate how an ideal capacity-disruption range can be objectively determined for a particular network and introduce a scalable system-wide performance measure, called the Network Trip Robustness (NTR) that can be used to directly compare networks of different sizes, topologies, and connectivity levels. Our approach yields results that are independent of the degree of connectivity and can be used to evaluate robustness on networks with isolating links. We show that system-wide travel-times and the rank-ordering of the most critical links in a network can vary dramatically based on both the capacity-disruption level and on the overall connectivity of the network. We further show that the relationships between network robustness, the capacity-disruption level used for modeling, and network connectivity are non-linear and not necessarily intuitive. We discuss our findings with respect to Braess’ Paradox. [Copyright &y& Elsevier]