Research in Transportation Economics最新文献

Inland Waterway Transport (IWT) is pivotal for hinterland freight logistics, connecting numerous inland terminals with major deep-sea ports. Despite its significant advantages in cargo capacity and environmental sustainability, it remains underutilized due to operational inefficiencies, diminishing its competitive edge compared to road and rail transport. Addressing these challenges requires innovative solutions, yet existing studies often neglect to evaluate these innovations and their interactions within the broader IWT logistics framework and other transport modes.

This study bridges these gaps by introducing a comprehensive Discrete Event Simulation (DES) model to capture the dynamic interactions within the IWT logistics system, its interplay with other transport modes, and the potential impact of innovative measures on IWT performance. The model simulates the current container logistics system along the Rhine-Alpine (RALP) corridor, incorporating key elements such as cost-time calculations, transport mode selection, network flow allocation, and the assessment of IWT innovations.

The methodological framework and architecture of the DES model are presented, emphasizing verification and validation processes to ensure accuracy and reliability. The model outputs a network-wide analysis of the current IWT logistics system, examining mode split, cost, time, emissions, distance, and the interrelationships among these factors. This analysis serves as a benchmark for evaluating the effects of various innovative strategies on IWT performance.

By employing the DES methodology, this research advances the understanding of container IWT logistics, providing critical insights for stakeholders and policymakers. It evaluates the current performance of container IWT in the RALP corridor and identifies opportunities to improve the efficiency and competitiveness of container IWT.

In recent years, shared electric bikes (e-bikes), as a novel shared micro-mobility mode, have experienced a significant increase in popularity. Yet, there is still limited evidence on whether the two forms of micro-mobility act as complements or substitutes. By exploring the effects of the entry of shared e-bikes on bike-sharing and overall shared cycling usage, this paper aims to explore the role of e-bikes in sustainable transportation solutions. The paper combines nearest-neighbour matching and a difference-in-differences event study with bi-monthly panel data of conventional bike-sharing and e-bike-sharing trips from 2020 to 2021. Results suggest that the effect of e-bike-share on bike-sharing at the grid level shifted from an initial complementary effect to a later substitution effect, ultimately resulting in a 22.6% reduction in bike-sharing usage and a 65.9% increase in overall shared cycling usage. The introduction of shared e-bikes simultaneously attracted new user groups and reduced existing barriers to using conventional bikes. With growing market saturation, any further expansion is found to have come to the detriment of the incumbent technology, i.e. the conventional pedal bike. Although shared e-bikes ultimately replaced part of shared bikes, they have increased the overall use of micro-mobility tools, contributing to the popularization of sustainable transportation.

A recent market liberalisation of commercial passenger rail services since 2020 has brought a new era for long-distance transport in the EU. However, drawing from the experiences of countries with unsuccessful entry attempts, we investigate the effects of asymmetric train access charges (TAC). Asymmetric access regulation is based on lower access charges for entrants than for incumbents for a limited period in order to induce convergence of railway undertakings' (RU) market shares. Intending to compare the effects of symmetric and asymmetric TAC, we model oligopoly competition in the number of offered seats between the incumbent (Inoui) and entrant (Trenitalia) on the Paris–Lyon line, the first case of asymmetric TAC regulation on railways. In the first year of competition, consumer surplus, entrant's profit, and total welfare without infrastructure manager's profit increased with asymmetric TAC compared to symmetric TAC without discounts. As the discount for entrant diminishes over time, all previous welfare elements monotonically decline. By introducing new departures and running double trainsets, the entrant can reverse this monotonically declining trend. This implies that asymmetric TAC should provide additional incentives for entrants to increase their frequency and number of offered seats.

This paper aims to establish the impact of two medium-capacity transportation systems (MCTS) on housing prices in Medellín (Colombia): Metroplús, a bus rapid transit (BRT) system, and Tranvía, a tramway system. Using repeated cross-sectional data from the Medellín Quality of Life Survey from 2008 to 2018 and difference-in-differences estimators, we find that Metroplús has a negative impact on the growth of rental prices, whereas Tranvía has a positive impact. We do not find any effect on several other outcomes, such as the perception of quality and coverage of the public transportation in the neighborhoods they serve, and the number of private vehicles in the household.

The introduction of subways has a significant impact on surrounding land values due to increased floating population and improved accessibility. Many studies have sought to determine this change in the land value caused by subway operations. To overcome the limitations of the existing analysis, this study uses i) commercial land value, ii) a multilevel mixed-effects model, and iii) continuous yearly data before and after subway introduction. The study confirms that the land value changed significantly before and after the subway operation. The impact is larger in closer regions, and the rate of price reduction given a 1 m increase in distance to stations is greater. According to this study, the ability to more accurately estimate the indirect effects of introducing subways, such as fluctuations in land values, could contribute to the efficient distribution of transportation infrastructure funding and construction.

After the COVID-19 pandemic, passengers' concerns about crowding on public transit vehicles has increased due to their fear of being infected. Since WHO has announced that the elderly are the most vulnerable to COVID-19, it is important to understand the impact of crowding on the elderly and provide policy implications on public transit vehicles. The aim of this study is to analyze the behavioral differences between young adults and the elderly concerning the crowded conditions on public transit with a stated preference survey in Seoul metropolitan area. Crowding multipliers are estimated to quantify the impedance on crowding based on the mixed logit model. The results indicate that the elderly are more sensitive to crowding on public transit vehicles than younger people, and subway passengers are affected more by crowding than passengers who are using other modes of transit. In addition, it is confirmed that the preference of the elderly for public transit varies according to gender, income, and the purpose of travel. These analysis results can provide implications for setting new policy directions to improve the public hygiene and comfort of elderly people when they use public transit in the post-COVID-19 world.

As the global transportation sector grapples with challenges related to the energy crisis and climate change, New Energy Vehicles (NEVs) have emerged as a promising solution. In order to promote this new transportation technology, China has implemented strategic policies, such as the two-round NEV demonstration and pilot city program. Using a novel firm-month level panel data and the Difference-in-Difference (DID) strategy, this paper assesses the impact of the NEV pilot city program on NEV production from 2009 to 2016. Our findings reveal a significant increase in the production of Battery Electric Vehicles (BEVs) by 37.0% and Plug-in Hybrid Electric Vehicles (PHEVs) by 6.7%, primarily driven by financial subsidies in the private sector. The impact of the financial subsidy in both private and public sectors was further enhanced by government audit. Heterogeneous analysis shows the effect of the program was more pronounced in eastern regions, medium and small cities, and key cities for air pollution control. Based on the empirical findings, we discuss policy options for fostering new transportation technology in developing countries.

This paper presents results from a case study of fare revenue prediction in public transportation in Berlin using machine learning and time series analysis. Our work aims to aid in the implementation of automated revenue controlling and data-driven decision support within existing controlling processes.

We generate forecasts based on fare revenue data for different product segments aggregated on a monthly basis. Additionally, we model exogenous effects using data publicly available.

The results were obtained using a variety of methods including regression methods as well as autoregressive methods and exponential smoothing. Among others, SARIMAX, MLR, LASSO and Ridge were applied.

We evaluate the predictive quality of each method and compare them. Where appropriate, we apply automatic feature selection to improve performance.

Our findings, alongside a discussion of their interpretability, can serve as recommendations for practitioners, supporting them in choosing appropriate methods and suitable exogenous variables to reliably predict the fare revenues of different products.

Recent literature has documented consumers’ imperfect optimization when facing taxes. Despite the rich literature in this area, little research has been conducted in the airline industry context. I exploit the variation of tax changes in the airline industry to analyze how US passengers react to tax and price changes. I show that passengers react more strongly to taxes than to price changes through the use of semi-elasticities. Baseline estimates suggest that the tax elasticity of demand is approximately 1.5 times as strong as the price elasticity of demand. This paper extends the literature by allowing for heterogeneous price and tax responses, and by providing a series of possible rationales that explain how overoptimization can arise in the airline industry. Tax aversion, media coverage, persistent tax increases, psychological factors, and non-standard preferences suggested in the literature could all contribute to explaining passengers’ overoptimization in the airline industry. The findings in this paper have profound contributions both to the economic literature, to the airline industry, and practitioners at both the local and federal levels.