Case Studies on Transport Policy最新文献

The COVID-19 pandemic profoundly impacted the tourism and aviation sectors, leading to a shift from international to domestic travel, especially in China. Cultural tourism, including red tourism, was still active and played a pivotal role in China’s domestic tourism during the pandemic. This study used the panel vector autoregression (PVAR) model and the panel Granger causality test to investigate the interplay between red tourism, airline seat capacity, and the COVID-19 cases during the COVID-19 pandemic. This study contributed to the existing literature of the interplay (or the endogenous interaction) among these three endogenous variables. It found that red tourist numbers have significantly affected airline seat capacity in Chinese domestic market in the face of the disruptive effects of COVID-19. Red tourist numbers and airline seat capacity have the positive and negative relationships with the COVID-19 cases of origin cities but not at red tourism destinations. Although it primarily focuses on China’s red tourism, this study highlights avenues for cross-cultural exploration and a deeper understanding of the dynamic interplay among red tourism, aviation, and the impact of the COVID-19 pandemic. This study concludes by offering insights in developing and shaping cultural tourism and industry’s preparedness strategies, helping the tourism and aviation industries recover and thrive in the post-COVID-19 era.

Prior research has found that people’s intentions to use autonomous technologies such as autonomous buses largely depend on factors like trust towards the technology, while little is known about the role played by the shared benefits. Unlike benefits obtained by the individual user of technologies, shared benefits are commonly societal benefits shared by users. We formulated hypotheses to explore the role of shared benefits in driving the use intention of autonomous buses and tested the model with survey data collected from people living in the greater Helsinki metropolitan area. We analyzed data using Covariance-based SEM, and our results show that perceived shared benefits are among the most vital indicators of autonomous bus use intention. To promote citizens’ acceptance of autonomous buses, the public transport authorities and bus operators should ensure that autonomous buses deliver shared benefits through service that is environmentally friendly, comfortable, easy to use, and accessible for all.

Major transportation infrastructure projects are often associated with public disputes and polarised debates. However, by using the example of a controversial infrastructure project in Vienna (the “Lobau highway”), we show that a binary “pro-versus-con” framing does not do justice to the complex realities of such debates. Based on a Q methodological analysis, we reveal four distinct perspectives, which reflect a broad spectrum of “generally pro” and “generally against” positions: (i) More roads, more traffic, (ii) Less politics, more facts, (iii) Better roads, better city, and (iv) The highway must be built. While our analysis points at unexpected overlaps between perspectives and some entry points for consensus building, it also highlights disagreement on fundamental beliefs such as the impact of roads on the environment, the phenomenon of induced traffic, or the right to drive a car. Against this background, we discuss the wider socio-political context of the analysed debate, reflect on the basic premise of consensus building, and derive policy implications.

This paper investigates the Potential for More Walking (PMW) in work tour among car commuters and proposes ways to encourage them to activate this potential. The study utilized a sample of 621 car commuters in the city of Qom, Iran, who expressed a willingness to replace their daily commute pattern with an alternative commute pattern that involves more walking time. The findings of the random effect binary logit model indicated that network patterns with improved connectivity in the residential neighborhood have a significant impact on activating the PMW. Additionally, subjective factors such as positive perceptions towards sidewalk conditions, longer distances between home and workplace, and positive attitudes towards walking were found to be associated with an increased tendency to activate the PMW. Moreover, the study assessed a set of transportation demand management measures that could influence individual behavior towards activating the PMW. The results indicated that pull measures are generally more effective than push measures in promoting walking during work commuting. Furthermore, the measures of turning streets with dense land-uses into pedestrian malls, increasing green spaces on sidewalks, and widening sidewalks were found to have the highest impact on activating the PMW, respectively.

The Covid-19 pandemic has posed significant challenges to the sector, and Türkiye’s strategic location plays a crucial role in crisis management. This study aims to explore the repercussions of the pandemic on the sector and propose appropriate solutions. To identify the most effective solutions for prioritizing the challenges posed by Covid-19, 53 sector experts participated in the study. The Stepwise Weight Assessment Ratio Analysis method was used to weigh the criteria representing these challenges. The solutions were ranked using the Weighted Aggregated Sum Product Assessment and Combined Compromise Solution methods. The results indicate that the primary challenge is the increased shipping cost, followed by the prolongation of the transport time, global-scale impacts, and port congestion. The most appropriate solution identified was alternative vessel loading, followed by mixed-mode transportation usage, reservation guarantees, long-term contracts with shipping operators, integrated logistics services, container purchases, and technological integration.

This study explores the impact of emerging vehicle technologies on direct urban traffic emissions. It investigates emission reduction potential from shifts in fleet compositions and modal choices, especially considering climate change. To achieve this, three key research areas are explored for historical, current, and future scenarios (up to 2050): mode choice, emission factors for different vehicle categories, and diverse vehicle propulsion technologies. The estimation of the modal split is pivotal, developing a methodology utilizing Stated Preference survey data, discrete choice modeling, Monte Carlo simulations, and macroscopic traffic simulations. Future scenarios derive from the reference year’s modal split, and emission factors and fleet compositions are predetermined via an extensive literature review, aiding the assessment of their respective emissions. A subsequent sensitivity analysis identifies the impact of specific parameters on emissions, guiding future research focus. Study results underscore differences in greenhouse gas emissions and primary air pollutants between base and future scenarios.

The advent of connected devices, such as smartphones, has had a transformative impact on the landscape of recent years. Once privacy concerns have been addressed, data can be handled and analysed in a proficient manner to gain insights into patterns and movements, thereby influencing urban policies. It is likely that mobility and transport-related topics have been the subject of the most extensive investigation in the field of cell phone big data. While the topic of commuting patterns has been extensively researched by numerous authors, there is a paucity of literature on the monitoring of attendance during major motorsport events. Despite the predictability of crowding (tickets are sold in advance and the schedule is fixed and rigid), multiday motorsport events are disruptive in terms of traffic, overcrowding and uneasiness for hosting cities. This paper aims to address the aforementioned gap by presenting a case study of monitoring attendance during the Formula One Emilia-Romagna and Made in Italy Grand Prix, held in Imola, Italy, from 22nd to 24th April 2022. The results demonstrated the potential of data to inform the prediction of mobility choices and the planning of appropriate mobility-related policies, with the aim of reducing the impact of future events. This represents a significant challenge for public administrations and stakeholders.

High-capacity trucks (HCTs) are vehicles that are heavier or larger than normally allowed and are used as a means of increasing the efficiency of road freight transport and reducing emissions. The present research analyses the economic and environmental efficiency of HCTs by comparing them with normal semitrailers. Survey-based estimates on cost structure, fuel consumption, load factor and empty running of semitrailers, road trains and HCT combinations currently operating in Finland have been used to calculate whether HCTs improve the cost competitiveness and reduce the emissions of road transport. The results indicate that HCTs have a 42% emission reduction potential in mass-based transport and a 38% potential in volume-based transport compared to normal semitrailers.

This research is aimed at developing a method for relocating wholesale markets in a city with the objective of decongesting the central area by improving the traffic efficiency and to make it pollution free. This paper proposes a bi-level optimisation framework pursuing the local authority’s objective of maximising welfare benefits relative to the spend ensuring good value for money at the upper level. The lower-level framework considers retailers’ response to the relocation of wholesale markets allowing them the choice of procurement location. The lower-level problem also models the route choice of commercial vehicle traffic as well as the private vehicle traffic to measure the resulting on-street congestion. The bi-level problem has been solved with integer Particle Swarm Optimisation algorithm for the case of Bandung, Indonesia. The results show that relocating wholesale markets improves the city centre traffic efficiency and pollution level by about 14%. Traffic speeds over the entire city also improve by up to 6.6% and the pollution levels marginally would drop too. Market relocation as a strategy would significantly improve the efficiency and pollution levels but must be carefully planned and evaluated otherwise the emissions outside of city centre could increase.