Case Studies on Transport Policy最新文献

Vehicle sharing is one of the most innovative ways to transport business and management. The purpose of this study was to determine factors affecting the perceived usability of vehicle-sharing mobile applications by integrating the Unified Theory of Acceptance and Use of Technology (UTAUT), pro-environmental behavior (PEB), and system usability scale (SUS). 206 Taiwanese filled out an online questionnaire with 65 questions which was shared using a convenience sampling approach. Partial Least Squares-Structural Equation showed that perceived usability was found to be significantly influenced by price value, environmental concern, authority support, behavioral intention, and actual use. Interestingly, authority support was found to have the highest significant indirect effect on perceived usability, indicating that vehicle-sharing mobile applications must be supported by the national government in order for people to consistently use them. This study is one of the first studies that analyzed vehicle sharing, particularly the mobile application. The findings of this study may be used as a guideline or strategy for the national government to reduce environmental risks caused by thousands of vehicles in the country, for vehicle-sharing companies to further boost their profit, and for other investors who intend on utilizing mobile applications for their market.

Concern is growing regarding the increasing use of private car in many developing countries, including Thailand. Car usage is rising in Thailand in part because the public transit system is inadequate and unreliable, especially in rural and suburban communities. Often, children’s route to school is unsafe due to the increasing number of cars around the school. This prompts parents to worry about their child’s safety when in transit. The model of travel by public transportation is an alternative for reducing road congestion and improving children’s safety. This study seeks to better understand the factors that influencing parents’ decisions regarding the use of public transportation for their children’s school commutes. Data were gathered through a questionnaire from a sample of 750 parents with children between the ages of 6 and 18 years in Nakhon Ratchasima Province, Thailand. The findings of the structural equation model analysis showed a relationship between service users’ loyalty and the components of satisfaction, trust, expectation, and perception of service quality. The outcomes derived in this study can serve as practical guidelines for public and private transportation system operators to improve service efficiency, meet consumer demand, and foster positive interactions between service users and operators. In this way, this study can lead to important internal and external benefits for the continued development of the public transportation system and motivate more service users to transition to the use of public transportation.

Road traffic crashes (RTC) are the main cause of mortality, morbidity, and disability for children globally as well as in the United Arab Emirates (UAE). Although vehicle occupants usually account for the majority of children involved in RTC in developed countries and in the UAE, injuries sustained by child vulnerable road users (VRUs) are usually more severe due to their lack of protection compared to child occupants. Such injuries are known to result in long-term suffering for children including disabilities in some cases, thereby posing a severe public health burden and economic losses to the population. However, despite the severity of injuries to child VRUs involved in RTC, studies in the UAE have mostly focused on vehicle occupants for both children and adults. To the best of our knowledge, this is the first dedicated study on child VRU RTC injuries in the UAE. Additionally, the UAE government is promoting an active transportation policy among children in a bid to curb childhood obesity. Hence, this study examined the factors contributing to RTC injury severity for child VRUs in the UAE. The results of this study will help in enhancing the safety outcomes of child VRU RTC injuries as well as providing policy recommendations for safe active transport among children in the country.

Network Data Envelopment Analysis (NDEA) has been extensively applied to evaluate the air transportation sector. NDEA provides a tool for evaluating the internal processes of Decision-Making Units (DMUs). Optimistic Network Cross-Efficiency (ONCE) has recently been extended to the basic two-stage system. However, there are still two main shortcomings that need to be addressed. First, the ONCE evaluates DMUs based only on the optimistic viewpoint, neglecting the pessimistic viewpoint. The optimistic viewpoint assumes that there is only one set of reference points, which includes the best practice DMUs. The first contribution of this study is to develop a new Pessimistic Network Cross-Efficiency (PNCE) method. This method is based on a new set of reference points, which includes the worst-performing DMUs. The PNCE is developed as an extension of the ONCE. Second, both the ONCE and newly developed PNCE methods may lead to unrealistic results because they neglect the subjective preferences of Decision Makers (DMs). These NDEA models employ the Arithmetic Mean (AM) as the cross-evaluation aggregation method, which not only underestimates the importance of self-evaluation but also overestimates the importance of peer evaluations. Consequently, ONCE and PNCE may lead to biased efficiency results. To address this drawback, the second contribution of this study is to develop a new Aggregation method based on the Regret theory and Consensus (ARC). This method aims to reflect the psychological preferences of DMs when estimating cross-evaluation weights. To achieve this goal, we obtained new optimistic and pessimistic efficiencies by utilizing the newly developed ONCE-ARC and PNCE-ARC methods. Subsequently, a Double-Frontier Network Cross-Efficiency with ARC (DFNCE-ARC) is developed as a more comprehensive NDEA. Finally, a practical application is conducted to assess the performance of a set of Iranian airlines, demonstrating the usefulness and applicability of DFNCE-ARC.

This study examined the long-term impacts of the COVID-19 pandemic on mobility patterns in Indonesia, focusing on the transition from pre-pandemic norms to the endemic phase. Using quantitative methods and retrospective data analysis, we explored changes in travel behaviour, including mode choice, trip frequency, and travel time. We identified travel behaviour in three phases: pre-pandemic, pandemic (March 2020 to the end of January 2022), and transition to endemic (the data collection period: July – August 2022). Our investigation of the shifts in travel behaviour across these periods enabled us to distinguish between temporary fluctuations and enduring, potentially long-term changes in behaviour. The empirical investigation revealed significant alterations in trip frequency that persisted during the endemic phase, suggesting that these changes in mobility are likely to continue. Factors influencing these shifts include socioeconomic characteristics, work modalities, and attitudes toward health protocols. This study contributes to the understanding of pandemic-induced travel behaviour transformations and provides insights for policymakers and transportation planners to adapt to these changes in the Southeast Asian context.

Over the last two decades and a half, the Ethiopian government has been involved in extensive road construction as part of successive road development plans that have significantly increased road network coverage. However, the tendencies that worsen congestion show no signs of abating. As a result, drivers and passengers waste time in long traffic lines, rendering modern travel unreliable and increasing travel costs due to delays. To curb the problem, the remedies proposed by practitioners or researchers are mostly centred on the supply side. This study aims to determine drivers’ willingness to pay (WTP) (from the demand side) for a hypothetical congestion reduction project. A stated preference survey was utilised on the population identified in nine segments in Addis Ababa’s Kolfe Keraniyo sub-city. The data was gathered from 1012 respondents using a survey questionnaire based on the contingent valuation method (CVM). Tobit and Heckman two-step selection models were used to estimate factors determining WTP for congestion reduction. Accordingly, the analysis showed that the average amount of willingness to pay by drivers was estimated to be birr 2.7 ($0.05) per km. Education, marital status, income, segment use, and trip frequency significantly determined the outcome equation, while age, gender, income, occupation, work experience, and regularity and frequency of segment use were found to determine the decision to participate in WTP to accept congestion pricing. Identifying the willingness to pay and the desired price can assist the Addis Ababa City Administration in establishing a baseline for any future congestion reduction strategy based on congestion pricing.

In response to the imperatives outlined in SDGs 7, 11, and 13 and the Paris Agreement, folks increasingly focus on transportation to mitigate climate change. Uganda’s capital, Kampala, lacks ratified passenger land transportation plans. This study employs the KLAP-TIMES model, a bottom-up engineering framework, to examine Kampala commuters’ behaviors using three scenarios. Leveraging TIMES-VEDA, the study explores a baseline scenario (BAU) without time travel financial (TTF) limitations or distinctive Value of Travel Time (VTT) levels but with model permissions for competition among dissimilar trip modes, technologies, and fuels, a Kampala Accessibility and Priority Options (KAPO) Scenario with specific VTT levels under TTF limitations, and the Kampala Sustainable scenario (KSS), with a 50% carbon emissions bargain in the system by 2060, contingent upon the persistence of VTT and TTF over the planning horizon. The study utilizes the VTT purposively to measure infrastructure investments as a policy shock on travel time. By exogenously inputting travel demand, the model elucidates the endogenous preferences of individual commuters among various trip modes, including Boda-boda, Kampala sedans, and mass rapid transit (MRT) with an electrified Metro at its core, for both short—and long-distance journeys. The findings reveal significant shifts in consumer behavior, particularly in the Kampala Sustainable scenario, where commuters prefer the electrified Kampala Metro for both short—and long-distance travel, signaling a notable departure from traditional Kampala sedan usage. The study suggests prioritizing the value of travel time (VTT) alongside a carbon reduction trajectory (KSS) is a strategic route for sustainable mobility in Kampala. The study provides valuable insight to policymakers, aiding them in formulating and enacting transportation policies that effectively support Kampala’s sustainability objectives.

The increasing demand at maritime traffic nodes in multi-modal transport emerges as a critical factor for the country’s economy. Consequently, terminal operators should focus on proper strategies and policies to satisfy the increasing demand. This paper exploits the integration of Information Communications Technology systems into physical infrastructures and offers an in-depth study of operations and performance optimisation for a maritime terminal. The case study is the Messina-Tremestieri port (Sicily, South Italy), characterised by a high flow of cars and freight vehicles. This port is in the comprehensive Trans-European Transport Network, and it links Sicily Island with Italy, offering high-frequency services. About 30% of the goods by Ro-Ro services pass through this port: so, it makes sense to use it as a case study. The arrivals distribution, the terminal capacity and the supply offered by the shipping companies are considered input, and terminal efficiency is evaluated through indicators such as the saturation of the yard area and the average vessel load factor. Besides, the study offers two viable solutions to the emerging port saturation. First, a tactical policy (with no infrastructural costs) includes the introduction of flexible time windows. Alternatively, the introduction of additional vessel services has been evaluated during peak hours. Benefits have been simulated by comparing the total number of vehicles served in current and simulated scenarios.

The FMCG (Fast-Moving Consumer Goods) sector is the fourth largest sector in India, significantly contributing to the economy by driving the growth of gross domestic product (GDP) and enhancing employment opportunities. In India, most of the transportation of FMCG goods is dependent on road freight transport only hence the vehicle fill rate is gaining importance day by day. The vehicle fill rate is adversely influenced by various constraints including weight & load limits, variability in truck carrying capacity, etc. that further influence the performance of road freight transport, resulting in high transportation costs. Various strategies are required to overcome the constraints which will help optimize transportation costs for the FMCG sector in India. This study identified 32 solutions with Fuzzy TOPSIS (Fuzzy Technique for Order Preference by Similarity to Ideal Solution) employed for ranking of the solutions. Transport policy is identified as one of the top solutions, which plays a vital role in improving vehicle fill rate in the long run. Implementation of the solutions according to the need and rank may help the decision-makers and policymakers to achieve enhanced performance in road transport, compete globally, and contribute to the economy as well as the environment.

Introduction

Introducing new public transit systems impacts the surrounding built environment, and changes in the built environment can affect travel behavior. Prior research has yet to thoroughly conduct a comprehensive exploration of the influence of new investments in public modes of transit, particularly streetcars, on motor vehicle crashes occurring on adjoining streets, considering other related factors. In particular, the difference between short-term and mid-term impacts of streetcars considering initial break-in periods has yet to be thoroughly conducted. This study focuses on the short-term and mid-term effects of the streetcar on total, injury, and pedestrian-involved vehicle crash rates on the adjacent street, considering traffic volume, traffic speeds, and traffic conflicts (transit ridership, pedestrian volume, and traffic policy).

Data & Method

This paper used the Utah Department of Transportation’s (UDOT) crash count, annual average daily traffic (AADT), iPeMS data, Utah Transit Authority’s (UTA) ridership, manually calculated pedestrian volume from Google Street View, and conducted interviews with UDOT’s experts. In the method, we used three quasi-experimental research designs: (1) before-after without a control group, (2) interrupted time series, and (3) before-after with a control group. In addition, to identify the cause of this impact, we examined multiple dimensions, including traffic volume, traffic speeds, transit ridership, pedestrian volume, and adjustments in traffic policy changes.

Results

As a result, the establishment of the S-Line streetcar eventually led to a significant decrease in total (short: 11 %, mid: −15 %), injury (short: −9%, mid: −41 %), and pedestrian-involved (short: −25 %, mid: −43 %) crash rates on the adjacent street, especially after the streetcar was fully established (3 years after). In particular, injury and pedestrian-involved crash rates decreased significantly. Also, we found that increased drivers’ awareness and vitality of the street due to the increased transit ridership (short: 43 %, mid: 50 %), increased pedestrian volume (short: 35 %, mid: 75 %), and improvement of traffic signal on the adjacent street can be the main causes.

Practical Applications

The outcomes of this study are considered to help establish short-term and mid-term traffic policies that consider public transit improvements such as streetcars.