Asian Transport Studies最新文献

Maximizing the surplus received by each actor is an ongoing issue in the current rice supply chain model. This study assesses a supply chain network that involves five business actors, namely collectors, wholesalers, retailers, demand markets and freight carriers. The interconnectedness of the actors results in a dynamic supply chain problem and free competition. The Supply Chain Network Equilibrium (SCNE) method is commonly used to solve this problem but poses the important issue of the ease of computation. Another method to achieve network equilibrium is the method of successive average (MSA). The MSA is more capable of optimization to generate accurate results with fewer iterations than the SCNE method. The simple case and real case results demonstrate that the MSA method can be used as an alternative for optimizing rice supply chains.

The Northern Sea Route (NSR) has been navigated successfully with the melting polar ice and developing technology, which will impact China's bulk trade with the European Union (EU) countries. This research mainly investigates the effect of using NSR for grain transport with a minimum comprehensive cost, including shipping costs and environemental effects. Integer programming has been applied to optimize the simulation system with 24 routes and six types of vessels (five conventional vessels and one ice-class vessel) in the with-NSR and without-NSR situations. The result shows that the cost will be reduced by 20% with-NSR scenario, and an additional 7% reduction can be found with the increase in the ice-class vessel fleet. Due to the current demand, panamax-sized vessels are the most preferable. This article also provides an optimal and feasible framework for vessel scheduling in with-NSR and without-NSR situations.

Flooding in Metro Manila is a perennial problem given the frequency of typhoons hitting the country every year. When a flood occurs along major roads, vehicular traffic usually results in a standstill, causing major disruptions that impede the flow of people, goods and services. The study assessed the impact of flooding in terms of changes in the route of trucks under reduced road capacities and design speeds while considering the impact on vehicle-distance travelled, vehicle-hour travelled, average travel speed, among others. GPS data loggers were used to track the movements of selected trucks during normal conditions to determine their regular routes. Face-to-face questionnaire survey was also conducted to know the behavior of truck drivers during flooding incidents. Scenario modelling under flooded conditions was developed for a typical day during which trucks are allowed to operate on the road under a 5-year and 25-year flood incident. On a metro-wide scale, during flooding, the vehicle distance travelled (VDT) and vehicle hour travelled (VHT) may not necessarily increase since some vehicles, including trucks, may not be able to travel or are unassigned resulting in a lesser number of them on the road, effectively reducing VDT and VHT. Furthermore, higher VDT during the 5-year flood event were observed compared to the 25-year flood event since there are still many vehicles travelling during the former in search of alternate routes resulting in more distance travelled. However, focusing only on flooded roads, the travel time spent by vehicles increased in order for them to reach their destinations even with reduced number of vehicles traveling on these flooded roads.

This study aims to evaluate to what level bicycles can replace motorized vehicles during the outbreak. The survey respondents were asked to choose between a bicycle and existing motorized vehicles for seven choice scenarios based on traffic congestion and bicycle infrastructure. This study integrated a multiple-indicator, multiple-cause (MIMIC) and a mixed logit model to examine the attitudes change caused by the outbreak and the social influences on the preference for bicycles. The results indicated that developing bicycle infrastructure encourages the adoption of bicycles, although most users tend to come from low-income and less-educated people. Based on the MIMIC model results, this study found significant differences in attitudes change and social influences across respondents’ socioeconomic characteristics, as male respondents were more likely to be easily influenced by their friends with respect to cycling than females. Attitudes change related to global warming and environmental consciousness also affected the preference for bicycles.

The COVID-19 pandemic has disproportionately affected vulnerable populations and permanently changed travel behavior. This study aims to explore the relationship of social vulnerability and travel behavior with COVID-19 in Metro Manila, Philippines. Using data from an online questionnaire survey, and applying ordinal logistic regression analysis, results showed that gender, household crowding, lack of vehicle access and type of occupation can contribute to virus exposure. In addition, multiple linear regression analysis was applied to mobility data from Google and Apple. Results from the analysis support the hypothesis that traveling to groceries or retail stores can increase the risk of exposure to the virus, while staying at home and walking as transport mode, lessens the risk. Findings from this research provide a perspective of COVID-19 impacts in a developing country; moreover, results can be used by policymakers as a guide in formulating pandemic response strategies which considers the most vulnerable groups.

The rapid urbanisation in cities, and its associated complexities demand that sophisticated decision support tools such as the LUTI models be employed to assist the balanced and sustainable development of transport and land use. It is evident from literature studies that the majority of LUTI models need extensive data, making them expensive and time-consuming, which will be a challenge for developing countries. On the other hand, with the advent of information and communication technology, the availability of high frequency (HF) data is increasing which can be collected at disaggregated level data frequently at little or no cost. The main focus of this research is trying to bridge the gap that exists between research with this type of data and it subsequent application in real context. On the basis of this, the paper focuses on (1) summarizing existing LUTI models and their corresponding data requirements; (2) explaining the sources of HF data in LUTI modelling; and (3) discussing the applications and challenges in implementation of such data in LUTI modelling. This review identifies the recent development of technology and availability of HFD can fill the gap of data availability for LUTI which has been discussed by a great number of authors in literature. Furthermore this kind of novel source of data can increase the potential of LUTI model particularly in developing countries, where land use and transport patterns are changing rapidly and where traditional forms of data are expensive to collect.

This study identifies focal points for the successful development and operation of Port Community System (PCS). First, we conducted a literature review and present a comprehensive and systematic overview of the focal points. Second, as a case study, we analyzed the history of PCSs and their related systems in Japan, including an analysis of the systems that had been discontinued and the trend of integration. Consequently, we found some novel focal points that had been overlooked in existing research, such as the importance of avoiding the duplication of functionalities between PCSs and existing related systems and the difficulty in making users bear the cost burden of their own system's update for system linkage with a PCS before the utilization of the PCS is spread. Finally, we discuss the implications for certain focal points, such as the target PCS usage rate.

The COVID-19 pandemic and the resulting control measures by the government impacted the travel behavior of Filipinos. With work trips being a major part of trips generated, this study aimed to investigate the effects of the pandemic on working Filipinos' mode choice. Data were collected from employed residents of Metro Manila using an online survey. About 48% of the respondents preferred using public transportation for work pre-pandemic. This decreased to 22% during the transport lockdown and increased slightly to 25% after the lockdown was lifted. Active transport share increased by 3% during the lockdown but went back down after it was lifted. Using multinomial logistic regression, the significant factors that influence the pre-pandemic respondents’ mode choice were age, household income, travel cost, and vehicle ownership. During the lockdown, travel distance, travel time, and sex assigned at birth became significant also. After the lockdown, the significant factors reverted to that pre-pandemic.

This research aims to comprehend commuting experiences in rapidly growing metropolis from the perspective of accessibility, especially subjective accessibility, to better understand barriers and opportunities to using public transport. We examined Jakarta as an exemplar city experiencing an ever-increasing car dependency despite proactive policies and projects for modal shift. A qualitative descriptive method is used to investigate the nuances of individual experiences across mode and incomes. In-depth analysis of 110 questionnaires indicated that the public transport users perceived a higher-level accessibility due to convenience, affordability, and no congestion, while private transport users had low-level perception. The stereotypes of public transport appeared to nullify the benefits of public transport. Furthermore, most individuals had complicated attitudes about a certain mode, and positive feeling was not necessarily related to mode choice. For “access-for-all”, considering objective and subjective measures holistically is essential for interrogating critical issues of transport system and optimizing positive travel experiences.

The COVID-19 pandemic has radically altered how the world uses public transportation. Our study investigates the significant decrease in travel demand for public transport in Bangkok, Thailand due to the fear of contracting COVID-19, government public health measures aimed at mitigating risk, and remote and online behaviors adopted by the public. We examined the determinants of changes in travel frequency for all trip purposes among public transport users in Bangkok, Thailand during the COVID-19 pandemic using the within-between random effect model. These included online activities and behaviors, individual perceptions of COVID-19 risks, and sociodemographic and socioeconomic factors. Our findings revealed that demand for public transportation will likely return as COVID-19 becomes endemic and that work-from-home measures, remote learning, and food delivery services could substantially reduce individual travel demand. These hold important lessons for policymakers in balancing public health measures with the evolving supply and demand needs of Bangkok's transportation infrastructure.