This study investigates the optimization of ride-sharing services (RSS) on the ride-hailing service (RHS) providers in Bangladesh. This study employed an explanatory sequential mixed method research design- a qualitative study followed by a quantitative one. Qualitative data were collected through focus group discussions and in-depth interviews with twenty (20) riders and drivers in Bangladesh, and quantitative data were collected from 300 respondents consisting of riders and drivers using a convenience sampling technique. Factor analysis and hierarchical cluster analysis were applied to the data analysis. The qualitative analysis reveals several significant factors associated with RSS and RHS, including cost efficiency, fare, fuel consumption, traffic congestion, carbon emissions, environmental pollution, employment opportunities, business growth, and security. The quantitative results indicate that using RSS is associated with more significant benefits than RHS in various aspects, including cost efficiency, fare, fuel consumption, traffic congestion, carbon emissions, environmental pollution, employment opportunities, and expansion of the automobile industry. The findings may assist policymakers in understanding how RSS can yield more incredible economic, environmental, and social benefits than RHS by analyzing fare sharing among passengers, carbon emissions, fuel consumption, and the expansion of the vehicle markets etc. Therefore, the government can formulate distinct policies for RSS holders due to their contributions to economic, social, and environmental concerns. While RHS services are available in many cities in Bangladesh, this study considered only Dhaka and Sylhet cities. Thus, future studies can consider more respondents from other cities for a holistic understanding.
The use of public transport is one of the concepts of sustainable transport. However, people prefer to use private vehicles, which causes various problems, one of which is the high carbon emissions produced. This research aims to encourage programs to use passenger public transportation through a carbon tax. The method in this research is descriptive quantitative with primary data and secondary data. Secondary data was developed in the research by collecting literature study sources on the concept of sustainable transportation development as well as primary data carried out by analyzing calculations regarding the implementation of the carbon tax. There are several proposals that can significantly accelerate the achievement of goals, namely a collaborative approach through collaboration between local government agencies, a policy of progressively implementing a carbon tax as a coercive policy and supported by a program to provide supporting facilities for public transportation. Decision making in this research was carried out by looking at the percentage increase in public transportation use based on the application of a carbon tax or carbon tax.
This article focuses on studying how transportation connectivity affects Vietnam’s trade with Association of Southeast Asian Nations (ASEAN) countries. By using a gravity model, the article applies fixed effects (FE) and random effects (RE) to analyze panel data on trade, GDP, tariffs, border effects, and indicators. The number represents Vietnam’s transport connectivity with ASEAN countries from 2004 to 2021. Research results show that transport connectivity hurts Vietnam’s trade with other countries. ASEAN. The article proposes solutions for the Government and Vietnamese export enterprises to promote intra-ASEAN trade in the direction of increasing the added value of Vietnam’s imported and exported goods within ASEAN countries and balancing between Developing intra-ASEAN and foreign trade.
Urbanization and suburbanization have led to high population growth in certain city regions, resulting in increased population density and mobility. Therefore, there is a need for a concept to address congestion, public transportation, information and communication systems, and non-motorized vehicles. Smart mobility is a concept of urban development as part of the smart city concept based on information and communication technology. Through this concept, it is expected that transportation services will be easily accessible, safe, comfortable, fast, and affordable for the community. This research aims to analyze smart mobility and its relationship with regional transportation planning and the development of South Tangerang, as well as to design a policy strategy model for the planning and development of South Tangerang with smart mobility. The research method used in this study is a mixed method, including analyzing the relationships and weighting of relationships between variables using the Cross Impact Multiplication applied to a classification (MICMAC) matrix. Multi-criteria decision analysis (MCDA) with Promethee software is also used to obtain the necessary policies. The results of this research indicate that the measurement of relationships between variables shows that smart mobility influences regional transportation planning, smart mobility affects regional development, and regional planning affects regional development. This research also provides alternative policies that policymakers should implement in a specific order. First, ensure the availability of public transportation; second, improve public transportation safety; third, enhance public transportation security; fourth, improve public transportation routes; fifth, provide real-time information access; sixth, improve transportation schedules; and seventh, increase the number of bicycle lanes.
The carbon footprint, which measures greenhouse gas emissions, is a good environmental indicator for choosing the best sustainable mode of transportation. The available emission factors depend heavily on the calculation methodology and are hardly comparable. The minimum and maximum scenarios are one way of making the results comparable. The best sustainable passenger transport modes between Rijeka and Split were investigated and compared by calculating the minimum and maximum available emission factors. The study aims to select the best sustainable mode of transport on the chosen route and to support the decision-making process regarding the electrification of the Lika railroad, which partially connects the two cities. In the minimum scenario, ferry transport without vehicles was the best choice when the transportation time factor was not relevant, and electric rail transport when it was. In the maximum scenario, the electric train and the ferry with vehicles were equally good choices. Road transportation between cities was not competitive at all. The comparison of the carbon footprint based on minimum and maximum scenarios gives a clear insight into the ratio of greenhouse gas emissions from vehicles in passenger transport. It supports the electrification of the Lika railroad as the best sustainable transport solution on the route studied.
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