Ride-Hailing Service Adoption and Local Context in Motorcycle-Based Societies: Case Study in Hanoi, Vietnam

The ride-hailing service (RHS) has emerged as a major form of daily travel in many Southeast Asian cities where motorcycles are extensively used. This study aims to analyze the local context in motorcycle-based societies, which may affect the establishment of travelers’ choice set after the appearance of RHSs. In particular, it empirically compares three types of choice-set structures in the context of urban travel mode choice by estimating standard logit and nested logit models to test six hypotheses on the associations of RHS adoption with its determinants. Revealed preference data of 449 trips from both RHS users and non-RHS users were collected through a face-to-face interview-based questionnaire survey in Hanoi, Vietnam, in December 2020. The results of model estimations revealed: (1) a substitutional effect for two-wheelers but not for four-wheelers, (2) a significant positive influence of car ownership on car RHS adoption but not on motorcycle RHS adoption, (3) significantly high sensitivity to travel time of motorcycle RHS but not of car RHS, (4) a significant negative effect of traffic congestion on car RHS adoption but an insignificant one on motorcycle RHS adoption, and (5) a significant positive association of an individual’s experience in using a smartphone with car RHSs but insignificant association with motorcycle RHSs. Our findings suggest that transportation policies of RHS motorcycles should be different from those of RHS cars because of the heterogeneity in travel behaviors of RHS users between them. They also indicate that the transition from motorcycles to cars as well as the difference in service availability among different types of RHSs should be incorporated into the development of transportation policies in Southeast Asian cities.

Impact of Decentralization and Rail Network Extension on Future Traffic in the Bangkok Metropolitan Region

In many large cities in developing countries, investments in transportation infrastructure are insufficient for the growing population, resulting in chronic traffic congestion and overcrowding. The urban population of developing countries is expected to increase further toward the middle of this century, and urban planning and transportation policies that foresee future population changes and economic growth are necessary to make these cities more sustainable. Bangkok is one of the most congested metropolitan areas in the world, and transport projects such as the extension of the public transportation system are being implemented. However, due to the monocentric urban structure, both road and rail traffic is extremely congested during peak hours, which impedes some economic activities and personal interaction. In this study, we simulate the impact of urban and transportation measures in Bangkok from today to 2050. In addition to the expansion of the planned rail transit network, we evaluate the effects of a land use scenario in which sub-centers are established to develop a polycentric urban structure. The impact of alternative zoning and transportation policies and projects in Bangkok is discussed. Although this study is focused on Bangkok, the findings are assumed to be transferable to other large cities in developing countries.

FACTORS FORMING CITIZENS’ TRANSPORTATION BEHAVIOR: THE CASE OF ST. PETERSBURG

Successful implementation of public transportation reform cannot be achieved without studying transportation behavior of citizens. The results of an empirical analysis of the behavior of St. Petersburg residents presented in this article make it possible to assess what transportation policies will be successful in attracting car users to travel by public transport. The aim of the study was to identify the patterns of transportation behavior in St. Petersburg: attractiveness of various transportation modes, mode choice factors as well as satisfaction with public transport and transportation policies aimed at stimulating the use of public transport. The research methodology includes survey of the population and the analysis of descriptive information from the data obtained. In addition, principal component analysis was applied for travel factors grouping. The results of this study may be used in elaboration of transportation policies aimed at changing transportation behavior of the citizens. The main finding of this study is the relative importance of trip time for public transport in contrast to private car.

Framework for Country-Level Sustainable Transportation Policy Learning using Public Support as a Measure of Cultural Distance

As the world shapes a global agenda to mitigate climate change, national governments are looking to define sustainable development strategies for the transportation sector. In this international landscape, countries will look to learn from one another, but identifying peer countries for this learning can prove a challenge. In this study, we measure public support for transportation policies and use this as a measure of cultural distance to identify peer countries. We modeled public support for 11 transportation policies in an international sample of 41,932 individuals in 51 countries or regions. Using a model that controls for individual effects, we measure pure country-level differences in public policy support. Measuring public support for different transportation policies can help policymakers understand how the public evaluates and envisions the role of government in shaping the current as well as future transportation system, and to anticipate difficulties of implementing certain types of policy because of public resistance. In general, we find the highest public support for a given policy appears in countries that have not yet seen significant investment in the target infrastructure or service. We show that considering public support for transportation policies gives a different perspective than traditional indicators of economic development or level of motorization, helping policymakers understand what the public wants and how they might build support for new transportation policies. Finally, we present a clustering framework that goes beyond development status and geographical adjacency to help identify peer countries for policy learning using public policy support as a measure of cultural distance.