There is a question whether residents in the local context of developing cities in Asia can support changes in the built environment for the purpose of travel. This study analyzed the determinants of residential satisfaction using data from 948 respondents collected through a face-to-face questionnaire in the metropolitan area of Jakarta, Indonesia. The potential determinants of residential satisfaction included the respondents’ subjective evaluations of residential environments; the extent of their social interaction with neighbors; and built environment conditions including housing, neighborhood characteristics, and geographical location of the residence; in addition to individual socio-demographics and activities. Structural equation modeling was applied to simultaneously estimate the impacts of residential environments on residential satisfaction and individual activities. The results indicate that neighborhood-level built environment conditions have a significant impact on residential satisfaction, such that a larger residence lot size and shorter travel time to the nearest bus stop significantly increased residential satisfaction. The results indicate that the roles of the built environment, as an instrument for enabling sustainable travel and for enhancing residential satisfaction in our study area, can be in conflict. This reinforces the importance of setting a land use policy target aiming to create sustainable travel that can be shared by local residents.
This paper presents an empirical study on vehicle type choice, usage, and CO2 emissions in Ho Chi Minh City, using data of 1585 participants in a 2014 survey. A joint discrete-continuous model based on the copula approach is used to overcome selectivity bias in the data and to address the relationship between vehicle type choice (a discrete outcome) and usage (a continuous outcome) by specifying a joint distribution. The results show that the two choices are interdependent and probably impacted by socio-economic attributes rather than built environment attributes around the home location. In addition, the simulation describes a shift from motorcycles to cars, and an increase in usage, resulting in a 60% increase in CO2 emissions/passenger/month over a 10-year period. Lastly, the study analyzes two interventions intended to decrease vehicle usage and CO2 emissions, namely increasing operating costs and encouraging greater sharing of vehicles, which will be useful for policymaking.
Paratransit modes provide a pro-poor transport option with lower pollution and congestion rates, especially in developing countries. The recent emergence of new Web 2.0 fueled paratransit services like dial-a-cab in Tier-I Indian cities over the last decade motivates this research. We specifically focus on capturing different service delivery structures in our analysis by collecting data from Mumbai (zone-restricted) and Kolkata (route-restricted). A revealed preference survey was constructed with the aim of collecting information about socio-demographic characteristics, attitudinal parameters, individual preferences, service delivery characteristics, and trip characteristics. Latent variables were constructed and used to develop Structural Equation Models (SEMs), a separate one for each type of service (traditional and emerging). Results show that the segments of population that are catered to by each service are distinctly different. The inferences pave the way for urban transport system policies to encourage paratransit, especially with regard to service delivery structure and regulations on price and safety.
The existence of complex tours could be a major barrier to the shift from car/motorcycle to public transport. To properly reflect such a barrier in evaluating the introduction of new public transport, a tour-based approach rather than a trip-based approach is required. However, to the authors’ knowledge, there is no study exploring the impacts of tour patterns on commuting mode choice where a “currently unavailable” travel mode is included as an alternative. This study proposes a simple method to identify the impacts of tour patterns on such stated commuting mode choice, where tour patterns are defined by the combination of tour complexity (represented by the number of trips in the stated preference (SP) survey) and trip flexibility (obtained in the revealed preference (RP) survey). For empirical analysis, we collected SP and RP data in Ho Chi Minh City, Vietnam. The results confirm the significant impact of tour patterns on mode choice decisions.
Empirical approach is in use for the designing of granular or low volume pavements in many countries, including India. These types of pavements mainly comprise of unbound granular material layer over subgrade with thin asphalt surfacing. Accurate modeling of the granular material is essential for better correlation of the identified mechanistic responses with the performance of pavements. It is known that, unbound materials are nonlinear and have stress dependent resilient modulus. Hence, the stress dependency of unbound materials should be considered for an accurate estimation of true pavement responses. Writing suitable codes in Finite Element (FE) analysis software, model the nonlinearity of unbound granular layers. A 3-D FE was developed and analyzed. It was observed that the pavement responses obtained from the 3-D FE analysis carried out for typical low volume pavements taking into account the nonlinear characteristics of unbound pavement materials differ by 34% to 44% from those obtained using linear analysis.
In Asian and ASEAN countries, there are many urban development plans based on the concept of Transit Oriented Development (TOD). The Computable Urban Economic (CUE) model, which enables simultaneous evaluation of urban and transportation development, is one of the major approaches for estimating the effects of a development plan based on TOD. However, these effects have been difficult to evaluate, especially in Asian and ASEAN countries apart from Japan, owing to the lack of public data on geographic land use by small zone units. We have estimated a detailed spatial scale land use dataset by using satellite images. This enables land use classification on an appropriate scale for the evaluation of TOD. This paper describes the evaluation results of the development plan of Taoyuan City, Taiwan that was carried out by building a detailed spatial scale CUE model based on data and our estimation approach.
Although online purchases still make up only a small share of individuals’ purchases, they increasingly represent an alternative to in-store purchases. This alternative seems even more valuable in sparsely populated areas with poorer access to shops. Online purchases may smooth out spatial constraints on access to tangible goods. The efficiency hypothesis postulates that people with low accessibility tend to buy more online. This study examines this hypothesis. The aim is to check whether online purchasing is more developed in suburban areas and whether online purchasing practices for the inhabitants of such areas are a way of overcoming their poor access to shops. Our results show quite different patterns between suburban and urban households. The efficiency hypothesis is partially validated.
China has the world's most extensive high speed rail (HSR) network. The modernized railway network began commercial operations in April 2007. On the other side of the strait, Taiwan High Speed Rail was inaugurated in January 2007. The newly introduced travel mode has over time significantly changed the travel patterns in these areas. This study aims to understand the factors influencing how quickly travelers get used to taking high speed rail. A web-based questionnaire was conducted and carried out in Taiwan and Shanghai in 2014 using visualized usage patterns for respondents to choose the one that most fits to their actual HSR usage. Multinomial Logit model (MNL) is then employed to estimate parameters influencing HSR usage among different groups of travelers. The MNL results suggest that fast adopters and those who dropped usage at some point, share similar characteristics compared to slow adopters. From the attitudinal factors, one’s general "willingness to try" has a positive impact on a person's likelihood to start using HSR. As for socio demographics, higher education degree and personal income would encourage travelers adopting to HSR. A number of reasons to start using HSR are discussed and found to have different impacts on perceptions towards HSR among all travelers and regions.
The latest generation of bike-sharing, i.e. demand responsive multimodal systems are relatively new and highly innovative elements of urban mobility. Bike-sharing is also an emerging topic of urban transport and sustainable mobility related research. Due to its novelty, most scholars focus on the supply (repositioning problem, optimising the location of stations, pricing, etc.) and not the demand side problems (user behaviour and profiles, trip characteristics, etc.). The aim of this paper is (1) the analysis of the evolution of bike-sharing and the exploration of how innovative technologies have changed bike-sharing systems for users, (2) the review of cycling and bike-sharing related literature on user characteristics, and (3) the identification of user (and non-user) profiles of the latest generation of bike-sharing on the basis of an ex-ante case study on the BiciMAD system in Madrid, Spain.