This paper discusses examples of studies that reflect the recent shift in interest to study dynamics in activity-travel behavior. Studies are classified according the time window of impact (long term life cycle related change vs. short term travel information induced change), and exogenous versus endogenous change. As examples of exogenous change, road pricing, increase in energy costs and new technology (electric cars) are selected. Implications of these research findings for Asian countries are discussed.
Individual action space is an important indicator of an individual's ability and flexibility in pursuing daily activities under various constraints. Although a number of studies have explored the size and variability of individual action space, there is a lack of knowledge about how this individual activity space evolves over a long time-span. Using the results of household travel surveys conducted in 1980, 1990, and 2000 in the Osaka metropolitan area of Japan, this paper examines the temporal changes in individuals' action spaces. By composing a system of Tobit models, the stability over time of indices that characterize individuals' action spaces is examined. The results show that the commute distance of workers negatively influences the spread of activity locations, while in the case of nonworkers, activity locations tend to be more dispersed when activities are pursued away from home.
This paper presents the results of household auto/motorcycle ownership and joint mode and destination choice models that were developed based on two large-scale travel surveys conducted eight years apart. It compares the models and discusses implications of the changes that have occurred in the Jakarta Metropolitan Area in the last decade. Given that the context of the society does not change, both models should remain unchanged with fixed parameters over a period of time. However, the models that were estimated based on the surveys conducted in 2002 and 2010 indicated quite different parameters with different degrees of significance. Such implications may also be important and hence worth studying for other urban areas of the developing world, although similarities of the implications may be restricted to regions that have modal and cultural norms in common.
Conventional logit-based models with cross-sectional data are not capable of capturing the individual's behavior that is correlated over time. Although panel data provide the source of information to overcome this issue, collecting panel data, especially from revealed preference data, is generally expensive and difficult in practice. The present paper shows the use of repeated observations from Electronic Toll Collection (STC) data with information about attributes derived from detectoe data to analyze and model route choice and route switching behavior on a selected study area of the Tokyo Metropolitan Expresswey. In general, the estimated results show that drivers respond differently to different levels of congestion information. Moreover, when accounting for the panel data, the factors that capture panel effect are highly significant stasistically and improvement of the models' goodness of fit can be observed for both behavioral models.
In recent years, efforts have been made to develop bicycle-friendly environments across Japan. However, such development is conducted only where roads are sufficiently wide, and thus efficient networks are not easily developed. In this situation, it is essential to accurately evaluate demand change following development and to examine how to meet network needs, while developing the areas that are easier to proceed with. Therefore, to organize the information required to evaluate demand change, we build a route choice model using data from Takamatsu city and conduct verification using data from the actual implementation of measures. The study shows that bicycle route choice is mainly affected by discontinuity and presence of turns. Furthermore, we specify the need to note partial bottlenecks and consider measures under the assumption that route choice is impromptu when we evaluate demand change.
Transport mobility appears to be closely linked to a person's well-being, especially for elderly people. The development of specialized transport devices to compensate for the decline in mobility of the elderly is important so that they may move around and lead an independent life as they wish. Mobility devices such as electric carts offer great utility for transport; however, the electric cart has yet to gain popularity in the open market. Thus, it is necessary to examine ways of expanding the usage of such devices and to clarify their effects on improving the quality of life of the elderly. Here, we investigate the change in the quality of life from the viewpoint of health and welfare with the use of personal mobility mode, in the daily life of the elderly using various types of evaluation measurements.
This study focuses on identifying factors that promote personal mobility (PM) technologies as an immediate means of responding to the mobility needs of elderly populations. It is known that in the case of new products that are largely unfamiliar to customers, the behavior and judgments of friends and acquaintances have a powerful effect on people's desire to gather information and, ultimately, to purchase. To analyze quantitatively the effect of friends and acquaintances on individuals’ decision-making behavior, we developed a discrete choice model considering the impact of PM product penetration. We likewise modeled friend and acquaintance relationships by applying the complex network analysis method. The empirical analysis of questionnaires collected in Koyo Newtown in Hiroshima city reveals the existence of a social conformity effect with respect to PM use preferences. The influence of friends and acquaintances in that setting has an impact equivalent to a net 5% decrease in PM rental prices.
When proposing policies that aim to promote inbound and outbound tourism markets, there should be a focus not only on the tourism demand in a certain region but also on interregional relationships. To address this issue, we have developed the methodology for the quantitative analysis of tourism demand structure by focusing on the elasticity of destination choice activities. The demand function of destination choice activities is defined as a Dynamic AIDS (Almost Ideal Demand System) model. The main goal of this research is to examine the applicability of the AIDS models to the estimation of Japanese international tourism demand.
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