Akimasa Fujiwara

Urbanization and subsurface environmental issues: An attempt at DPSIR model application in Asian cities

This paper synthesizes existing information and knowledge on subsurface environments to understand the major cause and effect relationships of subsurface environmental issues by using the DPSIR (Driving force-Pressure-Status-Impact-Response) approach as the framework of analysis. Description is given to the major subsurface environmental issues common among the selected Asian cities (Bangkok, Jakarta, Manila, Osaka, Seoul, Taipei and Tokyo), such as excessive groundwater abstraction, land subsidence and groundwater contamination. The DPSIR framework is used to analyze the issues and problems of subsurface in key stages and suggestions are made for additional indicators to improve our description of the stages of urban development for the future.

Exploring Variation Properties of Time Use Behavior on the Basis of a Multilevel Multiple Discrete-Continuous Extreme Value Model

This study attempts to examine the variation properties of time use behavior on the basis of a multilevel multiple discrete–continuous extreme value model, which describes both activity participation and time allocation behavior by incorporating various variance components. Five major variation components are dealt with, including interindividual, interhousehold, temporal, spatial, and intraindividual variations. The MobiDrive data, continuous 6-week daily travel data, allow identification of these variations simultaneously. Two types of models are empirically examined: the model without consideration of the influence of explanatory variables (null model) and the model that introduces explanatory variables (full model). Estimation results of the null model confirm that intraindividual variation still accounts for more than 50% of the total variation (except for mandatory activities) even after incorporation of the aforementioned four other types of variations jointly. In contrast, the results from the full model reveal that most types of unobserved variations (especially the intraindividual variation) still dominate in the total variation even after the relevant observed information is introduced. These findings provide useful insights into both model development and data collection methods as well as to the understanding of the mechanisms of time use decisions.

Motorization in Asia: 14 Countries and Three Metropolitan Areas

Motorization in terms of passenger cars in 14 Asian countries and passenger cars and motorcycles in three metropolitan areas are analyzed in this study. Using country-based data which cover 20 years (1980–2000), a linear regression is conducted by panel estimation with random and fixed effects. As a result from the model, fixed income elasticity for the region was found to be 1.75. Fixed effect estimated separately for each country characterizes the motorization pace in the countries. Two groups of countries were detected with a significant difference in motorization paces—Sri Lanka, India, Nepal, Philippines, Pakistan, Indonesia and Thailand have motorization paces higher than the rest of the countries. Additionally, using a cross-sectional data household car and motorcycle ownerships were analyzed for three metropolitan areas characterizing South-East Asia that are Jabotabek (Indonesia), Kuala Lumpur (Malaysia) and Manila (Philippines) metropolitan areas. Results indicate that ownership of cars and motorcycles are independent of each other in Jabotabek and Manila, but negatively correlated in Kuala Lumpur; and generally, income is more influential on car ownership than motorcycle ownership.

Capturing Travelers' Stated Mode Choice Preferences Under Influence of Income in Yangon City, Myanmar

Abstract Focusing on the role of a new transit system (NTS) in mitigating current and future potential traffic issues in Yangon City of Myanmar, this paper attempts to analyze the mode choice behavior based on a stated preference (SP) survey. In comparison with developed countries, developing countries are characterized by rapidly changing socio-economic environments (especially, income). It is required to reflect the influence of such decision context in both survey method and modeling framework. Therefore, SP survey is first designed to incorporate the influence of future income, as well as other level-of-service attributes, whereas a revealed preference (RP) survey is also prepared. Second, a RP/SP combined mode choice model is estimated in which the parameters of travel time and cost are defined as a function of future income, respectively. A SP survey was conducted at a residential area of Yangon City in March 2003. This is the first SP survey done in Myanmar. Respondents show the highest preference of NTS among travel modes. The effectiveness of the proposed model structure was empirically confirmed. Furthermore, simulation analysis suggests that future income will bring about a potentially large increase in car usage and consequently reduction in transit systems.

Changes in Variations of Travel Time Expenditure

To improve methods of evaluating the benefits from investments in the transport infrastructure, this paper attempts to develop a method for capturing changes in variations in travel time expenditure and shows empirical results from data from the German Mobility Panel, a multiday and multiperiod panel survey. The proposed methodology can simultaneously and explicitly deal with changes and variations. The empirical analysis indicates that over time, travel time expenditures become more dependent on situational attributes than on individual or household attributes; such dependence implies that travel time expenditures change toward diversification and that longer periods of behavioral observation to describe peoples travel time expenditures become more important. The results also imply that understanding of the dynamic aspects of behavior is still important and remains a challenging issue to be revisited, not only for improving forecasting models but also for reconsidering the benefits from investment in transportation infrastructure.

A Tourist's Multi-Destination Choice Model with Future Dependency

This study is concerned with the interrelated choices underlying a tourists multi-destination behavior. A new destination choice model is developed based on the concept of future dependence, which argues that choice of a destination during a tour is influenced by choices of other destinations that will be visited later. The model is built within the universal (or mother) logit model framework and it is especially suitable to represent the choice behavior with many destinations, which are difficult to represent using a traditional nested logit model. The results of analysis empirically confirmed the effectiveness of the proposed modeling approach, using questionnaire survey data collected in Tottori Prefecture, Japan in 2007. It was also revealed that travel time, diversity of destination, and variety-seeking remarkably affect the multi-destination choice behavior.

Intrahousehold Interaction in Transit-Oriented Residential Choice Behavior Represented in Stated Preference Approach

A study applied a web-based stated preference (SP) survey to investigate household preferences for transit-oriented residential choices, incorporating intrahousehold interaction. The SP survey included five alternatives: one current residential location and four combinations of two residential areas and two commuting modes (a car and a transit system). The assumed residential areas were all located near stations of a transit system: one was close to and another was far from the city center. Commuting modes were only for household heads. Households with only couples were recruited, and the survey was conducted with the help of an Internet survey company. In the SP survey, the couple was first asked to answer the SP questions separately, and then the two members jointly answered the questions. It was found that members in 40% of the households changed their stated choices after joint decisions. This switch suggests the necessity to incorporate intrahousehold interaction into any household residential choice model. To this end, a group discrete choice model with multilinear utility was established; members’ relative influences and intrahousehold interaction were simultaneously represented in the model. Model estimation results first confirmed the effectiveness of the established model. It was then revealed that the existence of intra-household interaction reduced total household utility and that husbands wielded relatively greater influence than wives. It was also shown that with increases in age, members’ relative influence grew, and that dominant decision makers concerning household asset management had greater influence power on household residential choice behavior.

Dynamic Discrete Choice Model for Multiple Social Interactions

A dynamic discrete choice model for multiple social interactions was developed on the basis of retrospective panel data in the context of household vehicle-type choice. “Social interactions” refer to the influence of reference groups on household choice behavior. However, most studies in transportation have considered a household as a decision maker independent from the society to which it belongs. Social interactions have therefore not been well represented, especially if there were two or more types of reference groups, which may further vary over time. The model was built within the dynamic generalized extreme value framework, which included a set of dynamic elements, such as initial conditions, state dependence, and future expectation. This study defined three types of social interactions: diffusion rates of a vehicle type at the national level and at the neighborhood level and diffusion rate of households with the same income level. A survey was conducted in local Japanese cities in 2006. The survey focused on household vehicle ownership behavior over the 10 years from 1997 to 2006. Model estimation results confirmed that social interactions from reference groups of neighborhoods and households with the same income level were especially influential in decisions about household vehicle-type choice. On the contrary, social interaction from the whole society did not significantly influence the household choice. It was further found that effects of dynamic elements on the household choice were statistically significant.

A Household Time-Use and Energy-Consumption Model with Multiple Behavioral Interactions and Zero Consumption

This study develops a new household resource allocation model, which incorporates multiple interactions (including the interaction between time use and energy consumption, the interactivity interaction, the inter-end-use interaction, and the intrahousehold interaction) based on multilinear utility functions and endogenously represents zero consumption for both time and energy within the group decision-making modeling framework. This may be the first model in literature to jointly accommodate all these behavioral mechanisms in a unified and consistent modeling framework, especially in the context of time use and energy consumption. The model is estimated using data collected in a household survey in Beijing in 2010. Estimation results reveal that: (1) synergic effects are observed with respect to in-home time use and energy consumption, out-of-home time use across varied activities, and in-home energy consumption from different end uses; (2) competitive relationships are detected between in-home time use and out-of-home energy consumption, out-of-home time use and in-home energy consumption, in-home and out-of-home energy consumption, and time use. These not only support the joint representation for time use and energy consumption behavior but also for the energy consumption behavior of in-home end uses and out-of-home vehicles. Additionally, it is found that the intrahousehold interaction does exist.

Improved feedback modeling of transport in enlarging urban areas of developing countries

Toward the common issue of quick urban sprawls of many cities in developing countries today, this research incorporates the expectation-maximization (EM) algorithm into the feedback application process of a newly developed feedback model to improve the modeling studies of the urban transport prediction and planning for the developments of the cities with their urban areas enlarged in the future. By utilizing the survey data obtained in Jabodetabek metropolitan region of Indonesia in 2002, the study results numerically confirm that the iteratively computational calibrations to the K-factors for the newly urbanized areas of a developing city by employing the EM algorithm in the feedback process can truly improve the validity of the proposed feedback model’s application to effectively predict the urban transport developments of developing cities in the future.