Sumeeta Srinivasan

TRAVEL BEHAVIOR AT THE HOUSEHOLD LEVEL: UNDERSTANDING LINKAGES WITH RESIDENTIAL CHOICE

Abstract Previous work with data from the Boston Metropolitan Area has suggested that land use characteristics can have measurable impacts on travel behavior such as trip linking and mode choice at the individual level. However, trip planning, especially in households with children or more than one worker, is quite possibly done at the household level. In this paper, we begin to understand the travel behavior choices of households and understand the relationship of these choices with socio-economic characteristics as well as spatial characteristics of the places where the household resides, works and travels through. The results of preliminary models estimated indicate that the travel behavior of a household is indeed related to the households residential location. The models estimated are not for the purposes of travel demand forecasting as in the case of the household based Stockholm models. The results do indicate if land use, network and accessibility characteristics also affect household trip linking and mode choice and their relationship to residential choice. Thus, one can begin to determine whether planners can make a difference through the implementation of the ideas of neo-traditional theories in local level planning. These models should provide a starting point for further exploration of the land use and transportation linkages explored from the point of view of the more realistic unit of the household.

Modeling Private Car Ownership in China: Investigation of Urban Form Impact Across Megacities

The rising prevalence of private cars in the developing world is causing serious congestion and pollution. In China, private cars started to emerge as an important travel mode in the past decade. Prospective research on the relationship between urban form and car ownership is relatively uncommon in the developing world, and China offers a unique study opportunity, given the tremendous increases in private cars and fast-paced urbanization over the past decade. This study investigates the influence of urban form on car ownership as well as the impact of other socioeconomic and demographic factors on private car ownership across megacities in China. Analysis was conducted through the use of data from 36 megacities and two household survey data sets collected in Beijing and the city of Chengdu, China. Ordinary least squares regression and discrete choice models were employed to execute the aggregate and disaggregate analysis of the urban form impact on private car ownership across cities. The statistical model results demonstrate that urban affluence, urban scale, and road infrastructure supply factors have significant positive effects on the city level of private car ownership across cities. Population density calculated at the subdistrict level, however, had a significant negative effect on private car ownership across cities. Households with private cars were found to prefer to live close to urban centers where amenities were readily available. The results provide evidence for urban planners and policy makers.

Determinants of Changes in Mobility and Travel Patterns in Developing Countries: Case Study of Chennai, India

This study analyzes changes in sociodemographic, activity, land use, and mobility patterns and their effects on travel dimensions in the context of a developing country. More specifically, increase in vehicle ownership (both two-wheelers and cars) and changes in mode choice over time are observed and analyzed with the use of household data from Chennai, India. Three sources of dynamics are analyzed: exogenous variable dynamics, sensitivity changes over time, and the influence of lagged and persistent effects. The key drivers of growth in travel demand include the increase in vehicle ownership, the number of workers, and the increase in female drivers. The influence of social and technological factors on vehicle ownership and mode choice such as peer pressure and mobile phone ownership are also significant. In addition, the effect of land use, accessibility, and activity has been investigated. Results show significant evidence of differences in travel decisions across different user segments (on the basis of driving knowledge and vehicle–worker ratio) and over time. The proposed disaggregate models provide a reasonably good description (goodness of fit is 47% to 64%) of the observed changes in travel patterns. The findings and results assume importance in the context of increasing congestion, declining public transportation share, and the imminent need for enhancing urban transportation system capacity in cities of developing countries.

Household Income, Travel Behavior, Location, and Accessibility: Sketches from Two Different Developing Contexts

This paper analyzes the differences in travel behavior and location characteristics across different income groups in two cities in different parts of the world: Chile and China. Vehicle ownership rates, mode choices, trip rates and purposes, and travel times and distances are compared according to high-, middle-, and low-income terciles in Chengdu, China, and Santiago, Chile, with the use of recent household travel surveys. Household location characteristics are also compared, and different measures of accessibility are presented. Results suggest commonalities and differences and build a foundation on which future analytical models can be developed and more rigorous and comparable accessibility measures might be derived.

QUANTIFYING SPATIAL CHARACTERISTICS FOR TRAVEL BEHAVIOR MODELS

Land use initiatives represent a potentially effective tool for coping with the kinds of mobility patterns that North American cities face in the 1990s and in the coming century. As fine-grained data about land use and travel activity become available, they provide the opportunity to improve the understanding of the linkage between land use and transportation. The neighborhood characteristics that could affect travel behavior on the non-work tour are examined in detail. Neighborhood characteristics include land use, network, and accessibility-related characteristics quantified through the use of a geographic information system. Ultimately, such measures could be used in conjunction with detailed surveys of travel behavior to specify, calibrate, and use models of modal choice and trip type that are more sensitive to the fine-grained spatial structure of neighborhoods and transportation corridors in metropolitan areas. Microlevel data for the Boston metropolitan area, together with a 1991 activity survey of approximately 10,000 residents, provide a rich empirical basis for experimenting with relevant neighborhood measures and for simulating their effects on travel behavior. Spatial characteristics affect travel behavior even on the relatively (spatially) restricted nonwork tour and could be potentially useful for transportation planning.

Are They Well Situated? Spatial Analysis of Privately Owned Public Space, Manhattan, New York City

In this article, we attempt to examine how privately owned public spaces through incentive zoning have played out as a means to generate public spaces, as part of improving spatial equity in Manhattan, New York City. Using spatial statistical analyses, we find that the inclusion of privately owned public spaces reduces overall average distance to the nearest public space from both working and living population, and helps to balance the distribution of the public spaces throughout the city, by covering the locations where publicly owned public spaces are sparse. More importantly, the location of privately owned public spaces closely aligns with potential demand from the working and tourist population, though not from the resident population. We extend the findings to policy, suggesting that allocation of privately owned public space should be implemented comprehensively rather than discretely, as well as in relationship to publicly owned public spaces, to sharpen their role in achieving fair distribution of public spaces throughout the city.

Linking Travel Behavior and Location in Chengdu, China: Geographically Weighted Approach

This study uses geographically weighted regressions and multilevel models to understand the implications of location and attitudinal characteristics for travel behavior in Chengdu, China. In particular, the estimated distance traveled and the mode choice of nonmotorized versus motorized vehicles for work- and school-related trips were examined by using a recent household trip diary data set. The results suggest that location characteristics may be influential in the prediction of travel behavior but cannot be fully captured by simple categorization such as inner ring location versus peripheral location. Variations in travel behavior can be related to socioeconomic and location variables in ways that vary by location in a complex manner. Policy makers should therefore reconsider the role that location and attitudinal implications may play in meeting travel demand in rapidly developing cities like Chengdu.

Is open space a magnet for business? A spatial analysis of New York

In this paper, we investigate the spatial patterns of 22 types of industries in New York with respect to open space of four types – Central Park, waterfront, and passive and active inland open spaces – to compare industries’ preferences to, and their actual accessibility to, open space. As a preference indicator, we use logit regression to estimate the degree to which the occurrence of the business cluster may be attributed to open space. Also as an accessibility indicator, we use descriptive statistics to assess average distance to the nearest open space for each type of industry. We find that for businesses in the hospitality and creative industries, the probability of being part of a cluster is higher with better accessibility to open spaces. We also find that, on average, managerial service and public administration-related industries have the closest proximity to open spaces. Some of the industries that exhibited preference to open spaces indeed locate themselves in its vicinity, however spatial mismatch is also observed. We extend the finding to policy implications, suggesting cautious use of open space for the purpose of industrial recruitment within cities.