Jessica Y Guo

A mixed spatially correlated logit model: formulation and application to residential choice modeling

In recent years, there have been important developments in the simulation analysis of the mixed multinomial logit model as well as in the formulation of increasingly flexible closed-form models belonging to the generalized extreme value class. In this paper, we bring these developments together to propose a mixed spatially correlated logit (MSCL) model for location-related choices. The MSCL model represents a powerful approach to capture both random taste variations as well as spatial correlation in location choice analysis. The MSCL model is applied to an analysis of residential location choice using data drawn from the 1996 Dallas-Fort Worth household survey. The empirical results underscore the need to capture unobserved taste variations and spatial correlation, both for improved data fit and the realistic assessment of the effect of sociodemographic, transportation system, and land-use changes on residential location choice.

Comprehensive Econometric Microsimulator for Daily Activity-Travel Patterns

The Comprehensive Econometric Microsimulator for Daily Activity-Travel Patterns (CEMDAP) is a microsimulation implementation of an activity-travel modeling system. Given as input various land use, sociodemographic, activity system, and transportation level-of-service attributes, the system provides as output the complete daily activity-travel patterns for each individual in each household of a population. The underlying econometric modeling framework and the software development experience associated with CEMDAP are described. The steps involved in applying CEMDAP to predict activity-travel patterns and to perform policy analysis are also presented. Empirical results obtained from applying the software to the Dallas-Fort Worth area demonstrate that CEMDAP provides a means of analyzing policy impacts in ways that are generally infeasible with the conventional four-stage approach.

Effect of the Built Environment on Motorized and Nonmotorized Trip Making: Substitutive, Complementary, or Synergistic?

This paper describes how it has become well recognized that non-motorized transportation is beneficial to a community’s health as well as its transportation system performance. In view of the limited public resources available for improving public health and/or transportation, the present study aims to (a) assess the expected impact of built environment improvements on the substitutive, complementary, or synergistic use of motorized and non-motorized modes; and (b) examine how the effects of built environment improvements differ for different population groups and for different travel purposes. The bivariate ordered probit models estimated in this study suggest that few built environment factors lead to the substitution of motorized mode use by non-motorized mode use. Rather, factors such as increased bikeway density and street network connectivity have the potential of promoting more non-motorized travel to supplement individuals’ existing motorized trips. Meanwhile, the heterogeneity found in individuals’ responsiveness to built environment factors indicates that built environment improvements need to be sensitive to the local residents’ characteristics.It has become well recognized that nonmotorized transportation is beneficial to a communitys health as well as its transportation system performance. In view of the limited public resources available for improving public health and transportation, the present study aims to (a) assess the expected impact of built environment improvements on the substitutive, complementary, or synergistic use of motorized and nonmotorized modes and (b) examine how the effects of built environment improvements differ for different population groups and for different travel purposes. The bivariate ordered probit models estimated in this study suggest that few built environment factors lead to the substitution of motorized mode use by nonmotorized mode use. Instead, factors such as increased bikeway density and street network connectivity have the potential to promote more nonmotorized travel to supplement individuals’ existing motorized trips. Meanwhile, the heterogeneity found in individuals’ responsiveness to built environment factors indicates that built environment improvements need to be sensitive to local residents’ characteristics.

Modifiable Areal Units: Problem or Perception in Modeling of Residential Location Choice?

The sensitivity of spatial analytic results to the way in which the areal units are defined is known as the modifiable areal unit problem (MAUP). Although a general solution to the problem does not yet exist, it has been suggested in the literature that the effects of the problem may be controllable within specific application contexts. This line of inquiry is pursued, and MAUP is addressed in the context of residential location choice modeling. Previous residential location choice analysis typically involved the representation of alternative locations by areal units and the measurement of residential neighborhood characteristics based on these areal units. The vulnerability of such an approach to effects of the MAUP is demonstrated. It is contended that the fundamental issue is the inconsistency between the analysts definition of areal units and the decision makers perception of residential neighborhoods. An alternative approach of using a multiscale modeling structure is proposed to mimic the notion of a neighborhood being a hierarchy of residential groupings. The proposed approach allows the spatial extent of choice factors to be determined endogenously. The authors show that the multiscale approach produces richer and more interpretable results than its single scale counterpart.

An economic evaluation of health-promotive built environment changes.

OBJECTIVES This study aimed to help public investment decision makers see the greatest return on their built environment investments by developing an analysis framework for identifying the most promising improvement strategies and assessing the attainable return on investment. METHODS The 2001 National Household Travel Survey sample (N=4974) from Dane County, Wisconsin, was used to develop a Spatial Seemingly Unrelated Regression model of daily vehicle miles traveled and miles walked or biked. The empirical model was used to analyze the travel impacts of hypothetical built environment changes. These travel impacts were translated into health impacts and monetary values using cost-benefit analysis. RESULTS Two win-win built environment strategies were found: increased regional retail accessibility and increased prevalence of sidewalks. Based on the present analyses, an investment of

Population Updating System Structures and Models Embedded in the Comprehensive Econometric Microsimulator for Urban Systems

450 million to make sidewalks available to all Dane County residents was estimated to yield a cost-benefit ratio of 1.87 over a 10-year life cycle. CONCLUSION Certain built environment measures could be predicted to be effective strategies for exerting a positive influence on peoples travel behavior and the health of the community. Quantifiable public health benefits gained by better air quality and increased physical activity were shown to outweigh the cost of implementing the built environment measure of adding sidewalks to all roads.

Carsharing in a University Community: Assessing Potential Demand and Distinct Market Characteristics

This paper describes the development of a population update modeling system as part of the development of the comprehensive econometric microsimulator for socioeconomics, land use, and transportation systems (CEMSELTS), which is part of the comprehensive econometric micro-simulator for urban systems (CEMUS) under development at the University of Texas at Austin. The research in this paper recognizes that modeling the linkages among demographics, land use, and transportation is important for realistic travel demand forecasting. The population update modeling system focuses on modeling events and actions of individuals and households in the urban region. An analysis framework is proposed to predict future population characteristics by modeling the changes to all relevant attributes of the households and individuals. The models identified in the analysis framework are estimated for the Dallas–Fort Worth, Texas, region. The econometric structures used include deterministic models, rate-based probability models, binary logit models, multinomial logit models, and ordered-response probit models. To verify the outputs from these models, the predicted results for the year 2000 are compared with observed 2000 census data.

Identifying and Characterizing Truck Bottlenecks in the U.S. Mississippi Valley Region

As of September 2007, more than 70 colleges and universities in the United States have partnered with carsharing organizations, and this market segment is expected to continue growing. To maximize the benefits of these partnerships, it is important to understand both the unique features of academic institutions as markets for carsharing and ways to predict university-based demand for carsharing services. A study was done to estimate the potential carsharing market at the University of Wisconsin–Madison by (a) using a stated preference survey to collect information on university affiliates’ transportation habits and carsharing preferences, (b) developing a set of probabilistic models of willingness to join a carsharing program based on the stated preference survey data, and (c) applying these models to predict the potential market share under different conditions. Through this process, the relative impact of respondents’ socioeconomic characteristics, current travel habits, attitudes on transportation and the environment, and familiarity with carsharing on their decisions to use carsharing were examined. The results show that a respondents status at the university (e.g., faculty, student, or staff) had a strong influence over her individual acceptance of car-sharing, even more so than socioeconomic variables such as income or vehicle ownership, and that peoples attitudes play an important role in their decision making. Furthermore, the ease of accessing a car is also a critical factor. Although the University of Wisconsin–Madison population was the focus of the analysis, the findings provide useful insights for targeting carsharing programs in other university communities.

A comprehensive analysis of built environment characteristics on household residential choice and auto ownership levels

Freight movements throughout the Mississippi Valley region of the United States are complicated by the presence of recurring bottlenecks along the highway network. To help the states in the region take appropriate action to address freight bottlenecks, a methodology was developed to identify, characterize, and prioritize the regional freight bottlenecks characterized by significant delays for trucks on a per mile basis. The proposed methodology uses data from the Highway Performance Monitoring System. A prioritized list of regional freight bottlenecks is generated for the Mississippi Valley region to stimulate dialogue among freight planners and operators and to provide a basis to devise optimal alleviation plans for the greatest benefits for the region. The analysis results are verified through a series of qualitative comparisons against bottlenecks identified by state transportation engineers and planners, freight carriers, and previous studies. The general agreement between the findings and these other sources of bottleneck information suggests that the proposed methodology can identify the most prevalent truck bottlenecks while revealing additional locations that warrant further investigation.