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Tudor D. Bodea Laurie A. Garrow Michael D. Meyer Catherine L. Ross 《Transportation Research Part A: Policy and Practice》2009,43(4):430-444
This paper explores the association of socio-demographic and built environment characteristics on the odds of being overweight and obese using data from the Atlanta SMARTRAQ travel survey. A new methodological framework based on a multinomial logit (MNL) model and an enhanced odds ratio plot is presented. The use of an MNL model overcomes limitations of many prior studies that employ a sequence of binary logit models to examine multiple weight categories. The use of an enhanced odds ratio plot provides important information into the relative importance of socio-demographic and built environment characteristics. Several new findings for the Atlanta area result from this study. Socio-demographic variables, including age and educational attainment, exhibit a non-linear relationship with the odds of being overweight or obese. Gender, age, ethnicity, and educational attainment are strongly associated with the odds of being overweight or obese, while income and number of students between 5 and 16 years old in the household have smaller effects. Built environment characteristics such as increased net residential densities and enhanced street connectivity are associated with reductions in the odds of being overweight and/or obese. Relative to socio-demographic variables, however, such built environment characteristics have a much smaller impact on describing the odds of being overweight or obese. 相似文献
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Misuk Lee Alexandre Khelifa Laurie A. Garrow Michel Bierlaire David Post 《Transportation Research Part A: Policy and Practice》2012,46(10):1641-1653
We investigate how customers respond to an opaque airline product offered by a European carrier. In this opaque product design, customers are randomly assigned to travel to one of approximately ten destinations; however, for a fee they may exclude one or more destinations from the choice set (or a particular package design) prior to learning which destination they will travel to. We use a multidimensional binary logit model to predict the probability that one or more alternatives will be chosen by a customer. Results show that customers are more likely to pay to exclude destinations located close to the origin airport and destinations that speak the same language as the origin airport. Length of stay, cost of living at the destination, and measures of destination attractiveness are also found to be significant predictors for some package designs. Based on these findings, we offer general recommendations for how to design opaque packages for airline customers. 相似文献
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Despite the widespread use of synthetic data in discrete choice analysis, little is known about how the methodology used to
generate synthetic datasets influences the properties of parameter estimates and the validity of results based on these estimates.
That is, there are two potential sources of biases when using synthetic discrete choice data: (1) bias due to the method used
to generate the dataset; and, (2) bias due to parameter estimation. The primary objective of this study is to examine bias
due to the underlying data generation method. This study compares three methods for generating synthetic datasets and uses
design of experiments and analysis of variance methods to investigate the ability to recover estimates for “true” logsum parameters
for nested logit models. The method that uses nested logit probabilities to generate the chosen alternative results in unbiased
parameter estimates. The method that is based on Gumbel error component approximations reveals that while the error components
themselves are unbiased, subtle empirical identification problems can arise when these error components are combined with
synthetically generated utility functions. The method that is based on normal error component approximations reveals that
all logsum coefficients are biased upwards; the bias dramatically increases for those nests that have a low choice frequency
and is most pronounced for those nests with high correlations among alternatives. Based on the results of the analysis, several
recommendations for the generation of synthetic datasets for discrete choice analyses are provided. 相似文献
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Explaining obesity with urban form: a cautionary tale 总被引:1,自引:0,他引:1
Tudor D. Bodea Laurie A. Garrow Michael D. Meyer Catherine L. Ross 《Transportation》2008,35(2):179-199
In recent years, there has been a dramatic increase in studies exploring associations between the built environment and obesity.
Many studies have found that built environment characteristics, such as high-density land developments, mixed-land uses, and
connected street networks, are associated with lower rates of obesity. However, depending on the research field and the researcher,
how one specifies the experimental model and how sociodemographic characteristics of the population are defined and included
in the model has led to different policy conclusions and implications. This is not a surprising observation; however, it is
one that does seem to have been lost in current discussions. This article highlights several data-processing, model-specification,
and model-estimation factors that should be comprehensively considered in studies of the built environment and obesity. Empirical
results based on data from Atlanta, GA, USA, illustrate that the association between the built environment and obesity is
sensitive to how age, income, and educational attainment are included in the model. Also, a detailed examination of land-use-mix
measures shows that it is difficult to create this measure and that results are sensitive to the treatment of missing values.
Models that distinguish between overweight and obese individuals are shown to provide richer insights into the associations
among obesity, built environment, and sociodemographic characteristics for the Atlanta area. The article concludes by offering
modeling recommendations for future studies.
Tudor D. Bodea is a doctoral student in the School of Civil and Environmental Engineering at the Georgia Institute of Technology. His doctoral work examines the integration of customer-choice models into optimization algorithms for travel-industry applications. Laurie A. Garrow is an assistant professor in the School and Civil and Environmental Engineering at the Georgia Institute of Technology. Her research addresses the development and application of advanced models of travel demand that integrate discrete choice, econometric, and market research methods to enhance understanding of travel behavior. Michael D. Meyer is professor in the School of Civil and Environmental Engineering and Director of the Georgia Transportation Institute at the Georgia Institute of Technology. He has written over 160 technical articles and has authored or coauthored numerous texts on transportation systems, planning, and policy, including a college textbook. In 2006, he was the chairman of the Transportation Research Board Executive Committee. Catherine L. Ross is Harry West professor in the City and Regional Planning Program and Director of the Center for Quality Growth and Regional Development at the Georgia Institute of Technology. She has published extensively in the fields of urban planning, transportation planning, and public participation. She is the coauthor of The Inner City: Urban Poverty and Economic Development in the next Century. 相似文献
Laurie A. GarrowEmail: |
Tudor D. Bodea is a doctoral student in the School of Civil and Environmental Engineering at the Georgia Institute of Technology. His doctoral work examines the integration of customer-choice models into optimization algorithms for travel-industry applications. Laurie A. Garrow is an assistant professor in the School and Civil and Environmental Engineering at the Georgia Institute of Technology. Her research addresses the development and application of advanced models of travel demand that integrate discrete choice, econometric, and market research methods to enhance understanding of travel behavior. Michael D. Meyer is professor in the School of Civil and Environmental Engineering and Director of the Georgia Transportation Institute at the Georgia Institute of Technology. He has written over 160 technical articles and has authored or coauthored numerous texts on transportation systems, planning, and policy, including a college textbook. In 2006, he was the chairman of the Transportation Research Board Executive Committee. Catherine L. Ross is Harry West professor in the City and Regional Planning Program and Director of the Center for Quality Growth and Regional Development at the Georgia Institute of Technology. She has published extensively in the fields of urban planning, transportation planning, and public participation. She is the coauthor of The Inner City: Urban Poverty and Economic Development in the next Century. 相似文献
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Transportation - There is growing interest in using online outsourcing platforms that are part of the “gig economy” to conduct surveys for academic research. This interest has been... 相似文献
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