An analysis of destination choice for opaque airline products using multidimensional binary logit models

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.     

Socio-demographic and built environment influences on the odds of being overweight or obese: The Atlanta experience

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.     

Generation of synthetic datasets for discrete choice analysis

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.     

Explaining obesity with urban form: a cautionary tale

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.

A new twist on the gig economy: conducting surveys on Amazon Mechanical Turk

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...