In this paper, we formulate and estimate a nested model structure that includes a multiple discrete-continuous extreme value (MDCEV) The model developed in the paper is applied to predict the impact of land use and fuel cost changes on vehicle holdings and usage of the households. Such predictions can inform the design of proactive land-use, economic, and transportation policies to influence household vehicle holdings and usage in a way that reduces the negative impacts of automobile dependency such as traffic congestion, fuel consumption and air pollution.

The increasing diversity of vehicle type holdings and the growing usage of vehicles by households have serious policy implications for traffic congestion and air pollution.

Recent advances in global positioning systems (GPS) technology have resulted in a transition in household travel survey methods to test the use of GPS units to record travel details, followed by the application of an algorithm to both identify trips and impute trip purpose, typically supplemented with some level of respondent confirmation via prompted-recall surveys. As the research community evaluates this new approach to potentially replace the traditional surveyreported collection method, it is important to consider how well the GPS-recorded and algorithm-imputed details capture trip details and whether the traditional survey-reported collection method may be preferred with regards to some types of travel.This paper considers two measures of travel intensity (survey-reported and GPSrecorded) for two trip purposes (work and non-work) as dependent variables in a joint ordered response model. The empirical analysis uses a sample from the full-study of the 2009 Indianapolis regional household travel survey. Individuals in this sample provided diary details about their travel survey day as well as carried wearable GPS units for the same 24-hour period.The empirical results provide important insights regarding differences in measures of travel intensities related to the two different data collection modes (diary and GPS). The results suggest that more research is needed in the development of workplace identification algorithms, that GPS should continue to be used alongside rather than in lieu of the traditional diary approach, and that assignment of individuals to the GPS or diary survey approach should consider demographics and other characteristics.

This paper formulates a model for the joint analysis of the imperfect and perfect substitute goods case. That is, it enables the modeling of choice situations where consumers choose multiple alternatives at the same time from a certain set of alternatives, but also choose only one alternative from among a subset of alternatives. For example, in the context of time-use in leisure activity, individuals may participate in combinations of social, out-of-home recreation, and out-of-home non-maintenance shopping pursuits. These three activity types are imperfect substitutes in that they serve different functional needs of individuals and households. However, if an individual participates in out-of-home recreation, s/he may participate in only one of physically passive activities (for example, going to the movies), partially physically active activities (going to the beach or participating in spectator sports), or physically active activities (for example, working out at a gym) during a given time period (such as a weekday or a weekend day). To our knowledge, this paper is the first to consider a unified utility-maximizing framework for the analysis of such a joint imperfect-perfect substitute goods case in the economic literature.The model formulated in the paper is applied to the time-use decisions of individuals.

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Ensuring coverage of cell phone–only respondents in survey samples is becoming more important in transportation surveys. Various sampling approaches are available to accommodate this requirement. This paper compares and contrasts the efficiencies and outcomes associated with two of them: ( a) the active contact method using a sample of cell phone numbers and ( b) passive contact method using a sample of postal service addresses. The efficiency of the samples was evaluated on measures such as data collection efforts, response rates, and cost per interview. The characteristics of respondents reached via each of the sample types based on telephone ownership patterns were contrasted with demographic characteristics of cell-only respondents. Sizes of both samples were quite large and provided significant methodological insights. These insights have important implications for transportation surveys that use either sampling approach to ensure coverage of cell-only respondents.