Graduation Year

2011

Document Type

Thesis

Degree

M.S.C.E.

Degree Granting Department

Civil and Environmental Engineering

Major Professor

Abdul Pinjari, Ph.D.

Committee Member

Yu Zhang, Ph.D.

Committee Member

Steven Polzin, Ph.D.

Committee Member

John Lu, Ph.D.

Keywords

Long Distance Travel, Vacation Travel Demand, National Travel Model, Kuhn-Tucker Demand Model Systems, Destination Choice

Abstract

This study contributes to the literature on national long-distance travel demand modeling by providing an analysis of households' annual destination choices and time allocation patterns for long-distance leisure travel purposes. An annual vacation destination choice and time allocation model is formulated to simultaneously predict the different destinations that a household visits and the time it spends on each of these visited destinations, in a year. The model takes the form of a Multiple Discrete-Continuous Extreme Value (MDCEV) structure (Bhat, 2005; Bhat, 2008). The model assumes that households allocate their annual vacation time to visit one or more destinations in a year to maximize the utility derived from their choices. The model framework accommodates variety-seeking in households' vacation destination choices in that households can potentially visit a variety of destinations rather than spending all of their annual vacation time for visiting a single destination. At the same time, the model accommodates corner solutions to recognize that households may not necessarily visit all available destinations. An annual vacation time budget is also considered to recognize that households may operate under time budget constraints. Further, the paper proposes a variant of the MDCEV model that avoids the prediction of unrealistically small amounts of time allocation to the chosen alternatives. To do so, the continuously non-linear utility functional form in the MDCEV framework is replaced with a combination of a linear and non-linear form.

The empirical data for this analysis comes from the 1995 American Travel Survey Data, with the U.S. divided into 210 alternative destinations. The empirical analysis provides important insights into the determinants of households' leisure destination choice and time allocation patterns.

An appealing feature of the proposed model is its applicability in a national, long-distance leisure travel demand model system. The annual destination choices and time allocations predicted by this model can be used for subsequent analysis of the number of trips made (in a year) to each destination and the travel choices for each trip. The outputs from such a national travel modeling framework can be used to obtain national-level Origin-Destination demand tables for long-distance leisure travel.

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