Abstract
This study analyzes the annual vacation destination choices and related time allocation patterns of American households. More specifically, an annual vacation destination choice and time allocation model is formulated to simultaneously predict the different vacation destinations that a household visits in a year, and the time (no. of days) it allocates to each of the visited destinations. The model takes the form of a multiple discrete–continuous extreme value (MDCEV) structure. Further, a variant of the MDCEV model is proposed to reduce the prediction of unrealistically small amounts of vacation time allocation to the chosen destinations. 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 analysis was performed using the 1995 American Travel Survey data, with the United States divided into 210 alternative destinations. The model estimation results provide several insights into the determinants of households’ vacation destination choice and time allocation patterns. Results suggest that travel times and travel costs to the destinations, and lodging costs, leisure activity opportunities (measured by employment in the leisure industry), length of coastline, and weather conditions at the destinations influence households’ destination choices for vacations. The annual vacation destination choice model developed in this study can be incorporated into a larger national travel modeling framework for predicting the national-level, origin–destination flows for vacation travel.
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The authors would like to thank three anonymous reviewers and the US Co-Editor David T. Hartgen for valuable comments on an earlier version of the paper. Jeff Hood raised (at a conference) thought provoking questions related to overprediction of very short time allocations.
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Van Nostrand, C., Sivaraman, V. & Pinjari, A.R. Analysis of long-distance vacation travel demand in the United States: a multiple discrete–continuous choice framework. Transportation 40, 151–171 (2013). https://doi.org/10.1007/s11116-012-9397-6
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DOI: https://doi.org/10.1007/s11116-012-9397-6