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First published January 2006

Nonlinearity of Response to Level-of-Service Variables in Travel Mode Choice Models

Abstract

It is important to accommodate variations in responsiveness (or response heterogeneity) to level-of-service (LOS) attributes in travel mode choice models. This response heterogeneity may be disaggregated into a systematic (observed) component and a random (unobserved) component. Earlier studies typically considered systematic response heterogeneity by examining differences in LOS response sensitivities caused by individual demographic and other attributes. The emphasis of the presented research is on another element of systematic response heterogeneity: that originating from nonlinear responsiveness to LOS attributes. Specifically, both the components of systematic response heterogeneity (due to individual characteristics and nonlinear responsiveness) as well as unobserved response heterogeneity are considered at the same time, and the empirical results of models that assume a traditional linear responsiveness to LOS attributes are compared with those that adopt a nonlinear responsiveness to LOS attributes. The empirical analysis uses data from the Austin commuter stated preference survey to examine commute travel mode choice. The nonlinear specifications for travel time and travel time unreliability indicate that in the first 15 min commuters place little value on travel time and high value on travel time reliability. Beyond 15 min, however, the valuation of travel time increases rapidly, whereas that of travel time reliability drops dramatically. In addition to clearly indicating the nonlinear nature of responsiveness to travel time and travel time unreliability, the results indicate that ignoring nonlinear responsiveness leads, in the current empirical context, to (a) biased parameter estimates, (b) an inflated estimate of unobserved heterogeneity, (c) counterintuitive signs on the LOS variables for a high fraction of individuals, (d) inaccurate estimates of willingness-to-pay measures, and (e) loss in model fit.

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Article first published: January 2006
Issue published: January 2006

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© 2006 National Academy of Sciences.
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Authors

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Abdul Rawoof Pinjari
Department of Civil, Architectural and Environmental Engineering, University of Texas at Austin, 1 University Station C1761, Austin, TX 78712-0278.
Chandra Bhat
Department of Civil, Architectural and Environmental Engineering, University of Texas at Austin, 1 University Station C1761, Austin, TX 78712-0278.

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