Stated choice for transportation demand management models: Using a disaggregate truth set to study predictive validity

Document Type

Article

Publication Date

1-1-1997

Abstract

Discrete choice models have expanded the ability of tranportation planners to forecast future trends. Where new service or policies are proposed, the stated-choice approach can provide an objective basis for forecasts. Stated-chioce models are subject to a range of experimental errors not found in revealed-preference designs. Primary among the concerns facing researchers is the ability of respondents to understand and operate on hypothetical choice scenarios in a manner that will resproduce choices made under actual situations. These concerns are specified in the scaling factor. Estimation of the scaling factor has proceeded through various ways to link actual decisions to comparable decisions made under hypothetical conditions. However, where the alternative is new. real decision data are not available. The level of error icorporated in a study where no real-world information on the scaling factor is available is examined. The test of predictive validity focuses attention on the switching behavior of commuters at a single employment site. The result indicate that switching behavious between within 1 persent by stated-choice techniques and within 10 persent by backcasting techniques with revealed-preference data.

Identifier

0009555980 (Scopus)

Publication Title

Transportation Research Record

External Full Text Location

https://doi.org/10.3141/1598-01

ISSN

03611981

First Page

1

Last Page

8

Issue

1598

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