Stated choice: a study in predictive validity using an aggregate truth set

被引:6
作者
Beaton, P [1 ]
Chen, C
Meghdir, H
机构
[1] Rutgers State Univ, Ctr Polymer Studies, Newark, NJ 07102 USA
[2] Univ Calif Davis, Inst Transport Studies, Davis, CA USA
[3] HMDC, Lyndhurst, NJ 07071 USA
关键词
discrete choice; predictive validity; stated choice;
D O I
10.1023/A:1004986826320
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Stated Choice models expand the ability of transportation planners to forecast future trends. The Stated Choice approach can forecast demand for new services or policies. However, Stated Choice models are subject to a range of experimental error not found within Revealed Preference (RP) designs. Primary among the concerns facing researchers is the ability of respondents to understand and operate upon hypothetical choice scenarios in a manner that will reproduce choices made under actual situations. These concerns are specified in the magnitude of a scaling factor. Efforts to estimate the scaling factor has proceeded by linking real decisions taken from a revealed preference survey with comparable decisions made under hypothetical conditions. However, where the alternative is new, actual decision data is not available. This study examines the level of error incorporated in a study where no RP data is available. The test of predictive validity focuses on the switching behavior of commuters at a single employment site. The actual data used to test the forecast is limited to company wide or aggregate ridership levels on the public transit mode taken two years after estimation of the SC model. The Fowkes and Preston hypothesis is examined and shown to bound the future actual value between forecasts derived from probabilistic and deterministic methods. The results show that with the passage of time, the probabilistic method approaches the reported ridership levels within 15 percent error.
引用
收藏
页码:55 / 75
页数:21
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