Abstract
This paper studies demand for ridesharing in a university campus context, where authorities are planning to introduce programs aimed at reducing carbon-intensive travel activity. Following a descriptive analysis of commuter survey data, ordered probit models are developed to investigate interest in ridesharing. The model results show that participation in the program ranges from those who are possibly interested in being drivers to those who wish to be passengers. To further investigate differences in commuters’ taste, latent class ordered probit models are developed; the introduction of individual heterogeneity improves model fit. Residential distance, parking cost, web application, matching preferences, and service flexibility are found to significantly affect propensity to rideshare. These effects should be taken into account by universities or other large employers when planning carpooling/vanpooling services.
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