Non-linear utility functions in models of travel choice behavior

Models of individual choice behavior have been extensively developed and used in travel prediction during the last ten years. These models are generally formulated with utility functions that are linear in parameters. Theories of economics and psychology suggest that the true relationship between service variables and utility is non-linear. In this paper we demonstrate that non-linear transformations of time and cost variables produce statistically significant improvements in the model estimated, have a theoretically appealing interpretation, and lead to managerially important differences in policy evaluations. These results support the need to refine the specification of choice utility functions based on theoretical considerations and empirical research.