Measuring and modeling activity and travel well-being

This thesis develops methods for the measurement of activity and travel well-being and models for linking well-being and behavior. The hypotheses underlying this research are that (1) activities are planned to maintain or enhance subjective well-being, and (2) given the activity choices, travel choices are likely to be motivated by a desire to maintain or enhance travel well-being. The aim is to enhance travel demand models, which overemphasize the generalized cost of travel, to better capture travel benefits, and to contribute more broadly to measurement and modeling efforts in the subjective wellbeing field. The thesis develops and tests a modeling framework that incorporates happiness measures as additional indicators of utility in discrete choice models based on random utility theory. The framework is applied to modeling both activity and travel choices and, in doing so, new well-being measurement methods are developed. Even though the applications focus on activities and travel, the framework is general and can be applied to modeling behavior in other domains. Activity well-being is investigated both empirically and theoretically. The empirical analysis consists of the development of models of activity participation and well-being using data from a web-based cross-sectional survey of a sample of commuters. The models reveal significant correlations between well-being and behavior: higher propensity of activity participation is associated with greater activity happiness and greater satisfaction with travel to the activity.