This study focused on short-term dynamics of activity-travel behavior as a response to travel time increases. It is assumed that short-term changes are triggered by stress, which is defined as the deviation between an individual’s aspirations and his or her daily experiences. When stress exceeds a tolerance threshold, habitual behavior is dissociated, and various adaptation strategies emerge. A stated-adaptation experiment was designed to trace behavioral change. The analysis results of the empirical data corresponding to travel time scenarios are presented. Specifically, a random coefficient logit (binary) model that focused on the decision of activating a short-term change was estimated. Next, a random parameters (mixed) logit model is presented; it indicates which specific activity attribute is adjusted once a short-term adaptation is chosen. Then one random coefficient logit (binary) model indicates whether an exploitation of the existing choice set or an exploration effort occurs once an activity attribute is chosen to be adapted. These analyses led to interesting results about the inertia characterizing people’s behavior and their unwillingness to deviate from their habitual state. In addition, it is seen that richer choice sets lead to more short-term changes and specifically to more exploitation efforts. Moreover, heterogeneity plays a significant role in all these models. Finally, the effect of stress as well as of various sociodemographic and travel-specific variables (activity type, destination location, transport mode, and day of the week) is revealed and can be taken into account in the design of spatial and transportation policies.