How Do Individuals Adapt Their Personal Travel? Objective and Subjective Influences on the Consideration of Travel-Related Strategies for San Francisco Bay Area Commuters
Available online at doi: 10.1016/j.tranpol.2005.03.002
Cao, Xinyu and Patricia L. Mokhtarian (2005) How Do Individuals Adapt Their Personal Travel? Objective and Subjective Influences on the Consideration of Travel-Related Strategies for San Francisco Bay Area Commuters. Transport Policy 12 (4), 291 - 302
Abstract: This study operationalizes the conceptual analysis presented in a companion paper, to examine the effects of objective and subjective variables on the consideration of 16 travel-related strategies reflecting a range of individuals' potential reactions to congestion. Using 1283 commuting respondents to a 1998 survey conducted in the San Francisco Bay Area, binary logit models were developed for the consideration of each individual strategy. The proportion of information explained by these models ranges from 0.18 to 0.63. It was found that the consideration of travel-related strategies is affected not only by the amounts of travel that individuals actually do, but also by their subjective assessments, desires and affinities with respect to travel, as well as their travel attitudes, personality and lifestyle. The previous adoption of these strategies greatly affects their current consideration, demonstrating an effect of past experience. Mobility constraints and socio-economic and demographic characteristics exhibit distributional effects with respect to the options individuals consider. These findings imply that policies designed to alleviate congestion may be less effective than expected, because individuals' responses to the travel-related strategies analyzed here—many of them directly tied to public policies intended to reduce vehicle travel—are influenced by a large variety of qualitative and experiential variables that are seldom measured and incorporated into demand models. Therefore, understanding the role of such variables will improve our ability to design effective policies and to accurately forecast the response to policy interventions as well as natural trends.