University of California Transportation Center

A major aspect of transportation planning is understanding behavior: how to predict it and how to influence it over the long term. Behavioral models in transportation are predominantly rooted in the classic microeconomic paradigm of rationality. However, there is a long history in behavioral economics of raising serious questions about rationality. Behavioral economics has made inroads in transportation in the areas of survey design, prospect theory, and attitudinal variables. Further infusion into transportation could lead to significant benefits in terms of increased ability to both predict and influence behavior. The aim of this research is to investigate the transferability of findings in behavioral economics to transportation, with a focus on lessons regarding personalized information and social influences. We designed and conducted three computer experiments using UC Berkeley students: one on personalized-information and route choice, one on social influences and auto ownership, and one combining information and social influences and pedestrian safety. Our findings suggest high transferability of lessons from behavioral economics and great potential for influencing transport behavior. We found that person- and trip-specific information regarding greenhouse gas emissions has significant potential for increasing sustainable behavior, and we are able to quantify this Value of GREEN at around $0.24/pound of greenhouse gas avoided. Congruent with lessons from behavioral economics, we found that information on peer compliance of pedestrian laws had a stronger influence on pedestrian safety behavior than information on the law, citation rates, or accident statistics. We also found that social influences positively impact the decision to buy a hybrid car over a conventional car or forgo a car altogether.