Experimental Economics in Transportation

Abstract

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. Three computer experiments were designed and conducted by using University of California, 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. The findings suggest high transferability of lessons from behavioral economics and great potential for influencing transport behavior. It was found that person- and trip-specific information regarding greenhouse gas emissions has significant potential for increasing sustainable behavior, and it was possible to quantify this value of green at around $0.24/lb of greenhouse gas avoided. Congruent with lessons from behavioral economics, information on peer compliance with pedestrian laws was found to have a stronger influence on pedestrian safety behavior than information on the law, citation rates, or accident statistics. It was also found that social influences positively affect the decision to buy a hybrid car over a conventional car or to forgo a car altogether.