PART 2 in a series of posts documenting Sanford’s first Behavioral Economics for Municipal Policy Course.
As part of the Sanford School’s pilot Local Government Innovation program, 50 graduate students from Sanford and Pratt worked in teams with twelve North Carolina local governments over the course of a year to apply insights from behavioral science to solve problems facing cities and counties.
Students, under the instruction of Dan Ariely and researchers from the Center for Advanced Hindsight, developed new ways to tackle challenges facing city and county managers using behavioral economics. Students worked with local governments to design interventions and run real world experiments to test their ideas to see what worked — something too few students ever have the opportunity to do while in school, and too many local governments never have the time, resources, or capacity to try.
On March 8th, the News and Observer ran a story about the progress of one student team working with the Town of Knightdale to reduce speeding in residential areas. “Neighborhood speeding, especially, is an issue we frequently deal with,” [Police Chief Lawrence] Capps said. “With the growth we’ve experienced in town, it’s something that we put an emphasis on.”
Read the full story.
In the past, the Knightdale police department has multiple strategies to reduce instances of neighborhood speeding, including speed monitoring, increased police presence, physical barriers, speed limit reductions and informational campaigns. Some of these efforts proved successful in the short run, but none have had a longer-term impact on the perceptions of residents that neighborhood speeding remains a problem.
For this project, the team of Sanford and Pratt students tried a new approach: have the Knightdale police sponsor a community speed reduction competition that asks neighborhoods to compete to reduce speeds.
They based this idea on the behavioral economic principles of normative social influence and social proof. These principles describe situations where people use other’s behavior as a cue for what is acceptable.
The students describing their idea write, “The Safe Neighborhoods Competition was a town-wide event that put neighborhoods in competition with one another, each striving to be the community with the safest drivers. Over the course of the competition, drivers’ speeds were measured using STEALTH devices prior to the public campaign efforts and after the competition was advertised.”
The results from the first experiment are inconclusive (which means right now they don’t know if this strategy will work to reduce speeding). Out of the five neighborhoods where the Knightdale police department ran The Safe Neighborhood Competition, drivers in three of the neighborhoods, on average, drove more slowly after the competition than prior to it. The experiment cannot exclude other factors that might have contributed to this decrease or explain why two neighborhoods actually saw speeds increase after the competition, but the results could warrant additional tests.
The data collected through the STEALTH devices revealed one interesting finding: most excessive speeding occurs between the hours of 11PM and 4AM. The students speculate that drivers at this hour may feel more comfortable speeding because they think that community members are asleep and no one is watching. They recommend posting signs in high speeding areas that state police are monitoring drivers’ speeds, and then publicizing the results regularly to create more social pressure.