Estimating the Magnitude and Impacts of Bike Theft on Bicycling Behavior
Research Team: Trisalyn Nelson (lead) and Dillon Fitch
UC Campus(es): UC Davis, UC Santa Barbara
Problem Statement: Preliminary data analysis by this research team of early survey results indicates that after experiencing a bicycle theft, 30% of people bicycle less often and 20% of people stop bicycling. The magnitude of the problem is largely unknown, but it may be substantial given the ease of breaking bike locks, the potential for re-sale, and the challenges for law enforcement. Also, bike theft may deter a person from bicycling for a variety of reasons, such as difficulty replacing the bike or because concerns about another theft may limit where a person is willing to ride.
Project Description: The goals of this project are to characterize the magnitude and nature of impacts from bike theft on active transportation by addressing three questions: (1) How many bikes are stolen and what is the monetary cost of theft? (2) What are the patterns and conditions (e.g., location, lock type, time of day) most often associated with bicycle theft and recovery? And (3) How does theft impact bicycling behavior for different populations (by income, race, gender, frequency of bicycle usage)? The research will be conducted through a partnership with BikeIndex.org, a non-profit bicycling registration group. Given the lack of existing research on bicycle theft’s impact on travel decisions, the researchers recently launched a pilot survey, primarily recruiting participants that reported stolen bikes to BikeIndex, and will begin this project by analyzing pilot survey data to build hypotheses and design a comprehensive survey. The researchers will collect data on the magnitude of bike theft, patterns, conditions of bike theft and recovery, and impact of theft on bicycling behavior. They will recruit survey participation from the network of more than 1,300 bike shops that have already partnered with BikeIndex. All data will be integrated and weighted to estimate the scale of bike theft in California and across the US and Canada. The researchers will also conduct spatio-temporal pattern analysis of bike thefts, stolen bike recovery, and model theft patterns based on neighborhood characteristics to determine if and how theft varies across geography and populations based on social, economic, and demographic characteristics. They will determine the types of locks, locations, and times associated with the highest proportion of thefts. Finally, the researchers will estimate the effect theft has on bicycling rates for different types of people depending on age, gender, race, income, and past bicycling behavior. This research will help cities determine where and how to invest in infrastructure and other strategies to ensure that all Californian’s have access to bicycling. This includes guidance for the State’s Active Transportation Program, and other funding programs for bicycling.
Status: In Progress