Examining the Effects of a Bike and E-Bike Lending Program on Commuting Behavior

Abstract

In 2015, Google added a new transportation demand management (TDM) program to increase bike commuting to their two main campuses in Mountain View and Sunnyvale, California. An initial survey of employees indicated that bike ownership and worry about maintenance were primary bicycling barriers. With this information, Google began a program that loaned high-quality electric-assisted and conventional bicycles for a period of six months at no cost to interested employees. This research evaluates the effectiveness of the program at changing travel behavior to the corporate campuses by using self-reported and smartphone-integrated travel data. The lending program at Google represents one of, if not the largest, employer-sponsored bike and e-bike lending program in North America with over 1,000 bikes in its inventory. Thus, the evaluation of this program is a critical first step for understanding how bike lending can influence travel behavior in North American suburban contexts.

Review of Current Practice and Research on E-Bikes in Transport Models

“…In the three North American sources (25,35,36), ebikes appear to afford a shifting perspective on cycling away from being a leisure activity toward being a utilitarian mode of transport. Adopters tend to be former leisure cyclists who then go on to substitute utilitarian car trips with an e-bike (25).…”

“…When introduced to very carcentric people groups, e-bikes might increase c-bike use owing to complementary effects (38). The higher the previous car mode share, the larger the amount of e-bike travel sourced from that mode (34,(36)(37)(38)44). Most e-bike intervention studies report rather large impacts.…”

“…Several of the aforementioned studies (21,24,25,31,32,36,38,42,44,45) actively promoted e-bike purchase or use and reported larger mode shift impacts than might be expected from uninfluenced growth of e-bike ownership: an illustration of self-selection bias among the participants. However, it is important to note that in the context of transport modeling we also would not expect people to acquire e-bikes randomly.…”

“…Modeling these factors and future societal changes is difficult, and we address this issue in the discussion section below. Several sources (31,36,37) additionally point toward the common concept in transport research that fundamental changes in travel behavior, such as choosing an e-bike instead of a c-bike or even instead of nonbicycle modes, are more likely to occur after a considerable external stimulus. This could be a change in home or work location (37) or the act of participating in a study (31,36).…”

“…Several sources (31,36,37) additionally point toward the common concept in transport research that fundamental changes in travel behavior, such as choosing an e-bike instead of a c-bike or even instead of nonbicycle modes, are more likely to occur after a considerable external stimulus. This could be a change in home or work location (37) or the act of participating in a study (31,36). Since transport models are frequently used to forecast both short-and long-term changes in travel behavior (5), we have to take this time lag in users' reactions to incremental changes in the wider transport system into account.…”