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Citation |
Burmester B, LaMondia JJ. Transp. Res. Rec. 2022; 2676(6): 626-639. |
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Copyright |
(Copyright © 2022, Transportation Research Board, National Research Council, National Academy of Sciences USA, Publisher SAGE Publishing) |
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DOI |
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PMID |
unavailable |
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Abstract |
Bikeshare programs have grown exponentially over the last decade and have been found to be influential in increasing the nonmotorized mode share. With shared microbility programs proving to be a key component of modern urban environments and in first- and last-mile connections to transit, there is a need to better understand users and their facility preferences. This study utilizes 3 years' worth of data from a campus bikeshare program in Auburn, AL, that includes over 100,000 trips and almost 9,000 users to develop a bikeshare user typology. Whereas past research developing cyclist groupings has been based on self-reported cyclist comfort and confidence levels, this study utilized actual ridership data from the bikeshare program to create new typologies specific to bikeshare. Using a K-means cluster analysis, this study proposes four bikeshare user types: unsupported users, aspirational users, flexible users, and purposeful users. These users have varying travel motivations, needs, and patterns. Their choice between an on-road and off-road facility option was analyzed at nine specific locations displaying different roadway and physical conditions. A binary logistic regression analysis was performed to determine which variables are influential in a bikeshare user's choice between riding on an on-road or off-road facility. The modeling results found two typology memberships were a significant predictor of bicycle facility preference, keeping all other factors constant. Specifically, flexible and purposeful users had stronger preferences for off-road bicycle facilities. Additionally, the physical conditions were found to be significant with users choosing off-road options away from motor vehicle traffic as the roadway environment becomes more intimidating. Language: en |
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Keywords |
activity; behaviors; bicycle transportation; bicycles; bikesharing; choices; emerging; etc.); human factors; mode choices; modeling and forecasting; pattern (behavior; pedestrians; planning and analysis; planning and policy; preferences; traveler behavior and values |