4.7 Article

Examining market segmentation to increase bike-share use and enhance equity: The case of the greater Sacramento region

Journal

TRANSPORT POLICY
Volume 145, Issue -, Pages 279-290

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/j.tranpol.2023.10.021

Keywords

Cluster analysis; Equity; Electric bike-share market segments; Transport disadvantaged groups; Association rule mining

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As bike-share systems spread in the US, understanding the different segments of bike-share users is crucial in expanding and benefiting more people. This study analyzes bike-share user data in Sacramento and identifies low-income individuals, zero-car households, students, and transit and car-share users as significant market segments. The results show that bike-share is widely adopted, particularly by those with limited means of transportation. Targeting low-income and zero-car owners can help increase bike-share demand and enhance social equity.
As bike-share systems proliferate across the US, a deeper understanding of current bike-share users could enable an expansion of these services and their benefits to a larger population. To grow bike-share demand sustainably and equitably, cities must understand how different segments of the population use this service. Understanding the different segments within a market enable operators to develop strategies that are tailored toward the needs of each segment. This study uses data from bike-share user surveys in the Sacramento region to perform market segmentation based on perceptions of the bike-share service, mode use patterns, and bike-share use. We focus on the market segments with more limited means of transportation: low-income individuals, zero-car households, students, and transit and car-share users. The results show that individuals with low incomes, those without cars, and students use the service frequently for commuting and a variety of non-commuting purposes. Bike-share is generally adopted by all mode user groups but is used at a higher rate by the super multimodal and active multimodal groups. The occasional users of the bike-share service are mainly those with higher incomes and individuals who have access to a personal car. The segments consisting of non- and infrequent-personal bike users use the bike-share service at a greater rate for different purposes than regular bicyclists, suggesting that bike-share may act as a lever for increasing bike travel for some users. Results from data mining suggest that bike-share operators should target low-income and zero-car owners for new recruitment as these groups are more likely to use bike-share frequently. The results provide insights that may be helpful to cities as they consider strategies to increase bike-share demand in a way that enhances social equity.

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