Work

Examining social-demographic determinants of bike-sharing station capacity

Year: 2024

Type: article

Abstract: This study applied Negative Binomial models to examine the social-demographic determinants of bike-sharing station capacity. It used social-demographic data from Smart Location Database and over 7,000 bike-sharing stations located in the United States. Results revealed that the station's city, households with no cars, the percentage of workers aged 18–64, gas prices, the Caucasian population, gross residential density on unprotected land, intersection density, and low to medium-earning workers are associated with the increase in station capacity. Contrarily, station capacity decreased with vehicle miles traveled and the number of high-earning workers. Findings are crucial to planners and operators in improving bike-sharing operations.

Source: Sustainable Futures

DOI: 10.1016/j.sftr.2024.100274

Authors: Boniphace Kutela, Hamza Mashoor Mustafa Bani Khalaf, Meshack Mihayo, Emmanuel Kidando, Angela E. Kitali

Institutions: Texas A&M Transportation Institute, Cleveland State University, University of Washington Tacoma

Language: English

Topic: Urban Transport and Accessibility

Subfield: Transportation

Field: Social Sciences

Domain: Social Sciences

SDGs: Sustainable cities and communities, Reduced inequalities, Industry, innovation and infrastructure

Open Access status: gold

Estimated APC paid: $1,880