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Promoting Sustainable Urban Mobility: Factors Influencing E-Bike Adoption in Henan Province, China

Xiaoyu Zhang, Ee Shiang Lim and Maowei Chen ()
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Xiaoyu Zhang: Graduate School of Global Convergence, Kangwon National University, Chuncheon 24341, Republic of Korea
Ee Shiang Lim: School of Social Sciences, Universiti Sains Malaysia, Gelugor 11800, Pulau Pinang, Malaysia
Maowei Chen: Department of Global Convergence, Kangwon National University, Chuncheon 24341, Republic of Korea

Sustainability, 2024, vol. 16, issue 22, 1-15

Abstract: This study examines the key factors influencing e-bike adoption and explores how advancing e-bike usage in Henan Province, China, can foster sustainable urban transportation and contribute to urban environmental preservation. Utilizing data from an online survey, binary logistic regression analyzes the impact of socio-demographic characteristics, perceived advantages, neighborhood environmental attributes, and vehicle ownership on e-bike usage. The findings indicate that socio-demographic factors, such as family size and occupation, significantly influence adoption, with workmen more likely than office workers to choose e-bikes. Cost savings emerged as the primary motivator for e-bike use, overshadowing environmental concerns, which unexpectedly negatively affected usage patterns. However, the presence of supportive infrastructure—particularly charging stations and dedicated lanes—proves crucial for promoting e-bike usage, highlighting the importance of accessible, environmentally supportive urban design. Vehicle ownership characteristics further illuminate how access to e-bikes correlates with regular usage. These findings suggest that, beyond cost efficiency, targeted awareness campaigns and strategic infrastructure improvements are essential for embedding e-bikes into sustainable urban transport systems. By fostering adoption and supporting e-bike infrastructure, cities can significantly reduce urban pollution, improve air quality, and advance toward sustainable mobility goals in Henan Province and beyond.

Keywords: binary logistic regression; e-bike adoption; environmental benefits; sustainable urban mobility; vehicle ownership (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
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