Chapter
Aug 30, 2023

Investigating Bike-Sharing Brand Selection Using Hybrid Choice Model: An Empirical Analysis from Shanghai

ABSTRACT

Various bike-sharing brands exist in the market which differ in terms of bike fleet size, riding experience, charging rules, deposit prices, and may affect users’ brand selection toward cycling behavior. To investigate commuters’ bike-sharing brand selection and influential factors, a hybrid choice model (HCM) is established based on survey data in Shanghai. The results indicate: (1) riding experience has significant impact on bike-sharing brand selection; (2) deposit and charge both have major impact on brand selection; and (3) fleet size and individual characteristics such as gender, education level, and income will affect brand selection. The study also provides important policy implications for bike-sharing companies and government. Bike-sharing companies should improve the quality of bikes, increase the bike fleet size, and optimize deposit and charge to attract more users. This paper discovers hidden mechanism of commuters’ brand selection, reveals influential factors, and provides insights for policy making and traffic management.

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Go to CICTP 2023
CICTP 2023
Pages: 685 - 695

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Published online: Aug 30, 2023

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1Key Laboratory of Earthquake Engineering and Engineering Vibration, Institute of Engineering Mechanics, China Earthquake Administration, Harbin, China. Email: [email protected]
2Business School, Univ. of Shanghai for Science and Technology, Shanghai, China. Email: [email protected]
Yi-Wei Zhou [email protected]
3Business School, Univ. of Shanghai for Science and Technology, Shanghai, China. Email: [email protected]
Hong-Cheng Gan [email protected]
4Business School, Univ. of Shanghai for Science and Technology, Shanghai, China. Email: [email protected]
Xu-Chuan Lin [email protected]
5Key Laboratory of Earthquake Engineering and Engineering Vibration, Institute of Engineering Mechanics, China Earthquake Administration, Harbin, China. Email: [email protected]
6Logistics and Infrastructure Management Division, Wenzhou Univ. of Technology, Wenzhou, China. Email: [email protected]

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