Evaluation of Factors Affecting E-Bike Involved Crash and E-Bike License Plate Use in China Using a Bivariate Probit Model
Marginal effects for the BP model.
E-bike involved crash
E-bike license plate use
Gender (male versus female)
Age group (Young versus older)
Education level (high versus low)
Holding automobile driver license (yes versus no)
Type of e-bike (E-scooter versus e-bike)
Car in household (yes versus no)
Frequency of using e-bike (frequently versus occasionally)
Experiences in using e-bike (3–5 years versus <1 year)
Experiences in using e-bike (>5 years versus <1 year)
Law compliance (strong versus no)
Aggressive driving behaviors (frequently versus no)
Aggressive driving behaviors (generally versus no)
Impulse behavior (frequently versus no)
Degree of riding experience (skilled versus new driver)
Risk perception scale (high versus low)
Registration fee (low versus high)
Time for license registration (30 min versus >30 min)
— represents that the variable is not significant.
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