Journal of Advanced Transportation / 2017 / Article / Tab 6

Research Article

Evaluation of Factors Affecting E-Bike Involved Crash and E-Bike License Plate Use in China Using a Bivariate Probit Model

Table 6

Marginal effects for the BP model.

VariableE-bike involved crashE-bike license plate use

Gender (male versus female)0.177−0.285
Age group (Young versus older)0.124−0.442
Education level (high versus low)−0.1690.479
Holding automobile driver license (yes versus no)−0.2250.243
Type of e-bike (E-scooter versus e-bike)0.156
Car in household (yes versus no)−0.1650.137
Frequency of using e-bike (frequently versus occasionally)0.182
Experiences in using e-bike (3–5 years versus <1 year)−0.2030.267
Experiences in using e-bike (>5 years versus <1 year)−0.1640.221
Law compliance (strong versus no)−0.4250.433
Aggressive driving behaviors (frequently versus no)0.163−0.025
Aggressive driving behaviors (generally versus no)0.152
Impulse behavior (frequently versus no)0.144
Degree of riding experience (skilled versus new driver)−0.107
Risk perception scale (high versus low)−0.089
Registration fee (low versus high)0.146
Time for license registration (30 min versus >30 min)0.179

— represents that the variable is not significant.

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