基于强化敏感性理论的电动自行车风险骑行行为影响因素

从交通管理的奖惩机制角度，探究电动自行车骑行人的奖惩反应性对其风险骑行行为的影响机理。采用改进强化敏感性理论构建风险骑行行为的心理认知模型。在改进强化敏感性理论框架下，引入风险感知和风险骑行意向，同时考虑性别、年龄和骑行次数的影响，采用结构方程模型评估影响风险骑行行为的主要心理因素。通过问卷调查，共获取402个有效样本。研究结果表明:①修正后的心理认知模型对数据的适配性良好（χ2/df=1.343，RMSEA=0.029），能解释风险骑行行为48%的变异；②惩罚敏感性和奖励敏感性显著影响风险骑行行为，且奖励敏感性的影响程度更大；③风险感知和风险骑行意向显著影响风险骑行行为；④性别显著影响惩罚敏感性和奖励敏感性，且通过二者间接显著影响风险骑行行为；而年龄、骑行次数对各变量的影响均不显著。 

Influencing Factors of Electrical Bikes' Risky Riding Behaviors Based on Reinforcement Sensitivity Theory

From a traffic management perspective towards the reward and punishment strategies, the work studies the influence mechanisms of the reward and punishment responses of electric bike riders on their risky riding behaviors.A psychological cognitive model for risky riding behaviors is developed based on the revised reinforcement sensitivity.Perceived risk and risky riding intention are incorporated into the proposed framework, accounting for the potential impacts of gender, age, and riding frequency.The structural equation model is used to identify key psychological factors influencing risky riding behaviors with the self-reported survey data of 402 valid samples.The model-estimation results are as follows: ①The revised psychological cognitive model fits the data well(χ2/df=1.343, and RMSEA=0.029)and can explain 48%of the variance in risky riding behaviors.②Punishment sensitivity and reward sensitivity significantly affect risky riding behaviors, with the stronger influence of the latter.③Perceived risk and risky riding intention statistically affect risky riding behaviors.④Gender directly affects punishment sensitivity and rewardsensitivity and indirectly affects the risky riding behaviors via both variables.The influence of age and riding frequency on each variable is not significant.