Abstract: In order to solve the problem of lack of quantitative descriptive methods for influencing factors of traffic information reception behavior in social networks, based on technology reception model and micro-blog user information reception model, the structural equation model was used to quantitatively describe the coupling relationship among latent variables such as information cognition, subjective norms, perceived usefulness, perceived ease of use and willingness to receive information as well as the effect of latent variables on information acceptance behavior. Combined with gender, age and other individual attribute variables, a hybrid discrete model of traffic information reception behavior in social networks was constructed, which considered the interaction of latent variables and explicit variables. Empirical analysis was carried out through questionnaire data. The research results show that: in structural equation model, five latent variables all have a positive impact on information reception behavior, among which reception intention (0.742), information cognition (0.704) and subjective norm (0.641) have a greater impact on information reception behavior; the optimal ratio of the hybrid discrete model is 0.346, and it is 0.145 higher than that of BL model which only considers individual attribute variables.

Key words: traffic engineering, acceptance behavior, social network, traffic information, hybrid model

摘要： 为解决社交网络中交通信息接收行为影响因素缺少定量描述方法的问题，笔者基于技术接收模型和微博用户信息接收模型，运用结构方程模型对信息认知、主观规范、感知有用性、感知易用性和接收意愿等潜变量间相互耦合关系，及潜变量对信息接受行为结果进行定量作用描述；结合性别、年龄等个人属性变量，构建考虑潜变量与显变量共同作用的社交网络交通信息接收行为混合离散模型，通过问卷调查数据进行实证分析。研究结果表明：结构方程模型中，5个潜变量均对信息接收行为产生正向影响，其中接收意愿（0.742）、信息认知（0.704）与主观规范（0.641）对信息接收行为的影响效应较大；混合离散模型优度比为0.346，较传统只考虑个体属性变量的BL模型提升0.145。

关键词: 交通工程, 接受行为, 社交网络, 交通信息, 混合模型