网约车用户出行方式选择研究

发布时间：2018-03-26 10:27

本文选题：网约车　切入点：出行方式　出处：《首都经济贸易大学》2017年硕士论文

【摘要】：网约车是“互联网+”时代下的产物,其通过依托移动互联网建立的打车软件服务平台,实现了乘客与司机之间的信息沟通,从而使司机快速接单,乘客快速打车,有效地提高打车效率,成为共享经济的典型代表。在网约车市场新兴之时,围绕网约车市场规范发展的理论及应用研究是十分必要的。本文围绕网约车用户出行方式选择展开研究,运用问卷调查、数据挖掘等统计方法,调查了网约车用户的分布状况和行为信息,就网约车用户出行方式选择行为表现出的群体差异性展开探讨,最终刻画出影响网约车用户约车方式以及约车频率的主要特征,从而为网约车市场的科学发展提供建议。本文的重点、创新之处,主要表现在以下三点:第一、通过问卷调查收集网约车用户的基本信息以及行为信息,把握网约车用户基本信息以及行为信息,在此基础上利用列联分析以及交叉分析研究网约车用户在约车方式以及约车频率方面存在的群体差异性,结果表明收入、职业、年龄、约车原因、安全满意度等群体特征对约车方式选择以及约车频率具有显著影响。第二、围绕网约车用户约车方式利用决策树、logistic、神经网络建立分类判别模型,探讨影响网约车用户不同约车方式的主要特征,结果表明网约车用户的年龄、频率、约车原因、安全满意度、收入对网约车用户不同的约车方式存在显著影响。第三、围绕网约车用户约车频率利用决策树、logistic、神经网络建立分类判别模型,将约车频率作为衡量网约车忠实客户的特征,探讨影响网约车忠实用户选择行为的特征,结果表明,选车方式、选车原因、收入、年龄等对其有显著影响。
[Abstract]:Ride-hailing is the product of the era of "Internet". By relying on the mobile Internet, the ride-hailing software service platform has realized the communication of information between passengers and drivers, so that drivers can pick up orders quickly, and passengers can take a taxi quickly. Effectively improve the efficiency of ride-hailing, become a typical representative of the sharing economy. It is very necessary to study the theory and application of the development of the network car market standard. This paper focuses on the choice of the travel mode of the ride-hailing users, and applies the statistical methods such as questionnaire survey, data mining and so on. This paper investigates the distribution and behavior information of the network ride-hailing users, probes into the group differences in the behavior of the car-ride-sharing users, and finally depicts the main characteristics that affect the car-sharing modes and the ride-sharing frequency of the ride-hailing users. The key points and innovations of this paper are as follows: first, collecting the basic information and behavior information of ride-hailing users through questionnaires. To grasp the basic information and behavior information of ride-hailing users on the basis of the analysis and cross-analysis of network ride-hailing users in terms of car-sharing patterns and ride-sharing frequency, the results show that the income, occupation, age, and age of car-hailing users are different from each other. Group characteristics such as car-sharing reasons, safety satisfaction and so on have a significant impact on the choice of ride-hailing mode and the frequency of ride-hailing. Second, a classification and discrimination model is built around the decision tree of ride-hailing users using the decision tree logistic-neural network. This paper discusses the main characteristics that affect the different car-sharing modes of the net-ride-hailing users. The results show that the age, frequency, reasons, safety satisfaction and income of the net-ride-hailing users have significant influence on the different car-sharing modes of the net-ride-hailing users. According to the decision tree of ride-sharing frequency of ride-hailing users, the neural network is used to establish a classification and discriminant model. The frequency of ride-hailing is regarded as the characteristic to measure the loyal customers, and the characteristics that affect the behavior of network-ride-sharing loyal users are discussed. The results show that, Car selection, car selection reasons, income, age and so on have a significant impact on it.
【学位授予单位】：首都经济贸易大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：F724.6;F572

【参考文献】