基于BN和PLS-SEM的大学生网约车忠诚度研究

李纲，徐伟

大连交通大学交通运输工程学院，辽宁 大 连  116028

摘要：为分析大学生网约车乘客忠诚度及其影响因素的作用机制，将贝叶斯网络（Bayesian networks，BN）和偏最小二乘法结构方程模型（partial least squares structural equation modelling，PLS-SEM）结合，以2019年大连市大学生网约车乘客为例，分析大学生网约车乘客的负面体验、运营服务、环境满意、乘客满意度和忠诚度的关系。在BN中采用基于约束的自动学习方法学习因子间的作用关系，获得不同影响因素间相关关系的网络结构。通过PLS-SEM测试和分析BN结构，建立乘客忠诚度模型。结果表明：乘客满意度是影响忠诚度的最大因素，总效应为0.508；负面体验是影响忠诚度的最小因素，总效应为-0.146。乘客满意度是提高大学生网约车忠诚度的关键指标，网约车平台应通过优化车内环境、缩短出行时间、规范司机行为、升级应用软件等措施提升大学生的乘车体验，提高大学生网约车乘客的忠诚度。基于BN和PLS-SEM的大学生网约车忠诚度研究可丰富网约车乘客的决策行为机制与研究方法，为相关部门和网约车平台提供管理决策依据。

关键词：网约车；乘客忠诚度；乘客满意度；BN；PLS-SEM

Study on college students′ loyalty of online ride-hailing based on BN and PLS-SEM

LI Gang, XU Wei

School of Traffic and Transportation Engineering, Dalian Jiaotong University, Dalian 116028, China

Abstract: In order to analyze the mechanism of college student online ride-hailing passenger loyalty and its influencing factors, Bayesian networks (BN) and partial least squares structural equation modeling(PLS-SEM) is combined to analyze the relationship between negative experiences, operational services, environmental satisfaction, passenger satisfaction, and loyalty of college student online ride-hailing passengers in Dalian in 2019. Constraint-based automatic learning methods are used in BN to learn the relationship between factors and obtain the network structure of the correlation between different influencing factors. Through PLS-SEM testing and analyzing the BN structure, a passenger loyalty model is established. The results showed that passenger satisfaction is the largest factor affecting loyalty, with a total effect of 0.508; negative experience is the smallest factor affecting loyalty, with a total effect of -0.146. Passenger satisfaction is a key indicator to improve college student online ride-hailing loyalty. The online ride-hailing platform should improve college students′ ride experience and loyalty by optimizing the in-car environment, shortening travel time, regulating driver behavior, upgrading application software, and other measures. The study of college student online ride-hailing loyalty based on BN and PLS-SEM can enrich the decision-making behavior mechanism and research methods of online ride-hailing passengers, and provide management decision-making basis for relevant departments and online ride-hailing platforms.

Keywords: online ride-hailing; passenger loyalty; passenger satisfaction; BN; PLS-SEM