基于BP神经网络的网约车服务质量研究

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中图分类号：F572 文献标志码：A DOI： 10.13714/j.cnki.1002-3100.2025.12.014

Abstract：Toexplorethekeyfactorsafecting thequalityofonlineride-haiingservices，aBPneuralnetworkisusedto construct anonlineride-hailing servicequality model.The paperuses MIVtoanalyzetheimportanceof influencing factorsand appliesK-meansclusteringmethodtoanalyzetheheterogeneityofonlineride-hailingpassengers.Theresultsindicatethat factorssuchasdriversatisfaction，travelcosts，traveltime，operatingtimerange，andtraficsafetyplayakeyoleintheoeall servicesatisfactionofonlineride-halingservices，andthecorrespondingcountermeasuresareproposedbasedontheimportance of above-mentionedfactors.Usingpassngergender，age，averagemonthlyhouseholdincome，andfrequencyofonlineridehailing usageasclusteringvariables，fourdiferentcharacteristicsofolieridehailingpasengergroupsareidentified.Thepaperprovides a theoretical basis and practical guidance for improving the quality of online ride-hailing services.

Key Words： online ride-hailing; service quality; BP neural network; MIV; K-means

0引言

随着Uber、Lyft、滴滴出行、Grab各种网约车平台的兴起，网约车逐渐成为人们日常出行的重要组成部分。（剩余6289字）