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基于乘客感知的公交车线路服务质量评价模型
引用本文:刘莹,于淼,刘阳. 基于乘客感知的公交车线路服务质量评价模型[J]. 东北大学学报(自然科学版), 2019, 40(5): 750-755. DOI: 10.12068/j.issn.1005-3026.2019.05.027
作者姓名:刘莹  于淼  刘阳
作者单位:东北大学 工商管理学院,辽宁 沈阳 110819;沈阳城市建设学院 管理系,辽宁 沈阳 110168;沈阳建筑大学 管理学院,辽宁 沈阳,110016;沈阳城市建设学院 管理系,辽宁 沈阳,110168
基金项目:国家自然科学基金资助项目(71701137); 住建部科学技术计划项目(2016-K4-057).
摘    要:针对传统公交车服务质量评价方法的局限性,提出基于乘客感知的普适性因素权值分析方法.首先以相关乘客作为专家并分组,建立基于乘客感知视角的专家权重确定方法,得到专家权重及指标综合权重.然后以上述多组数据作为先验样本进行 BP 神经网络的训练、测试与验证,从而获得可供推广的城市公交线路服务质量评价AHP-BP神经网络模型.最后以沈阳市某条公交线路为例展开实证研究,结果表明该模型在充分反映乘客感知服务质量因素的同时,降低了主观评价的随意性,给出了特定公交线路服务质量改进方向.

关 键 词:改进AHP  BP神经网络  影响因素分析  乘客感知  公交车线路
收稿时间:2018-07-22
修稿时间:2018-07-22

Evaluation Model of Bus Route Service Quality Based on Passengers Perceptions
LIU Ying,YU Miao,LIU Yang. Evaluation Model of Bus Route Service Quality Based on Passengers Perceptions[J]. Journal of Northeastern University(Natural Science), 2019, 40(5): 750-755. DOI: 10.12068/j.issn.1005-3026.2019.05.027
Authors:LIU Ying  YU Miao  LIU Yang
Affiliation:1.School of Business Administration, Northeastern University, Shenyang 110819, China; 2.Department of Management, Shenyang Urban Construction University, Shenyang 110168, China; 3.School of Management, Shenyang Jianzhu University, Shenyang 110016, China.
Abstract:Aiming to solve the limitation of the evaluation method of traditional bus route service quality, a universal weight analysis method based on passengers perceptions is proposed. Firstly, a weight determination method is established based on passengers perceptions in order to determine the weight of experts and the comprehensive weight of each group. Secondly, the quality evaluation AHP-BP network model of urban bus route service can be acquired by training, testing and verifying with the above data as prior samples. Finally, an empirical study is launched on a certain bus route in Shenyang, and the results demonstrate that the model reflect passenger perceptions adequately as well as reduce the randomness of subjective evaluation which can provide an improved direction for a bus route service.
Keywords:improved AHP  BP neural network  analysis of influencing factors  passengers perceptions; bus route  
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