基于云理论的公路客运服务旅客满意度测评研究

发布时间：2018-01-20 14:45

本文关键词： 旅客满意度公路客运服务云理论大数据云计算升维攻击　出处：《长安大学》2015年硕士论文　论文类型：学位论文

【摘要】：随着市场经济的发展,高速铁路迎来了跨越式发展,同为陆上旅客运输的公路客运因而受到了一定程度的影响。公路旅客运输业作为我国传统服务业,在日趋竞争激烈的客运市场,应尽快通过改进自身服务质量来提高旅客满意度,从而保证在与其他运输方式的的竞争中保持优势。如何及时了解旅客的感受和需求,找出公路客运服务中存在的不足,从而提高旅客满意度,增加公路客运企业综合竞争力,建立一套系统、可行、科学的公路客运服务旅客满意度测评模型尤为重要。本文在分析现有满意度测评模型基础上,提出了基于云理论的公路客运服务旅客满意度测评方法。首先对相关理论进行研究。通过对公路客运服务理论的研究,明确了公路客运构成要素,即:公路、客运站、客车、经营主体、顾客、运管部门;以及公路客运服务内涵及特性。而后,在介绍满意度理论相关研究情况的基础上,通过对现有满意度测评模型进行对比分析,考虑到现有模型在定性指标定量表示方面存在不足,同时根据“升维攻击”思想提出了基于云理论的公路客运服务满意度测评模型。其次根据公路客运服务理论初步构建了公路客运服务满意度测评体系,为使得最终测评结果更加科学、准确,对初步构建的满意度测评体系利用SPSS进行因子分析来进行指标筛选,对筛选后的测评体系进行信度检验,检验结果显示满意度测评体系总体信度α=0.837,符合信度要求。进而根据云理论相关概念构建了公路客运服务满意度测评模型。首先根据云理论中虚拟概念树这一理论对满意度测评体系进行云模型转化;其次将满意度分为5个等级并根据云的黄金分割法则确定满意度云族(5个等级满意度云)的数字特征;而后对调查获得的旅客满意度调查数据进行数据处理使其具有大数据特点,从而获得各二级评价指标云族的最终数字特征,其所用模型主要为云双向认知模型及云更新模型,在级评价指标权重确定方面采用基于云理论的主客观权重确定法,在权重确定后根据云合成理论确定一级指标及总体的满意度云数字特征,最后通过正向云发生器生成满意度云族图和各待评价指标云族图,通过比对二维云图间相似度得出公路客运服务最终满意度测评结果。最后以杭州至缙云班线为例验证了模型的可行性,测评结果显示该条班线满意度最终得分为61.969分,旅客满意度等级为满意。
[Abstract]:With the development of the market economy, the high-speed railway has ushered in the leap-forward development, and the road passenger transport, which is also the overland passenger transport, has been affected to a certain extent. The highway passenger transport industry is the traditional service industry of our country. In the increasingly competitive passenger transport market, we should improve their service quality as soon as possible to improve passenger satisfaction. In order to ensure that the competition with other modes of transport to maintain the advantage. How to understand the feelings and needs of passengers in time to find out the shortcomings of road passenger transport services to improve passenger satisfaction. It is very important to increase the comprehensive competitiveness of highway passenger transport enterprises and establish a set of system, feasible and scientific passenger satisfaction evaluation model. This paper analyzes the existing satisfaction evaluation model. This paper puts forward the evaluation method of passenger satisfaction of highway passenger transport service based on cloud theory. Firstly, this paper studies the relevant theories. Through the research on the theory of highway passenger transport service, it clarifies the constituent elements of highway passenger transport, that is, highway. Passenger station, bus, main business, customer, transportation management department; And the connotation and characteristics of highway passenger transport service. Then, on the basis of introducing the relevant research of satisfaction degree theory, through the existing satisfaction evaluation model to carry on the comparative analysis. Considering the shortcomings of the existing models in the quantitative representation of qualitative indicators. At the same time, according to the idea of "ascending dimension attack", the paper puts forward the evaluation model of highway passenger service satisfaction based on cloud theory. Secondly, it constructs the evaluation system of highway passenger transport service satisfaction according to the theory of highway passenger transport service. In order to make the final evaluation results more scientific and accurate, the initially constructed satisfaction evaluation system is screened by factor analysis using SPSS, and the reliability of the selected evaluation system is tested. The results showed that the overall reliability of the satisfaction evaluation system was 0.837. According to the cloud theory related concepts, the evaluation model of satisfaction degree of highway passenger transport service is constructed. Firstly, the cloud model of satisfaction evaluation system is transformed according to the theory of virtual concept tree in cloud theory. Secondly, the satisfaction degree is divided into five grades and the numerical characteristics of the satisfaction cloud family (five grade satisfaction clouds) are determined according to the golden rule of cloud segmentation. Then the passenger satisfaction survey data obtained by the survey data processing to make it have big data characteristics, so as to obtain the final numerical characteristics of each secondary evaluation index cloud. The models used are mainly cloud bidirectional cognitive model and cloud update model. The subjective and objective weight determination method based on cloud theory is used to determine the weight of index. After the weight is determined, the first level index and the total satisfaction cloud number characteristics are determined according to the cloud composition theory. Finally, the satisfaction cloud family map and each index cloud family map are generated by the forward cloud generator. By comparing the similarity between two-dimensional cloud maps to get the final satisfaction evaluation results of road passenger service. Finally, the feasibility of the model is verified by taking Hangzhou to Jinyun as an example. The result showed that the final score of satisfaction was 61.969, and the passenger satisfaction was satisfactory.
【学位授予单位】：长安大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：U492.4

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