Research On Automobile Service Quality Evaluation Based On Data Mining

With the increasing changes in information production methods and communication media under the background of "Industry 4.0" and the increasingly fierce competition in the international market,the car industry needs to increase product value by adding fine-grained service elements that can meet the needs of diversified customers,thereby achieving differentiated competition Advantage.However,in the service process,uncertain factors that the service does not eet customer requirements may appear,which affects the service quality of the enterprise.Therefore,a comprehensive and systematic identification of car service quality elements based on customer needs and scientific evaluation are problems to be solved urgently for car 4S stores.The purpose of this paper is to use data mining technology to explore the evaluation indicators of car service quality based on customer needs,and to find possible problems in car service by constructing an evaluation model,and to make targeted improvement suggestions to improve service quality and optimize service resource allocation.On the basis of sorting out the relevant theories and research status of service quality,firstly,on the basis of identifying customer service needs,adopt the "purpose-means" analysis method to identify five dimensions of car service quality elements that may meet customer service needs;secondly,According to the characteristics of service quality elements,combined with literature analysis method,expert interview method and questionnaire survey method,21 car service quality evaluation indicators that can quantify the results of service quality elements were discovered;the method of combining set value statistics and entropy weight method was adopted.Compared with previous studies,the innovations of this article are as follows:First,the three methods of data mining technology,co-word analysis,and hierarchical clustering are combined to build a customer service demand identification framework for the car industry,which is beneficial to the car 4S The store can systematically identify customer service demand information in a shorter time and at a lower cost,which overcomes the lack of a systematic theoretical framework and system defects of traditional research methods.Second,identify the elements of car service quality based on customer needs,and explore car service quality evaluation indicators based on customer needs,to make up for the problem that the previous service quality evaluation indicators cannot accurately connect with customer service needs.Third,the combination of text sentiment analysis technology and service quality management theory makes up for the insufficiency of traditional evaluation methods that are difficult to quantify customer perception and emotional experience;using PROMETHEE-Ⅱ can not only get the ranking of evaluation indicators,but also can be based on random dominance The matrix quantitatively indicates the degree of random dominance between the two evaluation indicators;at the same time,the random dominance criterion is introduced to make up for the problem of the uncertainty of the index value of this method.