A Study Of Trilateral Matching Decision For Downward Product Quality Improvement In C2M Model

In recent years,with the improvement of people’s income level,consumers’requirements for quality of life have also been rising,and consumer demand has become increasingly high;Behind the upgrading of consumption,market segmentation is becoming increasingly evident,and personalization and diversification have become important trends in consumption growth.The C2M model is a new e-commerce model that enables reverse customization of products from consumers to manufacturers through the connection of e-commerce platforms.Although the C2M model can achieve direct information exchange between consumers and producers,at this stage,the cooperative relationship between the three parties is relatively loose,and the efficiency of information exchange is relatively low.Therefore,it is not possible to stably take consumer needs as the starting point for quality improvement,and continuously transmit their after-sales feedback on products to the quality improvement process,thereby improving customer loyalty.Moreover,as decision-making models become increasingly complex,there are complexities and limitations in the subject’s cognition and experience,so the preference information given by the subject is often fuzzy and descriptive feedback,rather than accurate quantitative information.In a complex decision-making environment,in order to improve the stable information exchange speed of trilateral agents in the C2M model and quickly respond to customer needs,this paper uses probabilistic language terminology sets as.the representation form of preference data,and trilateral matching decision models as the solution to the problem.Firstly,using the literature analysis method and selecting influencing factor indicators based on the economic and social benefits of the three parties;In order to simplify the decision-making complexity of trilateral matching and obtain the key indicator factors of the three parties,a DEMATEL factor analysis method based on probabilistic language distance measure was proposed,and the weights of the corresponding indicators were obtained to form the final evaluation indicator system;Secondly,according to the completeness of the information obtained by the decisionmaker,two trilateral matching decision models based on probabilistic language are proposed to solve the problem that the unstable information exchange environment hinders the continuous quality improvement of products in C2M mode.Under the condition that the preference information of the subject in the trilateral matching is complete,a trilateral matching decision model based on cloud model probabilistic language is constructed to solve the trilateral bidirectional circular matching problem for product quality improvement under the C2M mode;In the case of incomplete preference information for trilateral agents,a probabilistic language trilateral matching model based on the PA operator is constructed to solve the trilateral one-way acyclic problem in C2M mode.Finally,a C2M model based household appliance industry is selected as the research object for example analysis to verify the scientific validity of the model.The research conclusions and achievements of this paper not only expand the research paradigm of management decision-making models driven by objective data,but also enrich the relevant theoretical research on product quality improvement under the C2M model;On the other hand,it also has certain guiding value and practical significance in establishing an implementation environment for product quality improvement centered on consumer needs and management strategies to enhance consumer loyalty to manufacturing enterprises in complex decision-making environments.