With the popularization of personal computers and the development of the Internet, the number of netizens is increasing. The emerging B2C e-commerce platform shows the fierce competition in the e-commerce market. B2C e-commerce distribution is faced with the problems of high distribution cost, long time, and poor quality, which leads to the poor user experience of B2C online shopping and the lack of trust in e-commerce enterprises. This research mainly discusses the user experience evaluation of B2C e-commerce websites based on fuzzy information. First, the AHP analytic hierarchy process is used to construct a hierarchical evaluation system, and then, the two-by-two judgment matrix is compared to the index factors at all levels, and experts are invited to score the method to determine the weight of each index to test whether it meets the consistency requirements. Finally, the fuzzy comprehensive evaluation method is used to perform fuzzy conversion of the original weight, and the membership degree set of the user experience evaluation factors is given, and the fuzzy comprehensive calculation result of the B2C website performance level is calculated. By combining in-depth interviews with website users and questionnaire surveys to analyze the behavioral characteristics of user information navigation, summarize the demand list for product search, product selection, product comparison, and product detail page browsing, and provide a reference for the design and development of information navigation. Calculating the decision model, mainly using fuzzy calculation, calculate the foreground value under each attribute and get the comprehensive foreground value. By comparing with the decision-making behavior model constructed by expected utility theory, it is found that the behavioral decision-making model constructed in this paper based on prospect theory can be closer to the actual situation. In this study, the satisfaction with the function provided reached 68 points, the emotional response 66 points, the aesthetic response 70 points, and the information construction 64 points. Through empirical research, the key factors affecting user satisfaction of B2C e-commerce logistics distribution are summarized, and a B2C e-commerce logistics distribution evaluation system based on user experience is established. This research will provide methods and ideas for the research on user experience design of e-commerce websites and the research and development of related network products. The article helps to draw out the countermeasures and suggestions for the development of the current B2C e-commerce logistics distribution.
Enterprises have established a number of business processing systems and business websites according to their own characteristics and business needs, such as e-commerce websites and shopping websites. Over time, a large number of sales transaction data and customer purchase information have been generated, but no useful information has been generated stored in the database. Therefore, the management and decision-making levels of enterprises try to get useful information from huge and complex data. With the development of network technology and database, data mining technology has emerged. Nowadays, data mining technology has become one of the most concerned technologies of e-commerce. It can select appropriate data mining methods according to the characteristics of commodities, carry out effective statistical analysis and decision support for data, predict and analyze future market trends, greatly improve the business intelligence analysis of e-commerce enterprises, and make enterprises have greater advantages in market competition. This paper explains some important methods related to data mining and designs a data mining system. One of the systems can help e-commerce decision-makers analyze and predict data. Through experiments, it is concluded that the average absolute percentage errors of prediction data are 8.6% and 5.3%, respectively, with small errors and high accuracy. Second, make better recommendations for users. After investigation and analysis, the highest satisfaction has increased by 25% after using the system.
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