The e-commerce industry has broken through the original geographical restrictions, successfully integrated with world trade, and evolved new e-commerce model. The e-commerce model, that is, e-commerce transactions across international trade, has been rapidly expanded. However, e-commerce transactions across international trade have innate virtuality and information imbalance. These problems have caused many credibility problems and, at the same time, restrict and hinder the healthy and sustainable evolution of transactions across international trade. Credit evaluation of transaction entities through credit evaluation models is an effective way to restrict the behavior of transaction entities. However, the existing credit evaluation models lack pertinence and effectiveness when applied in the context of cross-border e-commerce. In the era of 5G communication, building a complete credit evaluation system through 5G-related technologies will certainly become a new way for the stable evolution of transactions across international trade. This not only can effectively control the risks of cross-border trade and improve efficiency but also properly resolve the uncertainty caused by information imbalance. In order to better promote the development of e-commerce, this article establishes an e-business evaluation module based on integrated fusion performance rating. The weight and the membership of each factor are determined by AHP. Finally, the model was verified by an example. The results show that the evaluation system and the method proposed in this paper are feasible and effective for solving practical problems and provide a solid foundation for the construction of the network of my country’s e-commerce credit rating system. Establishing a scientific and reasonable e-commerce integrity evaluation system has very good practical significance.

Modularization has been a research hotspot in recent years. Among these, there are two issues that many scholars pay attention to. First, we must know what factors cause modularization, and secondly, what impact modularization has brought to enterprises. The era of information technology background makes enterprises have to deal with more and more complex information. The integration and application of internal knowledge resources also force enterprises to adjust their structure, so that knowledge can spread and create value within the enterprise more effectively. This paper, based on artificial intelligence and modular enterprise big data, constructs a matching model of corporate strategy and performance management mode, determines four different matching methods based on corporate strategy and performance management mode, and puts forward corresponding assumptions. This article selects the participants of EMBA and MBA courses offered by several universities as the survey subjects. Most of them are enterprise managers, have many years of management practical experience, have a good understanding of the basic situation of the enterprise, and can truly understand the scale and make a choice based on the actual content. In this paper, a strategic management model based on artificial intelligence and modular enterprise big data construction proves that paired sample T test can be found, the data analysis is based on the various indicator scores of the enterprise modularity level, and the resulting P value is less than 0.05 as a significant difference, which proves that these two indicators are too quantitative. The company has not done relevant statistics, so it is difficult to make a practical answer. Through comparison and analysis, it is more likely to find the gap between the company’s financial strategy and its competitors, and then it is possible to make targeted improvements and upgrades.

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