With the increasing global concern for environmental protection and sustainable resource utilization, companies are facing unprecedented challenges. At the same time, consumers’ environmental protection awareness is increasing, which puts forward higher requirements for corporate social responsibility. The study establishes the evaluation index system of enterprise economic sustainable development based on the principle of evaluation index construction. The evaluation indexes are screened by principal component analysis, in which the cumulative contribution rate of total assets contribution, cost and expense profitability, product sales rate, and total capital preservation and value-added rate to the evaluation of enterprise economic sustainable development reaches 95.6%. Aiming at the problems of RBF neural network, the principal component analysis algorithm is introduced, and the genetic algorithm is used to optimize and construct the combined prediction model PCA-GARBF, and through the algorithm comparison, it can be seen that this method is able to effectively evaluate the sustainable development of the enterprise’s economy, with high accuracy and real-time performance. Combined with the fuzzy set qualitative analysis method for analysis, the results show that there are four types of modes to improve the performance of enterprise sustainable development, based on which the digital management path of the enterprise is proposed to provide reference for the development path of the enterprise.
