The development of social economy and Internet information technology has made the development of the sharing economy relatively rapid. This article aims to study how to promote the sharing economy based on neural networks to play a role in new business models. This article proposes that the sharing economy and the new business model are inseparable. It also discusses how to analyze the relationship between the sharing economy and the new business model based on the BP neural network. With the development of the economy and society, new economic development models have developed, and the sharing economy model has risen. The sharing economy model has brought an impact to the traditional economic development model, affecting the business model. The results show that with the development of society and enterprises, the development of the sharing economy is getting faster and faster. Today, some sharing economy companies are bound to face various obstacles in the process of copying other business models and development. Sharing economy enterprises have made various adjustments and responses to various problems, but they have not found a better model to adapt to the modern social market and environment. Therefore, the business model of the sharing economy requires further analysis and investigation.

Enterprise is an indispensable factor of production in the country’s economic and social development, and the operation of the enterprise is indispensable. The development of strategic operation of the enterprise is facing many problems, and the survival of the enterprise is facing serious threats. The purpose of this article is to study the method of establishing a reliable enterprise strategic management system based on GPRS wireless communication and neural network. Let the company continue to grow in a sustainable and healthy way. This article puts forward the importance of corporate strategic management under GPRS wireless communication. Strategic business management can improve the foresight and initiative of enterprises, overcome short-term behaviour, and provide a clear direction for the development of the enterprise. In the experimental data of this article, it can be seen from 2016 that the demand for talent management by enterprises is lower than that in 2019. By 2019, enterprises will have the demand is as high as 85.3%, so enterprise management development needs should be taken seriously. The error between the actual output of the network and the expected output is controlled within 5%, which shows that the established neural network has a good evaluation effect and can be used to evaluate the talents of business operators. This also shows that the established BP neural network can fully absorb the judgment experience of experts and the actual employment of enterprises. The results show that the evaluation results obtained according to the evaluation network model have certain guiding significance for the selection and assessment of employers and the self-evaluation of management talents.