Abstract

Abstract In the era of the digital economy, there is a widespread trend for property enterprise economic management to undergo digital transformation. The article examines how the digital economy propels the economic management of property enterprises, scrutinizing its risk components and the digital ecological model of management services. The evaluation index system for the digital economy and the economic management level of property enterprises has been designed, and its comprehensive score is solved using the entropy weight method. Based on the comprehensive score, a spatial Durbin model was established, and spatial autocorrelation tests and econometric regression analyses were performed. Additionally, the risk prediction model for the economic management of property enterprises was established using BP neural networks and risk evaluation indexes. The global Moran’s mean values for the economic management of property enterprises in the digital economy were 0.267 and 0.081, respectively, and both passed the 1% significance test. The development level of the digital economy significantly promotes the economic management of property enterprises at the 1% level, as indicated by the influence coefficients obtained from the neighbor weight matrix, geographic weight matrix, and economic distance weight matrix, which are 2.236, 2.132, and 2.078, respectively. The BP neural network predicts economic management risk for property enterprises with an accuracy of 91.95%. Relying on digital economy-related technology can effectively promote the improvement of the economic management level of property enterprises and can also effectively enable risk prediction in economic management.

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.