Welcome to Francis Academic Press

Academic Journal of Business & Management, 2022, 4(11); doi: 10.25236/AJBM.2022.041118.

Enterprise Working Capital Management by BP Neural Network under the Background of the Internet

Author(s)

Zhiyuan Xiao, Luyao Han, Yihang Zhao

Corresponding Author:
Zhiyuan Xiao
Affiliation(s)

Management College, Ocean University of China, Qingdao, 266100, China

Abstract

Today, with the rapid development of the Internet, the way of enterprise development has become more and more diversified. The development of the Internet not only brings opportunities for enterprise development but also certain risks. In order to deal with the uncertain risks in the future development of the enterprise, aiming at the operation and capital management problems of the enterprise, this study creates a scientific and effective performance evaluation system that conforms to the law of enterprise development to guide the enterprise's capital management problems in the operation process. This system can enable enterprises to improve economic efficiency and achieve sound development in the context of the Internet economy. This study sorts out the relevant theories of enterprise capital management and performance evaluation and refers to the existing performance evaluation system by analyzing the influencing factors of enterprise operation performance. The key factors of performance evaluation in the process of enterprise operation are extracted and processed by dimensionless normalization of sample data. The Pearson correlation test is used to eliminate data indicators with high correlation, and a model of enterprise operation performance evaluation based on the Back Propagation Neural Network (BPNN) is constructed. Valid panel data of some companies in 2015-2016 are selected. The constructed BPNN model is verified for feasibility. The results show that the constructed BPNN model has wide applicability and can be an effective tool for enterprise operation performance evaluation.

Keywords

back propagation neural network; enterprise working capital management; operational performance evaluation; Internet

Cite This Paper

Zhiyuan Xiao, Luyao Han, Yihang Zhao. Enterprise Working Capital Management by BP Neural Network under the Background of the Internet. Academic Journal of Business & Management (2022) Vol. 4, Issue 11: 124-128. https://doi.org/10.25236/AJBM.2022.041118.

References

[1] N. Xu, Y. Ma and J. Wang, "A Fund Management Method for Ocean Shipping Companies Based on Cost Control Theory," Journal of Coastal Research, vol. 98, no. SI, pp. 30-33, 2019.

[2] L. Liu, "Enterprise green management on the optimisation of financial management system," International Journal of Technology, Policy and Management, vol. 22, no. 1-2, pp. 82-97, 2022.

[3] K. Boiarynova, K. Kopishynska and N. Hryhorska, "Economic and management approach to defining effective projects for enterprise development under risks and uncertainty," Problems and Perspectives in Management, vol. 17, no. 4, pp. 299-313, 2019.

[4] X. Song, "Implementation of Centralized Administration and Management of Funds in Enterprise Groups," Proceedings of Business and Economic Studies, vol. 4, no. 4, pp. 166-171, 2021.

[5] X. Islami, E. Mulolli and N. Mustafa, "Using Management by Objectives as a performance appraisal tool for employee satisfaction," Future Business Journal, vol. 4, no. 1, pp. 94-108, 2018.

[6] A. Bayo-Moriones, J. E. Galdon-Sanchez and S. Martinez-de-Morentin, "Performance appraisal: dimensions and determinants," The International Journal of Human Resource Management, vol. 31, no. 15, pp. 1984-2015, 2020.

[7] L. Chen, V. Jagota and A. Kumar, "Research on optimization of scientific research performance management based on BP neural network," International Journal of System Assurance Engineering and Management, pp. 1-10, 2021.

[8] Y. Al-Jedaia and A. Mehrez, "The effect of performance appraisal on job performance in governmental sector: The mediating role of motivation," Management Science Letters, vol. 10, no. 9, pp. 2077-2088, 2020.

[9] D. Zhang and S. Lou, "The application research of neural network and BP algorithm in stock price pattern classification and prediction," Future Generation Computer Systems, vol. 115, pp. 872-879, 2021.

[10] Z. Liu, G. Du, S. Zhou, H. Luand H. Ji, "Analysis of internet financial risks based on deep learning and BP neural network," Computational Economics, vol. 59, no. 4, pp. 1481-1499, 2022.

[11] W. Bo, F. Tianyu, L. Zhiyongand N. Xiangtian, "Research and analysis on the coordination mechanism of financial innovation and economic growth based on BP neural network," Journal of Intelligent & Fuzzy Systems, vol. 37, no. 5, pp. 6177-6189, 2019.