The Ensuring of the Economic Security of Industrial Enterprises in the Context of Forming a Flexible Management Model: Prerequisites and Tools
- DOI
- 10.2991/aebmr.k.210826.017How to use a DOI?
- Keywords
- economic security, flexible management, neural network, model, tools, stakeholders
- Abstract
In the article the prerequisites for building a model of flexible enterprise management in order to ensure its economic security examines. It is determined that directive management methods, although they ensure the operative execution of tasks, in many cases do not contain a sufficient level of flexibility, and this does not allow the economic security system to function effectively. To build a model of flexible management it is propose to use intelligent data processing systems based on the construction and use of neural networks. The preconditions for the formation of the model and the main factors influencing on it are determined. The main groups of stakeholders that interested in developing a model of flexible management to ensure the economic security of the enterprise presented; their goals and expected results defined. It is substantiated that a probabilistic neural network is expedient to build in the Matlab environment, which ensures the efficiency and relevance of the obtained results.
- Copyright
- © 2021, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Larysa Liubokhynets AU - Yevhenii Rudnichenko AU - Nataliia Havlovska PY - 2021 DA - 2021/08/27 TI - The Ensuring of the Economic Security of Industrial Enterprises in the Context of Forming a Flexible Management Model: Prerequisites and Tools BT - Proceedings of the International Conference on Business, Accounting, Management, Banking, Economic Security and Legal Regulation Research (BAMBEL 2021) PB - Atlantis Press SP - 95 EP - 100 SN - 2352-5428 UR - https://doi.org/10.2991/aebmr.k.210826.017 DO - 10.2991/aebmr.k.210826.017 ID - Liubokhynets2021 ER -