Issue |
E3S Web Conf.
Volume 460, 2023
International Scientific Conference on Biotechnology and Food Technology (BFT-2023)
|
|
---|---|---|
Article Number | 04002 | |
Number of page(s) | 11 | |
Section | IoT, Big Data and AI in Food Industry | |
DOI | https://doi.org/10.1051/e3sconf/202346004002 | |
Published online | 11 December 2023 |
The risk analysis strategy of the uncertainty in the transport sector
1 Don State Technical University, 1, Gagarin square, Rostov-on-Don, 344000, Russia
2 Rostov State Transport University, 2, Rostovskogo Strelkovogo Polka Narodnogo Opolcheniya sq., Rostov-on-Don, 344038, Russia
* Corresponding author: sobolevao@yandex.ru
The limitedness of the available resources in transport companies determines the necessity of rationally using their potential. To formulate a development strategy, management, participants and shareholders of business units are to use strategic analysis to assess the risks and uncertainties inherent in transport companies. The risk analysis strategy provides to formulate the best development model in the field of possible alternatives using the business goals and objectives, and implement a list of appropriate activities. The key management human resources are interested in choosing a strategic position of the company that is acceptable for its functioning in the current and strategic perspective. The risk management forms such strategic foundation and decisions of participants and shareholders. This paper proposes the use of the strategic analysis concept in the transport sector companies. The developed concept is based on the principles of forming a company's strategy in the context of a risk factor and using a model for the implementation of long-term plans. The circular process of the strategic risk analysis under conditions of uncertainty must reduce the divide between desired goals and obtained results. The strategy considers requests of the transport sector companies in operating uncertainty process.
© The Authors, published by EDP Sciences, 2023
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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