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Incentive strategy of safe and intelligent production in assembled steel plants from the perspective of evolutionary game

Due to the numerous cross-operations and poor information communication, it is easy to cause production safety accidents in traditional assembled steel plants. The transformation and upgrading of smart production in the assembly steel plants is helpful to improve the efficiency of safety management....

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Autores principales: Wang, Yinglin, Chen, Leqi, Li, Yulong, Chen, Caiquan, Zhuang, Jiaxin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9899261/
https://www.ncbi.nlm.nih.gov/pubmed/36739449
http://dx.doi.org/10.1038/s41598-023-29097-8
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author Wang, Yinglin
Chen, Leqi
Li, Yulong
Chen, Caiquan
Zhuang, Jiaxin
author_facet Wang, Yinglin
Chen, Leqi
Li, Yulong
Chen, Caiquan
Zhuang, Jiaxin
author_sort Wang, Yinglin
collection PubMed
description Due to the numerous cross-operations and poor information communication, it is easy to cause production safety accidents in traditional assembled steel plants. The transformation and upgrading of smart production in the assembly steel plants is helpful to improve the efficiency of safety management. In order to effectively reduce the safety risks in the production of assembled steel components, this paper integrates policy incentives and safety supervision, constructs an evolutionary game model between the government and assembled steel producers, and analyzes the strategic evolution rules and stability conditions of stakeholders through the replication dynamics equation. Moreover, based on the empirical simulation of the Fuzhou X Steel Structure Plant project, the effectiveness of the evolutionary model incentive strategy setting is verified. The results show that whether an assembled steel plants adopt a smart management strategy or not is influenced by the government's incentive subsidy mechanism, penalty mechanism, the benefits and costs generated by traditional/ smart management, the probability and loss of safety accidents and other factors. The conclusion is important for upgrading the safety management mode, improving the safety production efficiency and constructing the safety supervision system of the assembled steel smart plant.
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spelling pubmed-98992612023-02-06 Incentive strategy of safe and intelligent production in assembled steel plants from the perspective of evolutionary game Wang, Yinglin Chen, Leqi Li, Yulong Chen, Caiquan Zhuang, Jiaxin Sci Rep Article Due to the numerous cross-operations and poor information communication, it is easy to cause production safety accidents in traditional assembled steel plants. The transformation and upgrading of smart production in the assembly steel plants is helpful to improve the efficiency of safety management. In order to effectively reduce the safety risks in the production of assembled steel components, this paper integrates policy incentives and safety supervision, constructs an evolutionary game model between the government and assembled steel producers, and analyzes the strategic evolution rules and stability conditions of stakeholders through the replication dynamics equation. Moreover, based on the empirical simulation of the Fuzhou X Steel Structure Plant project, the effectiveness of the evolutionary model incentive strategy setting is verified. The results show that whether an assembled steel plants adopt a smart management strategy or not is influenced by the government's incentive subsidy mechanism, penalty mechanism, the benefits and costs generated by traditional/ smart management, the probability and loss of safety accidents and other factors. The conclusion is important for upgrading the safety management mode, improving the safety production efficiency and constructing the safety supervision system of the assembled steel smart plant. Nature Publishing Group UK 2023-02-04 /pmc/articles/PMC9899261/ /pubmed/36739449 http://dx.doi.org/10.1038/s41598-023-29097-8 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Wang, Yinglin
Chen, Leqi
Li, Yulong
Chen, Caiquan
Zhuang, Jiaxin
Incentive strategy of safe and intelligent production in assembled steel plants from the perspective of evolutionary game
title Incentive strategy of safe and intelligent production in assembled steel plants from the perspective of evolutionary game
title_full Incentive strategy of safe and intelligent production in assembled steel plants from the perspective of evolutionary game
title_fullStr Incentive strategy of safe and intelligent production in assembled steel plants from the perspective of evolutionary game
title_full_unstemmed Incentive strategy of safe and intelligent production in assembled steel plants from the perspective of evolutionary game
title_short Incentive strategy of safe and intelligent production in assembled steel plants from the perspective of evolutionary game
title_sort incentive strategy of safe and intelligent production in assembled steel plants from the perspective of evolutionary game
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9899261/
https://www.ncbi.nlm.nih.gov/pubmed/36739449
http://dx.doi.org/10.1038/s41598-023-29097-8
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