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Exploring the Application and Optimization Strategy of the LMBP Algorithm in Supply Chain Performance Evaluation
In recent years, with the emergence of new technologies, big data, artificial intelligence, and other technologies have had a greater impact on supply chain management. Among them, big data analysis capability, as one of the important capabilities that supply chain enterprises should have, has a par...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Hindawi
2022
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9427211/ https://www.ncbi.nlm.nih.gov/pubmed/36052047 http://dx.doi.org/10.1155/2022/7977335 |
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author | Gu, Fei |
author_facet | Gu, Fei |
author_sort | Gu, Fei |
collection | PubMed |
description | In recent years, with the emergence of new technologies, big data, artificial intelligence, and other technologies have had a greater impact on supply chain management. Among them, big data analysis capability, as one of the important capabilities that supply chain enterprises should have, has a particularly significant impact on supply chain resilience management. From the perspective of performance management, based on supply chain resilience theory, the relationship between the supply chain performance management level, supply chain collaboration, and other supply chain resilience elements, as well as big data analysis capability and supply chain performance can be analyzed to study the impact of big data analysis capability on supply chain performance of enterprises of different scales. The impact on the level of supply chain performance is being studied. This paper investigates the problem of supply chain performance evaluation and optimization based on the LMBP algorithm and provides some references for supply chain performance evaluation and optimization. |
format | Online Article Text |
id | pubmed-9427211 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-94272112022-08-31 Exploring the Application and Optimization Strategy of the LMBP Algorithm in Supply Chain Performance Evaluation Gu, Fei Comput Intell Neurosci Research Article In recent years, with the emergence of new technologies, big data, artificial intelligence, and other technologies have had a greater impact on supply chain management. Among them, big data analysis capability, as one of the important capabilities that supply chain enterprises should have, has a particularly significant impact on supply chain resilience management. From the perspective of performance management, based on supply chain resilience theory, the relationship between the supply chain performance management level, supply chain collaboration, and other supply chain resilience elements, as well as big data analysis capability and supply chain performance can be analyzed to study the impact of big data analysis capability on supply chain performance of enterprises of different scales. The impact on the level of supply chain performance is being studied. This paper investigates the problem of supply chain performance evaluation and optimization based on the LMBP algorithm and provides some references for supply chain performance evaluation and optimization. Hindawi 2022-08-23 /pmc/articles/PMC9427211/ /pubmed/36052047 http://dx.doi.org/10.1155/2022/7977335 Text en Copyright © 2022 Fei Gu. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Gu, Fei Exploring the Application and Optimization Strategy of the LMBP Algorithm in Supply Chain Performance Evaluation |
title | Exploring the Application and Optimization Strategy of the LMBP Algorithm in Supply Chain Performance Evaluation |
title_full | Exploring the Application and Optimization Strategy of the LMBP Algorithm in Supply Chain Performance Evaluation |
title_fullStr | Exploring the Application and Optimization Strategy of the LMBP Algorithm in Supply Chain Performance Evaluation |
title_full_unstemmed | Exploring the Application and Optimization Strategy of the LMBP Algorithm in Supply Chain Performance Evaluation |
title_short | Exploring the Application and Optimization Strategy of the LMBP Algorithm in Supply Chain Performance Evaluation |
title_sort | exploring the application and optimization strategy of the lmbp algorithm in supply chain performance evaluation |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9427211/ https://www.ncbi.nlm.nih.gov/pubmed/36052047 http://dx.doi.org/10.1155/2022/7977335 |
work_keys_str_mv | AT gufei exploringtheapplicationandoptimizationstrategyofthelmbpalgorithminsupplychainperformanceevaluation |