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<p>Agricultural products, as the necessities of people’s daily consumption, are related to the national economy and people’s livelihood, and the development of information technology provides a new direction and ideas for the transformation of agricultural products supply chain management. The article proposes the risk assessment method for the agricultural products supply chain based on the Bayesian network inference algorithm and OWA algorithm, firstly constructs the Bayesian network model for risk assessment of agricultural products supply chain, elaborates on the belief updating algorithm and the belief-free updating algorithm in the Bayesian network, then combines with the OWA operator, proposes the method of risk diagnosis of agricultural products supply chain based on the Bayes-OWA hybrid operator, and with this The algorithm is the core of the proposed agricultural supply chain management strategy. Through empirical tests, it can be obtained that the average supply time of enterprise 4 in agricultural products is 22.3 days, and the reliability of supply is 92.3%, which is highly efficient. In the agricultural products supply program, the average value of quality qualification rate has been improved by 2.67%, the average number of days for supplier delivery has been shortened by 13 days, and the supplier’s ability to respond quickly to demand has been improved by 3.61%. Therefore, actively constructing the informationization construction of the agricultural supply chain, building a logistics information platform, improving rural communication facilities, and providing timely market information to farmers can better ensure the efficient operation of the agricultural supply chain.</p>
</abstract>

Agricultural products, as the necessities of people’s daily consumption, are related to the national economy and people’s livelihood, and the development of information technology provides a new direction and ideas for the transformation of agricultural products supply chain management. The article proposes the risk assessment method for the agricultural products supply chain based on the Bayesian network inference algorithm and OWA algorithm, firstly constructs the Bayesian network model for risk assessment of agricultural products supply chain, elaborates on the belief updating algorithm and the belief-free updating algorithm in the Bayesian network, then combines with the OWA operator, proposes the method of risk diagnosis of agricultural products supply chain based on the Bayes-OWA hybrid operator, and with this The algorithm is the core of the proposed agricultural supply chain management strategy. Through empirical tests, it can be obtained that the average supply time of enterprise 4 in agricultural products is 22.3 days, and the reliability of supply is 92.3%, which is highly efficient. In the agricultural products supply program, the average value of quality qualification rate has been improved by 2.67%, the average number of days for supplier delivery has been shortened by 13 days, and the supplier’s ability to respond quickly to demand has been improved by 3.61%. Therefore, actively constructing the informationization construction of the agricultural supply chain, building a logistics information platform, improving rural communication facilities, and providing timely market information to farmers can better ensure the efficient operation of the agricultural supply chain.

Promoting the transformation of agricultural supply chain management under the development of digital economy in the Internet era

Guangxi Vocational and Technical College of Manufacturing Engineering

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

Agricultural products, as the necessities of people’s daily consumption, are related to the national economy and people’s livelihood, and the development of...

Promoting the transformation of agricultural supply chain management under the development of digital economy in the Internet era

Data publikacji: 09 lip 2024

Zakres stron: -

Otrzymano: 17 mar 2024

Przyjęty: 13 cze 2024

DOI: https://doi.org/10.2478/amns-2024-1809

Słowa kluczowe
Agricultural supply chain, Bayesian network, OWA operator, Risk assessment, Bayes-OWA hybrid operator

© 2024 Xueliang Wang et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Promoting the transformation of agricultural supply chain management under the development of digital economy in the Internet era

Data publikacji: 09 lip 2024

Zakres stron: -

Otrzymano: 17 mar 2024

Przyjęty: 13 cze 2024

DOI: https://doi.org/10.2478/amns-2024-1809

Słowa kluczoweAgricultural supply chain, Bayesian network, OWA operator, Risk assessment, Bayes-OWA hybrid operator

© 2024 Xueliang Wang et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Słowa kluczowe
Agricultural supply chain, Bayesian network, OWA operator, Risk assessment, Bayes-OWA hybrid operator