Education, Science, Technology, Innovation and Life
Open Access
Sign In

Risk Assessment of Agricultural Products Supply Chain Based on Combined Weighting of Level Difference Maximization

Download as PDF

DOI: 10.23977/agrfem.2022.050102 | Downloads: 3 | Views: 94

Author(s)

Dechuan Geng 1, Huixia Zhu 1, Shuliang Chen 1

Affiliation(s)

1 School of Economics and Management, Liaoning University of Technology, Jinzhou, Liaoning, 121001, China

Corresponding Author

Dechuan Geng

ABSTRACT

In the context of the prevalence of novel coronavirus epidemic, effective risk factor assessment of agricultural supply chain and further improvement of supply chain risk management are the key links to stabilize the development of agricultural supply chain. Based on this, taking the potential risk of agricultural product supply chain as the research object, the risk assessment index system of agricultural product supply chain is constructed, and the risk factors of agricultural product supply chain in Northeast China are evaluated by combining a variety of single weighting methods to improve the combination weighting method of level difference maximization. The results show that the combination weighting method of level difference maximization is more reasonable in weight distribution than the single weighting method. On the whole, production risk is the key field of agricultural product supply chain risk management. Among the secondary risk factors, agricultural products refrigeration security, supply and demand uncertainty and product processing quality risk factors are the main factors affecting the risk of agricultural products supply chain.

KEYWORDS

Agricultural product supply chain, Supply chain risk, Risk assessment, Level difference maximization, Combination weighting method

CITE THIS PAPER

Dechuan Geng, Huixia Zhu, Shuliang Chen, Risk Assessment of Agricultural Products Supply Chain Based on Combined Weighting of Level Difference Maximization. Agricultural & Forestry Economics and Management (2022) Vol. 5: 7-13. DOI: http://dx.doi.org/10.23977/agrfem.2022.050102.

REFERENCES

[1] Zhang, X.C. (2022) Study on Safety Risk and Coping Mechanism of Agricultural Products Supply Chain. Agricultural Economic Issues,2,97-107.
[2] Han, Y.Q., and Zhao, X.F. (2021) Research on the Impact of Agricultural Product Supply Chain Quality Integration on Financial Performance of Agricultural Enterprises. Commercial Economy and Management,12,5-18.
[3] Xu, P. (2018) Research on financial risk prevention of agricultural product supply chain based on structural equation model. Journal of Southwest University of Politics and Law,20(6),128-135.
[4] Li, Y.Y., and Liu, L.S. (2017) Research on Risk Assessment of Agricultural Products Supply Chain Based on ANP-Fuzzy Model. Mathematical Practice and Understanding, 47(13),24-32.
[5] Zhou, Y.F., and Luo, X. (2016) Risk identification and supervision of agricultural products supply chain — taking the poultry industry in Jiangxi Province as an example. East China economic management,30(11),33-37.
[6] Fan, X., Shao, J.P., and Sun, Yan Y.A. (2016) Risk Identification and Evaluation of Transnational Agricultural Products Supply Chain Based on Fuzzy Theory. Science and Technology Management Research,36(6),210-215.
[7] Zhang, L.Q., and Zhao, Z. (2021) Fresh agricultural products supply chain risk identification and prevention. Logistics engineering and management,43(2),52-55.
[8] Yu, P., Ma, H., and Zhou, F.L. (2019) The dynamic evaluation of regional carbon efficiency based on the combined weighted TOPSIS grey correlation projection method with maximum difference. Operation and management,28(12),170-177.
[9] Yu, P., Ma, H., and Dang, Y.G. (2019) The model and application of relative closeness degree of area grey correlation based on differential maximization. Statistics and decision-making,35(20),11-15.
[10] Chen, Y.C., Dai, J.Y., and Xie, D. (2020) Comprehensive evaluation of combined weighting cloud model for mine ventilation system. Systems engineering,38(6),35-42.

Downloads: 618
Visits: 31730

All published work is licensed under a Creative Commons Attribution 4.0 International License.

Copyright © 2016 - 2031 Clausius Scientific Press Inc. All Rights Reserved.