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

Research on Performance Evaluation of Green Supply Chain of Agricultural Products Based on G1-Entropy Weight Method

Download as PDF

DOI: 10.23977/agrfem.2022.050103 | Downloads: 3 | Views: 76

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

With the continuous improvement of consumers' demand for green quality of products, it is necessary to strengthen the green supply chain management of agricultural products to reduce the useless consumption of resources and environmental pollution losses. Taking the green supply chain of agricultural products as the research object, this study constructs the performance evaluation index system from five aspects: financial performance, innovation performance, supply chain operation performance, green performance and social performance. Then based on the G1 and entropy weight method, the combination weighting performance evaluation with the minimum sum of squares deviation is used. The empirical research shows that supply chain operation performance factor and green performance factor play a leading role in the performance evaluation framework of agricultural green supply chain. In terms of decomposition, it is necessary to focus on the brand size, inventory capacity, response time, environmental reputation and resource utilization efficiency of agricultural products. It also proves that this method is feasible.

KEYWORDS

Agricultural products, Green supply chain, Performance evaluation, G1-Entropy weight method, Index system

CITE THIS PAPER

Dechuan Geng, Huixia Zhu, Shuliang Chen, Research on Performance Evaluation of Green Supply Chain of Agricultural Products Based on G1-Entropy Weight Method. Agricultural & Forestry Economics and Management (2022) Vol. 5: 14-21. DOI: http://dx.doi.org/10.23977/agrfem.2022.050103.

REFERENCES

[1] He, L., and Zou, J. (2022) Analysis on Influencing Factors of Supply Chain Performance of Fresh Agricultural Products in Sichuan Province. Economist,1,152-154.
[2] Han, Y.F., Li, S., Sun, Y., and Zheng, S.Y. (2021) Performance Evaluation of Agricultural Products Supply Chain Based on Factor Analysis-Taking Jiangsu Province as an Example. Journal of Shijiazhuang Railway University (Social Science Edition),15(2),6-12.
[3] He, L., and Long, N.F. (2021) Performance Evaluation of Fresh Agricultural Products Supply Chain. Economic Research Guide,9,19-21.
[4] Zheng, X.D. (2021) Performance Evaluation of Green Supply Chain Management in Agricultural Products Enterprises. Modern Marketing (Business Edition),6,121-122.
[5] Wang, K.X., and Yang, Y.Z. (2020) Grey Clustering-Fuzzy Comprehensive Model and Its Application on Performance Evaluation of Green Agricultural Products Supply Chain. Practice and Understanding of Mathematics,50(2),111-119.
[6] Chen, X.Q., Zhao, L.H., Shen C.F., and Liu, G.H. (2018) Research on the Construction of Performance Evaluation Index System of Agricultural Products Green Supply Chain in Hebei Province. Journal of Xingtai Vocational and Technical College,35(6),78-81.
[7] Cao, B.R., and Fan, Y.Q. (2017) Performance Evaluation of Green Agricultural Products Supply Chain Based on DEA and Principal Component Analysis. Science and Technology Management Research,37(6),72-77.
[8] Zhou, Y., Yin, L., and Jia, Y.L. (2016) Performance Evaluation of Agricultural Products Cold Chain Logistics Enterprises Based on Green Supply Chain. Commercial Economic Research,16,102 - 103.
[9] Li, Y.T., and Qiao, Z. (2016) Research on the process and technology of collaborative disposal in the late stage of green supply chain security emergencies of agricultural products. Value engineering,35(28),242-244.
[10] Pan, Y., Liu, Y., Huang, Z.X., Hu, X.H., and Donald, M. (2022) The evaluation model of community residents ' safety literacy based on G1 method and entropy weight method. Security,43(1),59-64.

Downloads: 618
Visits: 31735

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

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