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Ȩ Ȩ > ¿¬±¸¹®Çå > ¿µ¹® ³í¹®Áö > JIPS (Çѱ¹Á¤º¸Ã³¸®ÇÐȸ)

JIPS (Çѱ¹Á¤º¸Ã³¸®ÇÐȸ)

Current Result Document : 8 / 143 ÀÌÀü°Ç ÀÌÀü°Ç   ´ÙÀ½°Ç ´ÙÀ½°Ç

ÇѱÛÁ¦¸ñ(Korean Title) Models and Methods for the Evaluation of Automobile Manufacturing Supply Chain Coordination Degree Based on Collaborative Entropy
¿µ¹®Á¦¸ñ(English Title) Models and Methods for the Evaluation of Automobile Manufacturing Supply Chain Coordination Degree Based on Collaborative Entropy
ÀúÀÚ(Author) SungChul Byun   Seong-Soo Han   Chang-Sung Jeong   Qiang Xiao   Hongshuang Wang  
¿ø¹®¼ö·Ïó(Citation) VOL 18 NO. 02 PP. 0208 ~ 0222 (2022. 04)
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(Korean Abstract)
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(English Abstract)
Through the analysis of the coordination mechanism of the supply chain system of China¡¯s automobile manufacturing industry, the factors affecting the supply subsystem, the manufacturing subsystem, the sales subsystem, and the consumption subsystem are sorted out, the supply chain coordination index system based on the influence factor of four subsystems is established. The evaluation models of the coordination degree in the subsystem of the supply chain, the coordination degree among the subsystems, and the comprehensive coordination degree are established by using the efficiency coefficient method and the collaborative entropy method. Experimental results verify the accuracy of the evaluation model using the empirical analysis of the collaborative evaluation index data of China¡¯s automobile manufacturing industry from 2000 to 2019. The supply chain synergy of automobile manufacturing industry was low from 2001 to 2005, and it increased to a certain extent from 2006 to 2008 with a small growth rate from 0.10 to 0.15. From 2009 to 2013, the supply chain synergy of automobile manufacturing industry increased rapidly from 0.24 to 0.49, and it also increased rapidly but fluctuated from 2014 to 2019, first rising from 0.68 to 0.84 then dropping to 0.71. These results provide reference for the development of China¡¯s automobile manufacturing supply chain system and scientific decision-making basis for the formulation of relevant policies of the automobile manufacturing industry.
Å°¿öµå(Keyword) Captured Image   CNN   Deep Learning Dataset   Image Classification   Object Detection   Widget   Coefficient Method   Collaborative Entropy   Evaluation models   Supply Chain Coordination Degree  
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