Coal Industrial Supply Chain Network and Associated Evaluation Models

Ge He, Li Zhou, Yiyang Dai, Yagu Dang and Xu Ji
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Ge He: School of Chemical Engineering, Sichuan University, Chengdu 610065, China
Li Zhou: School of Chemical Engineering, Sichuan University, Chengdu 610065, China
Yiyang Dai: School of Chemical Engineering, Sichuan University, Chengdu 610065, China
Yagu Dang: School of Chemical Engineering, Sichuan University, Chengdu 610065, China
Xu Ji: School of Chemical Engineering, Sichuan University, Chengdu 610065, China

Sustainability, 2020, vol. 12, issue 23, 1-20

Abstract: To improve integration and achieve better coal industry materials and energy balance, integrated collaborative supply chains (SCs) are needed. However, as single-core SC models are not suitable for complex coal industry systems, a multicore, correlated, conditional SC model, called a supply chain network (SCN), is proposed. SCN collaborative evaluation models are discussed including industrial metabolic balance (IMB), enterprise profitability, contract execution ability and information interaction ability, for which IMB is used as the efficiency index of resource coordination of SCN, also as the constraints of the models on system levels. Further, data modeling by using BP-ANN algorithm is used to predict the profitability of supply chain network. Finally, the feasibility of the above models is illustrated by cases. The proposed evaluation models in this paper form the scientific and quantitative evaluation method of SC, which could be used for both SC planning and operations management helping detect and eliminate risks.

Keywords: supply chain network; coal industry; grey relational analysis; neural networks; industrial metabolism balance; collaboration (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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