TY - GEN
T1 - Evaluation of Enterprise Green and Digital-Intelligent Development via Coupling Index System
AU - Huang, Taihang
AU - Mi, Zhilong
AU - He, Qingcai
AU - Guo, Binghui
AU - Li, Mao
AU - Gao, Xiaonan
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.
PY - 2025
Y1 - 2025
N2 - In the context of the strategic drive for Digital China and green development, modern supply chains are undergoing significant transformations, moving away from traditional paradigms towards green and digital-intelligent frameworks. The current green and digital-intelligent evaluation models of supply chains face significant challenges of inadequate coupling and coordination among multi-dimensional indicators and strong subjectivity. The establishment of an adaptive evaluation model for green and digital-intelligent progress is of paramount importance for enterprises and supply chains alike, as it enables the optimization of resource allocation and business processes. Thus, we have devised an integrated index system comprising core and distinctive indicators, and employed long-term multi-dimensional supply chain data to construct a development evaluation model utilizing the CRITIC-G1 method and Bonferroni mean operator. The empirical analysis of three cable suppliers demonstrate that the evaluation results are consistent with their developmental patterns and characteristics, thereby confirming the comprehensive practicality of the index system and the scientific validity of the evaluation model. This coupling coordinative evaluation framework offers a quantitative basis for the refinement of enterprise development strategies and the delineation of pathways for the enhancement of supply chain quality and efficiency.
AB - In the context of the strategic drive for Digital China and green development, modern supply chains are undergoing significant transformations, moving away from traditional paradigms towards green and digital-intelligent frameworks. The current green and digital-intelligent evaluation models of supply chains face significant challenges of inadequate coupling and coordination among multi-dimensional indicators and strong subjectivity. The establishment of an adaptive evaluation model for green and digital-intelligent progress is of paramount importance for enterprises and supply chains alike, as it enables the optimization of resource allocation and business processes. Thus, we have devised an integrated index system comprising core and distinctive indicators, and employed long-term multi-dimensional supply chain data to construct a development evaluation model utilizing the CRITIC-G1 method and Bonferroni mean operator. The empirical analysis of three cable suppliers demonstrate that the evaluation results are consistent with their developmental patterns and characteristics, thereby confirming the comprehensive practicality of the index system and the scientific validity of the evaluation model. This coupling coordinative evaluation framework offers a quantitative basis for the refinement of enterprise development strategies and the delineation of pathways for the enhancement of supply chain quality and efficiency.
KW - Bonferroni Mean Operator
KW - CRITIC-G1 Method
KW - Coupling Index System
KW - Development Evaluation Model
KW - Green and Digital-Intelligent Supply Chain
UR - https://www.scopus.com/pages/publications/105003856755
U2 - 10.1007/978-981-96-4059-1_34
DO - 10.1007/978-981-96-4059-1_34
M3 - 会议稿件
AN - SCOPUS:105003856755
SN - 9789819640584
T3 - Lecture Notes in Electrical Engineering
SP - 368
EP - 377
BT - Proceedings of the 1st Electrical Artificial Intelligence Conference, EAIC 2024
A2 - Qu, Ronghai
A2 - Song, Zhengxiang
A2 - Ding, Zhiming
A2 - Mu, Gang
A2 - Xiong, Rui
A2 - Han, Li
PB - Springer Science and Business Media Deutschland GmbH
T2 - 1st Electrical Artificial Intelligence Conference, EAIC 2024
Y2 - 6 December 2024 through 8 December 2024
ER -