Evaluation of Node Importance in Collaborative Network of Traditional Manufacturing Enterprises Based on Multiple Attribute Decision Making

Tao Yang; Yihuan Ding; Fang Jiang

doi:10.31181/dmame7220241018

Authors

Tao Yang School of Business Administration, Chongqing Technology and Business University, Chongqing 400067, China; School of Economics and Management, University of Electronic Science and Technology of China, Chengdu 611731, China https://orcid.org/0009-0001-3650-007X
Yihuan Ding School of Business Administration, Chongqing Technology and Business University, Chongqing 400067, China https://orcid.org/0009-0007-9845-5255
Fang Jiang School of Business Administration, Chongqing Technology and Business University, Chongqing 400067, China https://orcid.org/0009-0001-8070-5312

DOI:

https://doi.org/10.31181/dmame7220241018

Keywords:

Traditional manufacturing enterprises, Multiple attribute decision making, Collaborative networks, Complex networks, Coefficient of variation method, TOPSIS

Abstract

The construction and operation of collaborative production networks based on multi-subject collaboration is an important path and means for enterprises to adapt to personalized, diversified, and differentiated market demand. It is of great practical significance to identify the key collaborative subjects in the collaborative network and protect and maintain them to ensure its normal operation. To identify the key collaborative subjects in the collaborative network of traditional manufacturing enterprises, this paper proposes a method for identifying and evaluating the importance of nodes in traditional manufacturing enterprise collaborative networks. Firstly, the method uses four parameters, degree centrality, betweenness centrality, closeness centrality, and subgraph centrality, as node importance evaluation indexes, based on complex network theory. Secondly, the coefficient of variation method (CVM) is used to calculate the weights of evaluation indexes. The Multiple Attribute Decision Making (MADM) based on the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) is then used to comprehensively evaluate node importance and identify key nodes (key collaborative subjects) in the network. Finally, the proposed method's effectiveness, rationality, and scientific nature are verified by using the measurement index of network connectivity in combination with specific enterprise cases. The results show that the failure of key nodes has a more significant impact on network connectivity. Therefore, the node importance evaluation method based on Multiple Attribute Decision Making has better performance. It helps traditional manufacturing enterprises to focus on the protection and maintenance of the key collaborative subjects when coping with the competitive environment of the external market and provides a valuable reference for the normal operation of collaborative network organizations.

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