A social network analysis in dynamic evaluate critical industries based on input-output data of China

被引:1
|
作者
Wang, Can [1 ]
Yang, Huipeng [1 ]
机构
[1] Zhongnan Univ Econ & Law, Sch Business Adm, Wuhan, Hubei, Peoples R China
来源
PLOS ONE | 2022年 / 17卷 / 04期
关键词
CENTRALITY; INTERDISCIPLINARITY; BETWEENNESS; WEIGHT;
D O I
10.1371/journal.pone.0266697
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
As the Chinese economy grows, the imbalance of industrial structure is prominent, and the optimization of industrial structure has become an urgent problem. Evaluation of industry is an important step in industry optimization. To this end, this study proposes an integrated evaluation method combining social network analysis (SNA) and the multi-criteria decision making (MCDM) method. Specifically, SNA method are used to calculate indicators, the measurement weights are calculated by the Entropy Weight (EW) Method, and the rank of each industry is determined by the TOPSIS method. Critical industries are identified based on China's input-output data from 2002 to 2017. The results indicate that Manufacturing Industry and the Metal products have a high evaluation, but the Research and Development have a low evaluation value at all times. According to the results, we suggest that the government should optimize the allocation of resources and promote the transfer of resources to balance industrial development.
引用
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页数:19
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