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Evaluating SMEs-Supporting Policies During COVID-19 Pandemic with K-Means Clustering |
Zhao Zheng1,Huang Qianqian1,2,Tong Nannan1,2() |
1Department of Big Data Development, State Information Center, Beijing 100045, China 2School of Information Resource Management, Renmin University of China, Beijing 100872, China |
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Abstract [Objective] This paper tries to better understand the overall situation of the SMEs-supporting policies during the COVID-19 pandemic, aiming to promote the effective realization of policy objectives. [Methods] First, we collected the policy texts, relationship between corporate registration and investment, as well as the COVID-19 diagnosis data. Then, we calculated the number of policies issued by each province, the scores of the three major policy evaluation metrics, the degree of disaster, the industry structure and their economic ties with Hubei Province. Finally, we used the K-means clustering method to determine the degree of deviation from the enterprise policies in each province. [Results] The degree of deviation of the policies in Beijing, Shanghai, Fujian and other provinces is “Level Ⅰ”, while the degree of deviation in Hunan, Henan, and Yunnan is “Level Ⅲ”. Therefore, more SMEs-supporting policies need to be added in the “Level Ⅲ” provinces. [Conclusions] The proposed method could effectively evaluate the enterprise supporting policies in each Chinese province.
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Received: 16 April 2020
Published: 20 January 2022
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Fund:National Social Science Fund of China(18CSH018) |
Corresponding Authors:
Tong Nannan,ORCID:0000-0001-6709-9031
E-mail: tongnn@sic.gov.cn
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