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Proceedings of the 2nd International Conference on Engineering Management and Information Science, EMIS 2023, February 24-26, 2023, Chengdu, China

Research Article

Research on Shanghai's Scientific and Technological Innovation Ability Based on Principal Component Analysis

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  • @INPROCEEDINGS{10.4108/eai.24-2-2023.2330672,
        author={Qingsong  Guo and Keke  Ge},
        title={Research on Shanghai's Scientific and Technological Innovation Ability Based on Principal Component Analysis},
        proceedings={Proceedings of the 2nd International Conference on Engineering Management and Information Science, EMIS 2023, February 24-26, 2023, Chengdu, China},
        publisher={EAI},
        proceedings_a={EMIS},
        year={2023},
        month={6},
        keywords={innovation ability; evaluation system; principal component analysis},
        doi={10.4108/eai.24-2-2023.2330672}
    }
    
  • Qingsong Guo
    Keke Ge
    Year: 2023
    Research on Shanghai's Scientific and Technological Innovation Ability Based on Principal Component Analysis
    EMIS
    EAI
    DOI: 10.4108/eai.24-2-2023.2330672
Qingsong Guo1, Keke Ge1,*
  • 1: Shanghai Institute of Technology
*Contact email: keke_vip@163.com

Abstract

The capacity for innovation in science and technology represents a city's potential and level of growth. This paper takes four municipalities (Shanghai, Beijing, Tianjin and Chongqing) as the research object. Evaluation indicators are created from the aspects of science innovation input and output. Based on the relevant data from 2017 to 2021, the innovation differences of the four municipalities are measured by principal component analysis using SPSS software. The research recommends that cooperation between universities and other institutions should be expanded to give full play to the advantages of universities. Also, foster scientific innovation capacity in high-tech industries more quickly. The innovation characteristics of Shanghai are compared and summarized in this empirical study, which serves as a guide for other regions planning scientific innovation work.

Keywords
innovation ability; evaluation system; principal component analysis
Published
2023-06-15
Publisher
EAI
http://dx.doi.org/10.4108/eai.24-2-2023.2330672
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