Research on evaluation of innovation curation potential of universities in the field of artificial intelligence: empirical analysis based on cross sectional data from 31 provinces in China
LI Ziyang1,2
1. Zhejiang Institute of Social Governance and Communication Innovation, Communication University of Zhejiang; 2. School of Cultural Creativity and Management, Communication University of Zhejiang, Hangzhou 310018, China
Abstract：Starting from the concept of curatorial innovation potential of universities and exploring its dimensional division and elemental composition, an evaluation system for the curatorial potential of universities in the field of artificial intelligence is constructed. Crosssectional data from 31 provinces in China are selected. The entropy weight TOPSIS method is used for empirical analysis and passes the robustness test. It is found that the potential of university innovation curation can be divided into three subsystems, namely, the resource potential on the supply side of university innovation curation, the production potential on the through side of university innovation curation, and the support potential on the demand side of university innovation curation; The evaluation system of university innovation curation potential in the field of artificial intelligence consists of 12 tertiary indicators with 3 primary indicators and 7 secondary indicators; The geographical distribution of provinces with high, medium and low potential is characterized by "strong in the east and weak in the west, balanced in the north and south, and spread in the three cores". This distributional characteristic basically corresponds to the level of industrial development of the provincial economy. It is necessary to rely on the concerted efforts of government, industry, academia, research and application to promote the continuous emergence of new disciplines, new knowledge, new talents, new technologies, new jobs, new business models and new markets, and to help high potential provinces continue to move up the ladder, medium potential provinces seek their own characteristics, support the structural adjustment and high quality development of low potential provinces.
李滋阳. 人工智能领域高校创新策源潜力评价研究——我国31个省份截面数据的实证分析[J]. 高校教育管理, 2024, 18(3): 95-109.
LI Ziyang. Research on evaluation of innovation curation potential of universities in the field of artificial intelligence: empirical analysis based on cross sectional data from 31 provinces in China. Journal of Higher Education Management, 2024, 18(3): 95-109.
