摘要
基于主成分分析的方法对全国31个省域的智能制造创新能力进行评价,结果发现:该方法能够对反映智能制造创新能力的14个指标进行降维;11个省域的智能制造创新能力高于全国平均水平,其余20个省域低于全国平均水平,进一步来看,各省域智能制造创新能力呈现出“规模—收益双高型”“规模主导型”“收益特色型”和“规模—收益双低型”四种典型发展模式;智能制造创新能力与经济发展显著正相关。基于此,从优化评价指标体系与方法、实施差异化发展战略、深化智能制造创新能力与经济发展的融合三个方面提出增强智能制造创新能力的政策建议。
Using principal component analysis,this study evaluates the intelligent manufacturing innovation capability of 31 provinces in China.The results show that this method can reduce the dimensionality of 14 indicators reflecting intelligent manufacturing innovation capability.Eleven provinces exhibit intelligent manufacturing innovation capabilities above the national average,while the remaining 20 provinces fall below it.Furthermore,provincial intelligent manufacturing innovation capabilities display four typical development models:high scale—high benefit,scale—dominated,benefit—featured,and low scale—low benefit.Intelligent manufacturing innovation capability is significantly and positively correlated with economic development.Based on these findings,policy recommendations are proposed to enhance intelligent manufacturing innovation capability from three aspects:optimizing evaluation indicator systems and methods,implementing differentiated development strategies,and deepening the integration of intelligent manufacturing innovation capability with economic development.
作者
尚从永
净昀飞
韩劲松
李洋
SHANG Congyong;JING Yunfei;HAN Jinsong;LI Yang(School of Economics and Management,Hefei Normal University,Hefei 230601,China;Institute of Talent Development,Hefei Normal University,Hefei 230601,China)
出处
《合肥师范学院学报》
2025年第5期83-89,共7页
Journal of Hefei Normal University
基金
合肥师范学院校级科研项目“数字经济时代大学生参与农村就业创业研究”(2024KY19)
合肥师范学院校级科研项目“‘新质生产力’视角下长三角三省一市战略科学家分布及流动模式研究”(2024KY22)
安徽省社会科学创新发展研究课题重大项目“安徽省面向新质生产力发展的人力资源管理研究:新质生产力导向下安徽省人才生态评价及优化研究”(2024ZD007)。
关键词
智能制造
创新能力
主成分分析
intelligent manufacturing
innovation capability
principal component analysis
