Analysis on Key Influencing Factors of Production Efficiency of Advanced Manufacturing Industry and Efficiency Improvement Countermeasures:Taking Guangdong Province as an Example
Advanced manufacturing,as a complex system involving multiple aspects,requires a comprehensive consideration of technological innovation,economic operation,social environment,and international cooperation to deeply understand and accurately assess its development trend and impact mechanism.Based on a comprehensive review of relevant empirical literature,this paper selects 21 potential influencing factors from the perspectives of internal and external technological innovation entities and regional innovation environments.By employing data envelopment analysis(DEA)-Malmquist and Bayesian model averaging models,it explores the significant influencing factors of production efficiency in Guangdong's advanced manufacturing industry from 2015 to 2022,aiming to provide theoretical support for the high-quality development of advanced manufacturing in Guangdong and even across the nation.The results indicate that the production efficiency of Guangdong's advanced manufacturing industry exhibits a tortuous development trend,factors such as labor quality,market demand,industrial structure,R&D investment,and the degree of industrial integration are significant influencing factors.However,the collaborative capabilities between universities and enterprises and the level of international openness are not considered significant influencing factors.Among these,the impact of labor quality is negative,which may be related to the inefficient utilization of talent;the impact of industrial structure is also negative,reflecting the current disharmony between China's financial industry and the real economy,and there is a certain degree of development from real to virtual.Based on the empirical results,policy recommendations promoting the development of China's advanced manufacturing industry are proposed,including strengthening collaboration with enterprises,improving the support system of the tertiary industry for the advanced manufacturing industry,enhancing R&D support for the advanced manufacturing industry,and improving the level of industry-university-research cooperation in universities.
productivityadvanced manufacturingpotential influencing factorstechnological innovationdata envelopment analysis(DEA)-MalmquistBayesian model averagingindustrial innovationhigh-quality industrial developmentGuangdong Province
NETL
NSTL
万方数据
