Optimisation analysis of resource allocation for China's high-tech industry based on an extended inverse DEA with frontier changes.

Developing China's high-tech industry is important to make the country innovation-oriented. This requires optimising the allocation of innovation resources and improving innovation efficiency. However, few studies have investigated this topic and the realisation path for the high-tech industry. This study develops an input-oriented inverse data envelopment analysis (DEA) model with frontier changes to analyse the optimisation of resource allocation in China's high-tech industry during 2019–2025. With this method, decision makers can scientifically analyse the specific amount of resource investment. We also construct an analysis framework from short- and long-term perspectives. The results show that the excessive input of research and development (R&D) personnel and unbalanced allocation of capital resources are the main barriers to the development of high-tech industries in the short term, and in the mid- and long terms, the demands for investment in talent and capital will continue to increase. Improvement directions for promoting the development of China's high-tech industry are discussed. Finally, we present valuable information for policymaking to promote progress in high-tech industries in different regions. [ABSTRACT FROM AUTHOR]