Impact of Financial R&D Resource Allocation Efficiency Based on VR Technology and Machine Learning in Complex Systems on Total Factor Productivity

Abstract

With the development of the globalization of science and technology, innovation has become an important driving force for regional economic development. As a core element of regional innovation, financial R&D resources have also become a key element to enhance national innovation capabilities and national economic competitiveness. National and regional innovation capabilities have a direct impact. There are also many deep-seated problems behind the world-renowned achievements, such as irrational industrial structure, insufficient independent innovation capabilities, low resource utilization efficiency, and the service quality and efficiency of financial institutions for the transformation of total factor productivity. These problems extremely restrict the efficiency upgrade and further development of our country’s total factor productivity. This study uses the DEA-Malmquist index model to measure the efficiency of fiscal R&D resource allocation in 28 provinces and regions in China in the past 10 years and uses Mapinfo12.0 software to analyze regional differences in the efficiency of fiscal R&D resource allocation in China from a spatial perspective. During the year, the overall R&D resource allocation efficiency of 28 provinces and autonomous regions in China has shown an upward trend. The efficiency of fiscal R&D resource allocation and the concentration of financial factors have had a positive impact on total factor productivity, transform and upgrade factors, increase total factor productivity, and provide empirical evidence for building a strong country.

The effectiveness of dual regulation and synergistic governance of market-incentivized carbon reduction policies and public environmental supervision: a study based on the sustainable development performance of listed companies in China

“…Through the theoretical analysis in Section 2, it can be found that the synergistic governance effect of carbon trading policy and public environmental supervision enhances the ESG performance of firms by influencing their R&D and innovation investment, resource allocation efficiency, and sustainability awareness. In order to test whether this view is valid at the micro enterprise level in reality, referring to Sun and Zhong (2020), Wang R. et al (2022), andLi et al (2023), this paper uses firms' R&D investment intensity (RDI), total factor productivity (TFP), and executives' awareness of sustainable development (EAS) to measure firms' R&D and innovation investment, resource allocation efficiency, and sustainable development awareness, respectively. The mechanism test model is set up as follows:…”