The determining mechanism of technology catch-up in China's photovoltaic (PV) industry: Machine learning approaches

Abstract

The unexpected success of China's PV industry in technology catch-up has been noted. However, existing research has overlooked the multidimensional nonlinear complexities in its underlying mechanisms. This study introduces the "Seven-Element Diamond Model" theoretical framework and employs machine learning (ML) methods to address this. Using observed data from 84 listed China's PV companies from 2000 to 2021, we systematically examine the intricate mechanisms of technology catch-up in China's PV industry. Key findings include: 1) The self-enhancing mechanism stemming from R&D effort, government subsidies, and domestic demand is pivotal for the successful technology catch-up of China's PV industry. 2) Key regulatory directions are identified from R&D effort to market competition, technology spillover, productivity, and government subsidies. 3) R&D effort forms the underlying logic of China's PV industry technology catch-up, and domestic market demand is an extremely important driver for China's PV technology catch-up. Government subsidies exhibit a "blowout" incentive effect, and the synergistic coupling between key variables is also significant in driving China's PV technology catch-up. This study offers valuable insights into the catch-up of clean energy or sustainable technologies in China and other emerging economies.