A hybrid model analysis of digitalization energy system: evidence from China's green energy analysis

The integration of renewable energy sources can be supported by the digitalization of energy systems, which increase dependability and lower costs of energy production and consumption. However, the energy digitalization support energy infrastructures and technologies currently in place are insufficient. This research presented the study results by using the generalized least square estimates (GLS) model and the international sample of China regions from 2003 to 2017. Main results of the dynamic fixed effect (DFE) estimator for the autoregressive distributed lag (ARDL) method, establishing ES goals for lowering energy consumption and pollution emission fosters a country's renewable energy business sector's digital transformation in the short term, while encouraging the use of renewable energy sources fosters a country's long-term digitalization efforts. Based on this, the direct effects and dynamic effects of digitalization and financial development on environmental are explored, respectively, using the panel data regression model and panel vector autoregression (PVAR) model. The threshold regression model is then used to examine the two parameters' threshold effects on eco-efficiency. An accurate estimate of the resource consumption in smart factories is made possible by the digital twin that is created using the product's and its attributes as well as manufacturing data. The results suggests the future directions for the associated stakeholders.