Multiplication of number and quality rise: data elements enable low-carbon innovation - Dongri Han; Ke Lu; Peisen Liu (Humanities & Social Sciences Communications)
Abstract Low-carbon innovation, as a key driving force for achieving the “dual carbon” goals, is crucial for promoting the process of environmental sustainability and accelerating the development of a green economy. Based on panel data from 288 prefecture-level cities in China from 2011 to 2022, a benchmark regression model, mediating effect model and threshold regression model were constructed to systematically examine the effects of data elements on the quality and number of regional low-carbon innovation. The results reveal that: (1) Data elements can promote the increases in the number and quality of regional low-carbon innovation, and this conclusion remains valid after a series of robustness tests. (2) Data elements can directly promote the quality and number of regional low-carbon innovation, and indirectly affect the quality and number of low-carbon innovation through integrating data elements and technology elements, data elements and labor elements, and data elements and capital elements. (3) According to the threshold effect test, data elements have different threshold effects on low-carbon innovation. Specifically, data elements can play a stronger positive role at higher integration levels of data and technology elements, data and labor elements, and data and capital elements. These research conclusions have important implications for leveraging the role of data elements and accelerating the realization of low-carbon innovation-driven development.