This paper innovatively defines the structure of human capital based on existing theories and use the heterogeneous stochastic frontier model to test the relationship between various types of human capital and innovation. It is found that with the progress of technology, the structure of human capital and the mechanism of promoting innovation have undergone profound changes. Together with commercial leasing human capital, financial human capital, and entrepreneurs, information human capital and transportation human capital participate in innovation activities and create a new collaborative space, which in turn helps to spread the value of innovation and influence the effectiveness of the entire innovation system. This study enriches the theoretical research on the mechanism of human capital promoting innovation in the information age and provides new insight to explain the imbalance between human capital input and innovation output. Based on the theory of innovation chain value and flow space, this study redefines the connotation of innovative human capital structure by distinguishing the nature of innovation activities. This study also reveals the difference in the influence of human capital structure on different types of innovation activities. This study partly explains the problem of increasing human capital input but decreasing innovation efficiency in developing countries. Therefore, from a macro perspective, our research provides guidance for understanding the transformation of innovation under the background of technological progress and formulating effective urban innovation strategies for managers.

With the rapid development of digital technology, the role of digitalisation in urban governance continues to emerge. Building a theoretical analysis framework and evaluation system of digitally driven urban governance has important theoretical and practical significance for stimulating the efficiency of digital technology tools and improving the energy level of urban digital governance. This paper aims to explore the mechanism of urban governance enabled by digital technology, innovatively change the previous thinking mode that only attaches importance to facility construction and e-government platforms, adopt ecological thinking, and comprehensively consider the role of “soft elements” such as strategic support, industrial support, the security environment, talent support, and the market environment. Then, the extreme value variance method and the coefficient of variation method are used to calculate the overall capacity and secondary index scores of each city, and the standard deviation of secondary index scores is used to represent the sub-environmental balance of the cross-sectional data of China’s provinces. In order to further explore which indicators restrict the improvement of China’s urban digital governance capacity, this study also constructs an obstacle degree model. The results show the following: (1) The overall capability of China’s digitally driven urban governance is low, with a total score of 27.25, indicating that China’s digitally driven urban governance is in its infancy. (2) There is a significant development imbalance among Chinese provinces, with Beijing ranking first with a score of 81.16, and Tibet, Qinghai, Xinjiang, Heilongjiang, and Ningxia scoring less than 13.30 points, ranking as the bottom 5 among the 31 provinces. (3) The shortcomings of talent support, industrial support, and the security environment restrict the improvement of the entire digital ecological governance ability.

The role of the digital business environment (DBE) in the sustainable development of enterprises (SDE) has received extensive attention. This study aims to discover what factors of DBE affect SDE. The empirical results based on China’s inter-provincial panel data from 2011 to 2021 show that DBE has a dual impact on the quantity and quality of enterprises from five dimensions, digital infrastructure, digital industrial environment, digital R&D support, digital talent supply, and digital market demand, among which the digital industrial environment, digital R&D support, and digital talent supply are more conducive to enterprise sustainability. The digital industry environment, digital R&D support and digital talent supply are more conducive to improving enterprise development quality. The results of the heterogeneity analysis further show that there is a significant difference in the regional effect of DBE on SDE. Enterprises in eastern, central, and western China show a tendency to differentiate the demand for different factor conditions, such as technology, industry, and talent, in the process of development. The research in this study provides new theoretical perspectives and empirical evidence for optimising the business environment and achieving SDE.