The rapid development of the digital economy is a powerful driving force to promote high-quality economic growth all over the world. Although a number of studies have been conducted to investigate the development of the digital economy in China, these studies pay little attention to the spatial linkages between the 30 provinces in China and the developmental differences between northern and southern China. Using Chinese digital economic data from 2004 to 2019, we propose an index system to measure the developmental levels of the digital economy and obtain the annual developmental levels of these provinces by using the factor analysis method. We analyze the regional differences of developmental levels by using the Theil index and kernel density estimation method. More importantly, the network method is used to analyze the correlations between the developmental levels of the digital economy in all provinces of China. By decomposing regional differences, our study shows that polarized and uncoordinated development is prominent. The development level of the digital economy in the southern region is higher than that in the northern region. In terms of regional correlations, the network study suggests that there are beneficial and spillover effects of the digital economy development between provinces. Based on the analysis results, we propose policies for improving the development of the digital economy in China.

Digitalization is an excellent opportunity for the manufacturing industry all over the world to improve the core competitiveness and break through the “low-end locking” dilemma. However, it is not clear whether the digitalization of the manufacturing industry has positive ecological and environmental benefits under the resource and environmental constraints. To answer this question, we use the data from the world input–output database (WIOD) to investigate the impact of manufacturing input digitalization on carbon emission intensity by an extended analysis. The results show that the input digitalization of the manufacturing industry has mixed effects on reducing carbon emission intensity. The productive input digitalization can reduce carbon emission intensity, but the distributional input digitalization may increase carbon emission intensity. Non-pollution-intensive manufacturing and high-input digital manufacturing have stronger carbon emission reduction effects than the other industry sectors. From the perspective of input sources, input digitalization from domestic sources has a significant inhibitory effect on the carbon emission intensity. In contrast, input digitalization from foreign sources may increase carbon emission intensity.

Entrepreneurship is widely recognized as a key driver of both innovation and economic growth. It comprises two essential components: (i) discover entrepreneurial opportunities and (ii) accumulate entrepreneurial capital. Based on the Chinese Family Panel Studies in 2018, we consider online information acquisition and online learning to be important ways of discovering entrepreneurial opportunities. Additionally, we regard online social engagement and online businesses as essential channels of entrepreneurial capital accumulation. The study reveals that entrepreneurship is positively affected by online information acquisition, online learning, online social engagement, and online businesses. The robustness of our results has been confirmed in terms of model misspecification and the reverse causality of entrepreneurship to Internet utilization. Furthermore, evidence indicates that the impact of online learning on entrepreneurship is negatively moderated by human capital. Additionally, social capital and financial capital play a role in mediating the causal pathway linking online social engagement and online businesses to entrepreneurship.