Digitalization has become a key driver of business innovation in recent years. It provides businesses with new opportunities to innovate and create value. Digital technologies, such as cloud computing, big data analytics, and artificial intelligence, have helped businesses boost the development of new products and services, optimize their operations, and improve customer engagement. This study aimed to analyze the impact of digitalization on business performance within business innovation. This study applied an ordinary least square regression model and an intermediary to explore relationship in the chain of digital capability–business model innovation–company performance. The object of investigation was 1663 listed A-share companies Shanghai and Shenzhen in the software and information technology service sectors. The results showed that digital capabilities could be divided into three dimensions according to the hierarchical relationship: (1) basic digital capabilities, (2) digital operation capabilities, and (3) digital integration capabilities, all of which significantly positively affected enterprise performance. Furthermore, while business model innovation significantly positively affected corporate performance, it was also driven by the preceding variables of digital capabilities. Business model innovation enhanced the positive impact of basic digital capabilities, digital operation capabilities, and digital integration capabilities on company’s performance. Considering the empirical results, this study underlines that the government should promote digital skills development, create supportive regulatory environments, promote access to funding for innovations, foster partnerships between businesses and technology providers, and promote collaboration between businesses, which are conducive to extending digitalization within the business innovation model and improving business performance.

This article aims to analyze the interplay between the digital economy (DE) and the real economy (RE), examining how they impact each other in terms of empowerment and supply effects. The study object is China from 2011 to 2021. This study applies the panel vector autoregressive model (PVAR). The study’s findings underscore a delayed empowerment effect within the DE. While DE growth has the potential to substantially enhance the future overall expansion of the tangible economy, it might concurrently dampen the short-term structural balance of the latter. However, the supply effect in the RE mode exhibits a similar delay. The time-lagged factors relating to the tangible economy’s total growth and structural fine-tuning play a pivotal role in fostering the progress of DE. Self-enhancement mechanisms significantly influence the overall growth of the tangible economy. However, this mechanism does not have the same significance in regard to enhancing structural coordination. Although the tangible economy’s expansion can catalyze structural refinement, the inverse relationship—where structural enhancement profoundly fuels tangible economic growth—does not hold true to a substantial extent. By assessing the overall degree of coupling and coordination between the DE and the tangible economy, it becomes apparent that these two domains are not tightly integrated. Instead, they exist in a fundamentally coordinated state, with a year-on-year upwards trend in their alignment, albeit at a modest pace. Furthermore, this coupling coordination degree displays a progressively diminishing trend from the southeastern coastal regions to the western interior, revealing a pronounced spatial imbalance. The contribution of this paper lies in its comprehensive enhancement of the theoretical framework and empirical research in the integration of energy and digital economy, addressing sustainable development, regional economic disparities, and practical policy implications to support future strategies for blending digital advancement with renewable energy utilization.