This paper explored the reconstruction and evolution of business models of manufacturing enterprises in the era of artificial intelligence (AI), aiming to provide insights into how enterprises can develop new competitive advantages. By identifying five fundamental issues related to the commercialization of AI and employing a single-case study method, the research drew on the practical experiences of Midea Group in the field of intelligent manufacturing from a value perspective. First, the study conceptualized the business models in the AI era as a dynamic closed-loop analytical framework comprising six interconnected elements: value proposition, value creation, value delivery, value capture, value maintenance, and value transformation. Second, it revealed that the business models of manufacturing enterprises undergo incremental reconstruction driven by technological iterations in AI, with machine intelligence, trustworthy AI, and generative AI technologies serving as the foundations for three distinct stages: AI enabling, AI trust, and AI ubiquitous. Third, the study highlights Midea Group's evolutionary pathway from a "+AI" model to an "AI+" model, offering a practical roadmap for the intelligent transformation of business models. These findings will provide a theoretical foundation and actionable guidance for manufacturing enterprises seeking to leverage AI in creating distinctive value and achieving sustainable competitive advantages.

Integrate innovation is a crucial means of driving high-quality economic development and a key focus for achieving Chinese-style innovation. This study conducted a longitudinal case study of "NewMed Medical" to explore the intrinsic mechanisms and evolutionary pathways of integrate innovation from the perspective of the innovation chain. The findings revealed that: (1) Integrate innovation is embedded in the progressive evolution of the innovation chain, following the stages of "discovery-invention-development" and its evolution exhibits multi-dimensional dynamic characteristics, including vertical progression, horizontal expansion, and cross-dimensional interactions; (2) Integrate innovation possesses dual attributes of multi-stage interconnection and multi-actor symbiotic competition and cooperation, manifesting in integrated models such as absorptive, complementary, and collaborative innovation; (3) Integrate innovation drives hierarchical transitions across "elements-resources-ecosystem" characterized by adaptive integration, coordinated collaboration, and coupled integration mechanisms. This study has constructed an evolutionary process model of integrate innovation, and extracted its functional patterns and realization mechanisms, and it will provide theoretical foundations and practical guidance for optimizing and upgrading technological enterprise innovation practices.

The full utilization of data elements by economic entities is not only a crucial pathway for realizing the value of data elements but also a key focal point for digital economic development. Based on government data openness policies, this study employed a difference-in-differences model, utilizing the data from Chinese A-share listed companies, provincial-level regions, and cities from 2009 to 2022. It examined the impact of government data openness on corporate data element utilization levels and its underlying mechanisms. The findings revealed that: (1) Government data openness significantly enhances corporate data element utilization levels; (2) Firms' resource integration capabilities and digital transformation serve as key mediating mechanisms through which government data openness influences corporate data utilization; (3) The application of digital technologies, and levels of intelligent investment, executives' digital backgrounds, and digital industry agglomeration exert positive moderating effects on the relationship between government data openness and corporate data utilization; and (4) The heterogeneity analysis revealed that high-tech industry firms exhibit higher levels of data utilization. This study has explored the corporate data utilization process from the perspective of internal and external resource integration, and it will enrich research on unlocking data value and provide theoretical foundations and management insights for corporate data utilization.

Digital innovation is the core driving force for the high-quality development of digital economy, and how to effectively link the government, market and society to realize the "increase in quantity and quality" of digital innovation is an important issue to be solved. From the perspective of the new structural economic theory and based on the institutional framework of "government-market-society", this study, taking 280 prefecture-level cities in China from 2010 to 2021 as case studies, adopted the dynamic QCA methods to investigate the linkage effect and path selection of digital innovation driven by multiple factors in a spatial and temporal dimension. The study showed that: First, no single institutional factor of government, market and society constitutes a necessary condition to drive the "incremental improvement" of digital innovation. Second, the combination effect of multiple factors to form the "incremental quality" of digital innovation has the characteristics of "different paths to the same destination" and "multiple concurrency". There are three typical combinations of government-led, government-market-led and government-market-society synergistic promotion systems that can realize "incremental" digital innovation. And there are two organizational ways to achieve "quality improvement" in digital innovation: government-society-driven and government-market-society synergistic promotion. Third, the spatial context analysis based on the grouping pattern showed that there are obvious regional differences in urban digital innovation paths, with the government in the eastern region playing a leading role in the "incremental improvement" of digital innovation, while the central and western regions rely mainly on the market to cultivate it. Fourth, in a comparative analysis over multiple time periods, two types of institutional configurations, "government-led" and "government-market-society synergistic", are found to be among the "dominant trajectories" driving digital innovation, which consistently and steadily emerged. The study has both broadened the research horizon of digital innovation and provided new thinking on how to improve the institutional environment for high-level digital innovation.