The theoretical mechanism and multiple paths of digital ecosystems empowering urban carbon reduction: Analysis of complex mediation effects based on dynamic QCA

The digital ecosystem is an advanced form of digital economy evolution and a driving force for reducing carbon emissions and increasing economic efficiency in society and the economy. Based on the digital ecology view and complexity theory, this paper uses a hybrid dynamic QCA and regression analysis method to construct a complex mediation model and explore how the digital ecosystem affects urban carbon emissions from a configuration perspective. The results indicate that the interconnection and coordination of various elements within the digital ecosystem form five equivalent configuration paths that drive green technological innovation. The digital ecosystem models represented by different configurations can all empower carbon emission reduction by enhancing the level of green technology innovation in cities, but there are significant differences in the overall impact of different digital ecosystem models on the carbon emission intensity of cities. Among them, market-led network-based and dual-integrated resource accumulation types are two digital ecosystem models that can effectively reduce a city's carbon emissions intensity. However, this impact is constrained by differences in urban policy contexts and resource endowments, with more pronounced effects observed in low-carbon pilot cities and peripheral cities. The research conclusions provide new insights into mechanisms for reducing carbon emissions through the use of digital technology, based on configuration thinking. This study addresses the limitations of traditional linear intermediary models in addressing complex issues, providing empirical evidence and policy implications for the deep integration of the digital revolution and the "dual carbon" goals.