Networking Technologies And Green Management Platforms Driving Bank Digitalization And Corporate Green Innovation
Abstract
As the digital finance sector and green innovation ecosystems are increasingly interconnected and mutually reinforcing, technologies help to optimize resource allocation in a more sustainable way than traditional systems. While some platform-based frameworks, including eco-management solutions, are available for financial institutions, their systemic integration is not comprehensive. In this study, we analyzed the efficacy of two kinds of methods of network evaluation, GEPHI-based network modeling and the propensity score matching method, and divided banking entities into eco-aligned clusters and non-aligned clusters for comparative inference. This research focuses on the structural patterns and relational intensity of green banking transformation in the context of digital ecosystems. This framework consists of three aspects, including the identification of core-body nodes, the distribution of centrality-weighted ties, which is viewed as the backbone of eco-driven diffusion, and the measurement of variation in the deployment of green-digital interfaces. These outputs are fed to a score-matched estimation model, purposely designed and trained to detect some very salient causal links, policy gaps, and relational redundancies of the network. The empirical results show that the matched model has the advantages of improved accuracy and reduced bias, and higher predictive relevance. As a robust result, a rise in the green innovation index at network core nodes compared with the control clusters of the network was found. As a more general implication, the contribution of network centrality to the total green transformation may be underestimated if relational heterogeneity is not considered, in particular if the institutional setting is resistant to decentralized diffusion.