Enhancing environmental management through big data: spatial analysis of urban ecological governance and big data development - Lei, Yunliang (Frontiers in Environmental Science, 2024)
This research employs the Spatial Durbin Model (SDM) to rigorously investigate the impact of Big Data Development (BDD) on Urban Ecological Governance Performance (EGP), placing particular focus on the environmental dimensions both within and among various regions. Additionally, the study delves into the mediating role of Industrial Structure Level (ISL) and examines the moderating effects of both Level of Technological Investment (LTI) and Urbanization Level (URB). This comprehensive approach illuminates the diverse factors that influence urban ecological governance and shape environmental management outcomes. The findings indicate that big data plays a significant role in strengthening urban ecological governance, characterized by pronounced spatial spillover effects, underscoring the interregional interdependence in environmental management. Furthermore, the research demonstrates that urbanization levels markedly amplify the influence of Big Data Development (BDD) on Urban Ecological Governance Performance (EGP); however, the magnitude of technological investments fails to exhibit a similar effect. While the industrial structure acts as a partial mediator in the relationship between BDD and EGP, this mediating role demonstrates variability across different regions. These insights highlight the critical role of big data in augmenting urban ecological governance, especially in terms of environmental facets, and accentuate the vital contributions of technological advancements and urbanization in this field.