Abstract: From 2016 to 2023, China implemented pilot projects for blue bay remediation in coastal provinces and cities. This paper constructs an analytical framework that comprehensively considers the "internal characteristics of networks and external environments," employing the fsQCA method to conduct an in-depth analysis of 17 blue bay remediation projects. It explores how factors such as bonding social capital, bridging social capital, network load, project funding, and socioeconomic status jointly influence governance performance. The study finds two paths driving high blue bay remediation performance: the "internal government cooperation" type, centered on bridging social capital and project funding, and the "government-market cooperation" type, centered on bridging social capital and socioeconomic status. Conversely, a path driving low blue bay remediation performance is identified: the "tangled interests" type, characterized by high bonding social capital and low bridging social capital. The results reveal the importance of bridging social capital in blue bay governance, the dual role of bonding social capital, and the influencing mechanisms of network load, project funding, and socioeconomic status. Additionally, practical recommendations for enhancing blue bay governance performance are provided.

governance networks, bay environmental governance, governance performance, configurational analysis