Analyzing the governance efficacy of generative AI policies and regulations can not only facilitate the development of GenAI-driven new quality productive forces and enrich theoretical research on generative AI governance, but also help enhance information governance effectiveness and advance national cyberspace governance capabilities. Drawing on relevant theoretical frameworks, this paper first analyzes the factors influencing the governance efficacy of generative AI policies and regulations from three dimensions: government governance, resource endowment, and technological environment. Subsequently, this paper takes the policies and regulations of generative AI in 30 countries as samples, employs the fsQCA method and utilizes PMC index evaluation results to explore potential pathways for enhancing the governance efficacy of generative AI policies and regulations. The findings demonstrate that the governance efficacy of generative AI policies and regulations is primarily influenced by six critical factors: the quality of policies and regulations, government conduct, risk capital investment, AI governance capacity, public subject activities, and AI safety mechanisms. Finally, the paper proposes three synergistic configuration paths to upgrade governance efficacy: technology-resource-driven path, policy-actors coordination, and government-led multi-subject coordination.