Industrial parks and commercial parks in urban power grids possess substantial flexible resources, including electric vehicles (EVs) and air conditioners (ACs). However, operational constraints and divergent profit motives among stakeholders complicate coordinated control. Existing research has proposed game-theoretic models for shared energy storage interacting with multiple users, yet these models often neglect the influence of flexible resource endowments across different parks on price competition, leaving room for improving overall system benefits. To address these challenges, this paper establishes a flexibility model enabling massive micro-resources to participate in system impact power response. A two-layer game-theoretic control strategy for flexible resources in multi-park urban grids is proposed, utilizing a shared energy storage framework. This strategy incorporates the flexible resources from both commercial and industrial parks into the game formulation and influences the pricing strategy of shared energy storage. Furthermore, an adaptive gradient-based bi-level iterative solution algorithm is developed to solve the proposed bi-level game model. Comparative case studies demonstrate that, compared to existing shared energy storage game methods, the proposed approach can fully leverage the flexible resources within each park, markedly enhancing shared storage revenue and effectively reducing the comprehensive operational costs for the parks. Additionally, the proposed algorithm exhibits superior solving efficiency and convergence speed compared to heuristic algorithms.