The increasing volatility on both the supply and demand sides poses a significant challenge to the development of a new electricity system. As a key participant in demand response, the operational mechanism of Virtual Power Plants (VPPs) directly impacts the system"s flexibility. Based on Stackelberg game theory, this paper considers the response characteristics of heterogeneous resources and proposes a bilateral pricing–bidding strategy for load-oriented VPPs. The proposed strategy enables reasonable internal pricing for aggregators while enhancing the fulfillment capability of VPP through a dynamic adjustment mechanism. We developed an inner–outer nested iterative solution framework combined with a particle swarm optimization (PSO) algorithm. Simulation results demonstrate that the segmented pricing strategy with the proposed adjustment mechanism effectively improves the utilization of resources within the VPP and enhances its ability to match market response requirements. Significant differences are observed in response capabilities among various types of resources: energy storage resources exhibit higher flexibility and dispatchability, whereas curtailable and shiftable loads show relatively limited responsiveness. In addition, the segmented pricing strategy with the bidding adjustment mechanism improves resource utilization and raises the overall VPP revenue to approximately 1.4 times that of the baseline case.