Blockchain-Based Incentive Mechanisms: Single Incentive Mechanism and Compound Incentive Mechanism

With the wide application of blockchain in data sharing scenarios such as smart healthcare, the Internet of Things, and federated learning, how to maintain trusted collaboration and motivate nodes to continuously participate under the premise of privacy protection has become a key issue. The blockchain incentive mechanism builds a closed loop of "behavior - reward - continuous participation" through methods such as income rewards, reputation feedback and permission allocation, providing a reliable operation foundation for decentralized systems. This paper systematically reviews the relevant research in recent years based on the "incentive source structure" and "behavioral constraint logic", classifies the existing mechanisms into four categories: revenue-based, reputation-based, revenue-based and reputation-based, and rights-based, and conducts comparative analysis from aspects such as incentive processes, governance structures, and applicable scenarios. Research shows that a single incentive is difficult to balance efficiency, fairness and steady-state participation, while compound incentives have more advantages in enhancing incentive intensity, curbing free-riding and strengthening governance resilience. However, there are still challenges such as insufficient revenue confirmation, unstable reputation quantification and abuse of rights.