The threat intelligence market facilitates information sharing in cybersecurity, enabling various organizations to exchange insights about potential cyber threats. However, conventional threat intelligence sharing models, such as those based on federated learning or blockchain, have several limitations, including inconsistent data quality, inadequate incentives, and a lack of transparency. Hence, we propose a blockchain-based cybersecurity intelligence-sharing platform enhanced with an incentive mechanism to address challenges in efficiency, security, transparency, and mutual benefit. Central to the platform is a tripartite game-theoretic pricing contract that dynamically calculates optimal rewards for intelligence submissions, considering submission volume, market demand, and service evaluations. This model ensures a balance between intelligence quality and stakeholder benefit maximization, fostering a positive feedback loop that encourages continuous contributions of high-value intelligence. Our analysis also explores the impact of user scale on the accuracy of intelligence evaluation scores, providing insights into the interplay between user behavior, intelligence valuation, and platform performance. The results demonstrate that the proposed platform effectively incentivizes participation, enriches the intelligence sharing ecosystem, and enhances overall cybersecurity resilience.