A Hybrid Cooperative Game and Shapley Value Approach for Knowledge Sharing and Profit Allocation in Technology Supply Chain Strategic Alliance
针对技术供应链战略联盟中利润分配难题，提出结合沙普利值的混合博弈框架，通过蒙特卡洛模拟评估知识投资、吸收能力等贡献，在汽车供应链案例中验证了优化知识共享带来的利润增长。
Equitable profit allocation in strategic alliances within technology supply chains remains a formidable challenge, exacerbated by the inability of conventional game-theoretic models such as Nash bargaining and Stackelberg to effectively analyze dynamic, knowledge-driven contributions. These models, constrained by their bilateral and static design, fail to capture the intricacies of multi-agent interactions. This study introduces a hybrid game-theoretic framework utilizing the Shapley value's axiomatic fairness to allocate coalition profits by marginal contributions. The Shapley value surpasses equilibrium-based or power-centric approaches, offering superior suitability for complex multi-agent scenarios. Leveraging meticulously validated data including knowledge investment, absorptive capacity, and coordination costs—this framework employs Monte Carlo simulations to deliver statistically reliable contribution estimates, thereby overcoming the shortcomings of prior methodologies. Applied to an automotive supply chain, the model demonstrates substantial profit gains attributable to optimized knowledge-sharing processes. Absorptive capacity reflects the efficiency of organizational learning, coordination costs indicate potential frictions in collaborative processes, and knowledge investment captures the level of innovation intensity. The proposed model offers a robust, data-driven foundation for developing equitable profit-sharing mechanisms tailored to engineering management needs. At the policy level, it provides a scalable framework for strengthening supply chain resilience. This integrated approach contributes meaningfully to both the advancement of theoretical perspectives and the enhancement of practical strategies in supply chain management.