【摘要】 聚焦联盟企业在社交媒体使用情境下的复杂网络知识共享动态演化机制，旨在揭示网络规模、社交媒体使用强度和联系成本等因素对不同知识位势群体的知识共享行为的差异化影响机理，为优化联盟知识共享策略提供理论支撑和实践参考。讨论社交媒体使用情境下联盟企业复杂网络知识共享的动态演化规律，构建融合网络结构特征与群体异质性的动态演化博弈模型，通过复杂网络仿真模拟，系统分析关键变量对复杂网络知识共享的作用机制，重点探究各因素间的交互效应和核心阈值条件。研究结果表明，社交媒体使用强度与知识共享效果呈显著正向关联，且对高知识位势群体的驱动效应更为突出；网络规模与社交媒体使用强度存在交互适配特征，当网络规模与高社交强度形成耦合时，知识协同价值达到最优水平；联系成本的抑制作用随社交强度提升呈放大趋势，而知识互补系数与机会主义惩罚的促进效应在强社交网络中表现更为显著。进一步分析结果表明，高知识位势群体呈现与规模强度适配的行为特征，低知识位势群体则需依托高强度社交突破成本约束以实现知识共享效能的提升。研究结果丰富了对联盟知识网络共享的动态研究，为理解数字情境下联盟知识共享规律提供了新视角，为企业制定差异化共享策略提供了参考。更多还原

【Abstract】 Focusing on the dynamic evolutionary mechanism of knowledge sharing within the complex networks of alliance enterprises in the context of social media application, this study seeks to unravel how factors such as network scale, social media usage intensity, and connection costs heterogeneously influence the knowledge-sharing behaviors across groups with distinct knowledge potential levels. It aims to offer theoretical underpinnings and practical implications for optimizing the knowledgesharing strategies of alliance systems.By exploring the dynamic evolutionary laws governing knowledge sharing in the complex networks of alliance enterprises under social media-enabled scenarios, this study constructs a dynamic evolutionary game model that integrates network structure characteristics and group heterogeneity, thereby enriching the dynamic research paradigm of knowledge sharing in alliance knowledge networks. Employing complex network simulation methods, the study systematically analyzes the action mechanisms through which key variables affect knowledge sharing in complex networks, with a particular focus on investigating the interactive effects between variables and core threshold conditions.The results indicate that social media usage intensity exhibits a significant positive correlation with knowledge-sharing effectiveness, and its driving effect is more pronounced for groups with high knowledge potential. An interactive adaptive relationship exists between network scale and social media usage intensity: When network scale is coupled with high social media usage intensity, the knowledge synergy value reaches an optimal level. The inhibitory effect of connection costs is amplified with the increase of social media usage intensity, while the promoting effects of the knowledge complementarity coefficient and opportunism punishment mechanisms are more prominent in strong social networks. Further analysis reveals that groups with high knowledge potential exhibit scale-intensity adaptive behavioral traits. In contrast, groups with low knowledge potential require high-intensity social media interactions to overcome cost constraints and improve knowledge-sharing efficiency.This research provides a novel theoretical perspective for understanding the inherent mechanisms of alliance knowledge sharing in the digital context and offers actionable references for enterprises to formulate differentiated knowledge-sharing strategies.更多还原