基于贝叶斯网络的高校专利技术转移链式风险研究

Research on the chain risk of university patent technology transfer based on Bayesian network

摘要:

高校专利技术转移是一项高收益且高风险的复杂活动,在实践中对技术转移风险进行科学的评价和管理具有重要意义。针对高校专利技术转移中存在的链式风险,构建基于贝叶斯网络的高校专利技术转移链式风险评估模型,通过研究专利技术转移过程中各风险的内在关联及其相互作用,量化风险因素间的因果关系强度,对高校专利技术转移风险的发生概率和风险链传递机理进行深入分析。研究结果表明,高校专利技术转移存在显著的链式风险,技术风险和法律风险是主要的风险链源头,且链式风险具有传递性、放大性、偏异性、因果耦合性等特征。在专利技术转移工作中对技术可转移价值的风险、资金投入的风险等关键节点进行积极管控,可降低技术转移风险；对主要风险链进行及时预警与断链,可阻断风险的进一步发展。

Abstract:

Patent technology transfer in universities is a complex scientific and economic activity with high benefits and risks. It is of great significance to scientifically evaluate and manage risks in practice. In order to clarify the risk chain mechanism in the process of university patent technology transfer, the risk chain evaluation model of university patent technology transfer based on Bayesian network is built to analyze the intrinsic correlation and interaction of risks and quantify the strength of causality. This paper analyzes the probability of occurrence of university patent technology transfer risks and the risk chain transmission mechanism. The research results show that there is a significant risk chain effect for university patent technology transfer, and the risk chain structure is characterized by transmissibility, amplification, partial heterogeneity, and causal coupling. Technical risks and legal risks are the main sources of risks, which ultimately lead to the failure of patent technology transfer. It is found that the active control of key nodes of the risk chain, such as transferable value of patents and capital investment, can reduce the security risk of technology transfer, and timely warning and breaking of the key edges of the main risk chain can block the further development of the risk.