Balancing patent protection and knowledge spillover: A novel decision framework

In the context of a globalized market and rapid technological development, businesses are increasingly facing heightened risks of patent infringement, with the challenges becoming more severe. In patent litigation, businesses are required to disclose substantial technical information to defend their patent rights or prove the validity of their patents, which introduces the risk of knowledge spillover. Therefore, balancing patent protection with the risk of knowledge spillover and selecting an appropriate patent protection strategy has become a critical issue that needs to be addressed. This paper develops a novel multi-criteria decision-making method under the 2-tuple linguistic model to optimize the selection of patent protection strategies and effectively mitigate the risk of knowledge spillover. First, a patent protection strategy evaluation system is established to address the risk of knowledge spillover, which is often overlooked in traditional strategies. Then, an improved TDWA operator is proposed, which dynamically adjusts the weights through enhancement factors to enhance the robustness and accuracy of the decision-making process. Additionally, the paper introduces the SMAA-TODIM method based on the 2-tuple linguistic set. This method integrates weight uncertainty and risk preferences, offering more reliable decision analysis and determining the central weight vectors for each option. Finally, a case study is conducted to validate the effectiveness of the proposed method, followed by comparative analysis and sensitivity analysis. The results demonstrate that the proposed method in managing uncertainty, integrating multi-source information, and modeling risk preferences, offering robust managerial recommendations for patent protection. • A systematic patent protection strategy evaluation system was established to address the often-overlooked risk of knowledge spillover. • A novel multi-criteria decision-making method based on the 2-tuple linguistic model is proposed for patent protection strategies selection under uncertainty. • An improved TDWA operator is designed to dynamically adjust weights, enhancing robustness in uncertain information environments. • The method integrates expert risk preferences and handles weight uncertainty effectively through the combination of SMAA-2 and TODIM.