Fuzzy Predictive Modeling for the Hierarchical Structure of Strategic Innovation Management
针对总解释结构模型缺乏定量能力的问题，提出基于模糊集理论的预测建模方法，通过替代变量量化定性因素并模拟层次模型，帮助新创企业通过多情景仿真提升绩效。
Total interpretive structural modeling (TISM) constructs a hierarchical structure with interpretations of nodes and interrelationship links. While TISM performs qualitative research when conceptual modeling is preferred, it lacks quantitative capabilities at present. Conducting a quantitative study on TISM is difficult, especially when the model elements are qualitative. TISM enables the development of a predictive model based on fuzzy set theory. The proposed methodology benefits from using surrogate variables to quantify qualitative variables and fuzzy set theory to simulate the hierarchical model. The proposed method is exercised to conduct a simulation-based study on the existing hierarchical model of strategic innovation to generate multiple scenarios. Additionally, through simulation and scenario building, relevant decisions can be made to enhance productivity and performance in particular functional areas. In this article, multiple scenarios generated by the simulation provide a comprehensive view of the system's behavior in new ventures, which aids in the multicriteria decision-making process.