基于指数随机图模型的技术机会识别

Technology Opportunities Identification Based onExponential Random Graph Models

识别领域内的技术机会是研发组织创新管理的重要内容。本文提出一种识别特定领域技术机会的新方法,基于知识元素的组合属性(包括组合广度、组合强度和组合距离)、传递性和同配性,构建指数随机图模型,在模型参数估计的基础上计算知识元素间进行组合的概率,进而发现领域内的技术机会。本文采用2016—2021年物联网领域的发明专利数据验证了该方法的有效性,并利用工业机器人领域的发明专利数据验证了该方法的稳健性。

Identifying technology opportunities in specific fields is an important part of the R&D organizations’innovation management.This study proposes a new method to identify technical opportunities in specific fields.Based on the combination attributes of knowledge elements(i.e.,combination breadth,combination intensity,and combination distance),transitivity,and homogeneity,exponential random graph models are constructed.The probability of combination between knowledge elements is calculated based on the model parameter,and subsequently technical opportunities in the field are discovered.To validate the effectiveness of the proposed method,patent data in the field of the Internet of Things from 2016 to 2021 is used.To check the robustness of the proposed method,patent data in the field of industrial robots is used.