Identifying promising technologies using patents: A retrospective feature analysis and a prospective needs analysis on outlier patents

离群值 计算机科学 专利分析 可用性 数据科学 市场分析 新兴技术 业务 营销 人工智能 人机交互
作者
Kisik Song,Kyuwoong Kim,Sungjoo Lee
出处
期刊:Technological Forecasting and Social Change [Elsevier BV]
卷期号:128: 118-132 被引量:70
标识
DOI:10.1016/j.techfore.2017.11.008
摘要

This study suggests a patent-based methodology for identifying emerging technologies by combining a retrospective technological feature analysis and a prospective market-needs analysis. To do this, first, the candidate promising technologies were identified by applying bibliographic coupling to patents, thus producing a list of outlier patents. Then, the measures to evaluate both technological and market characteristics of the candidate technologies were developed, where retrospective patent analysis and sentiment analysis on customer opinions are required. Finally, the candidate technologies are mapped onto two-dimensional space according to the values of the two measures; the final promising technologies are determined to be those that have high values for either technological characteristics or market characteristics. The suggested methodology was applied to an automobile industry, through which its feasibility and usability were verified. This study is one of the few studies to develop technology-evaluation measures based on an ad-hoc analysis of technological characteristics. In addition, it attempts to link patent databases to market databases, aiming to directly reflect customer needs to evaluate the potential of a technology in a market. The approach suggested in this study can be applied to recent patents with little citation information for assessing their value to be deemed as promising technologies; this is expected to contribute both academically and practically to the existing literature on patent analysis.
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