Investigating technology opportunities: the use of SAOx analysis

Kyuwoong Kim (), Kyeongmin Park () and Sungjoo Lee ()
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Kyuwoong Kim: Ajou University
Kyeongmin Park: Ajou University
Sungjoo Lee: Ajou University

Scientometrics, 2019, vol. 118, issue 1, No 3, 45-70

Abstract: Abstract A patent is regarded as one of the most reliable data sources to investigate such opportunities and has been analyzed in numerous ways. The recent trend of patent analysis has focused on the unstructured part of patent information to extract detailed technological information. In particular, information regarding the purpose or effect of technology, which can be pulled from the unstructured part of patent information, is expected to offer useful insights into expanding its application to other areas. Some previous attempts have been made to systematically use this information to identify new technology opportunities, partly due to difficulties in analyzing the unstructured text data in patent documents. To overcome the limitations of previous studies, this study aims to develop a new method, namely Subject–Action–Object–others (SAOx), which enables an in-depth examination of the purpose and effect of the technology in an efficient manner by analyzing “for” and “to” phrases as well as gerund forms for an object element. We also introduce 39 engineering parameters of TRIZ and technology-designative terms of patent documents to define SAO sets and improve information accuracy. The proposed method is applied to human–machine interaction technologies to understand technology trends and explore technology opportunities based on topic modeling. Methodologically, the research findings contribute to patent engineering by extending the range of information extracted from patent information. Practically, the proposed approach will support corporate decision making in R&D investment by providing comprehensive information regarding the purpose or effect of technology in a structured form, fully extracted from patent documents.

Keywords: Technology opportunity; Patent; SAO analysis; Topic modeling; 68; W (search for similar items in EconPapers)
JEL-codes: O32 O34 (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (5)

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DOI: 10.1007/s11192-018-2962-9

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