Identifying Technology Opportunity Using a Dual-attention Model and a Technology-market Concordance Matrix

Author Name MOTOHASHI Kazuyuki (Faculty Fellow, RIETI) / ZHU Chen (University of Tokyo)
Creation Date/NO. March 2023 23-E-024
Research Project Research on innovation ecosystem formation processes
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To understand the role of new technologies in innovation, it is crucial to develop a methodology that links technology and market information. Conventionally, the relationship between technology and the market has been analyzed using a technology-industry concordance matrix, but the granularity of market information is confined by industrial classification systems. In this study, we propose a new methodology for extracting keyword-level market information related to firms’ technology. Specifically, we developed a dual-attention model to identify technical keywords from firms’ websites. We then vectorized the market information (extracted keywords) and technology information (patents) using word embedding to construct technology-market concordance matrices. Matrices were generated based on a group of high-growth companies that suggest new technologies and market opportunities in the automotive, electronics, and pharmaceutical industries.

Published: Motohashi, Kazuyuki, and Chen Zhu, 2023. "Identifying technology opportunity using dual-attention model and technology-market concordance matrix," Technological Forecasting and Social Change, Volume 197 (2023), 122916.