Navigating a product landscape for technology opportunity analysis: A word2vec approach using an integrated patent-product database

Changyong Lee, Daeseong Jeon, Joon Mo Ahn and Ohjin Kwon

Technovation, 2020, vol. 96-97

Abstract: Technology opportunity analysis has been the subject of many prior studies, although most of them have focused on discovering new technology ideas in a single narrow domain. This study proposes a product landscape analysis to identify product areas (i.e., potential technology opportunities) across multiple domains that firms can enter based on the technological capabilities embodied in their existing products. First, text mining is used to construct an integrated patent-product database from the United States patent and trademark database. Second, word2vec is employed to construct a product landscape as a vector space model where products with similar technological bases are located close to each other while maintaining the technological relationships. Third, given a product of interest, potential technology opportunities are identified via (1) automatic opportunity analysis that identifies product areas with technological bases similar to those of the product; and (2) interactive opportunity analysis that finds product areas based on experts’ queries modifying the technological bases of the product (i.e., addition and subtraction). Finally, ten quantitative indexes are developed to explore the implications of the potential technology opportunities identified. The case study covering 3,016,315 patents and 160,832 products confirms that the proposed approach is valuable as a creativity support tool for technology opportunity analysis in the era of convergence.

Keywords: Technology opportunity analysis; Product landscape analysis; Word2vec; Index analysis; Integrated patent-product database (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (23)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:techno:v:96-97:y:2020:i::s0166497220300237

DOI: 10.1016/j.technovation.2020.102140

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