Inventor–licensee matchmaking for university technology licensing: A fastText approach

Gyumin Lee, Sungjun Lee and Changyong Lee

Technovation, 2023, vol. 125, issue C

Abstract: Although many previous studies have explored university technology licensing, few have examined the value of quantitative data and scientific methods in improving operational efficiency. Focusing on the marketing phase of university technology licensing processes, this study proposes an analytical framework for inventor–licensee matchmaking by linking technological functions and business requirements. The proposed framework utilises fastText to construct a technological function-business requirement landscape, where similar technological functions and business requirements are located in close proximity. Potential pairs of inventors and licensees for technology licensing are identified through similarity analysis based on the constructed landscape. To validate the framework's effectiveness, an inventor-licensee matching rate is calculated by comparing the matchmaking results to actual technology licensing contracts. A case study covering 16,517 disclosed inventions and 565 licensed technologies from Sogang University confirms that the proposed analytical framework is useful in identifying potential inventor–licensee pairs. It can serve as a valuable complementary tool for university technology licensing in the era of open innovation.

Keywords: University technology licensing; Inventor–licensee matchmaking; Technological function; Business requirement; FastText (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:eee:techno:v:125:y:2023:i:c:s0166497223000767

DOI: 10.1016/j.technovation.2023.102765

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