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Lee, Changyong
Technology and Innovation Management Lab
Research Interests
  • applied data mining and machine learning, technology and innovation management, service engineering

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Valuation of University-Originated Technologies: A Predictive Analytics Approach

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Title
Valuation of University-Originated Technologies: A Predictive Analytics Approach
Author
Kim, Young-ChoonAhn, Joon MoKwon, OhjinLee, Changyong
Issue Date
2019-09
Publisher
Institute of Electrical and Electronics Engineers
Citation
IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT, pp.1 - 13
Abstract
Experts have difficulty assessing the economic value of university-originated technologies due to the high level of uncertainty associated with the commercialization of early stage and basic technologies. This article proposes a random forest approach to the valuation of university-originated technologies that integrates monetary value and patent value models for technology valuation. First, a technological characteristics-value matrix was constructed after defining a total of 23 indicators from the U.S. Patent and Trademark and Scopus databases and extracting the value of university-originated technologies from technology transaction databases. Second, a random forest model, an ensemble machine learning model based on a multitude of decision trees, was employed to assess the economic value of university-originated technologies. Finally, the performance of our approach was assessed using quantitative metrics. A case study of the technologies registered in the Office of Technology Licensing of Stanford University confirms, with statistically significant outcomes, that our method is valuable as a complementary tool for the valuation of university-originated technologies.
URI
https://scholarworks.unist.ac.kr/handle/201301/27784
URL
https://ieeexplore.ieee.org/document/8844800
DOI
10.1109/TEM.2019.2938182
ISSN
0018-9391
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