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A Technology Valuation Model Using Quantitative Patent Analysis: A Case Study of Technology Transfer in Big Data Marketing

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  • Sunghae Jun
  • Sangsung Park
  • Dongsik Jang

Abstract

Technology valuation (TV) is an important issue in management of technology (MOT). We use TV results for technology transfer, research and development (R&D) planning, and technology marketing. Diverse TV studies have been applied to MOT. Most of them were dependent on domain experts’ knowledge, so their TV results could be subjective and unstable. To solve this problem, we propose an objective TV model using quantitative patent analysis. In this article, we consider text mining, social network analysis, technology clustering, and descriptive statistics in constructing our TV model. To verify the performance of our model, we perform a case study of technology transfer in big data marketing.

Suggested Citation

  • Sunghae Jun & Sangsung Park & Dongsik Jang, 2015. "A Technology Valuation Model Using Quantitative Patent Analysis: A Case Study of Technology Transfer in Big Data Marketing," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 51(5), pages 963-974, September.
    • Handle: RePEc:mes:emfitr:v:51:y:2015:i:5:p:963-974
    DOI: 10.1080/1540496X.2015.1061387
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    Cited by:

    1. Eungchan Kim & Young Seok Ock & Seung-Jun Shin & Wonchul Seo, 2018. "An Approach to Generating Reference Information for Technology Evaluation," Sustainability, MDPI, vol. 10(9), pages 1-19, September.
    2. Tinôco, Daniel & Genier, Hugo Leonardo André & da Silveira, Wendel Batista, 2021. "Technology valuation of cellulosic ethanol production by Kluyveromyces marxianus CCT 7735 from sweet sorghum bagasse at elevated temperatures," Renewable Energy, Elsevier, vol. 173(C), pages 188-196.
    3. Koopo Kwon & Sungchan Jun & Yong-Jae Lee & Sanghei Choi & Chulung Lee, 2022. "Logistics Technology Forecasting Framework Using Patent Analysis for Technology Roadmap," Sustainability, MDPI, vol. 14(9), pages 1-30, April.
    4. Waßenhoven, Anna & Rennings, Michael & Laibach, Natalie & Bröring, Stefanie, 2023. "What constitutes a “Key Enabling Technology” for transition processes: Insights from the bioeconomy's technological landscape," Technological Forecasting and Social Change, Elsevier, vol. 197(C).
    5. I-Cheng Chang & Tai-Kuei Yu & Yu-Jie Chang & Tai-Yi Yu, 2021. "Applying Text Mining, Clustering Analysis, and Latent Dirichlet Allocation Techniques for Topic Classification of Environmental Education Journals," Sustainability, MDPI, vol. 13(19), pages 1-20, September.
    6. Sungchul Kim & Dongsik Jang & Sunghae Jun & Sangsung Park, 2015. "A Novel Forecasting Methodology for Sustainable Management of Defense Technology," Sustainability, MDPI, vol. 7(12), pages 1-17, December.

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