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Patent-Enhancing Strategies by Industry in Korea Using a Data Envelopment Analysis

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  • BangRae Lee

    (Department of Electrical and Computer Engineering, The Graduate School of the University of Seoul, 163 Seoulsiripdaero, Dongdaemun-gu, Seoul 02504, Korea
    Korea Institute of Science and Technology Information, 66 Hoegiro, Dongdaemun-gu, Seoul 02456, Korea)

  • DongKyu Won

    (Korea Institute of Science and Technology Information, 66 Hoegiro, Dongdaemun-gu, Seoul 02456, Korea)

  • Jun-Hwan Park

    (Korea Institute of Science and Technology Information, 66 Hoegiro, Dongdaemun-gu, Seoul 02456, Korea)

  • LeeNam Kwon

    (Korea Institute of Science and Technology Information, 66 Hoegiro, Dongdaemun-gu, Seoul 02456, Korea)

  • Young-Ho Moon

    (Korea Institute of Science and Technology Information, 66 Hoegiro, Dongdaemun-gu, Seoul 02456, Korea)

  • Han-Joon Kim

    (Department of Electrical and Computer Engineering, The Graduate School of the University of Seoul, 163 Seoulsiripdaero, Dongdaemun-gu, Seoul 02504, Korea)

Abstract

Global competition has increased the importance of patents as a means to protect and strengthen technology and competitiveness. The purposes of our study were to identify what industries in South Korea are strong or weak in terms of patent applications and to identify some strategies to enable weak industries to become strong. For this, we gathered statistics on seven variables as follows: number of businesses, number of employees, research and development investment, number of full-time equivalent researchers, number of research institutions, domestic market size, and number of patent applications. Especially, to compare the ratio of patent applications and the ratio of domestic market size across industries, the industries were classified into the following three categories: strong-, weak-, and no-patent. Furthermore, data envelopment analysis (DEA) suggested some strategies to strengthen patent applications for each industry. In the DEA analysis, the number of patent applications was used as the output variable and the other six variables were used as input variables. Our study will particularly assist industries where protection by patents is an important aspect of their businesses.

Suggested Citation

  • BangRae Lee & DongKyu Won & Jun-Hwan Park & LeeNam Kwon & Young-Ho Moon & Han-Joon Kim, 2016. "Patent-Enhancing Strategies by Industry in Korea Using a Data Envelopment Analysis," Sustainability, MDPI, vol. 8(9), pages 1-17, September.
    • Handle: RePEc:gam:jsusta:v:8:y:2016:i:9:p:901-:d:77490
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    References listed on IDEAS

    as
    1. Grimaldi, Michele & Cricelli, Livio & Di Giovanni, Martina & Rogo, Francesco, 2015. "The patent portfolio value analysis: A new framework to leverage patent information for strategic technology planning," Technological Forecasting and Social Change, Elsevier, vol. 94(C), pages 286-302.
    2. Janusz A. Ordover, 1991. "A Patent System for Both Diffusion and Exclusion," Journal of Economic Perspectives, American Economic Association, vol. 5(1), pages 43-60, Winter.
    3. Jae Young Choi & Seongkyoon Jeong & Kyunam Kim, 2015. "A Study on Diffusion Pattern of Technology Convergence: Patent Analysis for Korea," Sustainability, MDPI, vol. 7(9), pages 1-24, August.
    4. Sangsung Park & Seung-Joo Lee & Sunghae Jun, 2015. "A Network Analysis Model for Selecting Sustainable Technology," Sustainability, MDPI, vol. 7(10), pages 1-16, September.
    5. Jean O. Lanjouw & Ariel Pakes & Jonathan Putnam, 1998. "How to Count Patents and Value Intellectual Property: The Uses of Patent Renewal and Application Data," Journal of Industrial Economics, Wiley Blackwell, vol. 46(4), pages 405-432, December.
    6. Jaehyun Choi & Dongsik Jang & Sunghae Jun & Sangsung Park, 2015. "A Predictive Model of Technology Transfer Using Patent Analysis," Sustainability, MDPI, vol. 7(12), pages 1-21, December.
    7. Lanjouw, Jean O & Pakes, Ariel & Putnam, Jonathan, 1998. "How to Count Patents and Value Intellectual Property: The Uses of Patent Renewal and Application Data," Journal of Industrial Economics, Wiley Blackwell, vol. 46(4), pages 405-432, December.
    8. Nicky J. Welton & Howard H. Z. Thom, 2015. "Value of Information," Medical Decision Making, , vol. 35(5), pages 564-566, July.
    9. Goldin,Ian & Winters,L. Alan (ed.), 1995. "The Economics of Sustainable Development," Cambridge Books, Cambridge University Press, number 9780521469579.
    10. Keeeun Lee & Inchae Park & Byungun Yoon, 2016. "An Approach for R&D Partner Selection in Alliances between Large Companies, and Small and Medium Enterprises (SMEs): Application of Bayesian Network and Patent Analysis," Sustainability, MDPI, vol. 8(2), pages 1-18, January.
    11. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
    12. Inchae Park & Keeeun Lee & Byungun Yoon, 2015. "Exploring Promising Research Frontiers Based on Knowledge Maps in the Solar Cell Technology Field," Sustainability, MDPI, vol. 7(10), pages 1-30, October.
    13. Charnes, A. & Cooper, W. W. & Rhodes, E., 1979. "Measuring the efficiency of decision-making units," European Journal of Operational Research, Elsevier, vol. 3(4), pages 339-338, July.
    14. Jean O. Lanjouw & Mark Schankerman, 2004. "Patent Quality and Research Productivity: Measuring Innovation with Multiple Indicators," Economic Journal, Royal Economic Society, vol. 114(495), pages 441-465, April.
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    4. Chia-Nan Wang & Thanh-Tuan Dang & Ngoc-Ai-Thy Nguyen & Thi-Thu-Hong Le, 2020. "Supporting Better Decision-Making: A Combined Grey Model and Data Envelopment Analysis for Efficiency Evaluation in E-Commerce Marketplaces," Sustainability, MDPI, vol. 12(24), pages 1-24, December.
    5. Jong-Min Kim & Bainwen Sun & Sunghae Jun, 2019. "Sustainable Technology Analysis Using Data Envelopment Analysis and State Space Models," Sustainability, MDPI, vol. 11(13), pages 1-19, June.
    6. JinHyo Joseph Yun & Tan Yigitcanlar, 2017. "Open Innovation in Value Chain for Sustainability of Firms," Sustainability, MDPI, vol. 9(5), pages 1-8, May.
    7. Xiaochuan Shi & Lei Wu & Xiaoliang Meng, 2017. "A New Optimization Model for the Sustainable Development: Quadratic Knapsack Problem with Conflict Graphs," Sustainability, MDPI, vol. 9(2), pages 1-10, February.
    8. Shuichiro Kajima & Yuta Uchiyama & Ryo Kohsaka, 2020. "Intellectual Property Strategies for Timber and Forest Products: The Case of Regional Collective Trademark Applications by Japanese Forestry Associations," Sustainability, MDPI, vol. 12(5), pages 1-16, March.

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