IDEAS home Printed from https://ideas.repec.org/a/spr/scient/v101y2014i1d10.1007_s11192-014-1343-2.html
   My bibliography  Save this article

Analyzing technology impact networks for R&D planning using patents: combined application of network approaches

Author

Listed:
  • Sung-Seok Ko

    (Konkuk University)

  • Namuk Ko

    (Konkuk University)

  • Doyeon Kim

    (Konkuk University)

  • Hyunseok Park

    (Pohang University of Science and Technology)

  • Janghyeok Yoon

    (Konkuk University)

Abstract

Recently, national governments have tried to improve technology ecology, by formulating research and development (R&D) policies and investing in R&D programs. For strategically designed national R&D plans, analytic approaches that identify and assess the impact of each technology from short-term and long-term perspectives are necessary. Further, in methodological perspective, the approaches should be able to synthetically consider the most recent technological information, the direct and hidden impacts among technologies, and the relative impacts of the focal technology in globally-linked technological relationship from the overall perspective. However, most previous studies based patent citation networks are insufficient for these requirements. As a remedy, we present a combined approach for constructing a technology impact network and identifying the impact and intermediating capability of technology areas from the perspective of a national technology system. To construct and analyze the technology impact network, our method integrates three network techniques: patent co-classification (PCA), decision making trial and evaluation laboratory (DEMATEL), and social network analysis (SNA). The advantages of the proposed method are threefold. First, it identifies the directed technological knowledge flows from the most recent patents, by employing PCA. Second, the proposed network contains both the direct and indirect impacts among different technology areas, by applying the DEMATEL method. Third, using SNA, the method can analyze the characteristics of the technologies in terms of the comprehensive impacts and the potential brokerage capabilities. The method is illustrated using all of the recent Korean patents (58,279) in the United States patent database from 2008 to 2012. We expect that our method can be used to provide input to decision makers for effective R&D planning.

Suggested Citation

  • Sung-Seok Ko & Namuk Ko & Doyeon Kim & Hyunseok Park & Janghyeok Yoon, 2014. "Analyzing technology impact networks for R&D planning using patents: combined application of network approaches," Scientometrics, Springer;Akadémiai Kiadó, vol. 101(1), pages 917-936, October.
  • Handle: RePEc:spr:scient:v:101:y:2014:i:1:d:10.1007_s11192-014-1343-2
    DOI: 10.1007/s11192-014-1343-2
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11192-014-1343-2
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s11192-014-1343-2?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Jiménez-Sáez, Fernando & Zabala-Iturriagagoitia, Jon Mikel & Zofío, José L. & Castro-Martínez, Elena, 2011. "Evaluating research efficiency within National R&D Programmes," Research Policy, Elsevier, vol. 40(2), pages 230-241, March.
    2. Roberto Fontana & Alessandro Nuvolari & Bart Verspagen, 2009. "Mapping technological trajectories as patent citation networks. An application to data communication standards," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 18(4), pages 311-336.
    3. Bart Verspagen, 2007. "Mapping Technological Trajectories As Patent Citation Networks: A Study On The History Of Fuel Cell Research," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 10(01), pages 93-115.
    4. Hsin‐Ning Su, 2012. "Visualization of global science and technology policy research structure," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 63(2), pages 242-255, February.
    5. G. M.P. Swann, 2009. "The Economics of Innovation," Books, Edward Elgar Publishing, number 13211.
    6. Erjia Yan & Ying Ding, 2012. "Scholarly network similarities: How bibliographic coupling networks, citation networks, cocitation networks, topical networks, coauthorship networks, and coword networks relate to each other," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 63(7), pages 1313-1326, July.
    7. Erjia Yan & Ying Ding, 2012. "Scholarly network similarities: How bibliographic coupling networks, citation networks, cocitation networks, topical networks, coauthorship networks, and coword networks relate to each other," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 63(7), pages 1313-1326, July.
    8. Sternitzke, Christian & Bartkowski, Adam & Schramm, Reinhard, 2008. "Visualizing patent statistics by means of social network analysis tools," World Patent Information, Elsevier, vol. 30(2), pages 115-131, June.
    9. Garcia, Abraham & Mohnen, Pierre, 2010. "Impact of government support on R&D and innovation," MERIT Working Papers 2010-034, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
    10. Euiseok Kim & Yongrae Cho & Wonjoon Kim, 2014. "Dynamic patterns of technological convergence in printed electronics technologies: patent citation network," Scientometrics, Springer;Akadémiai Kiadó, vol. 98(2), pages 975-998, February.
    11. Hyojeong Lim & Yongtae Park, 2010. "Identification of technological knowledge intermediaries," Scientometrics, Springer;Akadémiai Kiadó, vol. 84(3), pages 543-561, September.
    12. Péter Érdi & Kinga Makovi & Zoltán Somogyvári & Katherine Strandburg & Jan Tobochnik & Péter Volf & László Zalányi, 2013. "Prediction of emerging technologies based on analysis of the US patent citation network," Scientometrics, Springer;Akadémiai Kiadó, vol. 95(1), pages 225-242, April.
    13. Breschi, Stefano & Lissoni, Francesco & Malerba, Franco, 2003. "Knowledge-relatedness in firm technological diversification," Research Policy, Elsevier, vol. 32(1), pages 69-87, January.
    14. Hyunseok Park & Janghyeok Yoon, 2014. "Assessing coreness and intermediarity of technology sectors using patent co-classification analysis: the case of Korean national R&D," Scientometrics, Springer;Akadémiai Kiadó, vol. 98(2), pages 853-890, February.
    15. Massimo Franceschet, 2011. "Collaboration in computer science: A network science approach," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 62(10), pages 1992-2012, October.
    16. Foray, D. & Mowery, D.C. & Nelson, R.R., 2012. "Public R&D and social challenges: What lessons from mission R&D programs?," Research Policy, Elsevier, vol. 41(10), pages 1697-1702.
    17. Wen-Hsien Tsai & Wen-Chin Chou, 2010. "Building an integrated multi-criteria decision-making model based on DEMATEL and ANP for selecting the risk management system of banking," International Journal of Management and Enterprise Development, Inderscience Enterprises Ltd, vol. 8(4), pages 358-382.
    18. Janghyeok Yoon & Kwangsoo Kim, 2011. "Identifying rapidly evolving technological trends for R&D planning using SAO-based semantic patent networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 88(1), pages 213-228, July.
    19. Shin, Juneseuk & Park, Yongtae, 2007. "Building the national ICT frontier: The case of Korea," Information Economics and Policy, Elsevier, vol. 19(2), pages 249-277, June.
    20. Shiu-Wan Hung & An-Pang Wang, 2010. "Examining the small world phenomenon in the patent citation network: a case study of the radio frequency identification (RFID) network," Scientometrics, Springer;Akadémiai Kiadó, vol. 82(1), pages 121-134, January.
    21. Bart Verspagen, 1997. "Measuring Intersectoral Technology Spillovers: Estimates from the European and US Patent Office Databases," Economic Systems Research, Taylor & Francis Journals, vol. 9(1), pages 47-65.
    22. Choi, Jin Young & Lee, Jong Ha & Sohn, So Young, 2009. "Impact analysis for national R&D funding in science and technology using quantification method II," Research Policy, Elsevier, vol. 38(10), pages 1534-1544, December.
    23. Robert J. W. Tijssen & Thed N. Van Leeuwen, 2006. "Measuring impacts of academic science on industrial research: A citation-based approach," Scientometrics, Springer;Akadémiai Kiadó, vol. 66(1), pages 55-69, January.
    24. Massimo Franceschet, 2011. "Collaboration in computer science: A network science approach," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 62(10), pages 1992-2012, October.
    25. Ta-Shun Cho & Hsin-Yu Shih, 2011. "Patent citation network analysis of core and emerging technologies in Taiwan: 1997–2008," Scientometrics, Springer;Akadémiai Kiadó, vol. 89(3), pages 795-811, December.
    26. Lee, Hakyeon & Park, Yongtae & Choi, Hoogon, 2009. "Comparative evaluation of performance of national R&D programs with heterogeneous objectives: A DEA approach," European Journal of Operational Research, Elsevier, vol. 196(3), pages 847-855, August.
    27. Hsin-Ning Su, 2012. "Visualization of global science and technology policy research structure," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 63(2), pages 242-255, February.
    28. Lee, Sungjoo & Kim, Moon-Soo & Park, Yongtae, 0. "ICT Co-evolution and Korean ICT strategy--An analysis based on patent data," Telecommunications Policy, Elsevier, vol. 33(5-6), pages 253-271, June.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Seo, Wonchul & Yoon, Janghyeok & Park, Hyunseok & Coh, Byoung-youl & Lee, Jae-Min & Kwon, Oh-Jin, 2016. "Product opportunity identification based on internal capabilities using text mining and association rule mining," Technological Forecasting and Social Change, Elsevier, vol. 105(C), pages 94-104.
    2. Mun, Changbae & Yoon, Sejun & Raghavan, Nagarajan & Hwang, Dongwook & Basnet, Subarna & Park, Hyunseok, 2021. "Function score-based technological trend analysis," Technovation, Elsevier, vol. 101(C).
    3. Chie Hoon Song, 2021. "Exploring and Predicting the Knowledge Development in the Field of Energy Storage: Evidence from the Emerging Startup Landscape," Energies, MDPI, vol. 14(18), pages 1-20, September.
    4. Chenlei Guan & Damin Dong & Feng Shen & Xin Gao & Linyan Chen, 2022. "Hierarchical Structure Model of Safety Risk Factors in New Coastal Towns: A Systematic Analysis Using the DEMATEL-ISM-SNA Method," IJERPH, MDPI, vol. 19(17), pages 1-17, August.
    5. Shu-Hao Chang, 2022. "Examining Key Technologies Among Academic Patents Through an Analysis of Standard-Essential Patents," SAGE Open, , vol. 12(3), pages 21582440221, July.
    6. Aaldering, Lukas Jan & Leker, Jens & Song, Chie Hoon, 2019. "Uncovering the dynamics of market convergence through M&A," Technological Forecasting and Social Change, Elsevier, vol. 138(C), pages 95-114.
    7. Seung-Jun Shin & Wonchul Seo, 2017. "Identifying new technology areas based on firm’s internal capabilities," Journal of Administrative and Business Studies, Professor Dr. Usman Raja, vol. 3(3), pages 114-121.
    8. Worasak Klongthong & Veera Muangsin & Chupun Gowanit & Nongnuj Muangsin, 2021. "A Patent Analysis to Identify Emergent Topics and Convergence Fields: A Case Study of Chitosan," Sustainability, MDPI, vol. 13(16), pages 1-28, August.
    9. Jungkyu Park & Eunnyeong Heo & Dongjun Lee, 2017. "Effective R&D investment planning based on technology spillovers: the case of Korea," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(1), pages 67-82, April.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ying Huang & Donghua Zhu & Yue Qian & Yi Zhang & Alan L. Porter & Yuqin Liu & Ying Guo, 2017. "A hybrid method to trace technology evolution pathways: a case study of 3D printing," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(1), pages 185-204, April.
    2. Euiseok Kim & Yongrae Cho & Wonjoon Kim, 2014. "Dynamic patterns of technological convergence in printed electronics technologies: patent citation network," Scientometrics, Springer;Akadémiai Kiadó, vol. 98(2), pages 975-998, February.
    3. Huang, Ying & Li, Ruinan & Zou, Fang & Jiang, Lidan & Porter, Alan L. & Zhang, Lin, 2022. "Technology life cycle analysis: From the dynamic perspective of patent citation networks," Technological Forecasting and Social Change, Elsevier, vol. 181(C).
    4. Antonelli, Cristiano & Krafft, Jackie & Quatraro, Francesco, 2010. "Recombinant knowledge and growth: The case of ICTs," Structural Change and Economic Dynamics, Elsevier, vol. 21(1), pages 50-69, March.
    5. Adam B. Jaffe & Gaétan de Rassenfosse, 2017. "Patent citation data in social science research: Overview and best practices," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 68(6), pages 1360-1374, June.
    6. Patrick Wolf & Tobias Buchmann, 2021. "Analyzing development patterns in research networks and technology," Review of Evolutionary Political Economy, Springer, vol. 2(1), pages 55-81, April.
    7. Malhotra, Abhishek & Zhang, Huiting & Beuse, Martin & Schmidt, Tobias, 2021. "How do new use environments influence a technology's knowledge trajectory? A patent citation network analysis of lithium-ion battery technology," Research Policy, Elsevier, vol. 50(9).
    8. Calvin Weng & Tugrul Daim, 2012. "Structural Differentiation and Its Implications—Core/Periphery Structure of the Technological Network," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 3(4), pages 327-342, December.
    9. Hyunseok Park & Janghyeok Yoon, 2014. "Assessing coreness and intermediarity of technology sectors using patent co-classification analysis: the case of Korean national R&D," Scientometrics, Springer;Akadémiai Kiadó, vol. 98(2), pages 853-890, February.
    10. Su, Hsin-Ning & Moaniba, Igam M., 2017. "Investigating the dynamics of interdisciplinary evolution in technology developments," Technological Forecasting and Social Change, Elsevier, vol. 122(C), pages 12-23.
    11. Martinelli, Arianna, 2012. "An emerging paradigm or just another trajectory? Understanding the nature of technological changes using engineering heuristics in the telecommunications switching industry," Research Policy, Elsevier, vol. 41(2), pages 414-429.
    12. Roman Jurowetzki, 2015. "Unpacking Big Systems - Natural Language Processing meets Network Analysis. A Study of Smart Grid Development in Denmark," SPRU Working Paper Series 2015-15, SPRU - Science Policy Research Unit, University of Sussex Business School.
    13. Ren, Haiying & Zhao, Yuhui, 2021. "Technology opportunity discovery based on constructing, evaluating, and searching knowledge networks," Technovation, Elsevier, vol. 101(C).
    14. Ichiro Watanabe & Soichiro Takagi, 2021. "Technological Trajectory Analysis of Patent Citation Networks: Examining the Technological Evolution of Computer Graphic Processing Systems," The Review of Socionetwork Strategies, Springer, vol. 15(1), pages 1-25, June.
    15. Kim, Dong-hyu & Lee, Heejin & Kwak, Jooyoung, 2017. "Standards as a driving force that influences emerging technological trajectories in the converging world of the Internet and things: An investigation of the M2M/IoT patent network," Research Policy, Elsevier, vol. 46(7), pages 1234-1254.
    16. Zhong, Sheng & Verspagen, Bart, 2016. "The role of technological trajectories in catching-up-based development: An application to energy efficiency technologies," MERIT Working Papers 2016-013, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
    17. van der Have, Robert P. & Rubalcaba, Luis, 2016. "Social innovation research: An emerging area of innovation studies?," Research Policy, Elsevier, vol. 45(9), pages 1923-1935.
    18. Guan, Jiancheng & Liu, Na, 2015. "Invention profiles and uneven growth in the field of emerging nano-energy," Energy Policy, Elsevier, vol. 76(C), pages 146-157.
    19. Arianna Martinelli & Önder Nomaler, 2014. "Measuring knowledge persistence: a genetic approach to patent citation networks," Journal of Evolutionary Economics, Springer, vol. 24(3), pages 623-652, July.
    20. Flavia Filippin, 2021. "Do main paths reflect technological trajectories? Applying main path analysis to the semiconductor manufacturing industry," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(8), pages 6443-6477, August.

    More about this item

    Keywords

    Patent analysis; Technology impact network; Patent co-classification analysis; DEMATEL; Social network analysis; R&D planning;
    All these keywords.

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • C82 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Macroeconomic Data; Data Access

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:scient:v:101:y:2014:i:1:d:10.1007_s11192-014-1343-2. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.