IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v12y2020i21p9084-d438373.html
   My bibliography  Save this article

Technology Fusion Characteristics in the Solar Photovoltaic Industry of South Korea: A Patent Network Analysis Using IPC Co-Occurrence

Author

Listed:
  • Sungho Son

    (Electricity Policy Research Center, Korea Electro-technology Research Institute (KERI), 138 Naesonsoonhwan-ro, Uiwang-si, Gyeonggi-do 16029, Korea
    Technology Management, Economics, and Policy Program (TEMEP), Seoul National University (SNU), Seoul 01811, Korea)

  • Nam-Wook Cho

    (Industrial and Information Systems Engineering, Seoul National University of Science and Technology (SEOUL TECH), 232 Gongneung-ro, Nowon-gu, Seoul 01811, Korea)

Abstract

This study analyzes the technology fusion phenomena and its characteristics, focusing on the solar photovoltaic (PV) industry in South Korea. Co-occurrence networks of international patent classification (IPC) codes have been analyzed based on the photovoltaic patents in South Korea during a 15-year period (2002–2016). The results reveal that, while the strength of technology fusion has greatly increased during the period, the structural pattern of fusion has been diversified or decentralized. In the early stage, widespread emergence of new technologies has been observed but, in the later stage, the focus of fusion shifted to the utilization of existing technologies. The characteristics of key technologies also changed as the technology fusion progressed. In the early stage, product technologies such as materials and components played a central role, while operation technologies such as monitor, structure, and arrangement were the drivers of fusion during the later stage.

Suggested Citation

  • Sungho Son & Nam-Wook Cho, 2020. "Technology Fusion Characteristics in the Solar Photovoltaic Industry of South Korea: A Patent Network Analysis Using IPC Co-Occurrence," Sustainability, MDPI, vol. 12(21), pages 1-19, October.
  • Handle: RePEc:gam:jsusta:v:12:y:2020:i:21:p:9084-:d:438373
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/12/21/9084/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/12/21/9084/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Yawei Wang & Frauke Urban & Yuan Zhou & Luyi Chen, 2018. "Comparing the Technology Trajectories of Solar PV and Solar Water Heaters in China: Using a Patent Lens," Sustainability, MDPI, vol. 10(11), pages 1-29, November.
    2. Foxon, Timothy J., 2013. "Transition pathways for a UK low carbon electricity future," Energy Policy, Elsevier, vol. 52(C), pages 10-24.
    3. Negro, Simona O. & Alkemade, Floortje & Hekkert, Marko P., 2012. "Why does renewable energy diffuse so slowly? A review of innovation system problems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(6), pages 3836-3846.
    4. Breschi, Stefano & Lissoni, Francesco & Malerba, Franco, 2003. "Knowledge-relatedness in firm technological diversification," Research Policy, Elsevier, vol. 32(1), pages 69-87, January.
    5. James G. March, 1991. "Exploration and Exploitation in Organizational Learning," Organization Science, INFORMS, vol. 2(1), pages 71-87, February.
    6. 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.
    7. Huang, Ping & Negro, Simona O. & Hekkert, Marko P. & Bi, Kexin, 2016. "How China became a leader in solar PV: An innovation system analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 64(C), pages 777-789.
    8. Bekkers, Rudi & Martinelli, Arianna, 2012. "Knowledge positions in high-tech markets: Trajectories, standards, strategies and true innovators," Technological Forecasting and Social Change, Elsevier, vol. 79(7), pages 1192-1216.
    9. Suzuki, Jun & Kodama, Fumio, 2004. "Technological diversity of persistent innovators in Japan: Two case studies of large Japanese firms," Research Policy, Elsevier, vol. 33(3), pages 531-549, April.
    10. Karvonen, Matti & Kässi, Tuomo, 2013. "Patent citations as a tool for analysing the early stages of convergence," Technological Forecasting and Social Change, Elsevier, vol. 80(6), pages 1094-1107.
    11. Martin, Ben R. & Nightingale, Paul & Yegros-Yegros, Alfredo, 2012. "Science and technology studies: Exploring the knowledge base," Research Policy, Elsevier, vol. 41(7), pages 1182-1204.
    12. Criscuolo, Paola & Verspagen, Bart, 2008. "Does it matter where patent citations come from? Inventor vs. examiner citations in European patents," Research Policy, Elsevier, vol. 37(10), pages 1892-1908, December.
    13. Si Hyung Joo & Yeonbae Kim, 2010. "Measuring relatedness between technological fields," Scientometrics, Springer;Akadémiai Kiadó, vol. 83(2), pages 435-454, May.
    14. Rao, K. Usha & Kishore, V.V.N., 2010. "A review of technology diffusion models with special reference to renewable energy technologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(3), pages 1070-1078, April.
    15. Kim, Kyunam & Kim, Yeonbae, 2015. "Role of policy in innovation and international trade of renewable energy technology: Empirical study of solar PV and wind power technology," Renewable and Sustainable Energy Reviews, Elsevier, vol. 44(C), pages 717-727.
    16. Kim, Heetae & Park, Eunil & Kwon, Sang Jib & Ohm, Jay Y. & Chang, Hyun Joon, 2014. "An integrated adoption model of solar energy technologies in South Korea," Renewable Energy, Elsevier, vol. 66(C), pages 523-531.
    17. Ernst, Holger, 2003. "Patent information for strategic technology management," World Patent Information, Elsevier, vol. 25(3), pages 233-242, September.
    18. Mina, A. & Ramlogan, R. & Tampubolon, G. & Metcalfe, J.S., 2007. "Mapping evolutionary trajectories: Applications to the growth and transformation of medical knowledge," Research Policy, Elsevier, vol. 36(5), pages 789-806, June.
    19. Park, Noeon & Lee, Ki Jong & Lee, Kyong Jae & Lee, Yun Jie & Lee, Kyoungmi & Lee, Sang Hyon, 2013. "In-depth analysis on R&D investment and strategy on PV in South Korea," Energy Policy, Elsevier, vol. 54(C), pages 391-396.
    20. Park, Eunil, 2017. "Potentiality of renewable resources: Economic feasibility perspectives in South Korea," Renewable and Sustainable Energy Reviews, Elsevier, vol. 79(C), pages 61-70.
    21. Weiwei Liu & Yuan Tao & Zhile Yang & Kexin Bi, 2019. "Exploring and Visualizing the Patent Collaboration Network: A Case Study of Smart Grid Field in China," Sustainability, MDPI, vol. 11(2), pages 1-18, January.
    22. Tijssen, Robert J. W., 1992. "A quantitative assessment of interdisciplinary structures in science and technology: Co-classification analysis of energy research," Research Policy, Elsevier, vol. 21(1), pages 27-44, February.
    23. Maleki, Ali & Rosiello, Alessandro, 2019. "Does knowledge base complexity affect spatial patterns of innovation? An empirical analysis in the upstream petroleum industry," Technological Forecasting and Social Change, Elsevier, vol. 143(C), pages 273-288.
    24. Shu-Hao Chang & Chin-Yuan Fan, 2020. "Using Patent Technology Networks to Observe Neurocomputing Technology Hotspots and Development Trends," Sustainability, MDPI, vol. 12(18), pages 1-15, September.
    25. Lee, Won Sang & Han, Eun Jin & Sohn, So Young, 2015. "Predicting the pattern of technology convergence using big-data technology on large-scale triadic patents," Technological Forecasting and Social Change, Elsevier, vol. 100(C), pages 317-329.
    26. Ryu, Hanee & Dorjragchaa, Shonkhor & Kim, Yeonbae & Kim, Kyunam, 2014. "Electricity-generation mix considering energy security and carbon emission mitigation: Case of Korea and Mongolia," Energy, Elsevier, vol. 64(C), pages 1071-1079.
    27. Kumar Sahu, Bikash, 2015. "A study on global solar PV energy developments and policies with special focus on the top ten solar PV power producing countries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 43(C), pages 621-634.
    28. Choi, David & Valikangas, Liisa, 2001. "Patterns of strategy innovation," European Management Journal, Elsevier, vol. 19(4), pages 424-429, August.
    29. Ghimire, Laxman Prasad & Kim, Yeonbae, 2018. "An analysis on barriers to renewable energy development in the context of Nepal using AHP," Renewable Energy, Elsevier, vol. 129(PA), pages 446-456.
    30. Lizin, Sebastien & Leroy, Julie & Delvenne, Catherine & Dijk, Marc & De Schepper, Ellen & Van Passel, Steven, 2013. "A patent landscape analysis for organic photovoltaic solar cells: Identifying the technology's development phase," Renewable Energy, Elsevier, vol. 57(C), pages 5-11.
    31. Wieczorek, Anna J. & Negro, Simona O. & Harmsen, Robert & Heimeriks, Gaston J. & Luo, Lin & Hekkert, Marko P., 2013. "A review of the European offshore wind innovation system," Renewable and Sustainable Energy Reviews, Elsevier, vol. 26(C), pages 294-306.
    32. Zhang, Sufang & Zhao, Xiaoli & Andrews-Speed, Philip & He, Yongxiu, 2013. "The development trajectories of wind power and solar PV power in China: A comparison and policy recommendations," Renewable and Sustainable Energy Reviews, Elsevier, vol. 26(C), pages 322-331.
    33. Dusonchet, L. & Telaretti, E., 2015. "Comparative economic analysis of support policies for solar PV in the most representative EU countries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 42(C), pages 986-998.
    34. Caviggioli, Federico, 2016. "Technology fusion: Identification and analysis of the drivers of technology convergence using patent data," Technovation, Elsevier, vol. 55, pages 22-32.
    35. Zhang, Sufang & He, Yongxiu, 2013. "Analysis on the development and policy of solar PV power in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 21(C), pages 393-401.
    36. Constant, Edward II, 2002. "Why evolution is a theory about stability: constraint, causation, and ecology in technological change," Research Policy, Elsevier, vol. 31(8-9), pages 1241-1256, December.
    37. Barton, John & Davies, Lloyd & Dooley, Ben & Foxon, Timothy J. & Galloway, Stuart & Hammond, Geoffrey P. & O’Grady, Áine & Robertson, Elizabeth & Thomson, Murray, 2018. "Transition pathways for a UK low-carbon electricity system: Comparing scenarios and technology implications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 2779-2790.
    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. Ruifeng Hu & Weiqiao Xu, 2022. "Exploring the Technological Changes of Green Agriculture in China: Evidence from Patent Data (1998–2021)," Sustainability, MDPI, vol. 14(17), pages 1-18, August.
    2. Su, Yu-Shan & Huang, Hsini & Daim, Tugrul & Chien, Pan-Wei & Peng, Ru-Ling & Karaman Akgul, Arzu, 2023. "Assessing the technological trajectory of 5G-V2X autonomous driving inventions: Use of patent analysis," Technological Forecasting and Social Change, Elsevier, vol. 196(C).
    3. Yong-Jae Lee & Young Jae Han & Sang-Soo Kim & Chulung Lee, 2022. "Patent Data Analytics for Technology Forecasting of the Railway Main Transformer," Sustainability, MDPI, vol. 15(1), pages 1-25, December.
    4. Song, Haoyang & Hou, Jianhua & Zhang, Yang, 2023. "The measurements and determinants of patent technological value: Lifetime, strength, breadth, and dispersion from the technology diffusion perspective," Journal of Informetrics, Elsevier, vol. 17(1).
    5. Sick, Nathalie & Bröring, Stefanie, 2022. "Exploring the research landscape of convergence from a TIM perspective: A review and research agenda," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
    6. Haoyang Song & Jianhua Hou & Yang Zhang, 2022. "Patent protection: does it promote or inhibit the patented technological knowledge diffusion?," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(5), pages 2351-2379, May.

    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. Su, Yu-Shan & Huang, Hsini & Daim, Tugrul & Chien, Pan-Wei & Peng, Ru-Ling & Karaman Akgul, Arzu, 2023. "Assessing the technological trajectory of 5G-V2X autonomous driving inventions: Use of patent analysis," Technological Forecasting and Social Change, Elsevier, vol. 196(C).
    2. Jungpyo Lee & So Young Sohn, 2021. "Recommendation system for technology convergence opportunities based on self-supervised representation learning," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(1), pages 1-25, January.
    3. Xiong, Yongqing & Yang, Xiaohan, 2016. "Government subsidies for the Chinese photovoltaic industry," Energy Policy, Elsevier, vol. 99(C), pages 111-119.
    4. Ying Tang & Xuming Lou & Zifeng Chen & Chengjin Zhang, 2020. "A Study on Dynamic Patterns of Technology Convergence with IPC Co-Occurrence-Based Analysis: The Case of 3D Printing," Sustainability, MDPI, vol. 12(7), pages 1-26, March.
    5. 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.
    6. Carlo Giglio & Roberto Sbragia & Roberto Musmanno & Roberto Palmieri, 2021. "Cross-country learning from patents: an analysis of citations flows in innovation trajectories," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(9), pages 7917-7936, September.
    7. Carlo Giglio & Gianluca Salvatore Vocaturo & Roberto Palmieri, 2023. "Patent Acquisitions in the Healthcare Industry: An Analysis of Learning Mechanisms," IJERPH, MDPI, vol. 20(5), pages 1-13, February.
    8. Higham, Kyle & Contisciani, Martina & De Bacco, Caterina, 2022. "Multilayer patent citation networks: A comprehensive analytical framework for studying explicit technological relationships," Technological Forecasting and Social Change, Elsevier, vol. 179(C).
    9. Yuan Zhou & Meijuan Pan & Frauke Urban, 2018. "Comparing the International Knowledge Flow of China’s Wind and Solar Photovoltaic (PV) Industries: Patent Analysis and Implications for Sustainable Development," Sustainability, MDPI, vol. 10(6), pages 1-34, June.
    10. Corradini, Carlo & De Propris, Lisa, 2017. "Beyond local search: Bridging platforms and inter-sectoral technological integration," Research Policy, Elsevier, vol. 46(1), pages 196-206.
    11. 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.
    12. Seongkyoon Jeong & Jong-Chan Kim & Jae Young Choi, 2015. "Technology convergence: What developmental stage are we in?," Scientometrics, Springer;Akadémiai Kiadó, vol. 104(3), pages 841-871, September.
    13. Sick, Nathalie & Preschitschek, Nina & Leker, Jens & Bröring, Stefanie, 2019. "A new framework to assess industry convergence in high technology environments," Technovation, Elsevier, vol. 84, pages 48-58.
    14. Song, Kisik & Kim, Kyuwoong & Lee, Sungjoo, 2018. "Identifying promising technologies using patents: A retrospective feature analysis and a prospective needs analysis on outlier patents," Technological Forecasting and Social Change, Elsevier, vol. 128(C), pages 118-132.
    15. Nicola Melluso & Andrea Bonaccorsi & Filippo Chiarello & Gualtiero Fantoni, 2021. "Rapid detection of fast innovation under the pressure of COVID-19," Papers 2102.00197, arXiv.org.
    16. Feng Zhang & Guohua Jiang, 2019. "Combination of Complementary Technological Knowledge to Generate “Hard to Imitate” Technologies," Journal of Information & Knowledge Management (JIKM), World Scientific Publishing Co. Pte. Ltd., vol. 18(02), pages 1-24, June.
    17. Park, Mingyu & Geum, Youngjung, 2022. "Two-stage technology opportunity discovery for firm-level decision making: GCN-based link-prediction approach," Technological Forecasting and Social Change, Elsevier, vol. 183(C).
    18. Ifaei, Pouya & Tayerani Charmchi, Amir Saman & Loy-Benitez, Jorge & Yang, Rebecca Jing & Yoo, ChangKyoo, 2022. "A data-driven analytical roadmap to a sustainable 2030 in South Korea based on optimal renewable microgrids," Renewable and Sustainable Energy Reviews, Elsevier, vol. 167(C).
    19. Martin Kalthaus, 2020. "Knowledge recombination along the technology life cycle," Journal of Evolutionary Economics, Springer, vol. 30(3), pages 643-704, July.
    20. 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.

    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:gam:jsusta:v:12:y:2020:i:21:p:9084-:d:438373. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.