IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v14y2021i18p5822-d635540.html
   My bibliography  Save this article

Exploring and Predicting the Knowledge Development in the Field of Energy Storage: Evidence from the Emerging Startup Landscape

Author

Listed:
  • Chie Hoon Song

    (Endicott College of International Studies, Woosong University, 171 Dongdaejeon-ro, Jung-gu, Daejeon 34606, Korea)

Abstract

The distribution and deployment of energy storage systems on a larger scale will be a key element of successfully managing the sustainable energy transition by balancing the power generation capability and load demand. In this context, it is crucial for researchers and policy makers to understand the underlying knowledge structure and key interaction dynamics that could shape the future innovation trajectory. A data-driven approach is used to analyze the evolving characteristics of knowledge dynamics from static, dynamic and future-oriented perspective. To this end, a network analysis was performed to determine the influence of individual knowledge areas. Subsequently, an interaction trend analysis based on emergence indicators was conducted to highlight the promising relations. Finally, the formation of new knowledge interactions is predicted using a link prediction technique. The findings show that ensuring the energy efficiency is a key issue that has persisted over time. In future, knowledge areas related to digital technologies are expected to gain relevance and lead the transformative change. The derived insights can assist R&D managers and policy makers to design more targeted and informed strategic initiatives to foster the adoption of energy storage solutions.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:18:p:5822-:d:635540
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/14/18/5822/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/14/18/5822/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Seunghyun Oh & Jaewoong Choi & Namuk Ko & Janghyeok Yoon, 2020. "Predicting product development directions for new product planning using patent classification-based link prediction," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(3), pages 1833-1876, December.
    2. Christoph Goebel & Vicky Cheng & Hans-Arno Jacobsen, 2017. "Profitability of Residential Battery Energy Storage Combined with Solar Photovoltaics," Energies, MDPI, vol. 10(7), pages 1-17, July.
    3. Hochull Choe & Duk Hee Lee, 2017. "The structure and change of the research collaboration network in Korea (2000–2011): network analysis of joint patents," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(2), pages 917-939, May.
    4. Shubbak, Mahmood H., 2019. "Advances in solar photovoltaics: Technology review and patent trends," Renewable and Sustainable Energy Reviews, Elsevier, vol. 115(C).
    5. Stefano Breschi & Julie Lassébie & Carlo Menon, 2018. "A portrait of innovative start-ups across countries," OECD Science, Technology and Industry Working Papers 2018/2, OECD Publishing.
    6. David Liben‐Nowell & Jon Kleinberg, 2007. "The link‐prediction problem for social networks," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 58(7), pages 1019-1031, May.
    7. Muhyaddin Rawa & Abdullah Abusorrah & Yusuf Al-Turki & Saad Mekhilef & Mostafa H. Mostafa & Ziad M. Ali & Shady H. E. Abdel Aleem, 2020. "Optimal Allocation and Economic Analysis of Battery Energy Storage Systems: Self-Consumption Rate and Hosting Capacity Enhancement for Microgrids with High Renewable Penetration," Sustainability, MDPI, vol. 12(23), pages 1-25, December.
    8. Alessandro Marra & Vittorio Carlei & Cristiano Baldassari, 2020. "Exploring networks of proximity for partner selection, firms' collaboration and knowledge exchange. The case of clean‐tech industry," Business Strategy and the Environment, Wiley Blackwell, vol. 29(3), pages 1034-1044, March.
    9. Rotolo, Daniele & Hicks, Diana & Martin, Ben R., 2015. "What is an emerging technology?," Research Policy, Elsevier, vol. 44(10), pages 1827-1843.
    10. Cassetta, Ernesto & Marra, Alessandro & Pozzi, Cesare & Antonelli, Paola, 2017. "Emerging technological trajectories and new mobility solutions. A large-scale investigation on transport-related innovative start-ups and implications for policy," Transportation Research Part A: Policy and Practice, Elsevier, vol. 106(C), pages 1-11.
    11. Yannis Caloghirou & Ioannis Giotopoulos & Efthymia Korra & Aggelos Tsakanikas, 2018. "How do employee training and knowledge stocks affect product innovation?," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 27(4), pages 343-360, May.
    12. 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.
    13. Frederik Plewnia, 2019. "The Energy System and the Sharing Economy: Interfaces and Overlaps and What to Learn from Them," Energies, MDPI, vol. 12(3), pages 1-17, January.
    14. Aaldering, Lukas Jan & Song, Chie Hoon, 2021. "Of leaders and laggards - Towards digitalization of the process industries," Technovation, Elsevier, vol. 105(C).
    15. Laugs, Gideon A.H. & Benders, René M.J. & Moll, Henri C., 2020. "Balancing responsibilities: Effects of growth of variable renewable energy, storage, and undue grid interaction," Energy Policy, Elsevier, vol. 139(C).
    16. Erjia Yan, 2014. "Finding knowledge paths among scientific disciplines," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 65(11), pages 2331-2347, November.
    17. Porter, Alan L. & Garner, Jon & Carley, Stephen F. & Newman, Nils C., 2019. "Emergence scoring to identify frontier R&D topics and key players," Technological Forecasting and Social Change, Elsevier, vol. 146(C), pages 628-643.
    18. Holger C. Hesse & Rodrigo Martins & Petr Musilek & Maik Naumann & Cong Nam Truong & Andreas Jossen, 2017. "Economic Optimization of Component Sizing for Residential Battery Storage Systems," Energies, MDPI, vol. 10(7), pages 1-19, June.
    19. Kim, Junhan & Geum, Youngjung, 2021. "How to develop data-driven technology roadmaps:The integration of topic modeling and link prediction," Technological Forecasting and Social Change, Elsevier, vol. 171(C).
    20. Ekaterina Turkina & Boris Oreshkin, 2021. "The Impact of Co-Inventor Networks on Smart Cleantech Innovation: The Case of Montreal Agglomeration," Sustainability, MDPI, vol. 13(13), pages 1-17, June.
    21. Baumann, Manuel & Domnik, Tobias & Haase, Martina & Wulf, Christina & Emmerich, Philip & Rösch, Christine & Zapp, Petra & Naegler, Tobias & Weil, Marcel, 2021. "Comparative patent analysis for the identification of global research trends for the case of battery storage, hydrogen and bioenergy," Technological Forecasting and Social Change, Elsevier, vol. 165(C).
    22. Mohamed Ben-Daya & Elkafi Hassini & Zied Bahroun, 2019. "Internet of things and supply chain management: a literature review," International Journal of Production Research, Taylor & Francis Journals, vol. 57(15-16), pages 4719-4742, August.
    23. Hyojeong Lim & Yongtae Park, 2010. "Identification of technological knowledge intermediaries," Scientometrics, Springer;Akadémiai Kiadó, vol. 84(3), pages 543-561, September.
    24. Bin Ye & Jingjing Jiang & Lixin Miao & Peng Yang & Ji Li & Bo Shen, 2015. "Feasibility Study of a Solar-Powered Electric Vehicle Charging Station Model," Energies, MDPI, vol. 8(11), pages 1-19, November.
    25. Inkyung Cho & Jungkyu Park & Eunnyeong Heo, 2018. "Measuring Knowledge Diffusion in Water Resources Research and Development: The Case of Korea," Sustainability, MDPI, vol. 10(8), pages 1-15, August.
    26. Marra, Alessandro & Antonelli, Paola & Pozzi, Cesare, 2017. "Emerging green-tech specializations and clusters – A network analysis on technological innovation at the metropolitan level," Renewable and Sustainable Energy Reviews, Elsevier, vol. 67(C), pages 1037-1046.
    27. Bögel, Paula Maria & Upham, Paul & Shahrokni, Hossein & Kordas, Olga, 2021. "What is needed for citizen-centered urban energy transitions: Insights on attitudes towards decentralized energy storage," Energy Policy, Elsevier, vol. 149(C).
    28. Mueller, Simon C. & Sandner, Philipp G. & Welpe, Isabell M., 2015. "Monitoring innovation in electrochemical energy storage technologies: A patent-based approach," Applied Energy, Elsevier, vol. 137(C), pages 537-544.
    29. 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.
    30. 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.
    31. Lü, Linyuan & Zhou, Tao, 2011. "Link prediction in complex networks: A survey," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(6), pages 1150-1170.
    32. Sharma, Pooja & Kolhe, Mohan & Sharma, Arvind, 2020. "Economic performance assessment of building integrated photovoltaic system with battery energy storage under grid constraints," Renewable Energy, Elsevier, vol. 145(C), pages 1901-1909.
    33. Changbae Mun & Sejun Yoon & Hyunseok Park, 2019. "Structural decomposition of technological domain using patent co-classification and classification hierarchy," Scientometrics, Springer;Akadémiai Kiadó, vol. 121(2), pages 633-652, November.
    34. Mejia, Cristian & Kajikawa, Yuya, 2020. "Emerging topics in energy storage based on a large-scale analysis of academic articles and patents," Applied Energy, Elsevier, vol. 263(C).
    35. Stephan, Annegret & Bening, Catharina R. & Schmidt, Tobias S. & Schwarz, Marius & Hoffmann, Volker H., 2019. "The role of inter-sectoral knowledge spillovers in technological innovations: The case of lithium-ion batteries," Technological Forecasting and Social Change, Elsevier, vol. 148(C).
    36. Stephen Comello & Stefan Reichelstein, 2019. "The emergence of cost effective battery storage," Nature Communications, Nature, vol. 10(1), pages 1-9, December.
    37. Loet Leydesdorff, 2007. "Betweenness centrality as an indicator of the interdisciplinarity of scientific journals," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 58(9), pages 1303-1319, July.
    38. Fabian Duffner & Niklas Kronemeyer & Jens Tübke & Jens Leker & Martin Winter & Richard Schmuch, 2021. "Post-lithium-ion battery cell production and its compatibility with lithium-ion cell production infrastructure," Nature Energy, Nature, vol. 6(2), pages 123-134, February.
    39. 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.
    40. Jean-Michel Dalle & Matthijs den Besten & Carlo Menon, 2017. "Using Crunchbase for economic and managerial research," OECD Science, Technology and Industry Working Papers 2017/08, OECD Publishing.
    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. Nikita Dmitrievich Senchilo & Denis Anatolievich Ustinov, 2021. "Method for Determining the Optimal Capacity of Energy Storage Systems with a Long-Term Forecast of Power Consumption," Energies, MDPI, vol. 14(21), pages 1-25, October.
    2. Chie Hoon Song, 2023. "Examining the Patent Landscape of E-Fuel Technology," Energies, MDPI, vol. 16(5), pages 1-19, February.
    3. Elias Carayannis & Pantelis Kostis & Hasan Dinçer & Serhat Yüksel, 2022. "Balanced-Scorecard-Based Evaluation of Knowledge-Oriented Competencies of Distributed Energy Investments," Energies, MDPI, vol. 15(21), pages 1-23, November.

    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. Aaldering, Lukas Jan & Song, Chie Hoon, 2021. "Of leaders and laggards - Towards digitalization of the process industries," Technovation, Elsevier, vol. 105(C).
    2. 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).
    3. 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.
    4. Liu, Weiwei & Song, Yifan & Bi, Kexin, 2021. "Exploring the patent collaboration network of China's wind energy industry: A study based on patent data from CNIPA," Renewable and Sustainable Energy Reviews, Elsevier, vol. 144(C).
    5. Liu, Zhenfeng & Feng, Jian & Uden, Lorna, 2023. "Technology opportunity analysis using hierarchical semantic networks and dual link prediction," Technovation, Elsevier, vol. 128(C).
    6. Yang, Zaoli & Zhang, Weijian & Yuan, Fei & Islam, Nazrul, 2021. "Measuring topic network centrality for identifying technology and technological development in online communities," Technological Forecasting and Social Change, Elsevier, vol. 167(C).
    7. Gozuacik, Necip & Sakar, C. Okan & Ozcan, Sercan, 2023. "Technological forecasting based on estimation of word embedding matrix using LSTM networks," Technological Forecasting and Social Change, Elsevier, vol. 191(C).
    8. Chie Hoon Song, 2023. "Examining the Patent Landscape of E-Fuel Technology," Energies, MDPI, vol. 16(5), pages 1-19, February.
    9. Alessandro Marra & Vittorio Carlei & Cristiano Baldassari, 2020. "Exploring networks of proximity for partner selection, firms' collaboration and knowledge exchange. The case of clean‐tech industry," Business Strategy and the Environment, Wiley Blackwell, vol. 29(3), pages 1034-1044, March.
    10. Huang, Lu & Chen, Xiang & Ni, Xingxing & Liu, Jiarun & Cao, Xiaoli & Wang, Changtian, 2021. "Tracking the dynamics of co-word networks for emerging topic identification," Technological Forecasting and Social Change, Elsevier, vol. 170(C).
    11. Jong Wook Lee & So Young Sohn, 2021. "Patent data based search framework for IT R&D employees for convergence technology," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(7), pages 5687-5705, July.
    12. Gao, Qiang & Liang, Zhentao & Wang, Ping & Hou, Jingrui & Chen, Xiuxiu & Liu, Manman, 2021. "Potential index: Revealing the future impact of research topics based on current knowledge networks," Journal of Informetrics, Elsevier, vol. 15(3).
    13. Karimi, Fatemeh & Lotfi, Shahriar & Izadkhah, Habib, 2021. "Community-guided link prediction in multiplex networks," Journal of Informetrics, Elsevier, vol. 15(4).
    14. Choi, Jaewoong & Yoon, Janghyeok, 2022. "Measuring knowledge exploration distance at the patent level: Application of network embedding and citation analysis," Journal of Informetrics, Elsevier, vol. 16(2).
    15. Peter Sjögårde & Fereshteh Didegah, 2022. "The association between topic growth and citation impact of research publications," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(4), pages 1903-1921, April.
    16. Xu, Hua & Wang, Minggang & Jiang, Shumin & Yang, Weiguo, 2020. "Carbon price forecasting with complex network and extreme learning machine," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 545(C).
    17. Andreas Spitz & Anna Gimmler & Thorsten Stoeck & Katharina Anna Zweig & Emőke-Ágnes Horvát, 2016. "Assessing Low-Intensity Relationships in Complex Networks," PLOS ONE, Public Library of Science, vol. 11(4), pages 1-17, April.
    18. Qiaoran Yang & Zhiliang Dong & Yichi Zhang & Man Li & Ziyi Liang & Chao Ding, 2021. "Who Will Establish New Trade Relations? Looking for Potential Relationship in International Nickel Trade," Sustainability, MDPI, vol. 13(21), pages 1-15, October.
    19. Aslan, Serpil & Kaya, Buket & Kaya, Mehmet, 2019. "Predicting potential links by using strengthened projections in evolving bipartite networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 998-1011.
    20. Leto Peel & Tiago P. Peixoto & Manlio De Domenico, 2022. "Statistical inference links data and theory in network science," Nature Communications, Nature, vol. 13(1), pages 1-15, December.

    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:jeners:v:14:y:2021:i:18:p:5822-:d:635540. 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.