IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i5p3117-d765880.html
   My bibliography  Save this article

Investigating Company’s Technical Development Directions Based on Internal Knowledge Inheritance and Inventor Capabilities: The Case of Samsung Electronics

Author

Listed:
  • Fang Han

    (National Science Library, Chinese Academy of Sciences, Beijing 100190, China)

  • Sejun Yoon

    (Department of Information Systems, Hanyang University, Seoul 04763, Korea)

  • Nagarajan Raghavan

    (Engineering Product Development Pillar, Singapore University of Technology and Design, Singapore 487372, Singapore)

  • Hyunseok Park

    (Department of Information Systems, Hanyang University, Seoul 04763, Korea)

Abstract

This paper proposes a new method to analyze technical development directions of a company using knowledge persistence-based main path analysis and co-inventor network analysis. Main path analysis is used for identifying internal technical knowledge flows and inheritances over time within a company, and knowledge persistence-based main path analysis can well identify major knowledge streams of each sub-domain within a relatively small knowledge network generated by one company without omission of significant inventions. A co-inventor network analysis is used for identifying key inventors who can be represented as the major technical capabilities of a company. The method is a meaningful attempt in that it applies knowledge persistence-based main path analysis to analyzing a company’s internal technical development and combines the two approaches to provide the information on both base technical capabilities and new technical characteristics. To test the method, this paper conducted an empirical study of Samsung Electronics. The results show that the method generated major knowledge flows and identified key inventors of Samsung Electronics. In particular, the method can identify the base technical knowledge as the ‘backbone’ and newly injected knowledge as ‘fresh blood’ for forecasting future technical development. Based on the identified clue information, this paper forecasted the potential future technologies for each sub-domain of Samsung Electronics with technical keywords and descriptions.

Suggested Citation

  • Fang Han & Sejun Yoon & Nagarajan Raghavan & Hyunseok Park, 2022. "Investigating Company’s Technical Development Directions Based on Internal Knowledge Inheritance and Inventor Capabilities: The Case of Samsung Electronics," Sustainability, MDPI, vol. 14(5), pages 1-19, March.
  • Handle: RePEc:gam:jsusta:v:14:y:2022:i:5:p:3117-:d:765880
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/5/3117/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/14/5/3117/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Janghyeok Yoon & Hyunseok Park & Kwangsoo Kim, 2013. "Identifying technological competition trends for R&D planning using dynamic patent maps: SAO-based content analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 94(1), pages 313-331, January.
    2. Abbasiharofteh, Milad & Kogler, Dieter F. & Lengyel, Balázs, 2023. "Atypical combinations of technologies in regional co-inventor networks," Research Policy, Elsevier, vol. 52(10).
    3. Lu, Louis Y.Y. & Hsieh, Chih-Hung & Liu, John S., 2016. "Development trajectory and research themes of foresight," Technological Forecasting and Social Change, Elsevier, vol. 112(C), pages 347-356.
    4. Gergő Tóth & Balázs Lengyel, 2021. "Inter-firm inventor mobility and the role of co-inventor networks in producing high-impact innovation," The Journal of Technology Transfer, Springer, vol. 46(1), pages 117-137, February.
    5. Sungchul Choi & Hyunseok Park, 2016. "Investigation of Strategic Changes Using Patent Co-Inventor Network Analysis: The Case of Samsung Electronics," Sustainability, MDPI, vol. 8(12), pages 1-13, December.
    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. Nomaler, Onder & Verspagen, Bart, 2016. "River deep, mountain high: Of long-run knowledge trajectories within and between innovation clusters," MERIT Working Papers 2016-048, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
    8. Xiao-Ping Lei & Zhi-Yun Zhao & Xu Zhang & Dar-Zen Chen & Mu-Hsuan Huang & Jia Zheng & Run-Sheng Liu & Jing Zhang & Yun-Hua Zhao, 2013. "Technological collaboration patterns in solar cell industry based on patent inventors and assignees analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 96(2), pages 427-441, August.
    9. 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.
    10. Marianna Epicoco, 2013. "Knowledge patterns and sources of leadership: Mapping the semiconductor miniaturization trajectory," Post-Print hal-03381305, HAL.
    11. 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.
    12. Mun, Changbae & Yoon, Sejun & Raghavan, Nagarajan & Hwang, Dongwook & Basnet, Subarna & Park, Hyunseok, 2021. "Function score-based technological trend analysis," Technovation, Elsevier, vol. 101(C).
    13. Appio, Francesco Paolo & Martini, Antonella & Fantoni, Gualtiero, 2017. "The light and shade of knowledge recombination: Insights from a general-purpose technology," Technological Forecasting and Social Change, Elsevier, vol. 125(C), pages 154-165.
    14. Cantner, Uwe & Graf, Holger, 2006. "The network of innovators in Jena: An application of social network analysis," Research Policy, Elsevier, vol. 35(4), pages 463-480, May.
    15. Lin Zhu & Donghua Zhu & Xuefeng Wang & Scott W. Cunningham & Zhinan Wang, 2019. "An integrated solution for detecting rising technology stars in co-inventor networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 121(1), pages 137-172, October.
    16. Fan Zeng & Stacy Hyun Nam Lee & Chris Kwan Yu Lo, 2020. "The Role of Information Systems in the Sustainable Development of Enterprises: A Systematic Literature Network Analysis," Sustainability, MDPI, vol. 12(8), pages 1-29, April.
    17. Diana Lucio‐Arias & Loet Leydesdorff, 2008. "Main‐path analysis and path‐dependent transitions in HistCite™‐based historiograms," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 59(12), pages 1948-1962, October.
    18. Marcel Bednarz & Tom Broekel, 2019. "The relationship of policy induced R&D networks and inter-regional knowledge diffusion," Journal of Evolutionary Economics, Springer, vol. 29(5), pages 1459-1481, November.
    19. Epicoco, Marianna, 2013. "Knowledge patterns and sources of leadership: Mapping the semiconductor miniaturization trajectory," Research Policy, Elsevier, vol. 42(1), pages 180-195.
    20. Bing Wang & Yifan Wang & Yuqing Zhao, 2021. "Collaborative Governance Mechanism of Climate Change and Air Pollution: Evidence from China," Sustainability, MDPI, vol. 13(12), pages 1-16, June.
    21. Yu, Dejian & Sheng, Libo, 2021. "Influence difference main path analysis: Evidence from DNA and blockchain domain citation networks," Journal of Informetrics, Elsevier, vol. 15(4).
    22. Lorenzo Cassi & Anne Plunket, 2015. "Research Collaboration in Co-inventor Networks: Combining Closure, Bridging and Proximities," Regional Studies, Taylor & Francis Journals, vol. 49(6), pages 936-954, June.
    23. Hyunseok Park & Janghyeok Yoon & Kwangsoo Kim, 2013. "Identification and evaluation of corporations for merger and acquisition strategies using patent information and text mining," Scientometrics, Springer;Akadémiai Kiadó, vol. 97(3), pages 883-909, December.
    24. Gergő Tóth & Sándor Juhász & Zoltán Elekes & Balázs Lengyel, 2021. "Repeated collaboration of inventors across European regions," European Planning Studies, Taylor & Francis Journals, vol. 29(12), pages 2252-2272, December.
    25. Önder Nomaler & Bart Verspagen, 2016. "River deep, mountain high: of long run knowledge trajectories within and between innovation clusters1," Journal of Economic Geography, Oxford University Press, vol. 16(6), pages 1259-1278.
    26. Xiao, Yu & Lu, Louis Y.Y. & Liu, John S. & Zhou, Zhili, 2014. "Knowledge diffusion path analysis of data quality literature: A main path analysis," Journal of Informetrics, Elsevier, vol. 8(3), pages 594-605.
    27. 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.
    28. Pablo E Pinto & Guillermo Honores & Andrés Vallone, 2021. "Exploring the topology and dynamic growth properties of co-invention networks and technology fields," PLOS ONE, Public Library of Science, vol. 16(9), pages 1-27, September.
    29. Lu, Louis Y.Y. & Liu, John S., 2016. "A novel approach to identify the major research themes and development trajectory: The case of patenting research," Technological Forecasting and Social Change, Elsevier, vol. 103(C), pages 71-82.
    30. Qiong Wu & Kanittha Tambunlertchai & Pongsa Pornchaiwiseskul, 2021. "Examining the Impact and Influencing Channels of Carbon Emission Trading Pilot Markets in China," Sustainability, MDPI, vol. 13(10), pages 1-18, May.
    31. Mun, Changbae & Kim, Yongmin & Yoo, Donghyun & Yoon, Sejun & Hyun, Heesu & Raghavan, Nagarajan & Park, Hyunseok, 2019. "Discovering business diversification opportunities using patent information and open innovation cases," Technological Forecasting and Social Change, Elsevier, vol. 139(C), pages 144-154.
    32. Pinto, Pablo E. & Vallone, Andres & Honores, Guillermo, 2019. "The structure of collaboration networks: Findings from three decades of co-invention patents in Chile," Journal of Informetrics, Elsevier, vol. 13(4).
    33. Schilling, Melissa A. & Green, Elad, 2011. "Recombinant search and breakthrough idea generation: An analysis of high impact papers in the social sciences," Research Policy, Elsevier, vol. 40(10), pages 1321-1331.
    34. Nakamura, Hiroko & Suzuki, Shinji & Sakata, Ichiro & Kajikawa, Yuya, 2015. "Knowledge combination modeling: The measurement of knowledge similarity between different technological domains," Technological Forecasting and Social Change, Elsevier, vol. 94(C), pages 187-201.
    35. Donghyun You & Hyunseok Park, 2018. "Developmental Trajectories in Electrical Steel Technology Using Patent Information," Sustainability, MDPI, vol. 10(8), pages 1-15, August.
    36. Shih-Chang Hung & John S. Liu & Louis Y. Y. Lu & Yu-Chiang Tseng, 2014. "Technological change in lithium iron phosphate battery: the key-route main path analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 100(1), pages 97-120, July.
    37. Anne Ter Wal & Ron Boschma, 2009. "Applying social network analysis in economic geography: framing some key analytic issues," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 43(3), pages 739-756, September.
    38. Tseng, Fang-Mei & Palma Gil, Eunice Ina N. & Lu, Louis Y.Y., 2021. "Developmental trajectories of blockchain research and its major subfields," Technology in Society, Elsevier, vol. 66(C).
    39. Hughes, A. & Mina, A., 2010. "The Impact of the Patent System on SMEs," Working Papers wp411, Centre for Business Research, University of Cambridge.
    40. 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.
    41. Ben Zhang & Lei Ma & Zheng Liu, 2020. "Literature Trend Identification of Sustainable Technology Innovation: A Bibliometric Study Based on Co-Citation and Main Path Analysis," Sustainability, MDPI, vol. 12(20), pages 1-20, October.
    42. Dehdarian, Amin & Tucci, Christopher L, 2021. "A complex network approach for analyzing early evolution of smart grid innovations in Europe," Applied Energy, Elsevier, vol. 298(C).
    43. Shuto Miyashita & Shogo Katoh & Tomohiro Anzai & Shintaro Sengoku, 2020. "Intellectual Property Management in Publicly Funded R&D Program and Projects: Optimizing Principal–Agent Relationship through Transdisciplinary Approach," Sustainability, MDPI, vol. 12(23), pages 1-17, November.
    44. Han, Yoo-Jin & Park, Yongtae, 2006. "Patent network analysis of inter-industrial knowledge flows: The case of Korea between traditional and emerging industries," World Patent Information, Elsevier, vol. 28(3), pages 235-247, September.
    45. Dejian Yu & Zhaoping Yan, 2021. "Knowledge diffusion of supply chain bullwhip effect: main path analysis and science mapping analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(10), pages 8491-8515, October.
    46. Lee Fleming, 2001. "Recombinant Uncertainty in Technological Search," Management Science, INFORMS, vol. 47(1), pages 117-132, January.
    47. Moehrle, Martin G. & Caferoglu, Hüseyin, 2019. "Technological speciation as a source for emerging technologies. Using semantic patent analysis for the case of camera technology," Technological Forecasting and Social Change, Elsevier, vol. 146(C), pages 776-784.
    Full references (including those not matched with items on IDEAS)

    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. Martin Ho & Henry CW Price & Tim S Evans & Eoin O'Sullivan, 2023. "Order in Innovation," Papers 2302.13076, arXiv.org.
    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. John S. Liu & Louis Y. Y. Lu & Mei Hsiu-Ching Ho, 2019. "A few notes on main path analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(1), pages 379-391, April.
    4. Alessandri, Enrico, 2023. "Identifying technological trajectories in the mining sector using patent citation networks," Resources Policy, Elsevier, vol. 80(C).
    5. 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.
    6. Yoonki Rhee & Sejun Yoon & Hyunseok Park, 2022. "Exploring Knowledge Trajectories of Accounting Information Systems Using Business Method Patents and Knowledge Persistence-Based Main Path Analysis," Mathematics, MDPI, vol. 10(18), pages 1-22, September.
    7. Alessandri, Enrico, 2021. "Identifying technological trajectories in the mining sector using patent citation networks," MERIT Working Papers 2021-048, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
    8. 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.
    9. Epicoco, Marianna & Oltra, Vanessa & Maïder Saint, Jean, 2014. "Knowledge dynamics and sources of eco-innovation: Mapping the Green Chemistry community," Technological Forecasting and Social Change, Elsevier, vol. 81(C), pages 388-402.
    10. Abbasiharofteh, Milad & Kogler, Dieter F. & Lengyel, Balázs, 2023. "Atypical combinations of technologies in regional co-inventor networks," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 52(10), pages 1-1.
    11. Hwang, Seonho & Shin, Juneseuk, 2019. "Extending technological trajectories to latest technological changes by overcoming time lags," Technological Forecasting and Social Change, Elsevier, vol. 143(C), pages 142-153.
    12. Ichiro Watanabe & Soichiro Takagi, 2022. "NK model-based analysis of technological trajectories: a study on the technological field of computer graphic processing systems," Evolutionary and Institutional Economics Review, Springer, vol. 19(1), pages 119-140, April.
    13. Huenteler, Joern & Ossenbrink, Jan & Schmidt, Tobias S. & Hoffmann, Volker H., 2016. "How a product’s design hierarchy shapes the evolution of technological knowledge—Evidence from patent-citation networks in wind power," Research Policy, Elsevier, vol. 45(6), pages 1195-1217.
    14. Huenteler, Joern & Schmidt, Tobias S. & Ossenbrink, Jan & Hoffmann, Volker H., 2016. "Technology life-cycles in the energy sector — Technological characteristics and the role of deployment for innovation," Technological Forecasting and Social Change, Elsevier, vol. 104(C), pages 102-121.
    15. Junmo Kim & Juneseuk Shin, 2018. "Mapping extended technological trajectories: integration of main path, derivative paths, and technology junctures," Scientometrics, Springer;Akadémiai Kiadó, vol. 116(3), pages 1439-1459, September.
    16. Kim, Erin H.J. & Jeong, Yoo Kyung & Kim, YongHwan & Song, Min, 2022. "Exploring scientific trajectories of a large-scale dataset using topic-integrated path extraction," Journal of Informetrics, Elsevier, vol. 16(1).
    17. Abderahman Rejeb & Alireza Abdollahi & Karim Rejeb & Mohamed M. Mostafa, 2023. "Tracing knowledge evolution flows in scholarly restaurant research: a main path analysis," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(3), pages 2183-2209, June.
    18. Kuan, Chung-Huei & Huang, Mu-Hsuan & Chen, Dar-Zen, 2018. "Missing links: Timing characteristics and their implications for capturing contemporaneous technological developments," Journal of Informetrics, Elsevier, vol. 12(1), pages 259-270.
    19. 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.
    20. Triulzi, Giorgio & Alstott, Jeff & Magee, Christopher L., 2020. "Estimating technology performance improvement rates by mining patent data," Technological Forecasting and Social Change, Elsevier, vol. 158(C).

    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:14:y:2022:i:5:p:3117-:d:765880. 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.