IDEAS home Printed from https://ideas.repec.org/a/eee/tefoso/v118y2017icp246-257.html
   My bibliography  Save this article

Concentric diversification based on technological capabilities: Link analysis of products and technologies

Author

Listed:
  • Kim, Hyunwoo
  • Hong, Suckwon
  • Kwon, Ohjin
  • Lee, Changyong

Abstract

This research responds to the needs for concentric diversification by focusing on how firms can find new business opportunities based on their technological capabilities. We propose a systematic approach to identifying potential areas for concentric diversification at a product level via link analysis of products and technologies. For this, first, text mining is utilised to construct an integrated patent-product database from the US patent and trademark database. Second, association rule mining is employed to construct a product ecology network using directed technological relationships between products. Third, a link prediction analysis is conducted to identify potential areas for concentric diversification at a product level. Finally, three quantitative indicators are developed to assess the characteristics of the areas identified. Our case study employs a total of 850,676 patents and 328,288 products in the integrated patent-product database from 2010 to 2014 and shows that the proposed approach enables a wide-ranging search for potential areas for concentric diversification and the quick assessment of their characteristics, with statistically significant results. We believe that the proposed approach will be useful as a complementary tool for decision making for small and medium-sized high-tech companies that are considering entering new business areas, but which have little domain knowledge.

Suggested Citation

  • Kim, Hyunwoo & Hong, Suckwon & Kwon, Ohjin & Lee, Changyong, 2017. "Concentric diversification based on technological capabilities: Link analysis of products and technologies," Technological Forecasting and Social Change, Elsevier, vol. 118(C), pages 246-257.
    • Handle: RePEc:eee:tefoso:v:118:y:2017:i:c:p:246-257
    DOI: 10.1016/j.techfore.2017.02.025
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0040162516306254
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.techfore.2017.02.025?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. Yoon, Janghyeok & Park, Hyunseok & Seo, Wonchul & Lee, Jae-Min & Coh, Byoung-youl & Kim, Jonghwa, 2015. "Technology opportunity discovery (TOD) from existing technologies and products: A function-based TOD framework," Technological Forecasting and Social Change, Elsevier, vol. 100(C), pages 153-167.
    2. Breschi, Stefano & Lissoni, Francesco & Malerba, Franco, 2003. "Knowledge-relatedness in firm technological diversification," Research Policy, Elsevier, vol. 32(1), pages 69-87, January.
    3. Archibugi, Daniele & Pianta, Mario, 1992. "Specialization and size of technological activities in industrial countries: The analysis of patent data," Research Policy, Elsevier, vol. 21(1), pages 79-93, February.
    4. 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.
    5. Gautam Ahuja & Curba Morris Lampert, 2001. "Entrepreneurship in the large corporation: a longitudinal study of how established firms create breakthrough inventions," Strategic Management Journal, Wiley Blackwell, vol. 22(6‐7), pages 521-543, June.
    6. Lee, Changyong & Kang, Bokyoung & Shin, Juneseuk, 2015. "Novelty-focused patent mapping for technology opportunity analysis," Technological Forecasting and Social Change, Elsevier, vol. 90(PB), pages 355-365.
    7. Aaron Clauset & Cristopher Moore & M. E. J. Newman, 2008. "Hierarchical structure and the prediction of missing links in networks," Nature, Nature, vol. 453(7191), pages 98-101, May.
    8. Quintana-Garci­a, Cristina & Benavides-Velasco, Carlos A., 2008. "Innovative competence, exploration and exploitation: The influence of technological diversification," Research Policy, Elsevier, vol. 37(3), pages 492-507, April.
    9. Rong, Jia & Vu, Huy Quan & Law, Rob & Li, Gang, 2012. "A behavioral analysis of web sharers and browsers in Hong Kong using targeted association rule mining," Tourism Management, Elsevier, vol. 33(4), pages 731-740.
    10. Douglas J. Miller, 2004. "Firms' technological resources and the performance effects of diversification: a longitudinal study," Strategic Management Journal, Wiley Blackwell, vol. 25(11), pages 1097-1119, November.
    11. Wang, Ming-Yeu, 2012. "Exploring potential R&D collaborators with complementary technologies: The case of biosensors," Technological Forecasting and Social Change, Elsevier, vol. 79(5), pages 862-874.
    12. 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.
    13. Lionel Nesta & Pier Paolo Saviotti, 2005. "Coherence of the Knowledge Base and the Firms’ Innovative Performance. Evidence from the Bio-Pharmaceutical Industry," SciencePo Working papers Main hal-03417696, HAL.
    14. Lionel Nesta & Pier Paolo Saviotti, 2005. "Coherence Of The Knowledge Base And The Firm'S Innovative Performance: Evidence From The U.S. Pharmaceutical Industry," Journal of Industrial Economics, Wiley Blackwell, vol. 53(1), pages 123-142, March.
    15. Patel, Pari & Pavitt, Keith, 1997. "The technological competencies of the world's largest firms: Complex and path-dependent, but not much variety," Research Policy, Elsevier, vol. 26(2), pages 141-156, May.
    16. Stefano Valvano & Davide Vannoni, 2003. "Diversification Strategies and Corporate Coherence Evidence from Italian Leading Firms," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 23(1), pages 25-41, August.
    17. Leo Katz, 1953. "A new status index derived from sociometric analysis," Psychometrika, Springer;The Psychometric Society, vol. 18(1), pages 39-43, March.
    18. Nicky J. Welton & Howard H. Z. Thom, 2015. "Value of Information," Medical Decision Making, , vol. 35(5), pages 564-566, July.
    19. Yu-Shan Chen & Ke-Chiun Chang, 2012. "Using the entropy-based patent measure to explore the influences of related and unrelated technological diversification upon technological competences and firm performance," Scientometrics, Springer;Akadémiai Kiadó, vol. 90(3), pages 825-841, March.
    20. Yoon, Byungun & Park, Inchae & Coh, Byoung-youl, 2014. "Exploring technological opportunities by linking technology and products: Application of morphology analysis and text mining," Technological Forecasting and Social Change, Elsevier, vol. 86(C), pages 287-303.
    21. Granstrand, Ove, 1998. "Towards a theory of the technology-based firm1," Research Policy, Elsevier, vol. 27(5), pages 465-489, September.
    22. Cantwell, John & Piscitello, Lucia, 2000. "Accumulating Technological Competence: Its Changing Impact on Corporate Diversification and Internationalization," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 9(1), pages 21-51, March.
    23. Brian S. Silverman, 1999. "Technological Resources and the Direction of Corporate Diversification: Toward an Integration of the Resource-Based View and Transaction Cost Economics," Management Science, INFORMS, vol. 45(8), pages 1109-1124, August.
    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. Lee, Changyong & Kwon, Ohjin & Kim, Myeongjung & Kwon, Daeil, 2018. "Early identification of emerging technologies: A machine learning approach using multiple patent indicators," Technological Forecasting and Social Change, Elsevier, vol. 127(C), pages 291-303.
    2. Yogesh K. Dwivedi & A. Sharma & Nripendra P. Rana & M. Giannakis & P. Goel & Vincent Dutot, 2023. "Evolution of Artificial Intelligence Research in Technological Forecasting and Social Change: Research Topics, Trends, and Future Directions," Post-Print hal-04292607, HAL.
    3. Eum, Wonsub & Lee, Jeong-Dong, 2022. "The co-evolution of production and technological capabilities during industrial development," Structural Change and Economic Dynamics, Elsevier, vol. 63(C), pages 454-469.
    4. Jiwon Yu & Young Jae Han & Hyewon Yang & Sugil Lee & Gildong Kim & Chulung Lee, 2022. "Promising Technology Analysis and Patent Roadmap Development in the Hydrogen Supply Chain," Sustainability, MDPI, vol. 14(21), pages 1-20, October.
    5. Motohashi, Kazuyuki & Zhu, Chen, 2023. "Identifying technology opportunity using dual-attention model and technology-market concordance matrix," Technological Forecasting and Social Change, Elsevier, vol. 197(C).
    6. Jiwon Yu & Jong-Gyu Hwang & Jumi Hwang & Sung Chan Jun & Sumin Kang & Chulung Lee & Hyundong Kim, 2020. "Identification of Vacant and Emerging Technologies in Smart Mobility Through the GTM-Based Patent Map Development," Sustainability, MDPI, vol. 12(22), pages 1-22, November.
    7. Roma, Paolo & Vasi, Maria, 2019. "Diversification and performance in the mobile app market: The role of the platform ecosystem," Technological Forecasting and Social Change, Elsevier, vol. 147(C), pages 123-139.
    8. Liu, Zhenfeng & Feng, Jian & Uden, Lorna, 2023. "Technology opportunity analysis using hierarchical semantic networks and dual link prediction," Technovation, Elsevier, vol. 128(C).
    9. Kim, Juram & Kim, Seungho & Lee, Changyong, 2019. "Anticipating technological convergence: Link prediction using Wikipedia hyperlinks," Technovation, Elsevier, vol. 79(C), pages 25-34.
    10. Yoon, Byungun & Magee, Christopher L., 2018. "Exploring technology opportunities by visualizing patent information based on generative topographic mapping and link prediction," Technological Forecasting and Social Change, Elsevier, vol. 132(C), pages 105-117.
    11. Changyong Lee & Suckwon Hong & Juram Kim, 2021. "Anticipating multi-technology convergence: a machine learning approach using patent information," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(3), pages 1867-1896, March.
    12. Lee, Changyong, 2021. "A review of data analytics in technological forecasting," Technological Forecasting and Social Change, Elsevier, vol. 166(C).
    13. Youngjae Choi & Sanghyun Park & Sungjoo Lee, 2021. "Identifying emerging technologies to envision a future innovation ecosystem: A machine learning approach to patent data," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(7), pages 5431-5476, July.
    14. Lee, Hyunmin, 2023. "Strategic similarity in the co-evolution of technological and business diversification for firm growth: Evidence from smart-manufacturing related firms," Technological Forecasting and Social Change, Elsevier, vol. 189(C).
    15. Lee, Changyong & Jeon, Daeseong & Ahn, Joon Mo & Kwon, Ohjin, 2020. "Navigating a product landscape for technology opportunity analysis: A word2vec approach using an integrated patent-product database," Technovation, Elsevier, vol. 96.
    16. Ardito, Lorenzo & Ernst, Holger & Messeni Petruzzelli, Antonio, 2020. "The interplay between technology characteristics, R&D internationalisation, and new product introduction: Empirical evidence from the energy conservation sector," Technovation, Elsevier, vol. 96.
    17. Wu, Yingwen & Ji, Yangjian, 2023. "Identifying firm-specific technology opportunities from the perspective of competitors by using association rule mining," Journal of Informetrics, Elsevier, vol. 17(2).
    18. Changyong Lee & Gyumin Lee, 2019. "Technology opportunity analysis based on recombinant search: patent landscape analysis for idea generation," Scientometrics, Springer;Akadémiai Kiadó, vol. 121(2), pages 603-632, 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. Quintana-Garci­a, Cristina & Benavides-Velasco, Carlos A., 2008. "Innovative competence, exploration and exploitation: The influence of technological diversification," Research Policy, Elsevier, vol. 37(3), pages 492-507, April.
    2. Maria Chiara Di Guardo & Kathryn Rudie Harrigan & Elona Marku, 2019. "M&A and diversification strategies: what effect on quality of inventive activity?," Journal of Management & Governance, Springer;Accademia Italiana di Economia Aziendale (AIDEA), vol. 23(3), pages 669-692, September.
    3. Lorenz, Steffi, 2015. "Diversität und Verbundenheit der unternehmerischen Wissensbasis: Ein neuartiger Messansatz mit Indikatoren aus Innovationsprojekten," Discussion Papers on Strategy and Innovation 15-01, Philipps-University Marburg, Department of Technology and Innovation Management (TIM).
    4. Hur, Wonchang & Oh, Junbyoung, 2021. "A man is known by the company he keeps?: A structural relationship between backward citation and forward citation of patents," Research Policy, Elsevier, vol. 50(1).
    5. Seh-Hyun Yoo & Chang-Yang Lee, 2023. "Technological diversification, technology portfolio properties, and R&D productivity," The Journal of Technology Transfer, Springer, vol. 48(6), pages 2074-2105, December.
    6. Shafique, Muhammad & Hagedoorn, John, 2022. "Look at U: Technological scope of the acquirer, technological complementarity with the target, and post-acquisition R&D output," Technovation, Elsevier, vol. 115(C).
    7. Yu-Shan Chen & Chun-Yu Shih & Ching-Hsun Chang, 2012. "The effects of related and unrelated technological diversification on innovation performance and corporate growth in the Taiwan’s semiconductor industry," Scientometrics, Springer;Akadémiai Kiadó, vol. 92(1), pages 117-134, July.
    8. Hoskins, Jake D. & Carson, Stephen J., 2022. "Industry conditions, market share, and the firm’s ability to derive business-line profitability from diverse technological portfolios," Journal of Business Research, Elsevier, vol. 149(C), pages 178-192.
    9. Moaniba, Igam M. & Su, Hsin-Ning & Lee, Pei-Chun, 2019. "On the drivers of innovation: Does the co-evolution of technological diversification and international collaboration matter?," Technological Forecasting and Social Change, Elsevier, vol. 148(C).
    10. Lichtenthaler, Ulrich, 2010. "Determinants of proactive and reactive technology licensing: A contingency perspective," Research Policy, Elsevier, vol. 39(1), pages 55-66, February.
    11. Lin, Chinho & Chang, Chia-Chi, 2015. "The effect of technological diversification on organizational performance: An empirical study of S&P 500 manufacturing firms," Technological Forecasting and Social Change, Elsevier, vol. 90(PB), pages 575-586.
    12. Carlo Corradini & Pelin Demirel & Giuliana Battisti, 2016. "Technological diversification within UK’s small serial innovators," Small Business Economics, Springer, vol. 47(1), pages 163-177, June.
    13. Krammer, Sorin M.S., 2016. "The role of diversification profiles and dyadic characteristics in the formation of technological alliances: Differences between exploitation and exploration in a low-tech industry," Research Policy, Elsevier, vol. 45(2), pages 517-532.
    14. Yu-Shan Chen & Ke-Chiun Chang, 2012. "Using the entropy-based patent measure to explore the influences of related and unrelated technological diversification upon technological competences and firm performance," Scientometrics, Springer;Akadémiai Kiadó, vol. 90(3), pages 825-841, March.
    15. Lee, Jiho & Ko, Namuk & Yoon, Janghyeok & Son, Changho, 2021. "An approach for discovering firm-specific technology opportunities: Application of link prediction to F-term networks," Technological Forecasting and Social Change, Elsevier, vol. 168(C).
    16. Loet Leydesdorff & Dieter Franz Kogler & Bowen Yan, 2017. "Mapping patent classifications: portfolio and statistical analysis, and the comparison of strengths and weaknesses," Scientometrics, Springer;Akadémiai Kiadó, vol. 112(3), pages 1573-1591, September.
    17. Choi, Mincheol & Lee, Chang-Yang, 2021. "Technological diversification and R&D productivity: The moderating effects of knowledge spillovers and core-technology competence," Technovation, Elsevier, vol. 104(C).
    18. Silvestri, Daniela & Riccaboni, Massimo & Della Malva, Antonio, 2018. "Sailing in all winds: Technological search over the business cycle," Research Policy, Elsevier, vol. 47(10), pages 1933-1944.
    19. 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.
    20. Martin Kalthaus, 2020. "Knowledge recombination along the technology life cycle," Journal of Evolutionary Economics, Springer, vol. 30(3), pages 643-704, July.

    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:eee:tefoso:v:118:y:2017:i:c:p:246-257. 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: Catherine Liu (email available below). General contact details of provider: http://www.sciencedirect.com/science/journal/00401625 .

    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.