IDEAS home Printed from https://ideas.repec.org/a/eee/tefoso/v94y2015icp187-201.html
   My bibliography  Save this article

Knowledge combination modeling: The measurement of knowledge similarity between different technological domains

Author

Listed:
  • Nakamura, Hiroko
  • Suzuki, Shinji
  • Sakata, Ichiro
  • Kajikawa, Yuya

Abstract

This paper proposes the DB-Combination model that considers three different knowledge combinations in depth (D) and breadth (B) based on similarities of two technological knowledge domains. We also investigate three methodologies A1, A2 and A3 to highlight the three knowledge combinations. To identify technological knowledge domains, citation analysis on patent information was used for A1 and A2 and pre-existing patent classification analysis was used for A3. And to measure the similarity between identified technological knowledge domains, text similarity measurements, existing intra-industrial citation tracing and IPC share similarity comparison were used for A1, A2 and A3 respectively. The usability of the model and methodologies were demonstrated through a case study on technological knowledge of the automobile industry and the aircraft industry. While these methodologies still need to be improved, it was demonstrated that the three measurements can highlight candidates of the three knowledge combination proposed in DB-Combination model. This research contributes to accelerate breadth knowledge recombination in a complex technology industry.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:tefoso:v:94:y:2015:i:c:p:187-201
    DOI: 10.1016/j.techfore.2014.09.009
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0040162514002790
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.techfore.2014.09.009?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. repec:fth:harver:1473 is not listed on IDEAS
    2. 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.
    3. Fleming, Lee & Sorenson, Olav, 2001. "Technology as a complex adaptive system: evidence from patent data," Research Policy, Elsevier, vol. 30(7), pages 1019-1039, August.
    4. Martin, Ben R., 2012. "The evolution of science policy and innovation studies," Research Policy, Elsevier, vol. 41(7), pages 1219-1239.
    5. Jacques Michel & Bernd Bettels, 2001. "Patent citation analysis.A closer look at the basic input data from patent search reports," Scientometrics, Springer;Akadémiai Kiadó, vol. 51(1), pages 185-201, April.
    6. Hiroko Nakamura & Shinji Suzuki & Tomobe Hironori & Yuya Kajikawa & Ichiro Sakata, 2011. "Citation lag analysis in supply chain research," Scientometrics, Springer;Akadémiai Kiadó, vol. 87(2), pages 221-232, May.
    7. Dosi, Giovanni, 1993. "Technological paradigms and technological trajectories : A suggested interpretation of the determinants and directions of technical change," Research Policy, Elsevier, vol. 22(2), pages 102-103, April.
    8. Nelson, Richard R. & Winter, Sidney G., 1993. "In search of useful theory of innovation," Research Policy, Elsevier, vol. 22(2), pages 108-108, April.
    9. Neil R. Smalheiser, 2012. "Literature-based discovery: Beyond the ABCs," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 63(2), pages 218-224, February.
    10. 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.
    11. Loet Leydesdorff, 2008. "Patent classifications as indicators of intellectual organization," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 59(10), pages 1582-1597, August.
    12. Jaffe, Adam B, 1986. "Technological Opportunity and Spillovers of R&D: Evidence from Firms' Patents, Profits, and Market Value," American Economic Review, American Economic Association, vol. 76(5), pages 984-1001, December.
    13. Ikujiro Nonaka, 1994. "A Dynamic Theory of Organizational Knowledge Creation," Organization Science, INFORMS, vol. 5(1), pages 14-37, February.
    14. Martin Meyer, 2000. "What is Special about Patent Citations? Differences between Scientific and Patent Citations," Scientometrics, Springer;Akadémiai Kiadó, vol. 49(1), pages 93-123, August.
    15. Zvi Griliches, 1998. "Patent Statistics as Economic Indicators: A Survey," NBER Chapters, in: R&D and Productivity: The Econometric Evidence, pages 287-343, National Bureau of Economic Research, Inc.
    16. 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.
    17. Schoenmakers, Wilfred & Duysters, Geert, 2010. "The technological origins of radical inventions," Research Policy, Elsevier, vol. 39(8), pages 1051-1059, October.
    18. Aija Leiponen & Constance E. Helfat, 2010. "Innovation objectives, knowledge sources, and the benefits of breadth," Strategic Management Journal, Wiley Blackwell, vol. 31(2), pages 224-236, February.
    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. Dibiaggio, Ludovic & Nasiriyar, Maryam & Nesta, Lionel, 2014. "Substitutability and complementarity of technological knowledge and the inventive performance of semiconductor companies," Research Policy, Elsevier, vol. 43(9), pages 1582-1593.
    2. Martin Kalthaus, 2020. "Knowledge recombination along the technology life cycle," Journal of Evolutionary Economics, Springer, vol. 30(3), pages 643-704, July.
    3. von Wartburg, Iwan & Teichert, Thorsten & Rost, Katja, 2005. "Inventive progress measured by multi-stage patent citation analysis," Research Policy, Elsevier, vol. 34(10), pages 1591-1607, December.
    4. John-Paul Ferguson & Gianluca Carnabuci, 2017. "Risky Recombinations: Institutional Gatekeeping in the Innovation Process," Organization Science, INFORMS, vol. 28(1), pages 133-151, February.
    5. Francesco Lamperti & Franco Malerba & Roberto Mavilia & Giorgio Tripodi, 2019. "Does the Position in the Inter-sectoral Knowledge Space affect the International Competitiveness of Industries?," LEM Papers Series 2019/23, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    6. Francesco Quatraro, 2016. "Co-evolutionary Patterns in Regional Knowledge Bases and Economic Structure: Evidence from European Regions," Regional Studies, Taylor & Francis Journals, vol. 50(3), pages 513-539, March.
    7. Si Hyung Joo & Yeonbae Kim, 2010. "Measuring relatedness between technological fields," Scientometrics, Springer;Akadémiai Kiadó, vol. 83(2), pages 435-454, May.
    8. repec:hal:spmain:info:hdl:2441/43aq8ffdqb82sbffkv69bt1eaa is not listed on IDEAS
    9. repec:spo:wpmain:info:hdl:2441/43aq8ffdqb82sbffkv69bt1eaa is not listed on IDEAS
    10. 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).
    11. Francesco Quatraro, 2012. "The Co-Evolution of Knowledge and Economic Structure: Evidence from European Regions," GREDEG Working Papers 2012-16, Groupe de REcherche en Droit, Economie, Gestion (GREDEG CNRS), Université Côte d'Azur, France.
    12. 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.
    13. 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.
    14. Battke, Benedikt & Schmidt, Tobias S. & Stollenwerk, Stephan & Hoffmann, Volker H., 2016. "Internal or external spillovers—Which kind of knowledge is more likely to flow within or across technologies," Research Policy, Elsevier, vol. 45(1), pages 27-41.
    15. Inchae Park & Yujin Jeong & Byungun Yoon, 2017. "Analyzing the value of technology based on the differences of patent citations between applicants and examiners," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(2), pages 665-691, May.
    16. Krafft Jackie & Quatraro Francesco & Colombelli Alessandra, 2011. "High Growth Firms and Technological Knowledge: Do gazelles follow exploration or exploitation strategies?," Department of Economics and Statistics Cognetti de Martiis LEI & BRICK - Laboratory of Economics of Innovation "Franco Momigliano", Bureau of Research in Innovation, Complexity and Knowledge, Collegio 201114, University of Turin.
    17. 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.
    18. Antonelli Cristiano & Colombelli Alessandra, 2013. "Knowledge cumulability and complementarity in the knowledge generation function," Department of Economics and Statistics Cognetti de Martiis. Working Papers 201305, University of Turin.
    19. Ugo Rizzo & Nicolò Barbieri & Laura Ramaciotti & Demian Iannantuono, 2020. "The division of labour between academia and industry for the generation of radical inventions," The Journal of Technology Transfer, Springer, vol. 45(2), pages 393-413, April.
    20. Cristiano Antonelli & Alessandra Colombelli, 2017. "The locus of knowledge externalities and the cost of knowledge," Regional Studies, Taylor & Francis Journals, vol. 51(8), pages 1151-1164, August.
    21. Maryann Feldman & Dieter Kogler & David Rigby, 2013. "rKnowledge: The Spatial Diffusion of rDNA Methods," Papers in Evolutionary Economic Geography (PEEG) 1311, Utrecht University, Department of Human Geography and Spatial Planning, Group Economic Geography, revised Aug 2013.
    22. Barbieri, Nicolò & Marzucchi, Alberto & Rizzo, Ugo, 2020. "Knowledge sources and impacts on subsequent inventions: Do green technologies differ from non-green ones?," Research Policy, Elsevier, vol. 49(2).

    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:94:y:2015:i:c:p:187-201. 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.