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NK model-based analysis of technological trajectories: a study on the technological field of computer graphic processing systems

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  • Ichiro Watanabe

    (The University of Tokyo)

  • Soichiro Takagi

    (The University of Tokyo)

Abstract

This paper quantitatively analyzes how the interdependence of components and the complexity of technology relates to the formation of technological trajectories. This paper uses the idea of technological trajectory and a method called a main path analysis. Technological trajectory is an idea that describes the path-dependent technological evolution process. The technological trajectories of a technological field can be represented as the main paths of patent citation networks. This paper aims to elucidate some of the determinants of the evolution of technological trajectories using main path analysis. The hypotheses are derived from a model called the NK Model. The NK model describes the respective roles of the interdependence of components and of complexity in complex adaptive systems. Using the NK model, it can be understood that technologies with an intermediate level of interdependence and technologies with an intermediate level of complexity tend to be more successful than other technologies. According to the result, the patents on the main paths of this technological field are concentrated at the intermediate level of interdependence but the patents on the main paths of this technological field are not concentrated at the intermediate level of technological complexity. Additionally, in the technological field’s early stage, the interdependence values of patents that are locked-in within technological trajectories are high, whereas the same values of the later stage are low. This observation is also consistent with the idea of technological trajectories. These results suggest that the NK model is a useful tool to understand the formation of technological trajectories.

Suggested Citation

  • 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.
  • Handle: RePEc:spr:eaiere:v:19:y:2022:i:1:d:10.1007_s40844-021-00220-6
    DOI: 10.1007/s40844-021-00220-6
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    References listed on IDEAS

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    1. 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.
    2. Dejian Yu & Libo Sheng, 2020. "Knowledge diffusion paths of blockchain domain: the main path analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(1), pages 471-497, October.
    3. 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.
    4. 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.
    5. Nicolò Barbieri & Claudia Ghisetti & Marianna Gilli & Giovanni Marin & Francesco Nicolli, 2016. "A Survey Of The Literature On Environmental Innovation Based On Main Path Analysis," Journal of Economic Surveys, Wiley Blackwell, vol. 30(3), pages 596-623, July.
    6. Sendil K. Ethiraj & Daniel Levinthal, 2004. "Modularity and Innovation in Complex Systems," Management Science, INFORMS, vol. 50(2), pages 159-173, February.
    7. Taalbi, Josef, 2017. "What drives innovation? Evidence from economic history," Research Policy, Elsevier, vol. 46(8), pages 1437-1453.
    8. John S. Liu & Louis Y.Y. Lu, 2012. "An integrated approach for main path analysis: Development of the Hirsch index as an example," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 63(3), pages 528-542, March.
    9. Possas, Mario Luiz & Salles-Filho, Sergio & da Silveira, JoseMaria, 1996. "An evolutionary approach to technological innovation in agriculture: some preliminary remarks," Research Policy, Elsevier, vol. 25(6), pages 933-945, September.
    10. 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.
    11. 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.
    12. Ganco, Martin, 2017. "NK model as a representation of innovative search," Research Policy, Elsevier, vol. 46(10), pages 1783-1800.
    13. 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.
    14. Lee Fleming & Olav Sorenson, 2004. "Science as a map in technological search," Strategic Management Journal, Wiley Blackwell, vol. 25(8‐9), pages 909-928, August.
    15. Martin Ganco, 2013. "Cutting the Gordian knot: The effect of knowledge complexity on employee mobility and entrepreneurship," Strategic Management Journal, Wiley Blackwell, vol. 34(6), pages 666-686, June.
    16. Olav Sorenson & Jan W. Rivkin & Lee Fleming, 2010. "Complexity, Networks and Knowledge Flows," Chapters, in: Ron Boschma & Ron Martin (ed.), The Handbook of Evolutionary Economic Geography, chapter 15, Edward Elgar Publishing.
    17. Frenken, Koen, 2000. "A complexity approach to innovation networks. The case of the aircraft industry (1909-1997)," Research Policy, Elsevier, vol. 29(2), pages 257-272, February.
    18. 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.
    19. Koen Frenken, 2006. "Innovation, Evolution and Complexity Theory," Books, Edward Elgar Publishing, number 2939.
    20. 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.
    21. John S. Liu & Louis Y.Y. Lu, 2012. "An integrated approach for main path analysis: Development of the Hirsch index as an example," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 63(3), pages 528-542, March.
    22. John S. Liu & Chung-Huei Kuan, 2016. "A new approach for main path analysis: Decay in knowledge diffusion," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 67(2), pages 465-476, February.
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    More about this item

    Keywords

    Technological trajectory; Technology life cycle; Patent citation network; NK model;
    All these keywords.

    JEL classification:

    • O30 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - General
    • O32 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Management of Technological Innovation and R&D
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
    • L63 - Industrial Organization - - Industry Studies: Manufacturing - - - Microelectronics; Computers; Communications Equipment

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