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How industrial convergence happens: A taxonomical approach based on empirical evidences

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  • Geum, Youngjung
  • Kim, Moon-Soo
  • Lee, Sungjoo

Abstract

The current innovation paradigm clearly shows that the notion of “industry” is changing. Innovation no longer occurs within single industries. This paper employs practical data on 100 successful Korean cases of industrial convergence to analyze how industrial convergence takes place. Together, these practical cases represent the essential characteristics of industry convergence. We identify the pattern of industry convergence through a clustering analysis that identifies the characteristics of each cluster. As a result, we identify four industry convergence types: technology enhancer, policy-driven environmental enhancer, service-integrated social business generator, and technology-driven new value generator.

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  • Geum, Youngjung & Kim, Moon-Soo & Lee, Sungjoo, 2016. "How industrial convergence happens: A taxonomical approach based on empirical evidences," Technological Forecasting and Social Change, Elsevier, vol. 107(C), pages 112-120.
    • Handle: RePEc:eee:tefoso:v:107:y:2016:i:c:p:112-120
    DOI: 10.1016/j.techfore.2016.03.020
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    Cited by:

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    2. Sick, Nathalie & Preschitschek, Nina & Leker, Jens & Bröring, Stefanie, 2019. "A new framework to assess industry convergence in high technology environments," Technovation, Elsevier, vol. 84, pages 48-58.
    3. Xiaowei Chen & Tianyu Zhang & Fu Jia, 2020. "Industry convergence as a strategy for achieving sustainable development of agricultural complex: The case of Sandun‐Lanli in China," Business Strategy and the Environment, Wiley Blackwell, vol. 29(6), pages 2679-2694, September.
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    6. Sick, Nathalie & Bröring, Stefanie, 2022. "Exploring the research landscape of convergence from a TIM perspective: A review and research agenda," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
    7. Zhou, Yuan & Dong, Fang & Kong, Dejing & Liu, Yufei, 2019. "Unfolding the convergence process of scientific knowledge for the early identification of emerging technologies," Technological Forecasting and Social Change, Elsevier, vol. 144(C), pages 205-220.
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    10. Achrol, Ravi S. & Kotler, Philip, 2022. "Distributed marketing networks: The fourth industrial revolution," Journal of Business Research, Elsevier, vol. 150(C), pages 515-527.
    11. Chunbo Zhou & Marios Sotiriadis, 2021. "Exploring and Evaluating the Impact of ICTs on Culture and Tourism Industries’ Convergence: Evidence from China," Sustainability, MDPI, vol. 13(21), pages 1-18, October.
    12. Sajad Ashouri & Anne-Laure Mention & Kosmas X. Smyrnios, 2021. "Anticipation and analysis of industry convergence using patent-level indicators," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(7), pages 5727-5758, July.
    13. Song, Bomi & Suh, Yongyoon, 2019. "Identifying convergence fields and technologies for industrial safety: LDA-based network analysis," Technological Forecasting and Social Change, Elsevier, vol. 138(C), pages 115-126.
    14. Jianjia He & Yue Wang, 2023. "Patent-Based Analysis of China’s Emergency Logistics Industry Convergence," Sustainability, MDPI, vol. 15(5), pages 1-13, March.
    15. Nicola Melluso & Andrea Bonaccorsi & Filippo Chiarello & Gualtiero Fantoni, 2021. "Rapid detection of fast innovation under the pressure of COVID-19," Papers 2102.00197, arXiv.org.
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    17. Noh, Heeyong & Lee, Sungjoo, 2020. "What constitutes a promising technology in the era of open innovation? An investigation of patent potential from multiple perspectives," Technological Forecasting and Social Change, Elsevier, vol. 157(C).

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