IDEAS home Printed from https://ideas.repec.org/a/eee/tefoso/v129y2018icp285-296.html
   My bibliography  Save this article

Insights into relationships between disruptive technology/innovation and emerging technology: A bibliometric perspective

Author

Listed:
  • Li, Munan
  • Porter, Alan L.
  • Suominen, Arho

Abstract

“Disruptive technology & disruptive innovation” have been of scholarly interest for years, but there is still a need to better understand the nature of disruptions and their relationship to emerging technology processes. This paper pursues these issues by analyzing the interplay of technological emergence, disruption, and innovation. Applying bibliometric methods, the paper explores the conceptual foundations, themes, and research communities within these research domains. The results highlight the multiple theoretical foundations of research around technological change processes, disruption, and emergence. These differences among the domains invite conceptual cross-fertilization and consideration of interdisciplinary approaches to technological (and commercial) emergence.

Suggested Citation

  • Li, Munan & Porter, Alan L. & Suominen, Arho, 2018. "Insights into relationships between disruptive technology/innovation and emerging technology: A bibliometric perspective," Technological Forecasting and Social Change, Elsevier, vol. 129(C), pages 285-296.
    • Handle: RePEc:eee:tefoso:v:129:y:2018:i:c:p:285-296
    DOI: 10.1016/j.techfore.2017.09.032
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0040162517314609
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.techfore.2017.09.032?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. Robinson, Douglas K.R. & Huang, Lu & Guo, Ying & Porter, Alan L., 2013. "Forecasting Innovation Pathways (FIP) for new and emerging science and technologies," Technological Forecasting and Social Change, Elsevier, vol. 80(2), pages 267-285.
    2. David J. TEECE, 2008. "Profiting from technological innovation: Implications for integration, collaboration, licensing and public policy," World Scientific Book Chapters, in: The Transfer And Licensing Of Know-How And Intellectual Property Understanding the Multinational Enterprise in the Modern World, chapter 5, pages 67-87, World Scientific Publishing Co. Pte. Ltd..
    3. Jan Youtie & Luciano Kay & Julia Melkers, 2013. "Bibliographic coupling and network analysis to assess knowledge coalescence in a research center environment," Research Evaluation, Oxford University Press, vol. 22(3), pages 145-156, March.
    4. Chaomei Chen, 2006. "CiteSpace II: Detecting and visualizing emerging trends and transient patterns in scientific literature," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 57(3), pages 359-377, February.
    5. Alan L Porter & J David Roessner & Xiao-Yin Jin & Nils C Newman, 2002. "Measuring national ‘emerging technology’ capabilities," Science and Public Policy, Oxford University Press, vol. 29(3), pages 189-200, June.
    6. M. M. Kessler, 1963. "Bibliographic coupling between scientific papers," American Documentation, Wiley Blackwell, vol. 14(1), pages 10-25, January.
    7. 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.
    8. Small, Henry & Boyack, Kevin W. & Klavans, Richard, 2014. "Identifying emerging topics in science and technology," Research Policy, Elsevier, vol. 43(8), pages 1450-1467.
    9. 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.
    10. Kevin W. Boyack & Richard Klavans, 2010. "Co‐citation analysis, bibliographic coupling, and direct citation: Which citation approach represents the research front most accurately?," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 61(12), pages 2389-2404, December.
    11. Xiaotong Li, 2005. "Cheap Talk and Bogus Network Externalities in the Emerging Technology Market," Marketing Science, INFORMS, vol. 24(4), pages 531-543, October.
    12. Ali Gazni & Fereshteh Didegah, 2016. "The relationship between authors’ bibliographic coupling and citation exchange: analyzing disciplinary differences," Scientometrics, Springer;Akadémiai Kiadó, vol. 107(2), pages 609-626, May.
    13. Douglas K. R. Robinson & Lu Huang & Yan Guo & Alan L. Porter, 2013. "Forecasting Innovation Pathways (FIP) for new and emerging science and technologies," Post-Print hal-01070417, HAL.
    14. Rotolo, Daniele & Hicks, Diana & Martin, Ben R., 2015. "What is an emerging technology?," Research Policy, Elsevier, vol. 44(10), pages 1827-1843.
    15. Berman, Barry, 2012. "3-D printing: The new industrial revolution," Business Horizons, Elsevier, vol. 55(2), pages 155-162.
    16. Henry Small, 1973. "Co‐citation in the scientific literature: A new measure of the relationship between two documents," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 24(4), pages 265-269, July.
    17. Clayton M. Christensen & Matt Verlinden & George Westerman, 2002. "Disruption, disintegration and the dissipation of differentiability," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 11(5), pages 955-993, November.
    18. Kevin W. Boyack & Richard Klavans, 2010. "Co-citation analysis, bibliographic coupling, and direct citation: Which citation approach represents the research front most accurately?," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 61(12), pages 2389-2404, December.
    19. Huang, Lu & Zhang, Yi & Guo, Ying & Zhu, Donghua & Porter, Alan L., 2014. "Four dimensional Science and Technology planning: A new approach based on bibliometrics and technology roadmapping," Technological Forecasting and Social Change, Elsevier, vol. 81(C), pages 39-48.
    20. D.K. Robinson & Lu Huang & Ying Guo & Alan L. Porter, 2013. "Forecasting Innovation Pathways (FIP) for new and emerging science and technologies," Post-Print hal-01071140, HAL.
    21. Riordan, Michael H & Salant, David J, 1994. "Preemptive Adoptions of an Emerging Technology," Journal of Industrial Economics, Wiley Blackwell, vol. 42(3), pages 247-261, September.
    22. André O Laplume & Bent Petersen & Joshua M Pearce, 2016. "Global value chains from a 3D printing perspective," Journal of International Business Studies, Palgrave Macmillan;Academy of International Business, vol. 47(5), pages 595-609, June.
    23. Boon, Wouter & Moors, Ellen, 2008. "Exploring emerging technologies using metaphors - A study of orphan drugs and pharmacogenomics," Social Science & Medicine, Elsevier, vol. 66(9), pages 1915-1927, May.
    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. Porter, Alan L. & Garner, Jon & Carley, Stephen F. & Newman, Nils C., 2019. "Emergence scoring to identify frontier R&D topics and key players," Technological Forecasting and Social Change, Elsevier, vol. 146(C), pages 628-643.
    2. Mingyue Chu & Haslinah Binti Muhamad & Mazlina Binti Mustapha & Ong Tze San & Fangfang Zan & Xiaoxiao Jia, 2022. "Research Trends in Corporate Social Responsibility and Innovation: A Bibliometric Analysis," Sustainability, MDPI, vol. 14(21), pages 1-19, October.
    3. Ashkenazi, Dana, 2019. "How aluminum changed the world: A metallurgical revolution through technological and cultural perspectives," Technological Forecasting and Social Change, Elsevier, vol. 143(C), pages 101-113.
    4. Blume, Maximilian & Oberländer, Anna Maria & Röglinger, Maximilian & Rosemann, Michael & Wyrtki, Katrin, 2020. "Ex ante assessment of disruptive threats: Identifying relevant threats before one is disrupted," Technological Forecasting and Social Change, Elsevier, vol. 158(C).
    5. Mariani, Marcello & Borghi, Matteo, 2019. "Industry 4.0: A bibliometric review of its managerial intellectual structure and potential evolution in the service industries," Technological Forecasting and Social Change, Elsevier, vol. 149(C).
    6. Kwon, Seokbeom & Liu, Xiaoyu & Porter, Alan L. & Youtie, Jan, 2019. "Research addressing emerging technological ideas has greater scientific impact," Research Policy, Elsevier, vol. 48(9), pages 1-1.
    7. Jiqing Liu & Gui Zhang & Xiaojing Lv & Jiayu Li, 2022. "Discovering the Landscape and Evolution of Responsible Research and Innovation (RRI): Science Mapping Based on Bibliometric Analysis," Sustainability, MDPI, vol. 14(14), pages 1-32, July.
    8. Harald König & Martina F. Baumann & Christopher Coenen, 2021. "Emerging Technologies and Innovation—Hopes for and Obstacles to Inclusive Societal Co-Construction," Sustainability, MDPI, vol. 13(23), pages 1-13, November.
    9. Tandon, Anushree & Kaur, Puneet & Mäntymäki, Matti & Dhir, Amandeep, 2021. "Blockchain applications in management: A bibliometric analysis and literature review," Technological Forecasting and Social Change, Elsevier, vol. 166(C).
    10. Antonio, Jerome L. & Kanbach, Dominik K., 2023. "Contextual factors of disruptive innovation: A systematic review and framework," Technological Forecasting and Social Change, Elsevier, vol. 188(C).
    11. Zamani, Mehdi & Yalcin, Haydar & Naeini, Ali Bonyadi & Zeba, Gordana & Daim, Tugrul U, 2022. "Developing metrics for emerging technologies: identification and assessment," Technological Forecasting and Social Change, Elsevier, vol. 176(C).
    12. Xu, Haiyun & Winnink, Jos & Yue, Zenghui & Zhang, Huiling & Pang, Hongshen, 2021. "Multidimensional Scientometric indicators for the detection of emerging research topics," Technological Forecasting and Social Change, Elsevier, vol. 163(C).
    13. Mikel Zubizarreta & Jaione Ganzarain & Jesús Cuadrado & Rafael Lizarralde, 2020. "Evaluating Disruptive Innovation Project Management Capabilities," Sustainability, MDPI, vol. 13(1), pages 1-22, December.
    14. Alfonso Marino & Paolo Pariso, 2021. "Digital economy: technological, organizational and cultural contexts for the development of cooperation in Europe," Entrepreneurship and Sustainability Issues, VsI Entrepreneurship and Sustainability Center, vol. 9(2), pages 363-383, December.
    15. Porter, Alan L. & Chiavetta, Denise & Newman, Nils C., 2020. "Measuring tech emergence: A contest," Technological Forecasting and Social Change, Elsevier, vol. 159(C).
    16. Li, Munan & Wang, Wenshu & Zhou, Keyu, 2021. "Exploring the technology emergence related to artificial intelligence: A perspective of coupling analyses," Technological Forecasting and Social Change, Elsevier, vol. 172(C).
    17. Serhat Burmaoglu & Olivier Sartenaer & Alan Porter & Munan Li, 2019. "Analysing the theoretical roots of technology emergence: an evolutionary perspective," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(1), pages 97-118, April.
    18. Hongyu Liu & Shukuan Zhao & Ouyang Xin, 2019. "Analysis on the Evolution Path and Hotspot of Knowledge Innovation Study Based on Knowledge Map," Sustainability, MDPI, vol. 11(19), pages 1-14, October.
    19. Guo, Jianfeng & Pan, Jiaofeng & Guo, Jianxin & Gu, Fu & Kuusisto, Jari, 2019. "Measurement framework for assessing disruptive innovations," Technological Forecasting and Social Change, Elsevier, vol. 139(C), pages 250-265.

    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. Shuo Xu & Liyuan Hao & Xin An & Hongshen Pang & Ting Li, 2020. "Review on emerging research topics with key-route main path analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 122(1), pages 607-624, January.
    2. Li, Xin & Xie, Qianqian & Jiang, Jiaojiao & Zhou, Yuan & Huang, Lucheng, 2019. "Identifying and monitoring the development trends of emerging technologies using patent analysis and Twitter data mining: The case of perovskite solar cell technology," Technological Forecasting and Social Change, Elsevier, vol. 146(C), pages 687-705.
    3. Kwon, Seokbeom & Liu, Xiaoyu & Porter, Alan L. & Youtie, Jan, 2019. "Research addressing emerging technological ideas has greater scientific impact," Research Policy, Elsevier, vol. 48(9), pages 1-1.
    4. Zhang, Yi & Zhang, Guangquan & Chen, Hongshu & Porter, Alan L. & Zhu, Donghua & Lu, Jie, 2016. "Topic analysis and forecasting for science, technology and innovation: Methodology with a case study focusing on big data research," Technological Forecasting and Social Change, Elsevier, vol. 105(C), pages 179-191.
    5. Xu, Shuo & Hao, Liyuan & Yang, Guancan & Lu, Kun & An, Xin, 2021. "A topic models based framework for detecting and forecasting emerging technologies," Technological Forecasting and Social Change, Elsevier, vol. 162(C).
    6. Rotolo, Daniele & Hicks, Diana & Martin, Ben R., 2015. "What is an emerging technology?," Research Policy, Elsevier, vol. 44(10), pages 1827-1843.
    7. Alfonso Ávila-Robinson & Shintaro Sengoku, 2017. "Tracing the knowledge-building dynamics in new stem cell technologies through techno-scientific networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 112(3), pages 1691-1720, September.
    8. Coccia, Mario & Wang, Lili, 2015. "Path-breaking directions of nanotechnology-based chemotherapy and molecular cancer therapy," Technological Forecasting and Social Change, Elsevier, vol. 94(C), pages 155-169.
    9. Ying Huang & Wolfgang Glänzel & Lin Zhang, 2021. "Tracing the development of mapping knowledge domains," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(7), pages 6201-6224, July.
    10. Petros Gkotsis & Antonio Vezzani, 2016. "Technological diffusion as a recombinant process," JRC Working Papers on Corporate R&D and Innovation 2016-07, Joint Research Centre.
    11. Toshiyuki Hasumi & Mei-Shiu Chiu, 2022. "Online mathematics education as bio-eco-techno process: bibliometric analysis using co-authorship and bibliographic coupling," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(8), pages 4631-4654, August.
    12. Michel Zitt, 2015. "Meso-level retrieval: IR-bibliometrics interplay and hybrid citation-words methods in scientific fields delineation," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(3), pages 2223-2245, March.
    13. Rakas, Marija & Hain, Daniel S., 2019. "The state of innovation system research: What happens beneath the surface?," Research Policy, Elsevier, vol. 48(9), pages 1-1.
    14. Kyebambe, Moses Ntanda & Cheng, Ge & Huang, Yunqing & He, Chunhui & Zhang, Zhenyu, 2017. "Forecasting emerging technologies: A supervised learning approach through patent analysis," Technological Forecasting and Social Change, Elsevier, vol. 125(C), pages 236-244.
    15. Konstantin Fursov & Alina Kadyrova, 2017. "How the analysis of transitionary references in knowledge networks and their centrality characteristics helps in understanding the genesis of growing technology areas," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(3), pages 1947-1963, June.
    16. Zhang, Yi & Robinson, Douglas K.R. & Porter, Alan L. & Zhu, Donghua & Zhang, Guangquan & Lu, Jie, 2016. "Technology roadmapping for competitive technical intelligence," Technological Forecasting and Social Change, Elsevier, vol. 110(C), pages 175-186.
    17. Wang, Lili & Jiang, Shan & Zhang, Shiyun, 2020. "Mapping technological trajectories and exploring knowledge sources: A case study of 3D printing technologies," Technological Forecasting and Social Change, Elsevier, vol. 161(C).
    18. Porter, Alan L. & Garner, Jon & Carley, Stephen F. & Newman, Nils C., 2019. "Emergence scoring to identify frontier R&D topics and key players," Technological Forecasting and Social Change, Elsevier, vol. 146(C), pages 628-643.
    19. Suominen, Arho & Peng, Haoshu & Ranaei, Samira, 2019. "Examining the dynamics of an emerging research network using the case of triboelectric nanogenerators," Technological Forecasting and Social Change, Elsevier, vol. 146(C), pages 820-830.
    20. Sohrabi, Babak & Khalilijafarabad, Ahmad, 2018. "Systematic method for finding emergence research areas as data quality," Technological Forecasting and Social Change, Elsevier, vol. 137(C), pages 280-287.

    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:129:y:2018:i:c:p:285-296. 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.