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Inter-technology relationship networks: Arranging technologies through text mining

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  • Hofmann, Peter
  • Keller, Robert
  • Urbach, Nils

Abstract

Ongoing advances in digital technologies – which enable new products, services, and business models – have fundamentally affected business and society through several waves of digitalization. When analyzing digital technologies, a dynamic system or an ecosystem model that represents interrelated technologies is beneficial owing to the systemic character of digital technologies. Using an assembly-based process model for situational method engineering, and following the design science research paradigm, we develop an analytical method to generate technology-related network data that retraces elapsed patterns of technological change. We consider the technological distances that characterize technologies' proximities and dependencies. We use established text mining techniques and draw from technology innovation research as justificatory knowledge. The proposed method processes textual data from different information sources into an analyzable and readable inter-technology relationship network. To evaluate the method, we use exemplary digital technologies from the big data analytics domain as an application scenario.

Suggested Citation

  • Hofmann, Peter & Keller, Robert & Urbach, Nils, 2019. "Inter-technology relationship networks: Arranging technologies through text mining," Technological Forecasting and Social Change, Elsevier, vol. 143(C), pages 202-213.
    • Handle: RePEc:eee:tefoso:v:143:y:2019:i:c:p:202-213
    DOI: 10.1016/j.techfore.2019.02.009
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    as
    1. Janghyeok Yoon & Sungchul Choi & Kwangsoo Kim, 2011. "Invention property-function network analysis of patents: a case of silicon-based thin film solar cells," Scientometrics, Springer;Akadémiai Kiadó, vol. 86(3), pages 687-703, March.
    2. Loet Leydesdorff & Duncan Kushnir & Ismael Rafols, 2014. "Interactive overlay maps for US patent (USPTO) data based on International Patent Classification (IPC)," Scientometrics, Springer;Akadémiai Kiadó, vol. 98(3), pages 1583-1599, March.
    3. Janghyeok Yoon & Hyunseok Park & Kwangsoo Kim, 2013. "Identifying technological competition trends for R&D planning using dynamic patent maps: SAO-based content analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 94(1), pages 313-331, January.
    4. Si Hyung Joo & Yeonbae Kim, 2010. "Measuring relatedness between technological fields," Scientometrics, Springer;Akadémiai Kiadó, vol. 83(2), pages 435-454, May.
    5. Klaus Kultti & Tuomas Takalo & Juuso Toikka, 2007. "Secrecy versus patenting," RAND Journal of Economics, RAND Corporation, vol. 38(1), pages 22-42, March.
    6. Gupta, V. K. & Pangannaya, N. B., 2000. "Carbon nanotubes: bibliometric analysis of patents," World Patent Information, Elsevier, vol. 22(3), pages 185-189, September.
    7. Catia Pesquita & Daniel Faria & André O Falcão & Phillip Lord & Francisco M Couto, 2009. "Semantic Similarity in Biomedical Ontologies," PLOS Computational Biology, Public Library of Science, vol. 5(7), pages 1-12, July.
    8. 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.
    9. Luciano Kay & Nils Newman & Jan Youtie & Alan L. Porter & Ismael Rafols, 2014. "Patent overlay mapping: Visualizing technological distance," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 65(12), pages 2432-2443, December.
    10. Aharonson, Barak S. & Schilling, Melissa A., 2016. "Mapping the technological landscape: Measuring technology distance, technological footprints, and technology evolution," Research Policy, Elsevier, vol. 45(1), pages 81-96.
    11. Richard Klavans & Kevin W. Boyack, 2009. "Toward a consensus map of science," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 60(3), pages 455-476, March.
    12. Sungchul Choi & Janghyeok Yoon & Kwangsoo Kim & Jae Yeol Lee & Cheol-Han Kim, 2011. "SAO network analysis of patents for technology trends identification: a case study of polymer electrolyte membrane technology in proton exchange membrane fuel cells," Scientometrics, Springer;Akadémiai Kiadó, vol. 88(3), pages 863-883, September.
    13. Janghyeok Yoon & Kwangsoo Kim, 2011. "Identifying rapidly evolving technological trends for R&D planning using SAO-based semantic patent networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 88(1), pages 213-228, July.
    14. Janghyeok Yoon & Kwangsoo Kim, 2012. "Detecting signals of new technological opportunities using semantic patent analysis and outlier detection," Scientometrics, Springer;Akadémiai Kiadó, vol. 90(2), pages 445-461, February.
    15. Arthur, W. Brian, 2007. "The structure of invention," Research Policy, Elsevier, vol. 36(2), pages 274-287, March.
    16. David A. Hull, 1996. "Stemming algorithms: A case study for detailed evaluation," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 47(1), pages 70-84, January.
    17. Yi Zhang & Hongshu Chen & Donghua Zhu, 2016. "Semi-automatic Technology Roadmapping Composing Method for Multiple Science, Technology, and Innovation Data Incorporation," Innovation, Technology, and Knowledge Management, in: Tugrul U. Daim & Denise Chiavetta & Alan L. Porter & Ozcan Saritas (ed.), Anticipating Future Innovation Pathways Through Large Data Analysis, chapter 0, pages 211-227, Springer.
    18. 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.
    19. Scott Deerwester & Susan T. Dumais & George W. Furnas & Thomas K. Landauer & Richard Harshman, 1990. "Indexing by latent semantic analysis," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 41(6), pages 391-407, September.
    20. Leo Egghe & Ronald Rousseau, 2002. "Co-citation, bibliographic coupling and a characterization of lattice citation networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 55(3), pages 349-361, November.
    21. Kevin W. Boyack & Richard Klavans & Katy Börner, 2005. "Mapping the backbone of science," Scientometrics, Springer;Akadémiai Kiadó, vol. 64(3), pages 351-374, August.
    22. Ritu Agarwal & Vasant Dhar, 2014. "Editorial —Big Data, Data Science, and Analytics: The Opportunity and Challenge for IS Research," Information Systems Research, INFORMS, vol. 25(3), pages 443-448, September.
    23. 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.
    24. Farshad Madani, 2015. "‘Technology Mining’ bibliometrics analysis: applying network analysis and cluster analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 105(1), pages 323-335, October.
    25. 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.
    26. Engelsman, E. C. & van Raan, A. F. J., 1994. "A patent-based cartography of technology," Research Policy, Elsevier, vol. 23(1), pages 1-26, January.
    27. Francis Narin & Dominic Olivastro & Kimberly A. Stevens, 1994. "Bibliometrics/Theory, Practice and Problems," Evaluation Review, , vol. 18(1), pages 65-76, February.
    28. Christine Legner & Torsten Eymann & Thomas Hess & Christian Matt & Tilo Böhmann & Paul Drews & Alexander Mädche & Nils Urbach & Frederik Ahlemann, 2017. "Digitalization: Opportunity and Challenge for the Business and Information Systems Engineering Community," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 59(4), pages 301-308, August.
    29. Don R. Swanson, 1987. "Two medical literatures that are logically but not bibliographically connected," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 38(4), pages 228-233, July.
    30. Breschi, Stefano & Lissoni, Francesco & Malerba, Franco, 2003. "Knowledge-relatedness in firm technological diversification," Research Policy, Elsevier, vol. 32(1), pages 69-87, January.
    31. Bowen Yan & Jianxi Luo, 2017. "Measuring technological distance for patent mapping," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 68(2), pages 423-437, February.
    32. Schoenmakers, Wilfred & Duysters, Geert, 2010. "The technological origins of radical inventions," Research Policy, Elsevier, vol. 39(8), pages 1051-1059, October.
    33. Loet Leydesdorff & Liwen Vaughan, 2006. "Co‐occurrence matrices and their applications in information science: Extending ACA to the Web environment," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 57(12), pages 1616-1628, October.
    34. Loet Leydesdorff & Ismael Rafols, 2009. "A global map of science based on the ISI subject categories," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 60(2), pages 348-362, February.
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