IDEAS home Printed from https://ideas.repec.org/a/eee/tefoso/v138y2019icp45-68.html
   My bibliography  Save this article

Extracting commercialization opportunities of the Internet of Things: Measuring text similarity between papers and patents

Author

Listed:
  • Takano, Yasutomo
  • Kajikawa, Yuya

Abstract

In the field of technology management, methods have been developed to detect technologies that are important in industry by analyzing massive numbers of documents. Such methods have been applied to the field of the Internet of Things as well to investigate technological trends. The Internet of Things consists of several conventional concepts, such as radio frequency identification, near field communication, and sensor networks. However, no research compares these technologies by analyzing massive quantities of papers and patents. Thus, in this study, we explored the research areas of technologies related to the Internet of Things, for which there are opportunities for commercialization in the near future. We also discuss potential applications of these technologies in diverse systems.

Suggested Citation

  • Takano, Yasutomo & Kajikawa, Yuya, 2019. "Extracting commercialization opportunities of the Internet of Things: Measuring text similarity between papers and patents," Technological Forecasting and Social Change, Elsevier, vol. 138(C), pages 45-68.
  • Handle: RePEc:eee:tefoso:v:138:y:2019:i:c:p:45-68
    DOI: 10.1016/j.techfore.2018.08.008
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0040162516304516
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.techfore.2018.08.008?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. 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.
    2. Karvonen, Matti & Kässi, Tuomo, 2013. "Patent citations as a tool for analysing the early stages of convergence," Technological Forecasting and Social Change, Elsevier, vol. 80(6), pages 1094-1107.
    3. Ludo Waltman & Nees Jan Eck, 2012. "A new methodology for constructing a publication-level classification system of science," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 63(12), pages 2378-2392, December.
    4. Loet Leydesdorff & Daniele Rotolo & Ismael Rafols, 2012. "Bibliometric perspectives on medical innovation using the medical subject Headings of PubMed," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 63(11), pages 2239-2253, November.
    5. Richard Klavans & Kevin W. Boyack, 2017. "Which Type of Citation Analysis Generates the Most Accurate Taxonomy of Scientific and Technical Knowledge?," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 68(4), pages 984-998, April.
    6. 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.
    7. Jochen Gläser & Wolfgang Glänzel & Andrea Scharnhorst, 2017. "Same data—different results? Towards a comparative approach to the identification of thematic structures in science," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(2), pages 981-998, May.
    8. Takano, Yasutomo & Mejia, Cristian & Kajikawa, Yuya, 2016. "Unconnected component inclusion technique for patent network analysis: Case study of Internet of Things-related technologies," Journal of Informetrics, Elsevier, vol. 10(4), pages 967-980.
    9. Gustavo Cattelan Nobre & Elaine Tavares, 2017. "Scientific literature analysis on big data and internet of things applications on circular economy: a bibliometric study," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(1), pages 463-492, April.
    10. M. M. Kessler, 1963. "Bibliographic coupling between scientific papers," American Documentation, Wiley Blackwell, vol. 14(1), pages 10-25, January.
    11. Ismael Rafols & Alan L. Porter & Loet Leydesdorff, 2010. "Science overlay maps: A new tool for research policy and library management," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 61(9), pages 1871-1887, September.
    12. Yasutomo Takano & Yuya Kajikawa & Makoto Ando, 2017. "Trends and Typology of Emerging Antenna Propagation Technologies: Citation Network Analysis," International Journal of Innovation and Technology Management (IJITM), World Scientific Publishing Co. Pte. Ltd., vol. 14(01), pages 1-19, February.
    13. 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.
    14. Dotsika, Fefie & Watkins, Andrew, 2017. "Identifying potentially disruptive trends by means of keyword network analysis," Technological Forecasting and Social Change, Elsevier, vol. 119(C), pages 114-127.
    15. Andrew Whitmore & Anurag Agarwal & Li Xu, 2015. "The Internet of Things—A survey of topics and trends," Information Systems Frontiers, Springer, vol. 17(2), pages 261-274, April.
    16. Yoshiyuki Takeda & Yuya Kajikawa, 2010. "Tracking modularity in citation networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 83(3), pages 783-792, June.
    17. Shiu-Wan Hung & An-Pang Wang, 2010. "Examining the small world phenomenon in the patent citation network: a case study of the radio frequency identification (RFID) network," Scientometrics, Springer;Akadémiai Kiadó, vol. 82(1), pages 121-134, January.
    18. Li, Ling, 2013. "Technology designed to combat fakes in the global supply chain," Business Horizons, Elsevier, vol. 56(2), pages 167-177.
    19. Rongying Zhao & Ju Wang, 2011. "Visualizing the research on pervasive and ubiquitous computing," Scientometrics, Springer;Akadémiai Kiadó, vol. 86(3), pages 593-612, March.
    20. Kim, Suwon & Kim, Seongcheol, 2016. "A multi-criteria approach toward discovering killer IoT application in Korea," Technological Forecasting and Social Change, Elsevier, vol. 102(C), pages 143-155.
    21. 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.
    22. Prabhakaran, Thara & Lathabai, Hiran H. & Changat, Manoj, 2015. "Detection of paradigm shifts and emerging fields using scientific network: A case study of Information Technology for Engineering," Technological Forecasting and Social Change, Elsevier, vol. 91(C), pages 124-145.
    23. Ludo Waltman & Nees Jan van Eck, 2012. "A new methodology for constructing a publication‐level classification system of science," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 63(12), pages 2378-2392, December.
    24. Chyi-Kwei Yau & Alan Porter & Nils Newman & Arho Suominen, 2014. "Clustering scientific documents with topic modeling," Scientometrics, Springer;Akadémiai Kiadó, vol. 100(3), pages 767-786, September.
    25. 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.
    26. Hiroko Nakamura & Shinji Suzuki & Yuya Kajikawa & Masataka Osawa, 2015. "The effect of patent family information in patent citation network analysis: a comparative case study in the drivetrain domain," Scientometrics, Springer;Akadémiai Kiadó, vol. 104(2), pages 437-452, August.
    27. Shancang Li & Li Da Xu & Shanshan Zhao, 2015. "The internet of things: a survey," Information Systems Frontiers, Springer, vol. 17(2), pages 243-259, April.
    28. Masoud Shakiba & Azam Zavvari & Nader Aleebrahim & Mandeep Jit Singh, 2016. "Evaluating the academic trend of RFID technology based on SCI and SSCI publications from 2001 to 2014," Scientometrics, Springer;Akadémiai Kiadó, vol. 109(1), pages 591-614, October.
    29. Naoki Shibata & Yuya Kajikawa & Yoshiyuki Takeda & Katsumori Matsushima, 2009. "Comparative study on methods of detecting research fronts using different types of citation," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 60(3), pages 571-580, March.
    30. Bei-Ni Yan & Tian-Shyug Lee & Tsung-Pei Lee, 2015. "Mapping the intellectual structure of the Internet of Things (IoT) field (2000–2014): a co-word analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 105(2), pages 1285-1300, November.
    31. Arif Mehmood & Gyu Sang Choi & Otto F. Feigenblatt & Han Woo Park, 2016. "Proving ground for social network analysis in the emerging research area “Internet of Things” (IoT)," Scientometrics, Springer;Akadémiai Kiadó, vol. 109(1), pages 185-201, October.
    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. Moaniba, Igam M. & Lee, Pei-Chun & Su, Hsin-Ning, 2020. "How does external knowledge sourcing enhance product development? Evidence from drug commercialization," Technology in Society, Elsevier, vol. 63(C).
    2. Del Vecchio, Pasquale & Secundo, Giustina & Garzoni, Antonello, 2023. "Phygital technologies and environments for breakthrough innovation in customers' and citizens' journey. A critical literature review and future agenda," Technological Forecasting and Social Change, Elsevier, vol. 189(C).
    3. Xiaoli Wang & Yun Liu & Lingdi Chen & Yifan Zhang, 2022. "Correlation Monitoring Method and model of Science-Technology-Industry in the AI Field: A Case of the Neural Network," SAGE Open, , vol. 12(4), pages 21582440221, December.
    4. de Souza, Michele & Pereira, Giancarlo Medeiros & Lopes de Sousa Jabbour, Ana Beatriz & Chiappetta Jabbour, Charbel Jose & Trento, Luiz Reni & Borchardt, Miriam & Zvirtes, Leandro, 2021. "A digitally enabled circular economy for mitigating food waste: Understanding innovative marketing strategies in the context of an emerging economy," Technological Forecasting and Social Change, Elsevier, vol. 173(C).
    5. Yuya Kajikawa, 2022. "Reframing evidence in evidence-based policy making and role of bibliometrics: toward transdisciplinary scientometric research," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(9), pages 5571-5585, September.

    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. Takano, Yasutomo & Mejia, Cristian & Kajikawa, Yuya, 2016. "Unconnected component inclusion technique for patent network analysis: Case study of Internet of Things-related technologies," Journal of Informetrics, Elsevier, vol. 10(4), pages 967-980.
    2. Yun, Jinhyuk & Ahn, Sejung & Lee, June Young, 2020. "Return to basics: Clustering of scientific literature using structural information," Journal of Informetrics, Elsevier, vol. 14(4).
    3. Sjögårde, Peter & Ahlgren, Per, 2018. "Granularity of algorithmically constructed publication-level classifications of research publications: Identification of topics," Journal of Informetrics, Elsevier, vol. 12(1), pages 133-152.
    4. Rotolo, Daniele & Hicks, Diana & Martin, Ben R., 2015. "What is an emerging technology?," Research Policy, Elsevier, vol. 44(10), pages 1827-1843.
    5. Daniele Rotolo & Ismael Rafols & Michael Hopkins & Loet Leydesdorff, 2014. "Scientometric Mapping as a Strategic Intelligence Tool for the Governance of Emerging Technologies," SPRU Working Paper Series 2014-10, SPRU - Science Policy Research Unit, University of Sussex Business School.
    6. Jochen Gläser & Wolfgang Glänzel & Andrea Scharnhorst, 2017. "Same data—different results? Towards a comparative approach to the identification of thematic structures in science," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(2), pages 981-998, May.
    7. 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.
    8. Lin Zhang & Beibei Sun & Fei Shu & Ying Huang, 2022. "Comparing paper level classifications across different methods and systems: an investigation of Nature publications," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(12), pages 7633-7651, December.
    9. 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.
    10. 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).
    11. Yun, Jinhyuk, 2022. "Generalization of bibliographic coupling and co-citation using the node split network," Journal of Informetrics, Elsevier, vol. 16(2).
    12. Cristian Mejia & Yuya Kajikawa, 2018. "Using acknowledgement data to characterize funding organizations by the types of research sponsored: the case of robotics research," Scientometrics, Springer;Akadémiai Kiadó, vol. 114(3), pages 883-904, March.
    13. Sukrit Vinayavekhin & Feng Li & Aneesh Banerjee & Andrea Caputo, 2023. "The academic landscape of sustainability in management literature: Towards a more interdisciplinary research agenda," Business Strategy and the Environment, Wiley Blackwell, vol. 32(8), pages 5748-5784, December.
    14. Shuo Xu & Junwan Liu & Dongsheng Zhai & Xin An & Zheng Wang & Hongshen Pang, 2018. "Overlapping thematic structures extraction with mixed-membership stochastic blockmodel," Scientometrics, Springer;Akadémiai Kiadó, vol. 117(1), pages 61-84, October.
    15. Zhang, Yi & Shang, Lining & Huang, Lu & Porter, Alan L. & Zhang, Guangquan & Lu, Jie & Zhu, Donghua, 2016. "A hybrid similarity measure method for patent portfolio analysis," Journal of Informetrics, Elsevier, vol. 10(4), pages 1108-1130.
    16. Yanto Chandra, 2018. "Mapping the evolution of entrepreneurship as a field of research (1990–2013): A scientometric analysis," PLOS ONE, Public Library of Science, vol. 13(1), pages 1-24, January.
    17. Ignacio Rodríguez-Rodríguez & José-Víctor Rodríguez & Niloofar Shirvanizadeh & Andrés Ortiz & Domingo-Javier Pardo-Quiles, 2021. "Applications of Artificial Intelligence, Machine Learning, Big Data and the Internet of Things to the COVID-19 Pandemic: A Scientometric Review Using Text Mining," IJERPH, MDPI, vol. 18(16), pages 1-29, August.
    18. Wenceslao Arroyo-Machado & Daniel Torres-Salinas & Nicolas Robinson-Garcia, 2021. "Identifying and characterizing social media communities: a socio-semantic network approach to altmetrics," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(11), pages 9267-9289, November.
    19. Matthias Held & Grit Laudel & Jochen Gläser, 2021. "Challenges to the validity of topic reconstruction," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(5), pages 4511-4536, May.
    20. 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.

    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:138:y:2019:i:c:p:45-68. 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.