Skip to main content

Identify New Application Fields of a Given Technology

  • Conference paper
  • First Online:
Creative Solutions for a Sustainable Development (TFC 2021)

Abstract

The economic crisis caused by the closure of businesses forced many companies to review their business model and rethink their product catalogue. To achieve this, they need help to identify new forms of transfer of their technologies and knowledge towards new products. In this conference paper, the authors propose a methodology conceived as a tool to support start-ups, long before Covid-19 came along, and which is currently undergoing an important acceleration process to quickly respond to the demand of small and medium-sized companies. The objective of the proposed methodology is to analyze a given technology and to understand possible alternative fields of application to the starting one. For each new potential area there is a complex evaluation that tries to position the product according to technical and economic parameters. At the basis of the methodology there are the most modern tools of Information Retrieval: SAO (Subject Action Object) triads and algorithmic approaches based on patterns recognition. The combination of these two approaches, no antithetical to each other, forms the basis of the methodological proposal of this paper. They are used to automatically analyze large patent pools and extract features of technological nature such as functions, product requirements and fields of application. Once the list of potential fields has been extracted, it is possible to assess the potential impact and investment risk by introducing other key tools developed by the TRIZ community, such as market potential. In order to make the methodological process more fluid, specific indicators have been created, such as the Transfer Potential, which indicates the replacement potential of a new technology compared to an old one. The proposed approach is tested through an explanatory industrial case study.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. Lichtenthaler, U.: Open innovation in practice: an analysis of strategic approaches to technology transactions. IEEE Trans. Eng. Manage. 55(1), 148–157 (2008)

    Article  Google Scholar 

  2. Jeon, J., Lee, C., Park, Y.: How to use patent information to search potential technology partners in open innovation (2011)

    Google Scholar 

  3. Altshuller, G.S.: Creativity as an exact science: the theory of the solution of inventive problems. Gordon and Breach (1984)

    Google Scholar 

  4. TRIZ home page in Japan. https://www.osaka-gu.ac.jp/php/nakagawa/TRIZ/eTRIZ/epapers/eTRTechOpt980607/eTR-1.html. Accessed 21 Apr 2021

  5. Aulive. http://www.aulive.com. Accessed 01 May 2021

  6. Oxford creativity. https://www.triz.co.uk/triz-effects-database. Accessed 02 May 2021

  7. Montecchi, T., Russo, D.: FBOS: function/behaviour–oriented search. Procedia Eng. 131, 140–149 (2015)

    Article  Google Scholar 

  8. Fiorineschi, L., Frillici, F.S., Gregori, G., Rotini, F.: Stimulating idea generation for new product applications. Int. J. Innov. Sci. (2018)

    Google Scholar 

  9. Zanni-Merk, C., Cavallucci, D., Rousselot, F.: Use of formal ontologies as a foundation for inventive design studies. Comput. Ind. 62(3), 323–336 (2011)

    Article  Google Scholar 

  10. Fantoni, G., Apreda, R., Dell’Orletta, F., Monge, M.: Automatic extraction of function–behaviour–state information from patents. Adv. Eng. Inf. 27(3), 317–334 (2013)

    Article  Google Scholar 

  11. Russo, D., Spreafico, M., Precorvi, A.: Discovering new business opportunities with dependent semantic parsers. Comput. Ind. 123, 103330 (2020)

    Google Scholar 

  12. Ulwick, A.W.: Turn customer input into innovation. Harv. Bus. Rev. 80(1), 91–98 (2002)

    Google Scholar 

  13. Livotov, P.: Using patent information for identification of new product features with high market potential. Procedia Eng. 131, 1157–1164 (2015)

    Article  Google Scholar 

  14. Altuntas, S., Dereli, T.: An evaluation index system for prediction of technology commercialization of investment projects. Journal of Intelligent & Fuzzy Systems 23(6), 327–343 (2012)

    Article  Google Scholar 

  15. Aristodemou, L., Tietze, F.: The state-of-the-art on Intellectual Property Analytics (IPA): A literature review on artificial intelligence, machine learning and deep learning methods for analysing intellectual property (IP) data. World Patent Inf. 55, 37–51 (2018)

    Article  Google Scholar 

  16. Cascini, G., Russo, D.: Computer-aided analysis of patents and search for TRIZ contradictions. Int. J. Prod. Dev. 4(1–2), 52–67 (2007)

    Article  Google Scholar 

  17. Park, H., Ree, J.J., Kim, K.: Identification of promising patents for technology transfers using TRIZ evolution trends. Expert Syst. Appl. 40(2), 736–743 (2013)

    Article  Google Scholar 

  18. Jacoby, J.: The emerging behavioral process technology in consumer decision-making research. ACR North American Advances (1977).

    Google Scholar 

  19. Farris, P.W., Bendle, N., Pfeifer, P.E., Reibstein, D.: Marketing metrics: the definitive guide to measuring marketing performance. Pearson Education (2010)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Matteo Spreafico .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2021 IFIP International Federation for Information Processing

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Spreafico, M., Russo, D. (2021). Identify New Application Fields of a Given Technology. In: Borgianni, Y., Brad, S., Cavallucci, D., Livotov, P. (eds) Creative Solutions for a Sustainable Development. TFC 2021. IFIP Advances in Information and Communication Technology, vol 635. Springer, Cham. https://doi.org/10.1007/978-3-030-86614-3_9

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-86614-3_9

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-86613-6

  • Online ISBN: 978-3-030-86614-3

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics