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Patent Classification as Stimulus for Inspiring New Applications of Existing Knowledge

Published online by Cambridge University Press:  26 July 2019

Abstract

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This paper aims to provide suggestions for the identification of potential new applications for the existing knowledge. A method is presented for extracting information about a product or technology, processing the international patent database (IPD) and extracting useful hints for potential new applications. The approach uses the Cooperative Patent Classification as stimulus for inspiring new potential fields towards which export existing product or technologies. Although some limits inevitably affect the approach, relevant directions for future developments have been inferred for a more comprehensive exploitation of both the firm internal knowledge and the suggestions provided by the international patent database. The achieved results can support firms in expanding market opportunities for their products or technologies.

Type
Article
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
© The Author(s) 2019

References

Abbas, A., Zhang, L. and Khan, S.U. (2014), “A literature review on the state-of-the-art in patent analysis”, World Patent Information, Elsevier Ltd, Vol. 37, pp. 313.Google Scholar
Akers, L. (2003), “The future of patent information - A user with a view”, World Patent Information, Vol. 25 No. 4, pp. 303312.Google Scholar
Altuntas, S., Dereli, T. and Kusiak, A. (2015), “Forecasting technology success based on patent data”, Technological Forecasting and Social Change, Elsevier Inc., Vol. 96, pp. 202214.Google Scholar
Bacciotti, D., Borgianni, Y. and Rotini, F. (2016), “Computers in Industry An original design approach for stimulating the ideation of new product features”, Computers in Industry, Elsevier B.V., Vol. 75, pp. 80100.Google Scholar
Cascini, G., Fantechi, A. and Spinicci, E. (2004), “Natural language processing of patents and technical documentation”, Document Analysis Systems VI, pp. 508520.Google Scholar
Cascini, G., Fiorineschi, L. and Rotini, F. (2018), “Investigating on the Re-use of Conceptual Design Representations”, International Design Conference - Design 2018, pp. 10091020.Google Scholar
Chang, S.-H. and Chang, H.-Y. (2016), “The study of patent portfolio strategies of oil shale developers”, International Journal of Innovation Science, Vol. 8 No. 3, pp. 254268.Google Scholar
Chen, H., Zhang, G., Zhu, D. and Lu, J. (2017), “Topic-based technological forecasting based on patent data: A case study of Australian patents from 2000 to 2014”, Technological Forecasting and Social Change, Elsevier Inc, Vol. 119, pp. 3952.Google Scholar
Chiu, I. and Shu, L.H.H. (2012), “Investigating effects of oppositely related semantic stimuli on design concept creativity”, Journal of Engineering Design, Vol. 23 No. 4, pp. 271296.Google Scholar
Cho, H.P., Lim, H., Lee, D., Cho, H. and Kang, K.I. (2017), “Patent analysis for forecasting promising technology in high-rise building construction”, Technological Forecasting and Social Change, Elsevier, No. September 2016, pp. 01.Google Scholar
Dewulf, S. (2011), “Directed variation of properties for new or improved function product DNA – A base for connect and develop”, Procedia Engineering, Elsevier B.V., Vol. 9, pp. 646652.Google Scholar
Eckert, C., Ruckpaul, A., Alink, T. and Albers, A. (2012), “Variations in functional decomposition for an existing product: Experimental results”, Artificial Intelligence for Engineering Design, Analysis and Manufacturing, Vol. 26 No. 2, pp. 107128.Google Scholar
Fiorineschi, L., Rotini, F. and Rissone, P. (2016), “A new conceptual design approach for overcoming the flaws of functional decomposition and morphology”, Journal of Engineering Design, Vol. 27 No. 7, pp. 438468.Google Scholar
Fiorineschi, L., Frillici, F.S., Gregori, G. and Rotini, F. (2018), “Stimulating idea generation for new product applications”, International Journal of Innovation Science, Vol. 10 No. 4, pp. 454474.Google Scholar
Gadd, K. (2011), TRIZ for Engineers: Enabling Inventive Problem Solving, John Wiley and sons, Inc, available at: https://doi.org/10.1002/9780470684320.Google Scholar
Goldschmidt, G. and Sever, A.L. (2011), “Inspiring design ideas with texts”, Design Studies, Elsevier Ltd, Vol. 32 No. 2, pp. 139155.Google Scholar
Gonçalves, M., Cardoso, C. and Badke-Schaub, P. (2014), “What inspires designers? Preferences on inspirational approaches during idea generation”, Design Studies, Vol. 35 No. 1, pp. 2953.Google Scholar
Gonçalves, M., Cardoso, C. and Badke-Schaub, P. (2016), “Inspiration choices that matter: the selection of external stimuli during ideation”, Design Science, Vol. 2 No. E10, pp. 131.Google Scholar
Hirts, J., Stone, R.B., McAdams, D.A., Szykman, S. and Wood, K.L. (2002), “A Functional Basis for Engineering Design: Reconciling and Evolving Previous Efforts”, National Institute of Standards and Technology.Google Scholar
Howard, T.J., Dekoninck, E.A. and Culley, S.J. (2010), “The use of creative stimuli at early stages of industrial product innovation”, Research in Engineering Design, Vol. 21 No. 4, pp. 263274.Google Scholar
López-Mesa, B., Mulet, E., Vidal, R. and Thompson, G. (2011), “Effects of additional stimuli on idea-finding in design teams”, Journal of Engineering Design, Vol. 22 No. 1, available at: https://doi.org/http://doi.org/10.1080/09544820902911366.Google Scholar
Malmqvist, J. (1997), “Improved Function-Means Trees by Inclusion of Design History Information”, Journal of Engineering Design, Vol. 8 No. 2.Google Scholar
Pahl, G., Beitz, W., Feldhusen, J. and Grote, K.H. (2007), Engineering Design 3rd Ed, Springer-Verlag, London.Google Scholar
Park, Y. and Yoon, J. (2017), “Application technology opportunity discovery from technology portfolios: Use of patent classification and collaborative filtering”, Technological Forecasting and Social Change, Elsevier Inc., Vol. 118, pp. 170183.Google Scholar
Pugh, S. (1991), Total Design. Integrated Methods for Succesfull Product Engineering, Addison Wesley Publishing Company, Reading, Massachusetts.Google Scholar
Robotham, A.J. (2002), “The use of function/means trees for modelling technical, semantic and business functions”, Journal of Engineering Design, pp. 243251.Google Scholar
Ross, S.M. (2014), Introduction to Probability and Statistics for Engineers and Scientists, Academic Press.Google Scholar
Savransky, S.D. (2000), Engineering of Creativity: Introduction to TRIZ Methodology of Inventive Problem Solving, CRC Press.Google Scholar
Seo, W., Yoon, J., Park, H., Coh, B., Lee, J.-M. and Kwon, O.-J. (2016), “Product opportunity identification based on internal capabilities using text mining and association rule mining”, Technological Forecasting and Social Change, Elsevier Inc., Vol. 105, pp. 94104.Google Scholar
Singh, M.D. and Terzidis, O. (2015), “Introducing Innovation Phase Transition”, International Journal of Innovation Science, Vol. 7 No. 4.Google Scholar
Stone, R. and Wood, K. (2000), “Development of a Functional Basis for Design”, Journal of Mechanical Design, Vol. 122 No. 4, pp. 359370.Google Scholar
Vasconcelos, L.A., Cardoso, C.C., Maria, S., Chen, C. and Crilly, N. (2017), “Inspiration and Fixation : The Influences of Example Designs and System Properties in Idea Generation”, Journal of Mechanical Design, Vol. 139 No. March, pp. 113.Google Scholar
Vermaas, P.E. and Eckert, C. (2013), “My functional description is better!”, Artificial Intelligence for Engineering Design, Analysis and Manufacturing, Vol. 27 No. 3, pp. 187190.Google Scholar
Yoon, J., Park, H., Seo, W., Lee, J.M., Coh, B.y. and Kim, J. (2015), “Technology opportunity discovery (TOD) from existing technologies and products: A function-based TOD framework”, Technological Forecasting and Social Change, Elsevier Inc., Vol. 100, pp. 153167.Google Scholar
Yoon, J., Seo, W., Coh, B.Y., Song, I. and Lee, J.M. (2017), “Identifying product opportunities using collaborative filtering-based patent analysis”, Computers and Industrial Engineering, Elsevier Ltd, Vol. 107, pp. 376387.Google Scholar