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Frugal Invention Candidates As Antecedents Of Frugal Patents — The Role Of Frugal Attributes Analysed In The Medical Engineering Technology

Author

Listed:
  • NORA ALTGILBERS

    (Institute of Project Management and Innovation (IPMI), University of Bremen, Enrique-Schmidt-Straße 1, D 28359 Bremen, Germany)

  • LOTHAR WALTER

    (Institute of Project Management and Innovation (IPMI), University of Bremen, Enrique-Schmidt-Straße 1, D 28359 Bremen, Germany)

  • MARTIN G. MOEHRLE

    (Institute of Project Management and Innovation (IPMI), University of Bremen, Enrique-Schmidt-Straße 1, D 28359 Bremen, Germany)

Abstract

Frugal innovations enable companies to access new markets because of some specific characteristics. Typically, they focus on existing solutions as a blueprint, changing parts of their functionality while reducing the costs. Many companies are faced with the question how to find ideas for such frugal innovations. For this purpose, we introduce a method for the identification of frugal invention candidates and their qualification as frugal patents. We provide a general outline of a process and apply it to the medical engineering technology. By use of semantic analysis, we shed light on the moderating role of frugal attributes to qualify a frugal invention candidate as a frugal patent. The application produces a comprehensive set of frugal patents. Our approach deepens the understanding of frugality by providing an appropriate assessment based on a newly developed frugal thesaurus. Managers will have the option to adapt our method to their particular fields of experience.

Suggested Citation

  • Nora Altgilbers & Lothar Walter & Martin G. Moehrle, 2020. "Frugal Invention Candidates As Antecedents Of Frugal Patents — The Role Of Frugal Attributes Analysed In The Medical Engineering Technology," International Journal of Innovation Management (ijim), World Scientific Publishing Co. Pte. Ltd., vol. 24(06), pages 1-23, August.
    • Handle: RePEc:wsi:ijimxx:v:24:y:2020:i:06:n:s1363919620500826
    DOI: 10.1142/S1363919620500826
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    Cited by:

    1. Arash Hajikhani & Arho Suominen, 2022. "Mapping the sustainable development goals (SDGs) in science, technology and innovation: application of machine learning in SDG-oriented artefact detection," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(11), pages 6661-6693, November.

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