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A Risk Diagnosing Methodology Web-Based Platform for Micro, Small and Medium Businesses: Remarks and Enhancements

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Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2013)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 454))

Abstract

The indisputable necessity to innovate brings to companies vital responsibilities such as the inevitable errand of having consistent innovation and risk management procedures along their projects. This work presents a risk diagnosing methodology (RDM) web-platform, that can provide to Small and Medium Enterprises (SMEs) the ability to identify and self-assess risks associated with their innovative project’s portfolio, from the project’s idealization to its commercialization. The creation of this tool attempts to encourage SMEs on the systematic use of risk management approaches, in order to increase project’s successful rates. As groundwork, this paper also includes a bibliographical review and comparative analysis of other existing risk management tools and models available to SMEs. The present article also uncovers first empirical results available from exploratory research done and reveals ongoing research efforts regarding risk perception and potential bias correction.

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Acknowledgements

The authors gratefully acknowledge the funding by QREN, FEDER and PorLisboa, Ministério da Ciência, Tecnologia e Ensino Superior, FCT, Portugal, under grants WS NPT QREN - LISBOA-01-0202-FEDER-011999.

Author information

Authors and Affiliations

  1. Faculdade de Ciências e Tecnologia (FCT), Universidade NOVA de Lisboa (UNL), Lisbon, Portugal

    Luís Pereira, Alexandra Tenera & João Bispo

  2. Department of Mechanical and Industrial Engineering, UNIDEMI, Lisbon, Portugal

    Alexandra Tenera

  3. WS Energia, Lisbon, Portugal

    João Wemans

Authors
  1. Luís Pereira
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  2. Alexandra Tenera
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  3. João Bispo
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  4. João Wemans
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Corresponding author

Correspondence to Luís Pereira .

Editor information

Editors and Affiliations

  1. Technical University of Lisbon, Lisbon, Portugal

    Ana Fred

  2. Faculty of Electrical Engineering, Mathematics and Computer Science, Delft University of Technology, Delft, The Netherlands

    Jan L.G. Dietz

  3. Henley Business School, University of Reading, Reading, United Kingdom

    Kecheng Liu

  4. INSTICC, Setubal, Portugal

    Joaquim Filipe

Appendix

Appendix

Spotrisk’s Goal Oriented Questionnaire

 

 

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Pereira, L., Tenera, A., Bispo, J., Wemans, J. (2015). A Risk Diagnosing Methodology Web-Based Platform for Micro, Small and Medium Businesses: Remarks and Enhancements. In: Fred, A., Dietz, J., Liu, K., Filipe, J. (eds) Knowledge Discovery, Knowledge Engineering and Knowledge Management. IC3K 2013. Communications in Computer and Information Science, vol 454. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-46549-3_22

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  • DOI: https://doi.org/10.1007/978-3-662-46549-3_22

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-46548-6

  • Online ISBN: 978-3-662-46549-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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