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Advantages of fuzzy approach compared to probabilistic approach in project evaluation

Author

Listed:
  • Simona Hašková

    (Institute of Technology and Business in České Budějovice, Czech Republic)

  • Petr Šuleř

    (Institute of Technology and Business in České Budějovice, Czech Republic)

  • Tomáš Krulický

    (Institute of Technology and Business in České Budějovice, Czech Republic)

Abstract

Uncertainty is often encountered in relation to randomness or fuzziness. In the case of randomness, it can be described by means of a probability distribution; in the case of fuzziness, the fuzzy theory is applied. In the theoretical part, the authors deal with basic tools for describing both types of uncertainty. Probability and fuzzy method are interpreted in the context of their analogies and principal differences. Both techniques are applied in order to quantify the present expected value of a specific development project. The probabilistic solution leads to the point value E[PV], the fuzzy solution establishes the triangular fuzzy number with the subjective E[PV] not burdened with possible exaggerated expectations. The fuzzy approach proved to extend the probabilistic outcome by other additional information useful for decision-makers with different risk propensity.

Suggested Citation

  • Simona Hašková & Petr Šuleř & Tomáš Krulický, 2022. "Advantages of fuzzy approach compared to probabilistic approach in project evaluation," Entrepreneurship and Sustainability Issues, VsI Entrepreneurship and Sustainability Center, vol. 10(1), pages 483-493, September.
    • Handle: RePEc:ssi:jouesi:v:10:y:2022:i:1:p:483-493
    DOI: 10.9770/jesi.2022.10.1(27)
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    More about this item

    Keywords

    uncertainty; expected value; fuzzy number; risk propensity; evaluation;
    All these keywords.

    JEL classification:

    • C02 - Mathematical and Quantitative Methods - - General - - - Mathematical Economics
    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
    • C46 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Specific Distributions
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques

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