Randomness vs. fuzziness in managerial decision-making
Managers often deal with uncertainty of a different nature in their decision processes. They can encounter uncertainty in terms of randomness or fuzziness (i.e., mist, obscurity, inaccuracy or vagueness). In the first case (randomness), it can be described, for example, by probability distribution,...
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2019-01-01
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Online Access: | https://www.shs-conferences.org/articles/shsconf/pdf/2019/02/shsconf_ies2018_01002.pdf |
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doaj-7b5055deb8234785bc9951499697f9692021-03-02T09:25:09ZengEDP SciencesSHS Web of Conferences2261-24242019-01-01610100210.1051/shsconf/20196101002shsconf_ies2018_01002Randomness vs. fuzziness in managerial decision-makingHašková SimonaManagers often deal with uncertainty of a different nature in their decision processes. They can encounter uncertainty in terms of randomness or fuzziness (i.e., mist, obscurity, inaccuracy or vagueness). In the first case (randomness), it can be described, for example, by probability distribution, in the second case (fuzziness) it cannot be characterized in such a way. The methodological part of the paper presents basic tools for dealing with the uncertainty of both of these types, which are techniques of probability theory and fuzzy approach technique. The original contribution of the theoretical part is the interpretation of these different techniques based on the existence of fundamental analogies between them. These techniques are then applied to the problem of the project valuation with its “internal” value. In the first case, the solution is the point value of the statistical E[PV], in the second case the triangular fuzzy number of the subjective E[PV]. The comparison of the results of both techniques shows that the fuzzy approach extends the standard outcome of a series useful information. This informative “superstructure” of the fuzzy approach compared to the standard solution is another original benefit of the paper.https://www.shs-conferences.org/articles/shsconf/pdf/2019/02/shsconf_ies2018_01002.pdfUncertaintyProbabilityFuzzinessExpected valueFuzzy number |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Hašková Simona |
spellingShingle |
Hašková Simona Randomness vs. fuzziness in managerial decision-making SHS Web of Conferences Uncertainty Probability Fuzziness Expected value Fuzzy number |
author_facet |
Hašková Simona |
author_sort |
Hašková Simona |
title |
Randomness vs. fuzziness in managerial decision-making |
title_short |
Randomness vs. fuzziness in managerial decision-making |
title_full |
Randomness vs. fuzziness in managerial decision-making |
title_fullStr |
Randomness vs. fuzziness in managerial decision-making |
title_full_unstemmed |
Randomness vs. fuzziness in managerial decision-making |
title_sort |
randomness vs. fuzziness in managerial decision-making |
publisher |
EDP Sciences |
series |
SHS Web of Conferences |
issn |
2261-2424 |
publishDate |
2019-01-01 |
description |
Managers often deal with uncertainty of a different nature in their decision processes. They can encounter uncertainty in terms of randomness or fuzziness (i.e., mist, obscurity, inaccuracy or vagueness). In the first case (randomness), it can be described, for example, by probability distribution, in the second case (fuzziness) it cannot be characterized in such a way. The methodological part of the paper presents basic tools for dealing with the uncertainty of both of these types, which are techniques of probability theory and fuzzy approach technique. The original contribution of the theoretical part is the interpretation of these different techniques based on the existence of fundamental analogies between them. These techniques are then applied to the problem of the project valuation with its “internal” value. In the first case, the solution is the point value of the statistical E[PV], in the second case the triangular fuzzy number of the subjective E[PV]. The comparison of the results of both techniques shows that the fuzzy approach extends the standard outcome of a series useful information. This informative “superstructure” of the fuzzy approach compared to the standard solution is another original benefit of the paper. |
topic |
Uncertainty Probability Fuzziness Expected value Fuzzy number |
url |
https://www.shs-conferences.org/articles/shsconf/pdf/2019/02/shsconf_ies2018_01002.pdf |
work_keys_str_mv |
AT haskovasimona randomnessvsfuzzinessinmanagerialdecisionmaking |
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