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  • The paper is concerned with measuring and assessment of risks in managerial decision-making. It builds upon economic information entropy as a degree of uncertainty, which is converted into the concept of risk expressed in terms of probability and using confidence intervals of the predicted quantities. The paper explains the relation of a degree of risk expressed by the classical information measure, bit, by the concept of confidence intervals, or possibly by the standard deviation. When making decisions, the manager is interested not only in the quantitatively expressed value of risk with the use of forecasting models, but mainly in the impact of decrease/increase of decision-making risk expressed by the effect, i.e. profit/loss caused by such a decision to achieve targets. A method of decision effect calculation is proposed which is derived from the entropy change and the change in risk in managerial decision-making. Forecasting models are applied which are based on an expert estimate and a statistical theory, and the degree of risk is assessed in forecasting models based on neural networks, and their risks are assessed.
  • The paper is concerned with measuring and assessment of risks in managerial decision-making. It builds upon economic information entropy as a degree of uncertainty, which is converted into the concept of risk expressed in terms of probability and using confidence intervals of the predicted quantities. The paper explains the relation of a degree of risk expressed by the classical information measure, bit, by the concept of confidence intervals, or possibly by the standard deviation. When making decisions, the manager is interested not only in the quantitatively expressed value of risk with the use of forecasting models, but mainly in the impact of decrease/increase of decision-making risk expressed by the effect, i.e. profit/loss caused by such a decision to achieve targets. A method of decision effect calculation is proposed which is derived from the entropy change and the change in risk in managerial decision-making. Forecasting models are applied which are based on an expert estimate and a statistical theory, and the degree of risk is assessed in forecasting models based on neural networks, and their risks are assessed. (en)
Title
  • Managerial Decision-making: Measuring and Manifesrtaion of Risks and the Possibilities of their Reducing
  • Managerial Decision-making: Measuring and Manifesrtaion of Risks and the Possibilities of their Reducing (en)
skos:prefLabel
  • Managerial Decision-making: Measuring and Manifesrtaion of Risks and the Possibilities of their Reducing
  • Managerial Decision-making: Measuring and Manifesrtaion of Risks and the Possibilities of their Reducing (en)
skos:notation
  • RIV/47813059:19240/11:#0004443!RIV13-MSM-19240___
http://linked.open...avai/predkladatel
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • P(ED1.1.00/02.0070)
http://linked.open...iv/cisloPeriodika
  • 4
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
http://linked.open.../riv/druhVysledku
http://linked.open...iv/duvernostUdaju
http://linked.open...titaPredkladatele
http://linked.open...dnocenehoVysledku
  • 210411
http://linked.open...ai/riv/idVysledku
  • RIV/47813059:19240/11:#0004443
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • confidence interval; entropy; prediction models; neural networks; managerial decision; risk assessment (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...odStatuVydavatele
  • SK - Slovenská republika
http://linked.open...ontrolniKodProRIV
  • [92E786C21933]
http://linked.open...i/riv/nazevZdroje
  • Journal of Economics
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...vavai/riv/projekt
http://linked.open...UplatneniVysledku
http://linked.open...v/svazekPeriodika
  • 59
http://linked.open...iv/tvurceVysledku
  • Marček, Dušan
  • Marček, Milan
http://linked.open...ain/vavai/riv/wos
  • 000291707100004
issn
  • 0013-3035
number of pages
http://localhost/t...ganizacniJednotka
  • 19240
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