T. Galanc, W. Kołwzan, J. Pieronek, Agnieszka Skowronek-Grądziel
{"title":"Risk estimation and decision making in management (in selected areas of science)","authors":"T. Galanc, W. Kołwzan, J. Pieronek, Agnieszka Skowronek-Grądziel","doi":"10.37190/ord200103","DOIUrl":null,"url":null,"abstract":"Risk is a category that is inseparably connected with uncertainty and probability, which means that the nature of risk as a category of science is complex, and the concept of risk is very difficult to define by one conceptual system of modern science. Due to the above, the main research hypothesis of the work is oriented to the assumption that the complexity of the risk category is determined by the diversity (variety) of reality, as a result of which in science there is currently no uniform methodology for risk assessment and estimation. As a result, the main goal of the article is to describe the research area based on selected representative methods of risk estimation and logical decision-making schemes, as well as to systematise the knowledge about the methodology used in them. In the article, the authors illustrate risk estimation with examples developed by themselves and quoted from various fields of science, differing from one another in formal terms in quantitative and qualitative (numerical and content-verbally) dimensions. Strategic risk, risk of fraction estimation, Bayesian risk, Bayesian methods for estimation of population distribution parameters, risk of econometric model assessment, interest rate risk, banking risk, and adverse event as a measure of risk are here addressed. The article also focuses on the problem of risk estimation in terms of the theory of fractals. The work is to have not only cognitive but also practical meaning. The created source of knowledge should prove helpful for decision-makers in the area of management since effective process management requires the expertise of risk estimation in various dimensions and using various mathematical tools.","PeriodicalId":43244,"journal":{"name":"Operations Research and Decisions","volume":null,"pages":null},"PeriodicalIF":0.7000,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Operations Research and Decisions","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.37190/ord200103","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"OPERATIONS RESEARCH & MANAGEMENT SCIENCE","Score":null,"Total":0}
引用次数: 0
Abstract
Risk is a category that is inseparably connected with uncertainty and probability, which means that the nature of risk as a category of science is complex, and the concept of risk is very difficult to define by one conceptual system of modern science. Due to the above, the main research hypothesis of the work is oriented to the assumption that the complexity of the risk category is determined by the diversity (variety) of reality, as a result of which in science there is currently no uniform methodology for risk assessment and estimation. As a result, the main goal of the article is to describe the research area based on selected representative methods of risk estimation and logical decision-making schemes, as well as to systematise the knowledge about the methodology used in them. In the article, the authors illustrate risk estimation with examples developed by themselves and quoted from various fields of science, differing from one another in formal terms in quantitative and qualitative (numerical and content-verbally) dimensions. Strategic risk, risk of fraction estimation, Bayesian risk, Bayesian methods for estimation of population distribution parameters, risk of econometric model assessment, interest rate risk, banking risk, and adverse event as a measure of risk are here addressed. The article also focuses on the problem of risk estimation in terms of the theory of fractals. The work is to have not only cognitive but also practical meaning. The created source of knowledge should prove helpful for decision-makers in the area of management since effective process management requires the expertise of risk estimation in various dimensions and using various mathematical tools.