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dc.contributor.authorBravo-Sepúlveda M
dc.contributor.authorWilke D.N
dc.contributor.authorIsaza C.F
dc.contributor.authorPolanco J.-A.
dc.date.accessioned2024-07-31T21:07:09Z
dc.date.available2024-07-31T21:07:09Z
dc.date.created2023
dc.identifier.issn20817452
dc.identifier.urihttp://hdl.handle.net/11407/8487
dc.descriptionOperational risk has been widely studied, and international guidelines provide procedures for the correct management of operational risk; however, this has not been studied from a corporate sustainability point of view. Therefore, this work seeks to find a way to model and optimize the impact of operational risks on corporate sustainability. The methodology used is based on the assignment of two distribution functions for the creation of a probabilistic model that allows quantifying the probability of occurrence (frequency) and the expected monetary impact (severity) on the sustainability variables (environmental, social, and economic). The result is a statistical convolution through Monte Carlo simulation, which makes it possible to quantify aggregate losses to finally make an optimization process of the variables and estimate the financial impact. Therefore, this study extends the literature on risk quantification, proposing a stochastic model that quantifies and optimizes the operational risks that are related to corporate sustainability. The proposed model offers a practical way to quantify operational risks related to corporate sustainability while also being flexible, as it does not require historical information and can be used with data collected from the company based on the proposed probability distributions. Finally, the proposed model has three limitations: the distribution functions, use of Solver (Excel), and exclusion of some risk management strategies, which future research can consider. © 2023, Czestochowa University of Technology. All rights reserved.
dc.language.isoeng
dc.publisherCzestochowa University of Technology
dc.relation.isversionofhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85181652655&doi=10.17512%2fpjms.2023.28.2.04&partnerID=40&md5=9613ee9f9edafca886d817ab51f72ab6
dc.sourcePolish Journal of Management Studies
dc.sourcePol. J. Manag. Stud.
dc.sourceScopus
dc.subjectMonte Carlo Simulationeng
dc.subjectOperational Riskeng
dc.subjectOptimizationeng
dc.subjectSustainabilityeng
dc.titleA STOCHASTIC MODEL TO QUANTIFY AND OPTIMIZE THE IMPACT OF OPERATIONAL RISKS ON CORPORATE SUSTAINABILITY USING MONTE CARLO SIMULATION [MODEL STOCHASTYCZNY KWALIFIKACJI I OPTYMALIZACJI WPŁYWU RYZYKA OPERACYJNEGO NA ZRÓWNOWAŻONY ROZWÓJ KORPORACYJNY Z WYKORZYSTANIEM SYMULACJI MONTE CARLO]eng
dc.typearticle
dc.rights.accessrightsinfo:eu-repo/semantics/restrictedAccess
dc.publisher.programIngeniería en Energíaspa
dc.type.spaArtículo
dc.identifier.doi10.17512/pjms.2023.28.2.04
dc.relation.citationvolume28
dc.relation.citationissue2
dc.relation.citationstartpage59
dc.relation.citationendpage75
dc.publisher.facultyFacultad de Ingenieríasspa
dc.affiliationBravo-Sepúlveda, M., Faculty of Economic and Administrative Sciences, Universidad de Medellín, Antioquia, Colombia
dc.affiliationWilke, D.N., Faculty of Mechanical engineering, University of Pretoria, Pretoria, South Africa
dc.affiliationIsaza, C.F., Universidad de Medellin, Antioquia, Colombia
dc.affiliationPolanco, J.-A., Faculty of engineering, Universidad de Medellín, Antioquia, Colombia
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dc.identifier.reponamereponame:Repositorio Institucional Universidad de Medellín
dc.identifier.repourlrepourl:https://repository.udem.edu.co/
dc.identifier.instnameinstname:Universidad de Medellín


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