A fuzzy based model to assess the influence of project risk on corporate behavior

Ricardo Santos, Antonio Abreu, João M.F. Calado, José Miguel Soares, José Duarte Moleiro Martins, Vitor Anes

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Nowadays, the competitiveness on industry, requires a good preparation from the organizations, considering all events that may occur, which brings new challenges for the corporation’s management. To address such challenges, risk management’s models have been used to give a sense of threat prevention, by assessing each project’s risk and the risk from the corporation itself as well. However, such models are normally based on human perception, which brings some subjectivity around the risks involved, making their definition less accurate. Additionally, there is a lack of models that allows to better define the corporation’s risk, by exploring the influence from the risk’s project. To address these issues, this paper presents an approach, supported by fuzzy logic, to analyze the risk’s level in an organization, by considering the influence of their projects. A case study will be used to assess the model robustness and to discuss the benefits and challenges found.

Original languageEnglish
Title of host publicationCONTROLO 2020 - Proceedings of the 14th APCA International Conference on Automatic Control and Soft Computing
EditorsJosé Alexandre Gonçalves, Manuel Braz-César, João Paulo Coelho
PublisherSpringer Science and Business Media Deutschland GmbH
Pages383-393
Number of pages11
ISBN (Print)9783030586522
DOIs
Publication statusPublished - 2021
Event14th APCA International Conference on Automatic Control and Soft Computing, CONTROLO 2020 - Bragança, Portugal
Duration: 1 Jul 20203 Jul 2020

Publication series

NameLecture Notes in Electrical Engineering
Volume695 LNEE
ISSN (Print)1876-1100
ISSN (Electronic)1876-1119

Conference

Conference14th APCA International Conference on Automatic Control and Soft Computing, CONTROLO 2020
Country/TerritoryPortugal
CityBragança
Period1/07/203/07/20

Keywords

  • Corporate risk
  • Fuzzy logic
  • Project management
  • Project risk
  • Risk management

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