Development of the comprehensive method of situation management of project risks based on big data technology
DOI:
https://doi.org/10.15587/1729-4061.2023.274473Keywords:
comprehensive method, situational risk management, fuzzy situational graph, goal achievement indexAbstract
Project implementation is often carried out under the influence of negative changes in the environment and circumstances characterized as crisis. Therefore, the processes associated with risk management, which is the object of this study, are becoming important. The topic of this study is to increase the efficiency of projects by adapting the project to crisis conditions, promptly developing and making effective management decisions. For projects, it is necessary not only to identify the current situation as risky but also to determine rational ways to achieve the project goals under crisis conditions. Therefore, a comprehensive method of situational project risk management based on the combined application of situational analysis methods, intelligent and expert methods, as well as Big Data technology, is proposed. Within the framework of the method, a project risk management model has been built in the form of a fuzzy situational graph, which would provide a choice of strategies that could contribute to overcoming a risky situation, as well as reduce the time to make effective management decisions in crisis circumstances. The result of this method is compliance with time constraints, reducing resource overruns and losses in the project, as well as adapting to rapidly changing circumstances and adequate response.
A comprehensive method of situational project risk management is characterized by solving the task toformalize management decision-making procedures and their information support, taking into account the availability of both structured and unstructured data. The proposed procedure for situational project risk management based on the use of Big Data technology can also be the basis of project management information technology and the corresponding decision support system
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Copyright (c) 2023 Tetiana Prokopenko, Yevhen Lanskykh, Valentyn Prokopenko, Oleksandr Pidkuiko, Yaroslav Tarasenko
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