Risk Reduction Strategy and Risk Management on the Basis of Quality Assessments

Victoria Borkovskaya, David Passmore

Research output: Contribution to journalConference articlepeer-review

Abstract

The main issue of the study is the problem of improving the efficiency of risk management of the program. The article proposes a method for determining the quality of risk assessments of a program consisting of several projects. Risk management tasks are set and solved on the basis of risk reduction and risk avoidance strategies. The aim of the study is a systematic integrated approach to the formulation and solution of tasks to improve the efficiency of the risk management program, which allows you to objectively, fully and accurately assess the relationship of economic and technical indicators. Qualitative risk assessment can be carried out by a common method of analogy, the essence of which is to analyse the totality of data on similar projects. Here they conduct a study of impact of adverse factors on them in order to accurately determine the potential risk of new projects. The main difficulty of using the methods is the exact and correct choice of analogues, since there are no formal criteria for determining the degree of similarity of situations. All aggregate socially significant economic indicators of operational measures can become the basis of legislative regulation in the industry. Conclusions: the strategy of risk reduction is that activities are carried out that reduce either the probability or damage or both from medium to low, from high to medium or low.

Original languageEnglish (US)
Article number062051
JournalIOP Conference Series: Materials Science and Engineering
Volume869
Issue number6
DOIs
StatePublished - Jul 9 2020
Event23rd International Scientific Conference on Advance in Civil Engineering: Construction - The Formation of Living Environment, FORM 2020 - Hanoi, Viet Nam
Duration: Sep 23 2020Sep 26 2020

All Science Journal Classification (ASJC) codes

  • Materials Science(all)
  • Engineering(all)

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