scholarly journals Measuring project risk management performance: a preliminary model

2018 ◽  
Author(s):  
Larissa Rubio ◽  
Alfredo Serpell ◽  
Ximena Ferrada
Keyword(s):  
Risk Management ◽  
Project Risk Management ◽  
Management Performance ◽  
Project Risk ◽  
Preliminary Model

scholarly journals Measuring the performance of project risk management: a preliminary model

2019 ◽  
Vol 11 (1) ◽  
pp. 1984-1991
Author(s):  
Alfredo Federico Serpell ◽  
Ximena Ferrada ◽  
Larissa Rubio
Keyword(s):  
Risk Management ◽  
Construction Projects ◽  
Research Literature ◽  
Lessons Learned ◽  
Project Risk Management ◽  
Project Risk ◽  
Know How ◽  
Construction Companies ◽  
Important Concern ◽  
Preliminary Model

Abstract The function of project risk management (PRM) is to understand the uncertainty that surrounds a project and to identify the potential threats than can affect it as well as to know how to handle these risks in an appropriate way. Then, the measurement of the performance of PRM becomes an important concern, an issue that has not yet been addressed in the research literature. It is necessary to know how successful the application of the PRM process is and how capable is the process within the organization. Regarding construction projects, it is essential to know whether the selected responses to mitigate or eliminate identified risks were suitable and well implemented after the execution of the project. This paper presents a critical analysis of the relevance of measuring the performance of PRM and the benefits of doing so. Additionally, it presents a preliminary and pioneering methodology to measure the performance of PRM through the evaluation of the adequacy of responses applied to mitigate risks as well as to evaluate the resulting impacts as indicators of the effectiveness of these actions at the end of the project. This knowledge will allow construction companies to incorporate good practices, generate lessons learned, and thereby to promote a continuous improvement of the whole PRM process.

Project Risk Management

2013 ◽  
Vol 2 (4) ◽  
pp. 79-101
Author(s):  
Jan Terje Karlsen ◽  
Odin Folke-Olsen ◽  
Tim Torvatn
Keyword(s):  
Risk Management ◽  
Oil And Gas ◽  
Oil And Gas Industry ◽  
Project Risk Management ◽  
Management Performance ◽  
Management Tools ◽  
Project Risk ◽  
Gas Industry ◽  
Management Processes ◽  
Contribution Index

This study is about project risk management tools. The aim has been to identify which tools have the greatest potential for contribution to risk management processes in the Norwegian oil and gas industry, and which factors contribute to efficient risk management. Empirical data from the Norwegian industry have been gathered using a questionnaire. The results revealed strong relationships between project system complexity, average tool score and risk management contribution. Furthermore, the results of the analysis show that some of the previous recommendations of tools for project risk management may have been based on a restricted set of determinants. On the other hand, similarities are also found with previous research in terms of the highest ranked tools based on perceived contribution to the risk management performance. Compared to the previous findings, this study indicates that a new measure for project management performance is needed, and that the recommendation of tools based on the risk management contribution index may be flawed. Nevertheless, it is concluded that several of the recommended tools are of great value across industries.

Project Risk Management

2015 ◽  
pp. 250-271
Author(s):  
Jan Terje Karlsen ◽  
Odin Folke-Olsen ◽  
Tim Torvatn
Keyword(s):  
Risk Management ◽  
Oil And Gas ◽  
Oil And Gas Industry ◽  
Project Risk Management ◽  
Management Performance ◽  
Management Tools ◽  
Project Risk ◽  
Gas Industry ◽  
Management Processes ◽  
Contribution Index

This study is about project risk management tools. The aim has been to identify which tools have the greatest potential for contribution to risk management processes in the Norwegian oil and gas industry, and which factors contribute to efficient risk management. Empirical data from the Norwegian industry have been gathered using a questionnaire. The results revealed strong relationships between project system complexity, average tool score and risk management contribution. Furthermore, the results of the analysis show that some of the previous recommendations of tools for project risk management may have been based on a restricted set of determinants. On the other hand, similarities are also found with previous research in terms of the highest ranked tools based on perceived contribution to the risk management performance. Compared to the previous findings, this study indicates that a new measure for project management performance is needed, and that the recommendation of tools based on the risk management contribution index may be flawed. Nevertheless, it is concluded that several of the recommended tools are of great value across industries.

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