Optimal Reduction of Project Risk Severity: A Case Study

2015 ◽  
Author(s):  
Nael Zabel ◽  
Maged Georgy ◽  
Moheeb Ibrahim
Keyword(s):  
Project Risk ◽  
Optimal Reduction

scholarly journals A Framework for Project Risk Assessment in Dynamic Networks: A Case Study of Oil and Gas Megaproject Construction

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Amir Farmahini Farahani ◽  
Kaveh Khalili-Damghani ◽  
Hosein Didehkhani ◽  
Amir Homayoun Sarfaraz ◽  
Mehdi Hajirezaie
Keyword(s):  
Risk Assessment ◽  
Oil And Gas ◽  
Dynamic Networks ◽  
Project Risk ◽  
Project Risk Assessment

Economic Project Risk Assessment in Remediation Projects Prior to Construction: Methodology Development and Case Study Application

2015 ◽  
Vol 25 (2) ◽  
pp. 117-138 ◽  
Author(s):  
Petra Brinkhoff ◽  
Malin Norin ◽  
Jenny Norrman ◽  
Lars Rosén ◽  
Kristine Ek
Keyword(s):  
Risk Assessment ◽  
Project Risk ◽  
Methodology Development ◽  
Study Application ◽  
Project Risk Assessment

Project risk planning in high-tech new product development

2016 ◽  
Vol 29 (2) ◽  
pp. 110-124 ◽  
Author(s):  
Jorge Ayala-Cruz
Keyword(s):  
Risk Management ◽  
New Product Development ◽  
New Product ◽  
High Tech ◽  
Project Risk ◽  
Content Type ◽  
Management Framework ◽  
Risk Management Framework ◽  
Project Risks

Purpose The purpose of this paper is to present the implementation and testing of a modified project risk management framework that integrates PMI’s framework with Monte Carlo simulation to improve the effectiveness in high-tech new product development (NPD) projects. Design/methodology/approach The modified framework considers three bodies of knowledge: project management, risk management, and Monte Carlo simulation to produce an enhance project risk management framework. Its application is shown through a case study. Findings Using the integrated framework in a recent case study project and prior NPD projects measures (as benchmarks), it was shown that it could help to enhance risk responses caused by task durations and costs’ uncertainties. The framework proved to be better than segregated generic best practices and was key in providing insight to the issue of early project risk assessment. Research limitations/implications More experimental replications are required for enhancement effectiveness assertions of the framework, through the application of the framework to similar case studies. Furthermore, this could improve its reliability and soundness. Practical implications Future directions for research could include case and empirical studies that include hypothesis’s testing, and the integration of optimization procedure for improved NPD project’s planning and execution. Originality/value This paper outlines a way to close the gap of project risks management planning in NPD’s initiatives. It was motivated by a relatively new tendency in exploring integrated frameworks to deal with complex project risks issues.

Fuzzy Analytic Hierarchy in Project Risk Management - New Stadium Construction Project in Weifang City

2011 ◽  
Vol 243-249 ◽  
pp. 6362-6368
Author(s):  
Yan Zhang ◽  
Chang Jiang Liu
Keyword(s):  
Risk Management ◽  
Project Management ◽  
Construction Projects ◽  
Large Scale ◽  
Construction Project ◽  
Construction Project Management ◽  
Analytic Hierarchy ◽  
Project Risk ◽  
Management Case Study

In the field of engineering and construction, unqualified construction quality, time delays, cost more than expected phenomena to occur. Because of these characteristics such as its large-scale construction projects, long cycle, the production of single and complex, there is greater risk than the production of general products, the risk increases the difficulty of construction project management, operating costs and the possibility of potential losses, therefore, risk management emerged and become an increasingly important integral part of project management. In this paper, fuzzy analytic hierarchy be used to construction project risk assessment, and to order the sort of each risk in order to prevent significant risks. On an actual project - the new stadium construction in Weifang City risk management case study, the reduction of risk of project failure is expected, but also the project is hoped for other industries to provide some reference for risk management.

scholarly journals Project Risk time Management – A Proposed Model and a Case Study in the Construction Industry

2015 ◽  
Vol 64 ◽  
pp. 24-31 ◽  
Author(s):  
Barbara Gładysz ◽  
Dariusz Skorupka ◽  
Dorota Kuchta ◽  
Artur Duchaczek
Keyword(s):  
Construction Industry ◽  
Time Management ◽  
Project Risk ◽  
Proposed Model

Application of Monto-Carlo Method in HR Investment Risk Evaluation

2010 ◽  
Vol 458 ◽  
pp. 131-136
Author(s):  
Jing Jing Lu ◽  
Xuan Xi Ning
Keyword(s):  
Risk Analysis ◽  
Human Resources ◽  
Computer Program ◽  
Risk Evaluation ◽  
Investment Project ◽  
Investment Risk ◽  
Project Risk ◽  
Index Function ◽  
Project Risk Analysis

Monto-Carlo method is widely used for project risk analysis. Evaluating the risk in HR (Human Resources) investment project, which is of hi-investment and hi-return, by Monto-carlo method is a new attempt. In this paper, by taking cost, profit and risk in the HR investment as index, emulation model of HR investment and index function of risk evaluation were established. Simulation about the whole investment course was done by computer program using Monto-Carlo method. Case study of HR investment risk evaluation was done later using concrete data.

Amadubi Rural Tourism Project in Jharkhand: Development of Project Risk Management (B)

2015 ◽  
pp. 1-15
Author(s):  
Goutam Dutta
Keyword(s):  
Risk Management ◽  
Critical Path ◽  
Rural Tourism ◽  
Project Risk Management ◽  
Project Risk ◽  
Network Diagram ◽  
Likelihood Rating ◽  
Risk Sources ◽  
The Impact

This case should be taught after (A) case. This case study discusses how the stakeholders of the (A) can sit together can discuss prepare first the activities of the project, draw the network diagram, develop a critical path. The discussion further proceeds when these stakeholders through the discussion develop risk sources, assigns probabilities and computes the impact and likelihood rating.

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