Scenario based evaluation of a cost risk model through sensitivity analysis

2015 ◽  
Vol 22 (4) ◽  
pp. 403-423 ◽  
Author(s):  
Önder Ökmen ◽  
Ahmet Öztaş
Keyword(s):  
Risk Factors ◽  
Risk Analysis ◽  
Risk Model ◽  
Practical Method ◽  
Cost Evaluation ◽  
Sensitivity Analyses ◽  
Analysis Model ◽  
Content Type ◽  
Detailed Evaluation ◽  
Cost Risk

Purpose – Actual costs frequently deviate from the estimated costs in either favorable or adverse direction in construction projects. Conventional cost evaluation methods do not take the uncertainty and correlation effects into account. In this regard, a simulation-based cost risk analysis model, the Correlated Cost Risk Analysis Model, previously has been proposed to evaluate the uncertainty effect on construction costs in case of correlated costs and correlated risk-factors. The purpose of this paper is to introduce the detailed evaluation of the Cost Risk Analysis Model through scenario and sensitivity analyses. Design/methodology/approach – The evaluation process consists of three scenarios with three sensitivity analyses in each and 28 simulations in total. During applications, the model’s important parameter called the mean proportion coefficient is modified and the user-dependent variables like the risk-factor influence degrees are changed to observe the response of the model to these modifications and to examine the indirect, two-sided and qualitative correlation capturing algorithm of the model. Monte Carlo Simulation is also applied on the same data to compare the results. Findings – The findings have shown that the Correlated Cost Risk Analysis Model is capable of capturing the correlation between the costs and between the risk-factors, and operates in accordance with the theoretical expectancies. Originality/value – Correlated Cost Risk Analysis Model can be preferred as a reliable and practical method by the professionals of the construction sector thanks to its detailed evaluation introduced in this paper.

Cost-risk contingency framework for managing cost overrun in metropolitan projects: using fuzzy-AHP and simulation

2020 ◽  
Vol 13 (5) ◽  
pp. 1121-1139 ◽  
Author(s):  
Farman Afzal ◽  
Shao Yunfei ◽  
Danish Junaid ◽  
Muhammad Shehzad Hanif
Keyword(s):  
Risk Factors ◽  
Risk Analysis ◽  
Construction Cost ◽  
The Body ◽  
Cost Overrun ◽  
Content Type ◽  
High Uncertainty ◽  
Total Construction Cost ◽  
Cost Risk ◽  
Contingency Framework

PurposeRisk analysis plays a vital role in controlling and managing cost overruns in complex construction projects, particularly where uncertainty is high. This study attempts to address an important issue of cost overrun that encountered by metropolitan rapid transit projects in relation to the significance of risk involved under high uncertainty.Design/methodology/approachIn order to solve cost overrun problems in metropolitan transit projects and facilitate the decision-makers for effective future budgeting, a cost-risk contingency framework has been designed using fuzzy logic, analytical hierarchy process and Monte Carlo simulation.FindingsInitially, a hierarchical breakdown structure of important complexity-driven risk factors has been conceptualized herein using relative importance index. Later, a proposed cost-risk contingency framework has investigated the expected total construction cost in order to consider the additional budgeted cost required to mitigate the risk consequences for particular project activity. The results of cost-risk analysis imply that poor design issues, an increase in material prices and delays in relocating facilities show higher dependency and increase the risk of cost overrun in metropolitan transit projects.Practical implicationsThe findings and implication for project managers could possibly be achieved by assuming the proposed cost-risk contingency framework under high uncertainty of cost found in this research. Furthermore, this procedure may be used by experts from other engineering domains by replacing and considering the complex relationship between complexity-risk factors.Originality/valueThis study contributes to the body of knowledge by providing a practical contingency model to identify and evaluate the additional risk cost required to compute total construction cost for getting stability in future budgeting.

scholarly journals Developing a Risk Model for Assessment and Control of the Spread of COVID-19

Risks ◽  
2021 ◽  
Vol 9 (2) ◽  
pp. 38
Author(s):  
Usama H. Issa ◽  
Ashraf Balabel ◽  
Mohammed Abdelhakeem ◽  
Medhat M. A. Osman
Keyword(s):  
Risk Factors ◽  
Risk Analysis ◽  
Risk Model ◽  
Risk Groups ◽  
Personal Hygiene ◽  
Exact Nature ◽  
Analysis Model ◽  
Factors Affecting ◽  
Probability Of Occurrence ◽  
The Impact

Coronavirus disease 2019 (COVID-19) continues to spread rapidly all over the world challenging nearly all governments. The exact nature of COVID-19’s spread and risk factors for such a rapid spread are still imprecise as available data depend on confirmed cases only. This may result in an asymmetrically distributed burden among countries. There is an urgent need for developing a new technique or model to identify and analyze risk factors affecting such a spread. Fuzzy logic appears to be suitable for dealing with multi-risk groups with undefined data. The main purpose of this research was to develop a risk analysis model for COVID-19’s spread evaluation. Other objectives included identifying such risk factors aiming to find out reasons for such a fast spread. Nine risk groups were identified and 46 risk factors were categorized under these groups. The methodology in this study depended on identifying each risk factor by its probability of occurrence and its impact on viruses spreading. Many logical rules were used to support the proposed risk analysis model and represented the relation between probabilities and impacts as well as to connect other risk factors. The model was verified and applied in Saudi Arabia with further probable use in similar conditions. Based on the model results, it was found that (daily activities) and (home isolation) are considered groups with highest risk. On the other hand, many risk factors were categorized with high severity such as (poor social distance), (crowdedness) and (poor personal hygiene practices). It was demonstrated that the impact of COVID-19’s spread was found with a positive correlation with the risk factors’ impact, while there was no association between probability of occurrence and impact of the risk factors on COVID-19’s spread. Saudi Arabia’s quick actions have greatly reduced the impact of the risks affecting COVID-19’s spread. Finally, the new model can be applied easily in most countries to help decision makers in evaluating and controlling COVID-19’s spread.

Risk analysis of construction of administration projects using Bayesian networks

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mohammad Osama ◽  
Aly Sherif ◽  
Mohamed Badawy
Keyword(s):  
Risk Factors ◽  
Life Cycle ◽  
Risk Analysis ◽  
Construction Industry ◽  
Construction Projects ◽  
Causal Relationships ◽  
Content Type ◽  
Project Life Cycle ◽  
Project Objectives ◽  
Project Life

Purpose This paper aims to enlighten the importance of the risk management process which is considered as a major procedure to effectively handle the potential inherent risks in the construction industry. However, most traditional risk analysis techniques are based on theories that deal with each risk factor as an independent, which does not take into consideration the causal relationships between risk factors. Design/methodology/approach This study aspires to identify the overall risk of the administrative construction projects in Egypt and to recognize the most influencing risk factors through the project life cycle by using Bayesian belief networks (BBN). Through a review of the literature, 27 risk factors were identified and categorized as the most common risk factors in the construction industry. A structured questionnaire was performed to estimate the probability and severity of these risks. Through site visits and interviews with experts in the construction field, 200 valid questionnaires were collected. A risk analysis model was developed using BBNs, then the applicability of this model was verified using a case study in Egypt. Findings However, the outcome showed that critical risks that manipulate administrative construction projects in Egypt were corruption and bribery, contractor financial difficulties, force majeure, damage to the structure and defective material installation. Practical implications The proposed study presents the possibilities available to the project parties to obtain a better forecast of the project objectives, including the project duration, total project cost and the target quality by examining the causal relationships between project risks and project objectives. Originality/value This study aspires to identify the overall risk of the administrative construction projects in Egypt and to recognize the most influencing risk factors through the project life cycle by using BBNs.

Research of Bid Evaluation Risk Analysis Model Based on Decision Tree

2014 ◽  
Vol 998-999 ◽  
pp. 1595-1600
Author(s):  
Hui Kai Gao ◽  
Lin Ying Xu ◽  
Cai Hong Li
Keyword(s):  
Risk Factors ◽  
Statistical Theory ◽  
Risk Analysis ◽  
Decision Tree ◽  
Project Implementation ◽  
Classification Rules ◽  
Analysis Model ◽  
C4.5 Algorithm ◽  
Potential Risks ◽  
Bid Evaluation

Human and objective factors in bid evaluation might bring some risks to the relevant project. Therefore, an evaluation results-oriented model is developed for analyzing the projects' risks. The risk analysis model analyzes bidders’ evaluation results data by adopting the C4.5 algorithm, and then conducts risk analysis based on statistical theory and classification rules of the decision tree. The experiment result shows that the model could correctly detect risk factors of the bid-winning enterprise, issue early warnings of the potential risks during the project implementation, and provide suggestions to cope with the risks.

scholarly journals Integration of Interpretive Structural Modeling with Fuzzy Bayesian Network for Risk Assessment of Tunnel Collapse

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Leping He ◽  
Tao Tang ◽  
Qijun Hu ◽  
Qijie Cai ◽  
Zhijun Li ◽  
...  
Keyword(s):  
Risk Factors ◽  
Risk Analysis ◽  
Bayesian Network ◽  
Risk Model ◽  
Multicriteria Decision Making ◽  
Structural Modeling ◽  
Interpretive Structural Modeling ◽  
Construction Risk ◽  
Tunnel Collapse ◽  
The Relationship

Frequent collapse accidents in tunnels are associated with many construction risk factors, and the interrelationship among these risk factors is complex and ambiguous. This study’s aim is to clarify the relationship among risk factors to reduce the tunnel collapse risk. A multicriteria decision-making method is proposed by combining interpretive structural modeling (ISM) and fuzzy Bayesian network (FBN). ISM is used to determine the hierarchical relationships among risk factors. FBN quantitatively analyzes the strength of the interaction among risk factors and conducts risk analysis. The ISM-FBN method contains three steps: (1) drawing the ISM-directed graph; (2) obtaining the probability of the FBN nodes; and (3) using GeNle to implement risk analysis. The proposed method is also used to assess the collapse risk and detect the critical factors in the Canglongxia Tunnel, China. This method’s tunnel collapse risk model can provide managers with clear risk information and better realize project management.

scholarly journals The impact of changes in the base and precious metals prices on credit risk factors

2020 ◽  
Vol 17 (2) ◽  
pp. 45-64
Author(s):  
Vladimir Živanović
Keyword(s):  
Risk Factors ◽  
Credit Risk ◽  
Risk Model ◽  
Precious Metals ◽  
Multivariate Regression Analysis ◽  
Metal Exchange ◽  
Analysis Model ◽  
Proposed Model ◽  
Credit Risk Model ◽  
The Impact

The changes in the prices of base and precious metals on the global metal market have a significant impact on credit risk factors. The link between these factors has been neglected over the years by traditional credit risk models. The inclusion of correlation coefficients within the set credit risk model will show the impact of these changes on other variables of credit risk over the years under review and the impact of these changes on the probability of default and the recovery rate. Changes in base metals prices on the London Metal Exchange (LME) for lead and zinc and the London Bullion Metal Association (LBMA) for gold and silver as precious metals were used in the proposed credit risk model for the period of ten years. The research was done by using the multivariate regression analysis model and based on the statistical model evaluation,the significant impact of all observed independent variables on the dependent variable of the proposed model was proved. The construction of the proposed model with proven predictability gives a scientific significance to the research that includes variables of models from different markets, which have a significant impact on the variables from the financial market.

Belt and road initiative (BRI) supply chain risks: propositions and model development

2020 ◽  
Vol 31 (4) ◽  
pp. 777-799
Author(s):  
Jiwat Ram ◽  
Zeyang Zhang
Keyword(s):  
Risk Factors ◽  
Decision Making ◽  
Risk Management ◽  
Cyber Security ◽  
Risk Sharing ◽  
Risk Model ◽  
Model Development ◽  
Belt And Road Initiative ◽  
Content Type ◽  
Belt And Road

PurposeBelt and road initiative (BRI) is a transcontinental endeavor strategically connecting supply chains (SCs) and economic infrastructures to ignite business activities and achieve trade benefits. However, the rising global SC failure costs and risks associated with this initiative (owing to unique geopolitical, economic and mega-connectivity involving over 70 countries) necessitate examining BRI SC risks. Yet, research on the subject remains limited, and the purpose of this paper is to address this gap in knowledge.Design/methodology/approachA two-pronged approach was taken. First, a data sample of 554 articles was analyzed and 178 articles found relevant were used to present a systematic, structured framework of risk factors along operational, economic, financial, social and security dimensions. Then informed by the theory of risk management and supplemented by literature evidence, we have built a BRI SC risk model.FindingsThe results presented through the model show that BRI SCs face a combination of risks triggered by operational processes, informational and environmental (PIE) deficiencies. Findings show that lack of risk and liability management, unbalanced risk-sharing partnerships, lack of transparency, inadequate project evaluation, incompatible corporate governance structures and cyber security all pose threats to BRI SCs specifically and SCs in general.Research limitations/implicationsAcademically, the results facilitate theory development by identifying and proposing seven risk factors and modeling relationship among them and BRI SC risks outcome. The results also extend application of theory of risk management to SC context.Practical implicationsThe findings provide a decision-making tool for managers to assess risk factors in their SCs, thus enabling improved decision making to avoid, mitigate, transfer or accept risks.Originality/valueIdentifies and proposes a set of seven risk factors that drive BRI SC risks. Develops a model of BRI SC risks which help build theory of SC risk management.

Risk analysis model for regional railroad investment

2017 ◽  
Vol 34 (1) ◽  
pp. 164-173 ◽  
Author(s):  
Sunduck Suh ◽  
Wonho Suh ◽  
Jung In Kim
Keyword(s):  
Risk Analysis ◽  
Financial Analysis ◽  
Mathematical Optimization ◽  
Optimal Solution ◽  
Optimization Procedure ◽  
Solution Procedure ◽  
Risk Modeling ◽  
Analysis Model ◽  
Content Type ◽  
Goals And Objectives

Purpose The purpose of this study is to model risks in financial analysis. These risks associated with uncertainties in the projects should be properly addressed to ensure proper decision regarding the projects. Performance indicators should be developed and assessing risks has high priority. All these activities comprise appraisal, and based on these, a proper course of action should be recommended. Design/methodology/approach To analyze the attractiveness of a project for foreign regional railroad investment or participation, the project should be analyzed in a systematic way. First, the project’s goals and objectives should be evaluated for compatibility. Also, criteria of acceptability for stakeholders should be checked against output from the project. Usually, a project can have many alternatives, and impacts of each alternative should be analyzed in terms of quantitative and qualitative forecasts of impacts. Benefits and costs need to be counted in proper units of measurement per goals and objectives. Findings This paper shows that risk modeling can reflect uncertainty in decision-making and provide robustness of modeling process and improved communication. Also, challenges are presented in using risk analysis. Originality/value To overcome the shortcomings of traditional mathematical optimization model in identifying best sets of projects for private application, the proposed model finds ways to incorporate risk management components for the optimization procedure. Based on simulation results, a brute force solution procedure using enumeration can be used. Another approach is recommended to use the genetic algorithm process to reduce the number of alternatives to search to reach an optimal solution.

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