Development of a Risk Assessment Model for Oman Construction Industry

2014 ◽  
Vol 70 (7) ◽  
Author(s):  
K. N. Yafai ◽  
J. S. Hassan ◽  
S. Balubaid ◽  
R. M. Zin ◽  
M. R. Hainin
Keyword(s):  
Risk Factors ◽  
Risk Assessment ◽  
Construction Industry ◽  
Construction Projects ◽  
Model Development ◽  
Arabian Gulf ◽  
Assessment Model ◽  
Research Approach ◽  
Secondary Sources ◽  
Assessment Procedures

Oman as one of the Arabian Gulf countries which have invested billions of dollars in the construction industries, infrastructural services and real estate, but it is clearly identified that risk assessment was not applied for once on these awarded contracts. Lack of knowledge and awareness of risk management or assessment procedures in the construction industry in Oman caused additional cost and time delay in most of the awarded construction projects. This paper aimed at developing a model for risk assessment in the Oman construction industry to save huge amounts of millions of money wasted due to this problem. A field survey of semi-structured questionnaire with face-to-face interviews was carried out in the Oman construction industry including public, contractors and consultants. The research approach relies on data collected from primary and secondary sources. Combination of quantitative and qualitative data analysis was used in analysing the data for the Model development. The risk factors in the Oman construction industry varies from one category to another, the risk factors in government category are more than the consultant category and contractor’s category. Overall, the Oman construction industry has no very high risk factors, which means it has good opportunities for investment. It is expected that the output of this research will have a good and beneficial contribution to save time and money for both public and private sectors in Oman due to expected awareness and improvements in the risk assessment procedures. 

Developing a fuzzy risk assessment model for guaranteed maximum price and target cost contracts in South Australia

Facilities ◽  
2014 ◽  
Vol 32 (11/12) ◽  
pp. 624-646 ◽  
Author(s):  
Daniel W.M. Chan ◽  
Joseph H.L. Chan ◽  
Tony Ma
Keyword(s):  
Risk Factors ◽  
Risk Assessment ◽  
Construction Projects ◽  
South Australia ◽  
Assessment Model ◽  
Risk Assessment Model ◽  
Content Type ◽  
Risk Levels ◽  
Target Cost ◽  
Fuzzy Risk Assessment

Purpose – This paper aims to develop a fuzzy risk assessment model for construction projects procured with target cost contracts and guaranteed maximum price contracts (TCC/GMP) using the fuzzy synthetic evaluation method, based on an empirical questionnaire survey with relevant industrial practitioners in South Australia. Design/methodology/approach – A total of 34 major risk factors inherent with TCC/GMP contracts were identified through an extensive literature review and a series of structured interviews. A questionnaire survey was then launched to solicit the opinions of industrial practitioners on risk assessment of such risk factors. Findings – The most important 14 key risk factors after the computation of normalised values were selected for undertaking fuzzy evaluation analysis. Five key risk groups (KRGs) were then generated in descending order of importance as: physical risks, lack of experience of contracting parties throughout TCC/GMP procurement process, design risks, contractual risks and delayed payment on contracts. These survey findings also revealed that physical risks may be the major hurdle to the success of TCC/GMP projects in South Australia. Practical implications – Although the fuzzy risk assessment model was developed for those new-build construction projects procured by TCC/GMP contracts in this paper, the same research methodology may be applied to other contracts within the wide spectrum of facilities management or building maintenance services under the target cost-based model. Therefore, the contribution from this paper could be extended to the discipline of facilities management as well. Originality/value – An overall risk index associated with TCC/GMP construction projects and the risk indices of individual KRGs can be generated from the model for reference. An objective and a holistic assessment can be achieved. The model has provided a solid platform to measure, evaluate and reduce the risk levels of TCC/GMP projects based on objective evidence instead of subjective judgements. The research methodology could be replicated in other countries or regions to produce similar models for international comparisons, and the assessment of risk levels for different types of TCC/GMP projects (including new-build or maintenance) worldwide.

scholarly journals Construction Schedule Risk Assessment and Management Strategy for Foreign General Contractors Working in the Ethiopian Construction Industry

2021 ◽  
Vol 13 (14) ◽  
pp. 7830
Author(s):  
Min-Yuan Cheng ◽  
Mohammadzen Hasan Darsa
Keyword(s):  
Risk Factors ◽  
Risk Assessment ◽  
Construction Industry ◽  
Management Strategy ◽  
Assessment Model ◽  
Project Schedule ◽  
Schedule Delay ◽  
General Contractors ◽  
Schedule Risk ◽  
Construction Schedule

Construction project schedule delay is a worldwide concern and especially severe in the Ethiopian construction industry. This study developed a Construction Schedule Risk Assessment Model (CSRAM) and a management strategy for foreign general contractors (FGCs). 94 construction projects with schedule delay were collected and a questionnaire survey of 75 domain experts was conducted to systematically select 22 risk factors. In CSRAM, the artificial neural network (ANN) inference model was developed to predict the project schedule delay. Integrating it with the Garson algorithm (GA), the relative weights of risk factors with rankings were calculated and identified. For comparison, the Relative Importance Index (RII) method was also applied to rank the risk factors. Management strategies were developed to improve the three highest-ranked factors identified using the GA (change order, corruption/bribery, and delay in payment), and the RII (poor resource management, corruption/bribery, and delay in material delivery). Moreover, the improvement results were used as inputs for the trained ANN to conduct a sensitivity analysis. The findings of this study indicate that improvements in the factors that considerably affect the construction schedule can significantly reduce construction schedule delays. This study acts as an important reference for FGCs who plan to enter or work in the Ethiopian construction industry.

A fuzzy model for evaluating risk impacts on variability between contract sum and final account in government-funded construction projects

2015 ◽  
Vol 13 (1) ◽  
pp. 45-69 ◽  
Author(s):  
Ernest Effah Ameyaw ◽  
Albert P.C. Chan ◽  
De-Graft Owusu-Manu ◽  
Ekow Coleman
Keyword(s):  
Risk Factors ◽  
Construction Projects ◽  
Fuzzy Model ◽  
High Impact ◽  
Assessment Model ◽  
Research Approach ◽  
Principal Component Factor Analysis ◽  
Related Factors ◽  
Content Type ◽  
Client Factors

Purpose – The purpose of this paper is to identify and then evaluate perceived risk factors influencing variability between contract sum and final count, and to develop a fuzzy risk assessment model for evaluating the overall impact of established critical risk factors impacting on variability between contract sum and final account in government-funded construction projects. Construction projects are characterised by risk factors that significantly impact on variability between the contract sum and final account. Design/methodology/approach – A research approach integrating questionnaire survey, mean scoring ranking and principal component factor analysis (PCFA) methods was adopted to evaluate and classify the critical risk factors. A fuzzy synthetic evaluation method was sequentially applied to compute the overall risk impact (ORI) of eight critical risk factors’ impact on variability between contract sum and final account. Findings – Initial results showed that eight critical risk factors have high impact on variations between contract sum and final account, namely (in order): project funding problems, underestimation of quantities, variations by client, change in scope of works, inadequate specification, change in design by client, defects in design and unexpected site (ground) conditions. PCFA produced two factor solutions: “professional-related factors” and “client factors”. The fuzzy model further showed that the ORI is 5.48, indicating that these risk factors have a high impact on variability between contract sum and final account in public construction projects. The client factors have a very high impact (5.59), while the professional-related factors indicated a high impact (5.41) on project cost variability. Originality/value – A practical model is proposed to evaluate the key risks associated with cost overruns in public projects. By giving effective and sustained attention to these factors, variability between contract sum and final account, a common situation in Ghana, can be controlled to achieve cost savings in public infrastructure projects.

scholarly journals DESIGN AND PILOT RUN OF FUZZY SYNTHETIC MODEL (FSM) FOR RISK EVALUATION IN CIVIL ENGINEERING

2013 ◽  
Vol 19 (2) ◽  
pp. 217-238 ◽  
Author(s):  
Hamzah Abdul-Rahman ◽  
Chen Wang ◽  
Yee Lin Lee
Keyword(s):  
Risk Assessment ◽  
Construction Projects ◽  
Optimal Allocation ◽  
Early Stage ◽  
Model Development ◽  
Assessment Tools ◽  
Assessment Model ◽  
Quality Data ◽  
Risk Assessment Model ◽  
Synthetic Model

Most of the current construction risk assessment tools deliver unsatisfactory results because the prerequisite for their effective applications rely on the availability of high quality data especially during the early stage of a project. Unfortunately, such data are limited, ambiguous or even not exist due to the great uncertainty inherent in construction projects. Based on Fuzzy Synthetic Analysis (FSA), a model development team was formed among construction engineers, IT professionals, and Mathematicians in developing a holistic risk assessment model to estimate the construction risks especially for the situations with incomplete data and vague environments. Through qualitative scales defined by triangular fuzzy numbers used in pairwise comparisons to capture the vagueness in the linguistic variables, a risk assessment model using Analytic Hierarchy Process (AHP) was developed. The Pilot Run revealed the developed Fuzzy Synthetic Model (FSM) could accelerate the decision-making process and provide optimal allocation of project resources to mitigate possible risks detrimental to the success of a project in terms of time, cost, and quality.

scholarly journals The risk assessment model for construction projects including value creation and protection aspects

2019 ◽  
Author(s):  
Jolanta Tamošaitienė ◽  
Miglė Lapeikytė
Keyword(s):  
Risk Assessment ◽  
Construction Industry ◽  
Value Creation ◽  
Construction Projects ◽  
Assessment Model ◽  
Risk Level ◽  
Risk Assessment Model ◽  
Construction Sector

The article focuses on the identification and classification of key risk management criteria that represent the value creation and protection aspects for the construction industry. Nowadays, the assessment of the risk level of a construction project is especially important for the quality of construction projects as well as the growth of enterprises and the sector. To establish the most important criteria for the successful growth of the construction sector including value creation and protection aspects are developed.

DEVELOPING A COMPREHENSIVE RISK ASSESSMENT MODEL BASED ON FUZZY BAYESIAN BELIEF NETWORK (FBBN)

2020 ◽  
Vol 26 (7) ◽  
pp. 614-634
Author(s):  
Li Guan ◽  
Qiang Liu ◽  
Alireza Abbasi ◽  
Michael J. Ryan
Keyword(s):  
Risk Factors ◽  
Risk Assessment ◽  
Risk Management ◽  
Construction Projects ◽  
Bayesian Belief Network ◽  
Assessment Model ◽  
Risk Assessment Model ◽  
Causal Relationships ◽  
Belief Network ◽  
International Construction

Reliable and efficient risk assessments are essential to deal effectively with potential risks in international construction projects. However, most conventional risk modeling methods are based on the hypothesis that risk factors are independent, which does not account adequately for the causal relationships among risk factors. In this study, a risk assessment model for international construction projects was developed to improve the efficacy of risk management by integrating fault tree analysis and fuzzy set theory with a Bayesian belief network. The risk rating of each risk factor, expressed as the product of risk occurrence probability and impact, was incorporated into the risk assessment model to evaluate degrees of risk. Therefore, risk factors were categorized into different risk levels taking into account their inherent causal relationships, which allowed the identification of critical risk factors. The applicability of the fuzzy Bayesian belief network-based risk assessment model was verified using a case study through a comparative analysis with the results from a fuzzy synthetic evaluation method. The comparison shows that the proposed risk assessment model is able to provide guidelines for an effective risk management process and ultimately to increase project performance in a complex environment such as international construction projects.

The Vulnerability of the Construction Ergonomics to Covid-19 and Its Probability Impact in Combating the Virus

2021 ◽  
Vol 4 (1) ◽  
pp. 01-17
Author(s):  
Ahmed Fahim Elgendi ◽  
◽  
◽  
◽  
◽  
...  
Keyword(s):  
Construction Industry ◽  
Construction Projects ◽  
World Health ◽  
Personal Hygiene ◽  
Extensive Literature ◽  
Novel Coronavirus ◽  
Health Organization ◽  
Assessment Procedures ◽  
Chronic Health Problems ◽  
The Relationship

Currently, the world encounters the outbreak of an unprecedented epidemic named novel coronavirus COVID -19. World Health Organization (WHO) advises maintaining social distancing, preserving personal hygiene, and staying informed with the latest guidelines. WHO also reports the patients with robust immunity can combat the virus. However, the workers in the construction industry work and live in a crowded and non-hygiene environment. Moreover, they are characterized by illiteracy, a dearth of awareness, and chronic health problems that prove weak immunity. Therefore, this study aims to find the relationship between the virus and the prevailing conditions and the environment of the construction industry, under focus, and study so that the construction industry is not a vulnerability gap that may exacerbate the crisis. An extensive literature exploration for the latest research deals with coronavirus, the construction industry ergonomics, and its relevant diseases. This study makes robust alerts to motivate the governments, organizations, and individuals to collaborate to find solutions to close the gap between the current situation in the construction of ergonomics and the required precaution to avoid the outbreak of the virus. This study makes a crucial and novel contribution by paving the way for providing solutions to save humanity worldwide. The management system should review the conventional risk assessment procedures, and developed criteria must be introduced and become an everyday practice of all construction projects. This will help identify the gaps within the safety procedures associated with the COVID – 19 protection aspects. This article also introduces a framework in this regard.

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.

Analytical model for assessing collapse risk during mountain tunnel construction

2016 ◽  
Vol 53 (2) ◽  
pp. 326-342 ◽  
Author(s):  
Guo-Hua Zhang ◽  
Yu-Yong Jiao ◽  
Li-Biao Chen ◽  
Hao Wang ◽  
Shu-Cai Li
Keyword(s):  
Risk Factors ◽  
Risk Assessment ◽  
Index System ◽  
Assessment Model ◽  
Tunnel Construction ◽  
Assessment Index ◽  
Assessment Index System ◽  
Geological Prediction ◽  
Tunnel Collapse ◽  
Mountain Tunnel

Risk management for safety in mountain tunnel construction is of great significance. However, existing research lags behind engineering applications. In this paper, the risk of mountain tunnel collapse is used as an example to illustrate a new assessment method based on case-based reasoning, advanced geological prediction, and rough set theory. First, the risk surroundings and risk factors involved in tunnel collapse are integrated and summarized, and a risk assessment index system is established for tunnel collapse. At the same time, because the dynamic response parameters obtained by the advanced geological prediction usually indicate a typical geological structure, sensitive response parameters are introduced in the assessment index system. Advanced risk assessment can be performed for tunnel sections at a certain distance ahead of the tunnel face. Second, the major risk surroundings and the advanced geological prediction results are analyzed for the tunnel under assessment. Cases with similar attribute characteristics are selected via comparison with previous cases. Attribute reduction and calculation of weights are subsequently performed for the risk surroundings and risk factors of similar cases based on the attribute significance theory of rough sets. Finally, index screening and objective weights are applied in the fuzzy comprehensive assessment model. The results of this paper can be used to improve the theoretical level and reliability of risk assessment in tunnel safety and serve as a reference for tunnel construction.

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