Application of a Fuzzy AHP Method to Risk Assessment of International Construction Projects

Chen, Peihong; Wang, Jiaqiong

doi:10.1109/ecbi.2009.14

Cited by 24 publications

(17 citation statements)

References 7 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Hence, the response rate for the questionnaire was 23.7 percent. This response rate is reasonable based on previous similar studies and research [22,60]. Of the respondents, 13 percent have 6-10 years' working experience, 31 surveyors, and two are project managers.…”

Section: Questionnaire Responsementioning

confidence: 64%

“…According to [21], the influencing factors of project cost can be grouped into project planning and control, market, technical, financial and regulatory categories. In the research conducted by [22], the influencing factors for project cost were classified into three groups, namely parent, management and resource factors. In [23], based on the nature of the influencing factors, they can be classified into physical, design, financial, political, legal, logistics, construction, environment and operation factors.…”

Section: Development Of Variables and Hypothesesmentioning

confidence: 99%

See 1 more Smart Citation

Bayesian Structural Equation Modeling for Examining the Relationship between Multidimensional Factors and Construction Project Cost

Zhao¹,

Liu²,

Mbachu³

2019

Preprint

View full text Add to dashboard Cite

Construction projects are usually operating in a complex and dynamic environment in which the accumulation of many interrelated factors causes high uncertainty. Construction projects are complex and frequently involve substantial uncertainties including process complicatedness, intricate organization structure, dynamic environment, and financial strain. The study aims to categorize the influencing factors into three groups, namely construction project system, economic-market climate, and external environment. It attempts to adopt a novel analysis tool to examine the relationship between the project cost and multiple influencing factors by using Bayesian SEM. While the Bayesian SEM method has been receiving increasing attention in exploring the relationship between latent variables, construction studies still heavily rely on the covariance-based SEM approach. This study introduces several advantages of Bayesian SEM that make it more flexible and powerful than covariance-based SEM and provides the foundation of Bayesian SEM estimation and inference by illustrating this method in a project cost application.

show abstract

Section: Questionnaire Responsementioning

confidence: 64%

Section: Development Of Variables and Hypothesesmentioning

confidence: 99%

Bayesian Structural Equation Modeling for Examining the Relationship between Multidimensional Factors and Construction Project Cost

Zhao¹,

Liu²,

Mbachu³

2019

Preprint

View full text Add to dashboard Cite

show abstract

“…Also, these approaches cannot match with current conditions of project. In addition to the stated advantages of the developed approach for construction project risk assessment, Table 14 shows that the ANFIS is very effective in modeling risk factors of construction project in comparison with some recently presented approaches for risk assessment such as Data Envelopment Analysis (DEA) and Analytic Hierarchy Process (AHP) , Analytic Hierarchy Process (AHP) (Zayed et al, 2008), Artificial Neural Network (ANN) (Yu et al, 2008), Fuzzy Group Decision Making (FGDM) , and fuzzy AHP (FAHP) (Chen and Wang, 2009).…”

Section: Discussionmentioning

confidence: 98%

“…Wang and Elhag (2007) have used grouped fuzzy decision making approach for assessment of risks in bridge construction project. Chen and Wang (2009) have used the fuzzy AHP method for evaluation of risks within global construction projects. However, in their work, some defects related to not considering the experts' mistakes in giving their opinion can be seen.…”

Section: Introductionmentioning

confidence: 99%

Construction project risk assessment by using adaptive-network-based fuzzy inference system: An empirical study

Ebrat

Ghodsi

2014

KSCE J Civ Eng

View full text Add to dashboard Cite

Managers require a good understanding about the nature of risks involved in a construction project because the duration, quality, and budget of projects can be affected by these risks. Thus, the identification of risks and the determination of their priorities in every phase of the construction can assist project managers in planning and taking proper actions against those risks. Therefore, prioritizing risks via the risk factors can increase the reliability of success. In this research, first the risks involved in construction projects has been identified and arranged in a systematic hierarchical structure. Next, based on the obtained data an Adaptive Neuro-Fuzzy Inference System (ANFIS) has been designed for the evaluation of project risks. In addition, a stepwise regression model has also been designed and its results are compared with the results of ANFIS. The results show that the ANFIS models are more satisfactory in the assessment of construction projects risks. Our proposed methodology can be applied by managers of construction projects and practitioners to assess of risk factor of construction projects in a proper manner.

show abstract

“…Chen and Wang in 2009 [22] have focused in their paper on International project risks as many constructors are involved in abroad and oversea projects. The assessment begins with the classification of risk using Hierarchical Risk breakdown structure.…”

Section: Literature Reviewmentioning

confidence: 99%

Risk Assessment for Project Construction Based on User Perspective: An Experimental Analysis using AHP

Mohanty¹,

Roy²,

Ganguly³

et al. 2019

IJITEE

View full text Add to dashboard Cite

Risk assessment has become essential tool for construction of project in a safe and secure manner. In this paper, one of the Multi-Criteria Decision-Making (MCDM) method is used i.e. AHP (Analytic Hierarchy Process) to rank the investment alternatives from a risk point of view, by taking into consideration the preferences of the investor or decision maker. The proposed approach not only involve identification of potential risks but also analyze the risks and mitigate them, so that it can lead to the overall success of a project.

show abstract

Application of a Fuzzy AHP Method to Risk Assessment of International Construction Projects

Cited by 24 publications

References 7 publications

Bayesian Structural Equation Modeling for Examining the Relationship between Multidimensional Factors and Construction Project Cost

Bayesian Structural Equation Modeling for Examining the Relationship between Multidimensional Factors and Construction Project Cost

Construction project risk assessment by using adaptive-network-based fuzzy inference system: An empirical study

Risk Assessment for Project Construction Based on User Perspective: An Experimental Analysis using AHP

Contact Info

Product

Resources

About