A proposal for construction project risk assessment using fuzzy logic

Construction Management and Economics (Impact Factor: 0.8). 02/2000; 18(4):491-500. DOI: 10.1080/01446190050024905
Source: RePEc


The construction industry is plagued by risk and often has suffered poor performance as a result. There are a number of risk management techniques available to help alleviate this, but usually these are based on operational research techniques developed in the 1960s, and for the most part have failed to meet the needs of project managers. In this paper, a hierarchical risk breakdown structure representation is used to develop a formal model for qualitative risk assessment. A common language for describing risks is presented which includes terms for quantifying likelihoods and impacts so as to achieve consistent quantification. The relationships between risk factors, risks and their consequences are represented on cause and effect diagrams. These diagrams and the concepts of fuzzy association and fuzzy composition are applied to identify relationships between risk sources and the consequences for project performance measures. A methodology for evaluating the risk exposure, considering the consequences in terms of time, cost, quality, and safety performance measures of a project based on fuzzy estimates of the risk components is presented.

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    • "In this research study, the FSE approach utilizes linguistic variables of risk probability and severity for assessing the risk level of principal risk factors and PPP water projects. This is appropriate, given that likelihood and severity are the major attributes of a risk factor (Tah & Carr, 2000). "
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    ABSTRACT: As governments embark on public–private partnerships (PPPs) to develop their water infrastructure, effective risk assessment, which has remained nebulous, has become an important step to ensure success of these projects. This paper investigates the risk factors and assesses the risk level of PPP water supply projects in developing countries using fuzzy synthetic evaluation (FSE) approach. A 40-factor risk list was established through investigation in water projects cases and related literature and an industry-wide questionnaire survey with industry practitioners. Initial statistical analysis yielded 22 critical risk factors that would have significant impacts on water supply partnerships. These factors were categorized into three principal factors (financial/commercial, legal and socio-political, and technical) forming the input variables for FSE analysis. The study showed that the overall risk level of water PPPs in developing countries is high, suggesting that these projects are risky to both governments and private participants. The fuzzy analysis, overall, confirmed that financial/commercial risk category is the most critical principal factor, followed by legal and socio-political category and technical category. The FSE approach to risk assessment can be used as an initial screening to establish risk factors that require attention of management and further detailed analysis. This study demonstrates that FSE methodology can be used to synthetically analyze local conditions in a country prior to setting up the project structure and normal due diligence. It is a multi-attribute risk assessment framework and may serve as a risk evaluation tool for private investors, policy-makers and decision-makers.
    Full-text · Article · Jul 2015 · Expert Systems with Applications
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    • "As for project delay, Shen [7] presented, based on a questionnaire, eight major risks. By using the hierarchical risk breakdown structure (HRBS), Tah and Carr [8] identified the internal and external risks in construction industry. Shen et al. [9] listed six groups of risks: financial, legal, management, market, policy and political. "

    Full-text · Conference Paper · May 2014
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    • "Even though 'human' experts can often accomplish a reasonable project result, deficits almost always follow due to managers failing to take all relevant factors into consideration and/or lacking access to all relevant information (Cheng, Tsai, & Sudjono, 2012; Cheng et al., 2009). The construction industry in the past has been plagued with similar problems and is categorised by (a) specific intricacy variables due to individual industry ambiguities and inter-dependencies , and (b) insufficiency of operations (Beavers et al., 2006; Dubois & Gadde, 2002; Tah & Carr, 2000). Despite the availability of several intelligent systems, construction managers are still perplexed when faced with a new problem in decision-making, when they ought to establish which existing intelligent systems are most apposite given the nature of the system, the objectives for development , time constraints and computing capacity (Bisaillon, Cordeau, Paporte, & Pasin, 2011; Bolduc, Renaud, Boctor, & Paporte, 2008; Cui & Lu, 2009). "
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    ABSTRACT: With the increasing complexity of problems in the construction industry, researchers are investigating computationally rigorous intelligent systems with the aim of seeking intelligent solutions. The purpose of this paper is therefore to analyse the research published on ‘intelligent systems in the construction industry’ over the past two decades. This is achieved to observe and understand the historical trends and current patterns in the use of different types of intelligent systems and to exhibit potential directions of further research. Thus, to trace the applications of intelligent systems to research in the construction industry, a profiling approach is employed to analyse 514 publications extracted from the Scopus database. The prime value and uniqueness of this paper lies in analysing and compiling the existing published material by examining variables (such as yearly publications, geographic location of each publication, etc.). This has been achieved by synthesising existing publications using 14 keywords2 ‘Intelligent Systems’, ‘Artificial Intelligence’, ‘Expert Systems’, ‘Fuzzy Systems’, ‘Genetic Algorithms’, ‘Knowledge-Based Systems’, ‘Neural Networks’, ‘Context Aware Applications’, ‘Embedded Systems’, ‘Human–Machine Interface’, ‘Sensing and Multiple Sensor Fusion’, ‘Ubiquitous and Physical Computing’, ‘Case-based Reasoning’ and ‘Construction Industry’. The prime contributions of this research are identified by associating (a) yearly publication and geographic location, (b) yearly publication and the type of intelligent systems employed/discussed, (c) geographic location and the type of research methods employed, and (d) geographic location and the types of intelligent systems employed. These contributions provide a comparison between the two decades and offer insights into the trends in using different intelligent systems types in the construction industry. The analysis presented in this paper has identified intelligent systems studies that have contributed to the development and accumulation of intellectual wealth to the intelligent systems area in the construction industry. This research has implications for researchers, journal editors, practitioners, universities and research institutions. Moreover, it is likely to form the basis and motivation for profiling other database resources and specific types of intelligent systems journals in this area.
    Full-text · Article · Mar 2014 · Expert Systems with Applications
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