A hybrid risk prioritization approach in construction projects using failure mode and effective analysis

Karamoozian, Amirhossein; Wu, Desheng Dash

doi:10.1108/ecam-10-2019-0535

Cited by 26 publications

(8 citation statements)

References 76 publications

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“…To determine the influence relationships in the driver system, the direct relation matrix X was first constructed and obtained through expert scoring. Given that previous literature using this approach invited between 10 and 25 experts to complete the process (Rostamnezhad et al, 2020;Karamoozian and Wu, 2020;, 32 construction industry experts in China were invited to attend this scoring process, and finally, 27 experts agreed (see Table 2); hence, the response rate is 84.38%. Most of these experts (n 5 21) were contractors.…”

Section: Determining Internal Influence Relationships Of the Drivers ...mentioning

confidence: 99%

Multidimensional drivers: exploring contractor rule violations in the construction industry

Liu

Wang

2022

ECAM

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PurposeThis research aims to build a three-tiered driver system that entices contractor rule violations and explores the importance and the relationships among these drivers, hence providing theoretical support for the contractor rule violations governance.Design/methodology/approachA literature review based on fraud diamond theory identified drivers from Pressure, Opportunity, Rationalization and Capability that drive contractor rule violations. In the Chinese context, through feedback, discussion and analysis of semistructured interviews with ten experts, an improved three-tiered driver system was drafted. Based on this system, a survey was conducted and scored with experts to provide the data for this research. The decision-making trial and evaluation laboratory (DEMATEL) method was used to determine relationships and influences between factors, and the DEMATEL-based analytic network process method was used to weigh these factors.FindingsThis paper systematically studied the drivers of contractor rule violations, specifically, the results showed that pressure had an important driving effect across the driver system, and those five factors – poor cultural atmosphere, weak internal control, prior experience, moral disengagement and information asymmetry – had the most influence on contractor rule violations. The results also indicated the strong effect pressure has on enticing rule violations and revealed that culture atmosphere and internal company governance played crucial roles in the occurrence of rule violations.Practical implicationsThis study provided construction practitioners with a robust tool to analyze the drivers of contractor rule violations. The rule violation drivers in the construction practice scenes identified in this study can provide more direct and effective violation-related guidance for contractors, regulators and the industry.Originality/valueBased on the new perspective of fraud diamond, this paper systematically bulit a three-tiered driver system combining theory with practice. This study contributed to understand the driver mechanism of contractor rule violations especially the importance of internal factors of contractors, which provided theory reference for compliance governance of construction industry.

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Section: Determining Internal Influence Relationships Of the Drivers ...mentioning

confidence: 99%

Multidimensional drivers: exploring contractor rule violations in the construction industry

Liu

Wang

2022

ECAM

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“…Herein, the fuzzy theory is applied with the DEMATEL method to include uncertainty of judgments in risk assessment. The procedure of fuzzy DEMATEL -trapezoidal calculations is as follows 66,67 :…”

Section: Fuzzy Dematel Calculationsmentioning

confidence: 99%

Risk assessment of renewable energy projects using uncertain information

Karamoozian

Lambert

et al. 2022

Intl J of Energy Research

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Summary The majority of countries attempting to switch from conventional energy sources to renewable energy sources have decided to make significant investments in these projects. Considering renewable energy is an industry with a high level of investment expenses, assessing investment risks is critical to making efficient investment strategies. Howbeit, since risk assessment is dependent on expert opinions, uncertainty in the judgment of the consultants should be avoided. In this study, a novel hybrid failure mode and effect analysis approach is proposed to assess the investment risks of renewable energy projects. Results indicated that wind energy is the most appropriate alternative considering technical, marketability, environmental, economic, social aspects. Moreover, the sensitivity analysis is carried out and the robustness and validity of results from the proposed approach are examined. Finally, six different scenarios are considered and the results are interpreted accordingly. The findings of this study will be valuable to authorities, investors, and enterprises involved in the renewable energy projects and evaluating their investment.

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“…Furthermore, Song et al [23] developed an extended TOPSIS method to analyze risk factors of direct delivery business from oil refineries, while Faghih-Roohi et al [24] used an intuitionistic fuzzy hybrid TOPSIS approach to select shipping lanes for pharmaceutical products. Recently, Zhong et al [25] employed TOPSIS, along with alpha cut levels, for ranking TRIZ-based strategies priorities of renewable energy investments based on a house of quality technique, while Karamoozian and Wu [26] used a joint failure mode and effects analysis (FMEA) to consider risks and, then, applied a Fuzzy Decision-Making Trial and Evaluation Laboratory (FDEMATEL) method to consider interdependencies among the failure modes found by the fuzzy FMEA. In addition, Zhang et al [27] proposed a slack-oriented robustness measuring method consisted of optimization and a decision-making part and used Monte Carlo Simulation to check the effectiveness of their approach, and Koc and Gurgun [28] used the TOPSIS method to assess the impact of ambiguity factors on construction conflicts.…”

Section: Literature Reviewmentioning

confidence: 99%

A TOPSIS—Risk Matrix and Monte Carlo Expert System for Risk Assessment in Engineering Projects

et al. 2021

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In this paper, we propose a process that combines the Risk Matrix approach with the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and the Monte Carlo Simulation for assessing risk factors that have an impact on the duration of a construction project’s activities and predict if it is feasible to terminate the project within the prescribed deadlines. Initially, we identified the risks affecting each task of the specific project, and then, we applied the risk matrix approach for determining the probability and impact of every risk to each activity. The resulting ranking is used to assign uncertainty to activities’ durations and estimate the probability of on-time project completion, employing the Monte Carlo Simulation approach. The main contribution of this paper is the development of an innovative framework that coordinates an established qualitative and quantitative risk classification approach, with a popular multicriteria method and a powerful simulation approach, to effectively predict time deviations while executing complex construction projects under uncertainty. The proposed framework was applied to estimate the possibility of a timely execution of an artificial lake real project on the island of Alonissos, Greece. The analysis results illustrate that this approach clearly could help the project risk manager proactively perform risk mitigation measures while allocating budget and programming a project with a significant impact on the quality of life of residents and tourists of a small island.

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A hybrid risk prioritization approach in construction projects using failure mode and effective analysis

Cited by 26 publications

References 76 publications

Multidimensional drivers: exploring contractor rule violations in the construction industry

Multidimensional drivers: exploring contractor rule violations in the construction industry

Risk assessment of renewable energy projects using uncertain information

A TOPSIS—Risk Matrix and Monte Carlo Expert System for Risk Assessment in Engineering Projects

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