Modeling the Construction Risk Ratings to Estimate the Contingency in Highway Projects

Diab, Mohamed; Varma, Amiy; Panthi, Kamalesh

doi:10.1061/(asce)co.1943-7862.0001334

Cited by 42 publications

(24 citation statements)

References 16 publications

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“…Contingencies can be set at various phases of the project development process. Contractors set time and cost contingencies during bidding processes (Smith, Bohn 1999;Laryea, Hughes 2011;Eldosouky et al 2014;Asgari et al 2016) and manage them during the construction phase (Ford 2002;Diab et al 2017). Some contributions propose or discuss methods to determine the initial size of contingencies (Yeo 1990;Seung, Hyung 2004;Barraza 2010;Idrus et al 2011;Bhargava et al 2017).…”

Section: Literature Reviewmentioning

confidence: 99%

“…Some efforts focus on methodologies to size contingencies that could improve the current practice. Ford (2002) and Diab et al (2017) are the only studies identified in the literature describing, though only partly, how contractors actually manage threats-related cost contingencies during the construction phase. However, Ford (2002) and Diab et al (2017) focused only on sizing cost contingency; hence, other aspects of the actual practices of contractors on time and cost contingency management during the construction phase remain undiscussed.…”

Section: Introductionmentioning

confidence: 99%

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Management of Time and Cost Contingencies in Construction Projects: A Contractor Perspective

Ortiz

Pellicer

Molenaar

2018

Journal of Civil Engineering and Management

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The management of threats and opportunities plays a key-role in enhancing project performance. However, there is a gap in literature concerning how general contractors manage threats and opportunities in construction projects, in particular in the use of time and cost contingencies. This research partially addresses this gap through a case study of two large Spanish construction companies. The research presented two key factors determining how the contractors analyzed manage time and cost contingencies: project objectives and existing mistrust among the contractor’s team members. The research also found that managers use time and cost contingencies not only to manage threats, but also as tools for managing opportunities, thereby providing insight into a previously undescribed form of contingency: the negative contingency. The research results enable a better understanding of the actual behavior of general contractors, which contributes to paving the way for developing enhanced methods for contingencies management.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Management of Time and Cost Contingencies in Construction Projects: A Contractor Perspective

Ortiz

Pellicer

Molenaar

2018

Journal of Civil Engineering and Management

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“…Therefore, many risk practitioners were driven by the severe nature of the construction business to develop risk-based decision support tools to facilitate the bid-no-bid and bid markups decision making process. To this end, Diab et al (2017) conducted a study for modeling the construction risk ratings to estimate the contingency in highway projects. On the other hand, Yildiz et al (2014) developed a knowledge-based tool to map international construction risk while estimating the construction cost.…”

Section: Competitiveness In the Industrymentioning

confidence: 99%

“…The construction industry is a very risky endeavor (Taroun, 2014). It can be claimed that there is a consensus among construction experts regarding the high risk associated with the construction industry (Hastak and Shaked, 2000;Nieto-Morote and Ruz-Vila, 2011;Zavadskas et al, 2010;Diab et al, 2017). While conducting business in the construction industry, experience represents an essential asset for success.…”

Section: Introductionmentioning

confidence: 99%

A critical success factors model for effective implementation of risk management process in the construction projects

Qammaz

AlMaian

2020

JER is an international, peer-reviewed journal that publishes f

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Construction experts are aware of the risk associated with the construction industry. The uniqueness of the delivered projects represents one of the main challenges while conducting business in this industry. Therefore, to succeed, construction organizations need to optimize the utilization of their resources and minimize the associated risks. Managing the anticipated risks may be implemented intuitively or systematically based on the construction organizations' experience and awareness of the risks. Regardless of the existence of the diverse approaches towards dealing with the expected risks, there is consensus on the need to eliminate its negative consequences to achieve project success. Moreover, it can be argued that, to maximize the likelihood of achieving the promised rewards from applying the risk management process, several factors must occur. These factors are recognized as the Critical Success Factors (CSFs) for effective implementation of risk management process in the construction projects. It is believed that, without creating the adequate environment for the risk management process, its effectiveness would be minimized, if not eliminated. Although the literature is rich with studies that are dedicated to study risk and its management in the construction industry, there is a shortage in the researches that focus on the CFSs of the risk management in the construction industry, particularly during the construction phase. Therefore, the aim of this study is to review several available studies in the literature that have discussed the CSFs for successful management processes and then to develop a CSFs model that is specifically designed for risk management success. The model is designed to deliver a framework that depicts the role of the considered factors in achieving the promised rewards from systematic implementation of risk management process in the construction industry.

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“…SRA models have been used extensively in different areas of construction management. For instance, assessing the critical factors affecting cost performance of public construction projects (Sinesilassie et al, 2017); modelling the construction risk ratings and estimating contingencies in highway projects (Diab et al, 2017); identifying the success factors for public, private partnership projects (Yun et al, 2015); evaluating project risks (Ebrat & Ghodsi, 2014); evaluating the risk factors leading to cost overrun in highway construction projects (Creedy et al, 2010); analysing the risk perception of buildoperate-transfer road project participants (Thomas et al, 2003); developing models to forecast the actual construction cost and time (Skitmore & Ng, 2003); and designing a multivariate analysis technique to rank project success factors (Chan et al, 2001).…”

Section: Introductionmentioning

confidence: 99%

Predicting the impact of size of uncertainty events on the construction cost of highway projects using ANFIS

Moghayedi¹,

Windapo²

2019

Proceedings of the 2019 European Conference on Computing in Construction

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This study examines the use of Adaptive Neuro-Fuzzy Inference System (ANFIS) as a machine learning technique in the prediction of the impact size of uncertainty events on construction cost of highway projects and whether this technique is more accurate than the classical statistical methods. The rationale for the study stems from the availability of several techniques such as regression analysis and machine learning for developing predictive models of relationships of various variables in the construction industry. However, there has been limited research undertaken to compare the accuracy of the available techniques. The success or failure of prediction depends on the credibility of the prediction method. In this study, the predicted impact size of 76 uncertain events on the construction of highway projects using ANFIS as an intelligence machine learning method and Stepwise Regression Analysis (SRA) as a classical statistical method were compared to delineate the ability and accuracy of the ANFIS prediction technique. The comparison of calculated R-Value and two error tests for ANFIS and SRA show that the constructed ANFIS model has a higher performance than the SRA method in both fitness and reliability of the prediction model. Also, the performance comparison showed that ANFIS is a good tool for predicting the impact of uncertainty events on construction project cost. Based on these findings, the study concludes that the use of intelligent methods such as ANFIS will minimise the potential inconsistency of correlations in construction cost and time prediction. The model developed enables cost engineers to estimate the construction cost with a higher degree of accuracy.

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Modeling the Construction Risk Ratings to Estimate the Contingency in Highway Projects

Cited by 42 publications

References 16 publications

Management of Time and Cost Contingencies in Construction Projects: A Contractor Perspective

Management of Time and Cost Contingencies in Construction Projects: A Contractor Perspective

A critical success factors model for effective implementation of risk management process in the construction projects

Predicting the impact of size of uncertainty events on the construction cost of highway projects using ANFIS

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