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Methodology for Project Risk Assessment of Building Construction Projects Using Bayesian Belief Networks

机译:贝叶斯信念网络的建筑工程项目风险评估方法

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The study aims to establish a risk assessment methodology to improve the performance of building construction projects especially in developing countries. A survey of randomly selected samples to evaluate risk factors experienced by construction practitioners was conducted based on the likelihood of occurrence and impacts on projects. A response rate of 53% comprising 305 contractors and subcontractors and 38 clients was received. Risk Acceptability Matrix (RAM) was used to rank/prioritise risk factors in order to determine critical risks that could affect building construction projects especially in developing countries. Bayesian Belief Network was then constructed by structural learning and used to appreciate the relationship amongst the risk factors. Results showed that critical risks affecting building construction projects were mainly improper construction methods, poor communication between involved parties, supplies of defective materials, delayed payment in contracts, fluctuation of materials prizes and unsuitable leadership style.
机译:该研究旨在建立一种风险评估方法,以改善建筑工程项目的绩效,尤其是在发展中国家。根据发生的可能性及其对项目的影响,对随机抽取的样本进行了调查,以评估建筑从业人员所经历的风险因素。收到305个承包商和分包商以及38个客户的回复率为53%。风险接受度矩阵(RAM)用于对风险因素进行排名/优先排序,以确定可能影响建筑施工项目的关键风险,尤其是在发展中国家。然后通过结构学习构建贝叶斯信念网络,并用于了解风险因素之间的关系。结果表明,影响建筑工程项目的重大风险主要是施工方法不当,当事方之间沟通不畅,有缺陷的材料供应,合同的延期支付,材料奖品的波动以及领导风格的不合适。

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