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Please use this identifier to cite or link to this item: http://dspace.bits-pilani.ac.in:8080/jspui/xmlui/handle/123456789/4066
Title: Risk enablers modelling for infrastructure projects using Bayesian belief network
Authors: Singh, Ajit Pratap
Sharma, Satyendra Kumar
Keywords: Civil Engineering
Infrastructure projects
Risk enabling factors
Bayesian belief network modelling
Issue Date: 25-Oct-2019
Publisher: Taylor & Francis
Abstract: Work in the area of risk assessment of infrastructure projects is full of different techniques; study on the risk management factors is non-existent. It is required because such risks of high impact paralyze the performance of infrastructure projects. Delay and cost overruns in infrastructure projects affect the society welfare at large. Because of this, the reputation of the government is at stake. This paper is an attempt to contribute to the risk enablers modelling, by first identifying major critical success factors for risk management and then finding cause-and-effect relationships between them for developing a Bayesian belief network (BBN) model. The analysis of this model and results determine relative importance of the critical success factors on which risk management efforts must be focused first to ensure that the project achieves objectives within the stipulated time and cost.
URI: https://www.tandfonline.com/doi/full/10.1080/15623599.2019.1678218
http://dspace.bits-pilani.ac.in:8080/xmlui/handle/123456789/4066
Appears in Collections:Department of Civil Engineering

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