@article{(Open Science Index):https://publications.waset.org/pdf/10007945,
	  title     = {Stochastic Risk Analysis Framework for Building Construction Projects},
	  author    = {Abdulkadir Abu Lawal},
	  country	= {},
	  institution	= {},
	  abstract     = {The study was carried out to establish the probability density function of some selected building construction projects of similar complexity delivered using Bill of Quantities (BQ) and Lump Sum (LS) forms of contract, and to draw a reliability scenario for each form of contract. 30 of such delivered projects are analyzed for each of the contract forms using Weibull Analysis, and their Weibull functions (α, and β) are determined based on their completion times. For the BQ form of contract delivered projects, α is calculated as 1.6737E20 and β as + 0.0115 and for the LS form, α is found to be 5.6556E03 and β is determined as + 0.4535. Using these values, respective probability density functions are calculated and plotted, as handy tool for risk analysis of future projects of similar characteristics. By input of variables from other projects, decision making processes can be made for a whole project or its components using EVM Analysis in project evaluation and review techniques. This framework, as a quantitative approach, depends on the assumption of normality in projects completion time, it can help greatly in determining the completion time probability for veritable projects using any of the contract forms under consideration. Projects aspects that are not amenable to measurement, on the other hand, can be analyzed using fuzzy sets and fuzzy logic. This scenario can be drawn for different types of building construction projects, and using different suitable forms of contract in projects delivery.
},
	    journal   = {International Journal of Civil and Environmental Engineering},
	  volume    = {10},
	  number    = {11},
	  year      = {2016},
	  pages     = {1478 - 1482},
	  ee        = {https://publications.waset.org/pdf/10007945},
	  url   	= {https://publications.waset.org/vol/119},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 119, 2016},
	}