Abstract

Purpose – Although projects’ experts always take into consideration the related cost-risks. They are experiencing the challenge of not being able to finish the project within the estimated budget. Latest cost-risks studies concentrated on modelling and estimating risks at the preconstruction stage. This article aims to approach Monte-Carlo simulation using stochastic mathematical modelling to measure cost-risks error (i.e., adjusting cost-risks).
 Methodology – The approach of this research is solely quantitative. It is using statistical modelling and simulations to ensure the accuracy and precision of the developed Monte-Carlo model. However, this study is utilizing Microsoft Office Excel Software Mersenne twister algorithm to generate random numbers to ensure most accurate Monte-Carlo approach. The mathematical equations system is built into Excel.
 Findings – The research outputs are considered significant in project management body of knowledge. This is because of the resulted evidence that is proving the applicability to measure cost risks error using Monte-Carlo simulation. This study presented cost risks and differentiated between contractors’ and clients’ views. 
 Unique contribution to theory, practice and policy – The originality of this article comes from providing the first Monte-Carlo approach for measuring projects’ cost-risks error from client’s perspective. The theoretical-implications, practical-implications, and limitations are presented in the conclusion for future research.

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