Paper Details

In this paper, to predict cost overturns percentage two models were presented in construction industry. In firstmodel 44 factors (based on regression model) were collected from literature which influences construction industry costperformance. ‘Contractors’ developed a questionnaire survey to know the relative impact of these causes on constructionindustry projects. Eleven factors were obtained as the most significant causes that lead to cost overrun. For previousfacto, occurrence data was gathered for 30 constructions projects which were divided in two sets. 20 projects composedthe first set of building model. The results showed strong direct relationship between percentage of cost overrun and theprevious 11 causes which highly influenced the cost overrun. These causes are: owner financial condition, contractorcash flow, procurement methods, increase in material cost due to inflation, tender stage competition, currencyfluctuations, size of project (small or large), design and approval delays, for quantity variations risk retained by client,detailed drawings, and material estimating inaccuracy. Remaining 10 projects composed as second set, based on casebased reasoning (CBR), and used for validation purposes. CBR is an effective method to solve new problems/issues withexperience obtained from past experience of similar project in construction industry. After validation of both modelsusing projects of 2nd set it was concluded that CBR model has less prediction capability as compared to regressionmodel. As attribute weight method gives the highest prediction accuracy of cost overrun percentage after applyingabsolute value of standardized coefficient (β)

Muhammad Waqar khan, Yaseen Mahmood, Muhammad Issa Khan, Sharifullah Khan, “To Study Cost overturn prediction in Construction industry A Review”, International Journal of Advance Engineering and Research Development (IJAERD), Vol. 7, Issue 5, pp. 41-46, May 2020.