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The rate of construction materials is subjected to constant changes. The unexpected price changes affect the carrying-out rates of projects and even challenges the competence to finish the projects. The rapid and vast changes that occur all over the world in construction materials prices impacts the individual construction market value of each country. To avoid this problem, the contractor should have a tool or method that is capable to predict the future material prices. It is essential to predict the material prices variations during the implementation of the project as well as for preparing the tenders. Prediction of material price is an important function for effectively handling projects in terms of more exactly estimating, pursuing and monitoring projects. There are many tools that can help the construction contractors by its ability to accurately predict the future material price. Some of the methods normally used for prediction of materials prices are Artificial Neural Network, Fuzzy Logic, Statistical Method (includes regression analysis, MONTE CARLO method, ANOVA), and Trend Analysis. The type of predictors to these tools can be any factors that tend to have an impact on the prices of material. Macroeconomic indicators are one such factor that influences the prices of material as it reflects a country’s economic status. This is a pilot study conducted in India to determine the possible macroeconomic indicators that influence the building material prices namely Portland cement and steel. Keywords-Cost estimation, Artificial Neural Network, Macroeconomic indicator
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