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Construction materials contribute to 50-60% of the project cost, and thus material management becomes very important. Prioritization of procurement of materials is rarely linked with construction schedule of a project which creates problems, especially in a budget constraint situation. Thus, the purpose of this study is to integrate material management with construction schedule and to prioritize construction materials for procurement. To address this, total criticality (TC) of nine construction materials are determined by combining material criticality (MC) and activity criticality (AC). A total of seven criteria for determining MC has been identified and subsequently, based on the responses from two stage questionnaire surveys conducted among material management experts in leading construction companies in India, weights of the criteria are determined using ANP (analytic network process). The volatility in price of material is found to have the highest criteria weight (0.344) followed by percentage contribution (0.194), lead time (0.125), customers’ specificity (0.112), environmental implication (0.090), buyer’s dependence on suppliers (0.077), and flexibility (0.058). Considering the criteria weights and based on the inputs from project professionals, MC values of materials are calculated using TOPSIS (technique for order preference by similarity to an ideal solution). AC values are determined using float available in associated activities of the project. Among the nine building materials considered in this study, TC value of structural steel (0.866) is found to be the highest followed by reinforcement bar (0.671), cement (0.457), autoclave aerated concrete block (0.381), coarse aggregate (0.323), tiles (0.249), sand (0.238), plywood (0.198), and biding wire (0.070). This study will support construction professionals in material management decisions, ensuring timely availability of materials and ultimately reducing time and cost overrun in a construction project.

Assessing criticality of construction materials for prioritizing their procurement using ANP-TOPSIS