| description abstract | An appropriate material-management strategy requires estimation of, and classification based on, the lead time of construction materials. To estimate the lead time precisely, the identification of the factors that influence it is essential. Previous studies in material management have not comprehensively examined the factors that influence lead time and have not emphasized the need to classify materials accordingly. To address these gaps, this study collected a large sample of procurement data from 16 building construction projects. A two-step cluster analysis resulted in three clusters, namely, long lead (L), moderate lead (M), and short lead (S), referred to here as LMS based on the average lead time of the materials. Combining the LMS classification with the existing ABC classifications can facilitate more reliable control over the inventory of materials. Furthermore, the regression analysis of the procurement data revealed that the lead time of construction materials is positively correlated with the unit price and order value but negatively correlated with the project value. Therefore, the lead time increases with the increase in unit price and order value of materials while it decreases as project value increases. Furthermore, the capacity of a supplier was found to have a negative influence on the lead time of bulk materials. Therefore, bulk materials delivered by a supplier with higher capacity will have a shorter lead time than those delivered by a supplier with lower capacity. The findings of this study enable construction practitioners to precisely estimate the lead time of materials and to adopt the appropriate strategies for managing construction materials, thereby enhancing the availability of materials for the project. | |
