Abstracts – Browse Results
Click on the titles below to expand the information about each abstract.
Viewing 18 results ...
Brosque, C, Skeie, G and Fischer, M (2021) Comparative Analysis of Manual and Robotic Concrete Drilling for Installation Hangers. Journal of Construction Engineering and Management, 147(03).
BuHamdan, S, Duncheva, T and Alwisy, A (2021) Developing a BIM and Simulation-Based Hazard Assessment and Visualization Framework for CLT Construction Design. Journal of Construction Engineering and Management, 147(03).
Cherkos, F D and Jha, K N (2021) Drivers of Road Sector Public-Private Partnership Adoption in New and Inexperienced Markets. Journal of Construction Engineering and Management, 147(03).
Dias Barkokebas, R and Li, X (2021) Use of Virtual Reality to Assess the Ergonomic Risk of Industrialized Construction Tasks. Journal of Construction Engineering and Management, 147(03).
El Sayed, A Y, Darwish, M and Nassar, K (2021) Design and Constructability of Novel Extendable Arched Steel Truss Falsework. Journal of Construction Engineering and Management, 147(03).
Hamledari, H, Sajedi, S, McCabe, B and Fischer, M (2021) Automation of Inspection Mission Planning Using 4D BIMs and in Support of Unmanned Aerial Vehicle–Based Data Collection. Journal of Construction Engineering and Management, 147(03).
Kar, S and Jha, K N (2021) Investigation into Lead Time of Construction Materials and Influencing Factors. Journal of Construction Engineering and Management, 147(03).
- Type: Journal Article
- Keywords: Lead time; Classification of materials; Regression; Cluster analysis; Construction;
- ISBN/ISSN: 0733-9364
- URL: https://doi.org/10.1061/(ASCE)CO.1943-7862.0001998
- 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.
Katsuragawa, C M, Lucko, G, Isaac, S and Su, Y (2021) Fuzzy Linear and Repetitive Scheduling for Construction Projects. Journal of Construction Engineering and Management, 147(03).
Kim, K and Cho, Y K (2021) Automatic Recognition of Workers’ Motions in Highway Construction by Using Motion Sensors and Long Short-Term Memory Networks. Journal of Construction Engineering and Management, 147(03).
Liu, Y, Jarvamardi, A, Zhang, Y, Liu, M, Hsiang, S M, Yang, S, Yu, X and Jiang, Z (2021) Comparative Study on Perception of Causes for Construction Task Delay in China and the United States. Journal of Construction Engineering and Management, 147(03).
Ma, G, Jia, J, Ding, J, Wu, M and Wang, D (2021) Examining the Impact of Social Media Use on Project Management Performance: Evidence from Construction Projects in China. Journal of Construction Engineering and Management, 147(03).
Mahdavian, A, Shojaei, A, Salem, M, Yuan, J S and Oloufa, A A (2021) Data-Driven Predictive Modeling of Highway Construction Cost Items. Journal of Construction Engineering and Management, 147(03).
O’Connor, J T, Shrestha, B K, Winkler, M and Ouk Choi, J (2021) Relationship between Commissioning and Start-Up Success Factors Achievement and Performance in Capital Projects. Journal of Construction Engineering and Management, 147(03).
Raymond, A J, Kendall, A, DeJong, J T, Kavazanjian, E, Woolley, M A and Martin, K K (2021) Life Cycle Sustainability Assessment of Fugitive Dust Control Methods. Journal of Construction Engineering and Management, 147(03).
Shirowzhan, S, Sepasgozar, S M E and Trinder, J (2021) Developing Metrics for Quantifying Buildings’ 3D Compactness and Visualizing Point Cloud Data on a Web-Based App and Dashboard. Journal of Construction Engineering and Management, 147(03).
Yoon, S, Weidner, T and Hastak, M (2021) Total-Package-Prioritization Mitigation Strategy for Deferred Maintenance of a Campus-Sized Institution. Journal of Construction Engineering and Management, 147(03).
Zhang, S, Jiang, P, Zhang, Z and Wang, C (2021) WebGIS-Based Collaborative Construction Quality Control of RCC Gravity Dam Using Sensing Devices. Journal of Construction Engineering and Management, 147(03).
Zuniga-Garcia, N, Machemehl, R B, Khwaja, N A, Pruner, K D and Fu, M (2021) Estimation of Road User Costs for Work Zones in Data-Limited or Time-Constrained Environments. Journal of Construction Engineering and Management, 147(03).