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Ballesteros-Pérez, P, Phua, F T T and Mora-Melià, D (2019) Human Resource Allocation to Multiple Projects Based on Members’ Expertise, Group Heterogeneity, and Social Cohesion. Journal of Construction Engineering and Management, 145(02).
Beltrão, L M P and Carvalho, M T M (2019) Prioritizing Construction Risks Using Fuzzy AHP in Brazilian Public Enterprises. Journal of Construction Engineering and Management, 145(02).
Carmichael, D G, Nguyen, T A and Shen, X (2019) Single Treatment of PPP Road Project Options. Journal of Construction Engineering and Management, 145(02).
Elmasry, M, Zayed, T and Hawari, A (2019) Multi-Objective Optimization Model for Inspection Scheduling of Sewer Pipelines. Journal of Construction Engineering and Management, 145(02).
Gurmu, A T (2019) Tools for Measuring Construction Materials Management Practices and Predicting Labor Productivity in Multistory Building Projects. Journal of Construction Engineering and Management, 145(02).
- Type: Journal Article
- Keywords: Labor productivity; Building construction projects; Materials management practices; Regression models;
- ISBN/ISSN: 0733-9364
- URL: https://doi.org/10.1061/(ASCE)CO.1943-7862.0001611
- Abstract:
Planning, monitoring, and evaluating materials management practices are important for enhancing construction productivity. This study is designed to develop a tool for scoring materials management practices for building projects and, on that basis, build a tool for predicting productivity. The research was carried out in two phases. During Phase I, in-depth interviews were conducted with 19 experts and context-specific materials management practices were identified. During Phase II, questionnaires were used to collect quantitative data from 39 contractors. To prioritize the practices that were identified during Phase I, the quantitative data were analyzed. Based on the analysis, tools for measuring and planning the materials management practices and probability-based regression models were developed. Procurement plans for materials, long-lead materials identification, and materials delivery schedule are the three most significant practices. Contractors can use the scoring tool to measure the levels of implementation of the practices and assess the risk of having low productivity using the predictive models. This research contributes to the body of knowledge by developing construction materials management practices measuring, planning, monitoring, and evaluating tools in the context of building projects. In addition, the logistic and linear regression models can be used to assess whether a certain level of implementation of the construction materials management practice might be associated with higher or lower labor productivity.
Hwang, B, Zhao, X and Yang, K W (2019) Effect of BIM on Rework in Construction Projects in Singapore: Status Quo, Magnitude, Impact, and Strategies. Journal of Construction Engineering and Management, 145(02).
Islam, M S, Nepal, M P and Skitmore, M (2019) Modified Fuzzy Group Decision-Making Approach to Cost Overrun Risk Assessment of Power Plant Projects. Journal of Construction Engineering and Management, 145(02).
Jafari, A, Valentin, V and Bogus, S M (2019) Identification of Social Sustainability Criteria in Building Energy Retrofit Projects. Journal of Construction Engineering and Management, 145(02).
Koskela, L, Ferrantelli, A, Niiranen, J, Pikas, E and Dave, B (2019) Epistemological explanation of lean construction. Journal of Construction Engineering and Management, 145(02), 04018131 .
Liang, R, Zhang, J, Wu, C, Sheng, Z and Wang, X (2019) Joint-Venture Contractor Selection Using Competitive and Collaborative Criteria with Uncertainty. Journal of Construction Engineering and Management, 145(02).
Noktehdan, M, Shahbazpour, M, Zare, M R and Wilkinson, S (2019) Innovation Management and Construction Phases in Infrastructure Projects. Journal of Construction Engineering and Management, 145(02).
Poleacovschi, C, Javernick-Will, A, Tong, T and Wanberg, J (2019) Engineers Seeking Knowledge: Effect of Control Systems on Accessibility of Tacit and Codified Knowledge. Journal of Construction Engineering and Management, 145(02).
Sakhakarmi, S, Park, J and Cho, C (2019) Enhanced Machine Learning Classification Accuracy for Scaffolding Safety Using Increased Features. Journal of Construction Engineering and Management, 145(02).
Tokdemir, O B, Erol, H and Dikmen, I (2019) Delay Risk Assessment of Repetitive Construction Projects Using Line-of-Balance Scheduling and Monte Carlo Simulation. Journal of Construction Engineering and Management, 145(02).
Trinh, M T, Feng, Y and Mohamed, S (2019) Framework for Measuring Resilient Safety Culture in Vietnam’s Construction Environment. Journal of Construction Engineering and Management, 145(02).
Valente, C P, Brandalise, F M P and Formoso, C T (2019) Model for Devising Visual Management Systems on Construction Sites. Journal of Construction Engineering and Management, 145(02).
Xu, J, Shi, Y and Zhao, S (2019) Reverse Logistics Network-Based Multiperiod Optimization for Construction and Demolition Waste Disposal. Journal of Construction Engineering and Management, 145(02).
Yao, H, Chen, Y, Chen, Y and Zhu, X (2019) Mediating Role of Risk Perception of Trust and Contract Enforcement in the Construction Industry. Journal of Construction Engineering and Management, 145(02).
Yoo, W, Ozer, H and Ham, Y (2019) System-Level Approach for Identifying Main Uncertainty Sources in Pavement Construction Life-Cycle Assessment for Quantifying Environmental Impacts. Journal of Construction Engineering and Management, 145(02).