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Abdul Nabi, M and El-adaway, I H (2021) Risk-Based Approach to Predict the Cost Performance of Modularization in Construction Projects. Journal of Construction Engineering and Management, 147(10).
- Type: Journal Article
- Keywords: Modularization; Proactive risk management; Decision-support tool; Modular risks;
- ISBN/ISSN: 0733-9364
- URL: https://doi.org/10.1061/(ASCE)CO.1943-7862.0002159
- Abstract:
The lack of proper management of the unique modular risks hinders the construction industry from maximizing the potential benefits associated with the use of modularization. Capturing the full cost benefits of modularized processes requires careful consideration of different aspects related to material, design, technology, logistics, installation, and so forth. Although many previous research efforts provided models to assess the feasibility of modularization in construction projects, no previous study developed a risk-based approach to assess the impact of adopting modular approaches on the cost performance of construction projects. This paper fills this knowledge gap. The authors followed an interrelated multistep research methodology. First, 50 modular risks were identified based on an extensive analysis of the literature conducted in a previous research study. Second, an industry survey was conducted in which 48 construction professionals—with an average of 24.25 years experience in construction operations and 13.6 years experience in modular construction—examined and assessed the impact of modular risks on cost performance. Third, integrated statistical and mathematical techniques—including distribution fitting—were utilized to develop a predictive model that (1) maps the 50 modular risks under investigation to cost performance data collected from 56 modular construction projects, and, consequently, (2) computes the associated cost saving and/or growth. The proposed model was verified using extreme condition tests, surprise behavior test, and sensitivity analysis, and was validated by industry experts. The authors provide guidelines for using the proposed model by industry practitioners. The developed model allows for maximized use of available project information to enable a reliable a priori cost assessment for the modularization processes throughout the different project phases. This is particularly important in the case of varying conditions over the project lifecycle. The developed model helps project stakeholders identify cost enablers and barriers that are interrelated with modularization processes. Accordingly, corrective actions and mitigation plans can be established. This research provides improved practices for decision-making, risk management, and project team alignment to maximize the cost benefits of modularization in construction projects.
Ahmed, M O, Khalef, R, Ali, G G and El-adaway, I H (2021) Evaluating Deterioration of Tunnels Using Computational Machine Learning Algorithms. Journal of Construction Engineering and Management, 147(10).
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Cruz Rios, F, Grau, D and Bilec, M (2021) Barriers and Enablers to Circular Building Design in the US: An Empirical Study. Journal of Construction Engineering and Management, 147(10).
Gharouni Jafari, K and Noorzai, E (2021) Selecting the Most Appropriate Project Manager to Improve the Performance of the Occupational Groups in Road Construction Projects in Warm Regions. Journal of Construction Engineering and Management, 147(10).
Grau, D, Cruz Rios, F and Sherman, R (2021) Project Validation: A Set-Based and Concurrent Design Approach to Inform Owner’s Authorization Decision on Complex Projects. Journal of Construction Engineering and Management, 147(10).
Haronian, E and Sacks, R (2021) Production Control in Earthworks: Concepts and Metrics. Journal of Construction Engineering and Management, 147(10).
He, W, Li, W, Xu, S, Wang, W and An, X (2021) Time, Cost, and Energy Consumption Analysis on Construction Optimization in High-Rise Buildings. Journal of Construction Engineering and Management, 147(10).
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Jang, Y, Kim, K, Leite, F, Ayer, S and Cho, Y K (2021) Identifying the Perception Differences of Emerging Construction-Related Technologies between Industry and Academia to Enable High Levels of Collaboration. Journal of Construction Engineering and Management, 147(10).
Kim, J, Kamari, M, Lee, S and Ham, Y (2021) Large-Scale Visual Data–Driven Probabilistic Risk Assessment of Utility Poles Regarding the Vulnerability of Power Distribution Infrastructure Systems. Journal of Construction Engineering and Management, 147(10).
Kim, J, Shan, Y, Kim, S, Song, D, Park, H and Bang, C (2021) Factors Influencing Fire Safety on Building Construction Sites: A Fire Officer’s Perspective. Journal of Construction Engineering and Management, 147(10).
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Le, C, Jeong, H D and Damnjanovic, I (2021) Network Theory–Driven Construction Logic Knowledge Network: Process Modeling and Application in Highway Projects. Journal of Construction Engineering and Management, 147(10).
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Liang, C, Wang, X, Kamat, V R and Menassa, C C (2021) Human–Robot Collaboration in Construction: Classification and Research Trends. Journal of Construction Engineering and Management, 147(10).
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Wu, K and García de Soto, B (2021) Lifting Sequence Optimization of Luffing Tower Cranes Considering Motion Paths with Dynamic Programming. Journal of Construction Engineering and Management, 147(10).
Xiang, Z, Rashidi, A and Ou, G (2021) Automated Framework to Translate Rebar Spatial Information from GPR into BIM. Journal of Construction Engineering and Management, 147(10).
Yoon, Y and GangaRao, H (2021) Prioritization Framework for Rockfall Countermeasures for Rock-Cut Slopes for Rural Roads. Journal of Construction Engineering and Management, 147(10).
Zhao, D, Duva, M, Mollaoglu, S, Frank, K, Garcia, A and Tait, J (2021) Integrative Collaboration in Fragmented Project Organizations: Network Perspective. Journal of Construction Engineering and Management, 147(10).