Abstracts – Browse Results
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Assad, A, Moselhi, O and Zayed, T (2021) Resilience-Driven Sustainability-Based Rehabilitation Planning for Water Distribution Networks. Journal of Construction Engineering and Management, 147(08).
Bademosi, F and Issa, R R A (2021) Factors Influencing Adoption and Integration of Construction Robotics and Automation Technology in the US. Journal of Construction Engineering and Management, 147(08).
Ballesteros-Pérez, P, Skitmore, M, Cerezo-Narváez, A, González-Cruz, M C, Pastor-Fernández, A and Otero-Mateo, M (2021) Standard Deviation of Bids for Construction Contract Auctions. Journal of Construction Engineering and Management, 147(08).
Clement, D, Aliabadi, A A, Mackey, J, Thé, J and Gharabaghi, B (2021) Dust Emissions Management Model for Construction Sites. Journal of Construction Engineering and Management, 147(08).
Duodu, B and Rowlinson, S (2021) Opening Up the Innovation Process in Construction Firms: External Knowledge Sources and Dual Innovation. Journal of Construction Engineering and Management, 147(08).
Dutta, A, Breloff, S P, Dai, F, Sinsel, E W, Warren, C M, Carey, R E and Wu, J Z (2021) Application of Data Fusion via Canonical Polyadic Decomposition in Risk Assessment of Musculoskeletal Disorders in Construction: Procedure and Stability Evaluation. Journal of Construction Engineering and Management, 147(08).
Eiris, R, Jain, E, Gheisari, M and Wehle, A (2021) Online Hazard Recognition Training: Comparative Case Study of Static Images, Cinemagraphs, and Videos. Journal of Construction Engineering and Management, 147(08).
Genc, O (2021) SymbioConstruction: A Bibliography-Driven Dynamic Construction Industry Symbiosis Database. Journal of Construction Engineering and Management, 147(08).
Han, Y, Li, Y, Rao, P and Taylor, J E (2021) Global Collaborative Network of Skyscraper Projects from 1990 to 2010: Temporal Evolution and Spatial Characteristics. Journal of Construction Engineering and Management, 147(08).
Hu, Y, Castro-Lacouture, D, Eastman, C M and Navathe, S B (2021) Component Change List Prediction for BIM-Based Clash Resolution from a Graph Perspective. Journal of Construction Engineering and Management, 147(08).
Huang, Y, Trinh, M T and Le, T (2021) Critical Factors Affecting Intention of Use of Augmented Hearing Protection Technology in Construction. Journal of Construction Engineering and Management, 147(08).
Kammouh, O, Nogal, M, Binnekamp, R and Wolfert, A R M ( (2021) Mitigation Controller: Adaptive Simulation Approach for Planning Control Measures in Large Construction Projects. Journal of Construction Engineering and Management, 147(08).
Kazar, G and Comu, S (2021) Effectiveness of Serious Games for Safety Training: A Mixed Method Study. Journal of Construction Engineering and Management, 147(08).
Liu, Y, Habibnezhad, M, Shayesteh, S, Jebelli, H and Lee, S (2021) Paving the Way for Future EEG Studies in Construction: Dependent Component Analysis for Automatic Ocular Artifact Removal from Brainwave Signals. Journal of Construction Engineering and Management, 147(08).
Naumets, S and Lu, M (2021) Investigation into Explainable Regression Trees for Construction Engineering Applications. Journal of Construction Engineering and Management, 147(08).
Ragab, M A and Marzouk, M (2021) BIM Adoption in Construction Contracts: Content Analysis Approach. Journal of Construction Engineering and Management, 147(08).
Sherman, R, Gibson, G E, Merrow, E and Parrish, K (2021) Examining the Impact of Rate-of-Return Regulation on Capital Project Planning. Journal of Construction Engineering and Management, 147(08).
Tetteh, M O, Chan, A P C, Darko, A, Torku, A and Nani, G (2021) Critical Barriers to International Construction Joint Ventures Success: Multiexpert Views and Contextual Disparities. Journal of Construction Engineering and Management, 147(08).
Wang, Y, Shao, Z and Tiong, R L K (2021) Data-Driven Prediction of Contract Failure of Public-Private Partnership Projects. Journal of Construction Engineering and Management, 147(08).
- Type: Journal Article
- Keywords: Public-private partnership (PPP); Contract failure; Failure factors; Machine learning; Decision-making process;
- ISBN/ISSN: 0733-9364
- URL: https://doi.org/10.1061/(ASCE)CO.1943-7862.0002124
- Abstract:
The public-private partnership (PPP) has been adopted by many governments in developing countries to provide better public services. However, PPP projects have a high risk of contract failure. To proactively predict PPP contract failure and obtain the most significant failure factors from a quantitative perspective, this research compared the performance of different combinations of machine learning models and data-balancing techniques. Forty-three project-specific and country-specific factors were examined, and the top 15 were chosen for the transportation, water and sewer, and energy sectors. The results show that the selected model can forecast contract failure with a recall of 75.9%, 73.3%, and 76.2%, respectively. This study showed the effectiveness and applicability of machine learning in predicting PPP contract failure. The results can facilitate decision making by forecasting the probability of PPP contract failure in the early planning stage.
Yevu, S K, Yu, A T W, Darko, A and Addy, M N (2021) Evaluation Model for Influences of Driving Forces for Electronic Procurement Systems Application in Ghanaian Construction Projects. Journal of Construction Engineering and Management, 147(08).
Zhang, J, Wang, T and Zhang, L (2021) Legal Risk Assessment Framework for International PPP Projects Based on Metanetwork. Journal of Construction Engineering and Management, 147(08).
Zhao, D, Simmons, D and Chen, Z (2021) Interconnectivity in Collaboration Networks Impact on Member Belongingness. Journal of Construction Engineering and Management, 147(08).