Data-Driven Prediction of Contract Failure of Public-Private Partnership Projects-Reference-Cited by-同舟云学术

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Data-Driven Prediction of Contract Failure of Public-Private Partnership Projects

Published:2021-08 Issue:8 Volume:147 Page:04021089
ISSN:0733-9364
Container-title:Journal of Construction Engineering and Management
language:en
Short-container-title:J. Constr. Eng. Manage.

Author:

Wang Yongqi¹,Shao Zhe²,Tiong Robert L. K.³

Affiliation:

1. Ph.D. Student, School of Civil and Environmental Engineering, Nanyang Technological Univ., 639798, Singapore.

2. General Manager, Urban Dot Solution Pte Ltd., 1 lrving Place, #08-01, 369546, Singapore.

3. Associate Professor, School of Civil and Environmental Engineering, Nanyang Technological Univ., 639798, Singapore (corresponding author).

Publisher

American Society of Civil Engineers (ASCE)

Subject

Strategy and Management,Industrial relations,Building and Construction,Civil and Structural Engineering

Link

http://ascelibrary.org/doi/pdf/10.1061/%28ASCE%29CO.1943-7862.0002124

Reference61 articles.

1. Principal component analysis

2. The trust-control nexus in public private partnership (PPP) contracts

3. Performance Comparison of Support Vector Machine, Random Forest, and Extreme Learning Machine for Intrusion Detection

4. The effect of critical success factors on project success in Public-Private Partnership projects: A case study of highway projects in Iran

5. Dynamic sustainable success prediction model for infrastructure projects: a rough set based fuzzy inference system

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1. Are PPP projects poor fundability in China：Based on ensemble learning;Project Leadership and Society;2024-12

2. A Structural Equation Model on Critical Risk and Success in Public–Private Partnership: Exploratory Study;Journal of Risk and Financial Management;2024-08-13

3. Mitigating Financial Risks in Sustainable Public–Private Partnership Infrastructure Projects: A Quantitative Analysis;Systems;2024-07-02

4. Uncovering value creation factors for healthcare public-private partnership (PPP) projects;Engineering, Construction and Architectural Management;2024-05-30

5. Data analytics for project delivery: unlocking the potential of an emerging field;International Journal of Managing Projects in Business;2024-04-02

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