Predicting Project Performance in the Construction Industry-Reference-Cited by-同舟云学术

Predicting Project Performance in the Construction Industry

Published:2020-05 Issue:5 Volume:146 Page:04020030
ISSN:0733-9364
Container-title:Journal of Construction Engineering and Management
language:en
Short-container-title:J. Constr. Eng. Manage.

Author:

Assaad Rayan¹,El-Adaway Islam H.²^ORCID,Abotaleb Ibrahim S.³

Affiliation:

1. Ph.D. Graduate Student, Dept. of Civil, Architectural, and Environmental Engineering, Missouri Univ. of Science and Technology, 218 Butler-Carlton Hall, 1401 N. Pine St., Rolla, MO 65409.

2. Hurst-McCarthy Professor of Construction Engineering and Management, Professor of Civil Engineering, and Founding Director of Missouri Consortium for Construction Innovation, Dept. of Civil, Architectural, and Environmental Engineering/Dept. of Engineering Management and Systems Engineering, Missouri Univ. of Science and Technology, 228 Butler-Carlton Hall, 1401 N. Pine St., Rolla, MO 65409 (corresponding author). ORCID: .

3. Postdoctoral Research Fellow, Dept. of Civil, Architectural, and Environmental Engineering, Missouri Univ. of Science and Technology, 211 Butler-Carlton Hall, 1401 N. Pine St., Rolla, MO 65409.

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.1943-7862.0001797

Reference111 articles.

1. Managing Construction Projects through Dynamic Modeling: Reviewing the Existing Body of Knowledge and Deriving Future Research Directions

2. Risk impact assessments in project budget development: architects’ perspectives

3. Agarwal R. S. Chandrasekaran and M. Sridhar. 2016. “Imagining construction’s digital future.” Accessed July 14 2019. https://www.mckinsey.com/industries/capital-projects-and-infrastructure/our-insights/imagining-constructions-digital-future.

4. Analysis of factors influencing project cost estimating practice

5. Andersson J. and M. Burberg. 2015. “Testing for normality of censored data.” Accessed October 10 2018. https://www.diva-portal.org/smash/get/diva2:816450/FULLTEXT01.pdf.

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