Business Failure Prediction of Construction Contractors Using a LSTM RNN with Accounting, Construction Market, and Macroeconomic Variables-Reference-Cited by-同舟云学术

Business Failure Prediction of Construction Contractors Using a LSTM RNN with Accounting, Construction Market, and Macroeconomic Variables

Published:2020-03 Issue:2 Volume:36 Page:04019039
ISSN:0742-597X
Container-title:Journal of Management in Engineering
language:en
Short-container-title:J. Manage. Eng.

Author:

Jang Youjin¹^ORCID,Jeong Inbae¹^ORCID,Cho Yong K.²^ORCID

Affiliation:

1. Postdoctoral Research Associate, School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA 30332-0355. ORCID: .

2. Associate Professor, School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA 30332-0355 (corresponding author). ORCID: .

Publisher

American Society of Civil Engineers (ASCE)

Subject

Management Science and Operations Research,Strategy and Management,General Engineering,Industrial relations

Link

http://ascelibrary.org/doi/pdf/10.1061/%28ASCE%29ME.1943-5479.0000733

Reference45 articles.

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4. Predicting the risk of contractor default in Saudi Arabia utilizing artificial neural network (ANN) and genetic algorithm (GA) techniques

5. Business failures in the construction industry

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