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Bridging theory and prediction : a hybrid SEM and machine learning approach to optimize lean construction for megaproject sustainability in China

Title: Bridging theory and prediction : a hybrid SEM and machine learning approach to optimize lean construction for megaproject sustainability in China
Authors: Ibrahim, A; Zayed, T; Lafhaj, Z; Maged, A; Kineber, AF; Yang, J
Contributors: Department of Building and Real Estate
Publisher Information: John Wiley & Sons Ltd.
Publication Year: 2026
Collection: Hong Kong Polytechnic University: PolyU Institutional Repository (PolyU IR)
Subject Terms: China; Gradient boosting; Lean construction practices; Machine learning; Megaprojects; PLS- SEM; SHAP; Sustainability
Description: 202601 bcch ; Version of Record ; Others ; The author would like to sincerely thank the Hong Kong Polytechnic University (PolyU) for funding this study. PolyU financing has advanced research and facilitated the advancements that underpin this review. ; Early release ; Wiley (2026) ; TA
Document Type: article in journal/newspaper
Language: English
Relation: https://hdl.handle.net/10397/117030; a4284, OA_TA; 52540
DOI: 10.1002/csr.70424
Availability: https://hdl.handle.net/10397/117030; https://doi.org/10.1002/csr.70424
Rights: This is an open access article under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits use, distribution and reproduction in any medium, provided the original work is properly cited. ; © 2026 The Author(s). Corporate Social Responsibility and Environmental Management published by ERP Environment and John Wiley & Sons Ltd. ; The following publication Ibrahim, A., Zayed, T., Lafhaj, Z., Maged, A., Kineber, A.F. and Yang, J. (2026), Bridging Theory and Prediction: A Hybrid SEM and Machine Learning Approach to Optimize Lean Construction for Megaproject Sustainability in China. Corp Soc Responsib Environ Manag is available at https://doi.org/10.1002/csr.70424.
Accession Number: edsbas.3FDAAEAE
Database: BASE