Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/115114
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dc.contributorDepartment of Building and Real Estateen_US
dc.creatorIbrahim, Aen_US
dc.creatorZayed, Ten_US
dc.creatorLafhaj, Zen_US
dc.date.accessioned2025-09-09T07:41:01Z-
dc.date.available2025-09-09T07:41:01Z-
dc.identifier.issn1387-585Xen_US
dc.identifier.urihttp://hdl.handle.net/10397/115114-
dc.language.isoenen_US
dc.publisherSpringer Dordrechten_US
dc.rights© The Author(s) 2025en_US
dc.rightsOpen Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.en_US
dc.rightsThe following publication Ibrahim, A., Zayed, T. & Lafhaj, Z. Bridging barriers to lean construction adoption in megaprojects: a data-driven contribution to sustainable development using SEM. Environ Dev Sustain (2025) is available at https://doi.org/10.1007/s10668-025-06424-9.en_US
dc.subjectAdoption Barriersen_US
dc.subjectCritical Success Factorsen_US
dc.subjectLean Constructionen_US
dc.subjectMegaprojectsen_US
dc.subjectStructural Equation Modellingen_US
dc.subjectSustainable Developmenten_US
dc.titleBridging barriers to lean construction adoption in megaprojects : a data-driven contribution to sustainable development using SEMen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.doi10.1007/s10668-025-06424-9en_US
dcterms.abstractMegaprojects frequently face cost overruns, delays, and inefficiencies due to their complexity and multi-stakeholder dynamics. As large-scale infrastructure projects with significant economic and social impacts, they demand innovative solutions to enhance performance and sustainability. Lean Construction (LC) offers a promising approach to achieving these goals, yet its adoption remains limited by various barriers. While prior studies have identified Critical Success Factors (CSFs), there is a lack of robust statistical validation on how these factors mitigate LC adoption challenges. To address this gap, this study employs a sequential mixed-methods approach integrating a systematic literature review to identify preliminary factors, followed by semi-structured interviews with industry experts to refine and validate these factors. A structured questionnaire was then administered to 379 construction professionals involved in megaprojects in China to gather quantitative data. Finally, Partial Least Squares Structural Equation Modeling (PLS-SEM) was used to examine the causal relationships between CSFs and LC Barriers (LCBs). Results show that CSFs significantly reduce LCBs, with Strategic Leadership (β = 0.243), Resource and Knowledge Availability (β = 0.193), and Process Improvement (β = 0.188) being most influential. The model demonstrates acceptable explanatory power (R2 = 0.263), predictive relevance (Q2 = 0.252), and effect size (F2 = 0.356). This study provides the first empirically validated framework linking success factors with LC adoption barriers, offering actionable strategies for more effective implementation in complex project environments.en_US
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationEnvironment, development and sustainability, Published: 03 June 2025, Latest articles, https://doi.org/10.1007/s10668-025-06424-9en_US
dcterms.isPartOfEnvironment, development and sustainabilityen_US
dcterms.issued2025-
dc.identifier.scopus2-s2.0-105007148371-
dc.identifier.eissn1573-2975en_US
dc.description.validate202509 bcchen_US
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberOA_Scopus/WOS, OA_TA-
dc.description.fundingSourceOthersen_US
dc.description.fundingTextThe author gratefully acknowledges the support provided by The Hong Kong Polytechnic University (PolyU) in funding this research. The financial assistance from PolyU has been instrumental in advancing the study and enabling the developments that form the foundation of this work.en_US
dc.description.pubStatusEarly releaseen_US
dc.description.TASpringer Nature (2025)en_US
dc.description.oaCategoryTAen_US
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