A MATLAB-Based Nonlinear Fuzzy PLS-SEM Framework for Ranking Barriers in Prefabricated Construction

Abstract This study develops a MATLAB-based nonlinear fuzzy partial least squares structural equation modeling (PLS-SEM) framework to analyze and rank interdependent barriers to prefabricated construction (PC) adoption in developing economies, using Egypt as a case study. The approach integrates symmetric triangular fuzzy numbers to capture uncertainty in expert judgments and employs geometric mean aggregation to model noncompensatory relationships within a hierarchical second-order technology–organization–environment (TOE) structure. The methodology also incorporates validation of the multiplicative risk formulation (probability × impact) and quantifies interaction effects among barrier dimensions through synergy analysis and multigroup analysis. Data collected from 249 industry professionals were analyzed. The results indicate that organizational barriers, particularly financial reluctance, resistance to change, and ineffective communication, are the most critical constraints to PC adoption. A significant interaction between technological and environmental barriers confirms the presence of reinforcing systemic effects. The model demonstrates strong explanatory and predictive performance, with stable rankings across alternative specifications. This study contributes by introducing a nonlinear fuzzy PLS-SEM framework that captures interdependent and noncompensatory relationships, extending the TOE model through hierarchical and interaction-based analysis, and providing empirical evidence on dominant barriers in developing economies.

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Publication Details

Journal
Journal of Construction Engineering and Management
Published
2026-08-20
DOI
https://doi.org/10.1061/jcemd4.coeng-18211
Primary Topic
BIM and Construction Integration
Type
article
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article

A MATLAB-Based Nonlinear Fuzzy PLS-SEM Framework for Ranking Barriers in Prefabricated Construction

Mohamed Badawy
Journal of Construction Engineering and Management
BIM and Construction Integration
article

A MATLAB-Based Nonlinear Fuzzy PLS-SEM Framework for Ranking Barriers in Prefabricated Construction

Mohamed Badawy
article en

Abstract

Abstract This study develops a MATLAB-based nonlinear fuzzy partial least squares structural equation modeling (PLS-SEM) framework to analyze and rank interdependent barriers to prefabricated construction (PC) adoption in developing economies, using Egypt as a case study. The approach integrates symmetric triangular fuzzy numbers to capture uncertainty in expert judgments and employs geometric mean aggregation to model noncompensatory relationships within a hierarchical second-order technology–organization–environment (TOE) structure. The methodology also incorporates validation of the multiplicative risk formulation (probability × impact) and quantifies interaction effects among barrier dimensions through synergy analysis and multigroup analysis. Data collected from 249 industry professionals were analyzed. The results indicate that organizational barriers, particularly financial reluctance, resistance to change, and ineffective communication, are the most critical constraints to PC adoption. A significant interaction between technological and environmental barriers confirms the presence of reinforcing systemic effects. The model demonstrates strong explanatory and predictive performance, with stable rankings across alternative specifications. This study contributes by introducing a nonlinear fuzzy PLS-SEM framework that captures interdependent and noncompensatory relationships, extending the TOE model through hierarchical and interaction-based analysis, and providing empirical evidence on dominant barriers in developing economies.

Journal of Construction Engineering and ManagementVol. 152(11)
Ain Shams University (EG)
Industry, innovation and infrastructure
Openalex Percentile: Top 13%
BIM and Construction Integration
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A MATLAB-Based Nonlinear Fuzzy PLS-SEM Framework for Ranking Barriers in Prefabricated Construction — Mohamed Badawy · Journal of Construction Engineering and Management (2026) | TGRS Research Map | TGRS