Unveiling the Barriers to Value Management Implementation in Building Projects: An Integrated EFA-SEM-ANN Analysis Approaches

Value Management (VM) is a structured method for enhancing the effectiveness of building projects, yet adoption in Jordan remains limited. The study identifies the principal barriers to VM adoption in Jordan’s building sector and ranks them to inform policy and practice. A survey of 101 industry stakeholders captured 19 Likert-type indicators. Exploratory factor analysis (EFA) reduced the indicators to coherent barrier clusters; partial least squares structural equation modeling (PLS-SEM) then validated a reflective measurement model and tested links with VM adoption. An artificial neural network (ANN) with k-fold cross-validation quantified predictor importance and assessed out-of-sample error. EFA produced three clusters—standardization and organizational practices, workshop design and participation, and culture and industry environment—explaining approximately 73% of total variance. PLS-SEM supported reliability and convergent/ discriminant validity and indicated that workshop-related and standardization barriers exert the strongest adverse effects on VM adoption. ANN results corroborated these patterns and highlighted workshop dynamics as the most influential predictor. This work presents the first integrated EFA–SEM–ANN analysis of VM adoption barriers in Jordan. The multi-method evidence yields actionable priorities: institutionalize standardized VM procedures, strengthen VM workshop design and participation, and address organizational culture to accelerate VM uptake.