Barriers and reported adoption of sustainable construction materials: a structural model in an emerging construction economy

Purpose This study extends prior empirical work on the multidimensional barriers to sustainable construction material (SCM) adoption by examining whether the established barrier domains are statistically associated with variation in self-reported implementation behavior. Therefore, it shifts the analytical focus from barrier identification and aggregate adoption readiness to the structural relationships between established barrier constructs and reported SCM implementation in Nigeria's architecture, engineering and construction (AEC) sector. Design/methodology/approach This study employs partial least squares structural equation modeling (PLS-SEM) to examine associations between the established barrier constructs and self-reported SCM adoption. The analysis uses survey responses from AEC professionals in Nigeria. The previously established barrier structure served as the measurement foundation for the PLS-SEM model and was assessed for indicator reliability, internal consistency, convergent validity, and discriminant validity. The structural model then estimated the associations between the barrier constructs and self-reported SCM adoption, with professional experience included as an additional single-factor variable. Findings Regulatory complexity and performance uncertainty was the only barrier construct significantly associated with self-reported SCM adoption (β = 0.208, p = 0.018), although the effect size was small (f2 = 0.022). Cost burden and supply constraints showed essentially no association with adoption (β = 0.000, p = 0.999), while institutional fragmentation and incentive deficiency, as well as policy weakness and market apathy, were also non-significant. Professional experience was positively associated with adoption (β = 0.133, p = 0.034). The model explained 7.8% of the variance in self-reported SCM adoption (R2 = 0.078; adjusted R2 = 0.057). Because the design is cross-sectional, these associations are correlational and may partly reflect greater regulatory engagement among adopters. Originality/value This study extends prior barrier identification and readiness assessment research by shifting the analytical focus from the structure and aggregate severity of SCM barriers to their associations with reported implementation behavior. It demonstrates that barrier salience and structural association with adoption represent distinct empirical questions. Barrier domains perceived as severe at the sectoral level do not necessarily explain variation in reported SCM implementation when considered simultaneously. This distinction provides a more discriminating basis for identifying institutional intervention priorities.

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Publication Details

Journal
Smart and Sustainable Built Environment
Published
2026-09-15
DOI
https://doi.org/10.1108/sasbe-01-2026-0032
Primary Topic
Sustainable Building Design and Assessment
Type
article
Field-Weighted Citation Impact
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article

Barriers and reported adoption of sustainable construction materials: a structural model in an emerging construction economy

Mumini Damilola Osuolale, Juliana Felkner
Smart and Sustainable Built Environment
Sustainable Building Design and Assessment
article

Barriers and reported adoption of sustainable construction materials: a structural model in an emerging construction economy

Mumini Damilola Osuolale, Juliana Felkner
article en

Abstract

Purpose This study extends prior empirical work on the multidimensional barriers to sustainable construction material (SCM) adoption by examining whether the established barrier domains are statistically associated with variation in self-reported implementation behavior. Therefore, it shifts the analytical focus from barrier identification and aggregate adoption readiness to the structural relationships between established barrier constructs and reported SCM implementation in Nigeria's architecture, engineering and construction (AEC) sector. Design/methodology/approach This study employs partial least squares structural equation modeling (PLS-SEM) to examine associations between the established barrier constructs and self-reported SCM adoption. The analysis uses survey responses from AEC professionals in Nigeria. The previously established barrier structure served as the measurement foundation for the PLS-SEM model and was assessed for indicator reliability, internal consistency, convergent validity, and discriminant validity. The structural model then estimated the associations between the barrier constructs and self-reported SCM adoption, with professional experience included as an additional single-factor variable. Findings Regulatory complexity and performance uncertainty was the only barrier construct significantly associated with self-reported SCM adoption (β = 0.208, p = 0.018), although the effect size was small (f2 = 0.022). Cost burden and supply constraints showed essentially no association with adoption (β = 0.000, p = 0.999), while institutional fragmentation and incentive deficiency, as well as policy weakness and market apathy, were also non-significant. Professional experience was positively associated with adoption (β = 0.133, p = 0.034). The model explained 7.8% of the variance in self-reported SCM adoption (R2 = 0.078; adjusted R2 = 0.057). Because the design is cross-sectional, these associations are correlational and may partly reflect greater regulatory engagement among adopters. Originality/value This study extends prior barrier identification and readiness assessment research by shifting the analytical focus from the structure and aggregate severity of SCM barriers to their associations with reported implementation behavior. It demonstrates that barrier salience and structural association with adoption represent distinct empirical questions. Barrier domains perceived as severe at the sectoral level do not necessarily explain variation in reported SCM implementation when considered simultaneously. This distinction provides a more discriminating basis for identifying institutional intervention priorities.

Smart and Sustainable Built Environment
The University of Texas at Austin (US)
Openalex Percentile: Top 14%
Sustainable Building Design and Assessment
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