Bayesian network reveals hidden barriers stalling circular construction in UAE

Circular economy adoption in construction is widely promoted as a way to reduce construction and demolition waste, preserve material value, and improve resource efficiency, yet implementation remains stubbornly difficult. A new study argues that the reason lies not in any single obstacle but in the way barriers interact with one another through procurement practices, stakeholder fragmentation, regulatory conditions, digital readiness, secondary-material markets, and investment behavior. Researchers from the American University of Sharjah and Norva Link examined these probabilistic interdependencies in the UAE construction industry using a Bayesian Belief Network, a modeling approach that treats barriers not as independent items on a checklist but as nodes in a connected system where influence propagates from one to the next.

The team built a literature-based index of 25 barriers organized across six dimensions: technological, economic, regulatory, organizational, infrastructure, and behavioral. Eight experts validated the index, and 60 UAE construction professionals then assessed it through survey responses. The analysis compared a conventional independence-based ranking, which scores each barrier in isolation, with an interdependence-based Network Propagation Impact ranking, which measures how strongly each barrier shapes the rest of the network. This distinction matters because a barrier that appears moderate when judged on its own can turn out to be critical once its downstream effects on other barriers are accounted for.

The findings show that complexity in shifting to the circular economy, with a Network Propagation Impact of 0.1245, is the most systemically influential barrier, followed by fragmentation of the building construction industry at 0.1212 and prioritization of cost and time at 0.1071. These three dominate not because professionals rated them as the most severe in direct assessment, but because their position in the network allows them to amplify other constraints. Fragmentation, for example, weakens coordination among contractors, designers, and waste handlers, which in turn undermines the secondary-material markets and information flows that circular construction depends on.

The study demonstrates that perceived severity and systemic influence are not equivalent. Barriers ranked moderately under direct assessment can become critical when their network propagation effects are considered, a result that challenges the barrier-ranking studies that dominate the circular economy literature. In those conventional approaches, each obstacle is scored independently and resources are directed at the highest-scoring items. The Bayesian approach instead captures conditional dependencies, allowing the model to estimate how a change in one barrier alters the probability distribution of others, and the resulting ranking reflects that cascading structure rather than isolated perceptions.

Building on these results, the researchers developed an integrated CE transition framework that links foundational barrier domains, dominant propagation barriers, intervention levers, and expected outcomes. The framework reframes circular economy implementation as a socio-technical transition challenge rather than a collection of discrete problems to be solved one by one. In practice, this means that interventions aimed at the dominant propagation barriers, such as reducing industry fragmentation or easing the complexity of the shift, are expected to produce effects that spread through the network and relieve multiple downstream constraints simultaneously.

The methodological contribution lies in showing how Bayesian Belief Network analysis can support more strategic prioritization of circular construction interventions in the UAE. Because the model encodes probabilistic relationships among the 25 barriers, it can identify which nodes offer the greatest leverage when policymakers, industry bodies, or firms design programs to accelerate circular practices. The authors suggest that this network view can help decision-makers move beyond simple severity scores and target the structural features of the system that keep circular construction from scaling.

The scope of the study is specific. It draws on survey responses from 60 UAE construction professionals and an expert panel of eight, and its conclusions describe perceived barriers within that industry context rather than measured outcomes of circular economy interventions. The index of 25 barriers was derived from the published literature and validated by the expert panel before being assessed by the survey respondents, giving the analysis a structured empirical basis while remaining a study of perceptions and modeled interdependencies rather than of realized waste reduction or material recovery.

For the UAE construction sector, the practical implication is that the barriers demanding the most attention may not be the ones that professionals rate as most severe. Complexity in shifting to the circular economy, fragmentation of the building construction industry, and prioritization of cost and time sit at the top of the propagation ranking, and the framework built around them connects these dominant barriers to intervention levers and expected outcomes. The study’s contribution is to show that treating circular economy implementation as a socio-technical transition, and analyzing its barriers as an interconnected network, can change which interventions are prioritized and, in principle, make those interventions more effective.

Subject of Research: Systemic barriers to circular economy adoption in the UAE construction industry analyzed with a Bayesian Belief Network

Article Title: Systemic barriers to circular economy adoption in UAE construction: Bayesian network evidence and a transition framework

Article References: Amer, S. D., Abdulmaksoud, S., Bahroun, Z., Abu-Lebdeh, G., & Atabay, S. (2026). Systemic barriers to circular economy adoption in UAE construction: Bayesian network evidence and a transition framework. Frontiers in Built Environment, 12, Article 1979368. https://doi.org/10.3389/fbuil.2026.1979368

Image Credits: AI Generated

DOI: 10.3389/fbuil.2026.1979368

Keywords: circular economy, construction and demolition waste, Bayesian belief network, UAE construction industry, network propagation impact, socio-technical transition, barrier ranking, secondary materials, resource efficiency, transition framework, Systemic, barriers