A multi-analytical empirical investigation into the Nigerian construction sector has demonstrated that technological barriers represent severe impediments to the digital transformation of circular economy practices, with financial burden and restricted technological access leading the obstacles. Across both mature and emerging global economies, the traditional linear production model continues to generate enormous volumes of construction waste and landfill build-up, documented at 145 million of 600 million tonnes discarded in the United States in 2018, 37.5 percent of total waste in Europe, 20 to 30 percent in Australia, 27 percent in Canada, 50 percent in Brazil, and 30 to 40 percent in China. In Nigeria, material waste from erecting 100 residential units can build an estimated additional 10 houses, driving project cost overruns, schedule delays, reduced contractor profitability, and environmental degradation. To resolve these challenges, a research team led by Emmanuel Chidiebere Eze evaluated 15 distinct technology-related barriers using data gathered from 169 construction professionals across Lagos State.

The circular economy paradigm aims to replace the prevailing take-make-dispose linear model through closed-loop regenerative systems that preserve materials and products in continuous utility, curtailing environmental pollution and ecosystem imbalance. Achieving this transformation requires the systematic integration of transformative digital technologies, including building information modelling, artificial intelligence, big data analytics, cloud computing, the Internet of Things, blockchain, smart contracts, materials passports, and digital twins. These tools provide the necessary digital architecture for lifecycle building management, materials circularity, and transparent tracking of resource recovery and reuse workflows. However, the uptake of these advanced solutions within the West African construction industry remains predominantly restricted to basic, fragmented tools rather than cohesive systems. Construction enterprises operating in developing markets continue to rely heavily on traditional management methods due to deficient digital infrastructure, constrained capital access, weak regulatory frameworks, and insufficient organizational readiness, leaving digital circularity initiatives isolated and technically underdeveloped.

To establish a rigorous conceptual foundation for interpreting how technological constraints impede circular transformation, the researchers integrated the Technology-Organisation-Environment framework with Dynamic Capability Theory. The Technology-Organisation-Environment model identifies how technological characteristics, organizational capabilities, and external environmental conditions collectively shape innovation adoption decisions among construction enterprises. Dynamic Capability Theory complements this environmental perspective by examining how firms intentionally sense operational opportunities and threats, seize strategic openings through resource allocation, and reconfigure internal assets and processes to maintain competitiveness. Within this theoretical architecture, the assessed barriers function as direct constraints that impair dynamic capabilities. Deficits in digital literacy and weak research-to-practice translation diminish an organization’s sensing capabilities by obscuring emerging technological value. Prohibitive initial capital requirements and limited tool availability hamper seizing capabilities, while pervasive software incompatibilities and immature technological standards prevent firms from reconfiguring operational workflows to institutionalize digital circular economy solutions throughout the building lifecycle.

The empirical investigation utilized a quantitative, cross-sectional survey design administered through structured questionnaires distributed across Lagos State, which was selected due to its concentration of construction firms, active projects, and experienced professionals. Because no comprehensive national sampling frame existed to determine the broader population of qualified experts, the researchers deployed non-probabilistic purposive and snowball sampling techniques. Strict participation criteria were enforced to minimize potential selection bias: participants were required to possess at least five years of industry experience, hold senior management or academic positions, maintain relevant professional body affiliations, and demonstrate verifiable working knowledge of digital sustainability tools. After circulating questionnaires to an initial cohort of 45 purposively selected professionals and tracking secondary referrals over a four-month collection window, 181 responses were retrieved. Following data screening, 12 incomplete submissions were removed, leaving 169 validated datasets representing experienced architects, civil engineers, quantity surveyors, and builders possessing an average industry tenure of 14 years.

To verify the psychometric integrity of the survey instrument, the researchers executed extensive statistical diagnostic evaluations prior to core analytical modeling. Internal consistency tests demonstrated acceptable reliability across the four conceptual constructs, with Cronbach’s alpha values ranging from 0.793 for system compatibility barriers to 0.896 for literacy and integration barriers. Normality testing via the Shapiro-Wilk test yielded significance values below the 0.05 threshold, confirming that the dataset departed from normal distribution and necessitating non-parametric analytical techniques. A Kruskal-Wallis test indicated no statistically significant perceptual differences across client, consultant, and contractor respondent groups for 93.33 percent of the evaluated barriers, with divergence observed exclusively regarding technology immaturity and integration complexity. Participant consensus was further corroborated by coefficient of variation scores consistently falling below 0.50, and an intraclass correlation coefficient of 0.809 within a 95 percent confidence interval of 0.764 to 0.848. Furthermore, Harman’s single-factor test generated a cumulative variance of 29.47 percent, remaining safely beneath the 50 percent threshold to confirm the absence of common method bias.

To overcome the subjective imprecision inherent in traditional five-point Likert ratings, the authors combined fuzzy set theory with the conventional relative importance index to create the Fuzzy Relative Importance Index. This hybrid formulation models ambiguous human judgment through fuzzy membership functions, generating more dependable variable prioritizations. Across all 15 evaluated factors, the mean Fuzzy Relative Importance Index reached 0.722, placing the overall barrier set firmly within the high criticality range spanning 0.600 to 0.799. The highest-ranked obstacle was the high investment cost and maintenance burden of enabling technologies, which attained an index of 0.784. This was followed closely by limited access to enabling technologies at 0.767, weak research-to-practice translation resulting in scarce industry-ready tools at 0.763, low digital and circular economy literacy at 0.749, and technology immaturity coupled with integration complexity at 0.743. In contrast, the lowest-ranked barriers were lack of digital inventories and diagnostics at 0.688, insufficient technical support structures at 0.670, and weak corporate digital infrastructure at 0.666.

Detailed examination of the individual barrier rankings highlights the decisive influence of macroeconomic conditions and commercial disparities on technological adoption within developing construction markets. The emergence of high procurement and ongoing maintenance costs as the primary impediment reflects the severe financial barriers associated with deploying building information modelling, artificial intelligence platforms, and digital twin infrastructures. While multinational contractors operating in developing regions possess capital reserves to absorb deployment costs and license specialized integration software, small and medium enterprises encounter severe financial hurdles. This digital access gap, ranked as the second most critical obstacle, prevents smaller enterprises from acquiring compatible tools and essential vendor support, creating deep disparities in technological capability across the regional construction value chain.

Beyond capital barriers, the study identified substantial bottlenecks in knowledge dissemination, human workforce readiness, and technological maturity that impede circular construction practices. The third-ranked barrier, weak translation between academic research and commercial construction practice, demonstrates a pervasive disconnection between university researchers and industry practitioners, which severely restricts the commercialization of digital circularity tools. Concurrently, low digital and circular economy literacy among practitioners, ranked fourth, leaves project professionals struggling to integrate digital workflows with complex resource recovery tasks, such as material provenance tracking, deconstruction modeling, and component reuse. The fifth-ranked impediment, technology immaturity and integration complexity, reflects professional apprehension regarding the unproven lifecycle performance and evolving interoperability standards of emerging tools. Because circular economy execution demands coordinated data exchange across multi-organizational project teams, inadequate technical standards and platform fragmentation diminish data reliability, obstruct material traceability, and foster stakeholder reluctance to abandon established linear construction techniques.

At the construct level, the researchers deployed Fuzzy Synthetic Evaluation to evaluate the four multi-item barrier groupings, finding that every category surpassed the 3.51 cut-off established for very critical status. The digital circular economy resource and adoption risk construct emerged as the most critical group with a synthetic evaluation index of 3.669, followed by interoperability and system compatibility barriers at 3.589, digital literacy and technology integration barriers at 3.551, and technological capability barriers at 3.543. To evaluate whether these analytical rankings were vulnerable to mathematical weighting assumptions, the team conducted sensitivity analyses by adjusting construct coefficients between minus 10 percent and plus 10 percent. The relative rankings of the four barrier categories remained completely stable across all simulated weighting adjustments. The authors emphasized that while this sensitivity analysis demonstrates the mathematical stability and internal robustness of the fuzzy ranking model, it should not be construed as empirical proof of causal mechanisms or permanent structural determinism.

To overcome these systemic barriers, the authors outlined actionable strategic interventions, including phased technology investment models, shared digital platforms, targeted tax credits, and collaborative university-industry consortia dedicated to co-developing standardized building information modeling protocols. However, the researchers emphasized essential methodological boundaries that govern the interpretation of their findings. The empirical sample was collected exclusively from Lagos State, meaning the observations reflect a metropolitan hub with relatively high concentrations of professional expertise and may not fully generalize across other Nigerian regions or international developing markets. Furthermore, the investigation relied on non-probabilistic purposive and snowball sampling, which carries inherent risks of selection bias despite strict participant screening. The authors also noted that their cross-sectional design captures a single point in time, the four barrier constructs were established conceptually from existing literature without exploratory or confirmatory factor analysis, and non-technological dimensions such as regulatory or market barriers remained outside the study’s analytical scope.

Subject of Research: Technological barriers to digital circular economy practices in construction

Article Title: A multi analytical assessment of critical technological barriers to digital circular economy practices in construction

Article References: Eze, E. C., Ugulu, R. A., Zakariyau, M., & Anumudu, A. C. (2026). A multi analytical assessment of critical technological barriers to digital circular economy practices in construction. Discover Civil Engineering, 3(1), Article 237. https://doi.org/10.1007/s44290-026-00612-w

Image Credits: AI Generated

DOI: 10.1007/s44290-026-00612-w

Keywords: circular economy, construction industry, digital technologies, fuzzy relative importance index, fuzzy synthetic evaluation, building information modelling, technology adoption, sustainable construction, construction waste, dynamic capability theory, technology organisation environment, interoperability, digital literacy, resource recovery, Lagos State, sensitivity analysis, intraclass correlation coefficient