Structuring strategies for big data analytics and lean six sigma integration in circular construction supply chains

Purpose This study aims to identify, validate and structure strategies for integrating big data analytics (BDA) and lean six sigma (LSS) to support circular economy (CE) adoption in construction supply chains. It aims to provide a prioritised strategy framework for sequencing BDA–LSS adoption. Design/methodology/approach This study adopts a hybrid multi-criteria decision-making approach. Firstly, strategies for promoting BDA–LSS integration CSCs were identified through an extensive literature review and expert consultation. Secondly, the fuzzy delphi method was applied to screen and validate the strategies based on expert consensus, reducing the preliminary list to 24 retained strategies. Thirdly, interpretive structural modelling was used to unfold the direct and hidden interactions among the validated strategies. Finally, Matrice d’Impacts Croisés Multiplication Appliquée à un Classement analysis was applied to classify the strategies into “driving”, “linkage” and “dependent” clusters. The natural resource-based view and institutional theory were used to interpret the results. Findings The findings identify “Integrate BDA–LSS into national plans” and “Top management support” as the strongest system drivers, with each strategy recording the maximum driving power of 24 and the minimum dependence power of two. “Provide targeted financial incentives” and “Advocate for collaborative contract models” form the secondary drivers, while “Governance”, “Establish unified data standards”, “Cross-functional BDA–LSS improvement teams” and several capability-building strategies occupy the feedback-sensitive linkage cluster. “Predictive analytics” and the operational LSS and CE practices are largely dependent on these upstream strategies. Practical implications The findings are translated into a three-phase, maturity-informed implementation roadmap covering system activation, coordination and capability building and operational value realisation. The roadmap may help policymakers and construction managers diagnose capability gaps, prioritise investments and avoid introducing advanced analytics before suitable governance, data, infrastructure and workforce conditions are established. Originality/value This study develops a construction-specific and theory-informed framework for BDA–LSS adoption in CE-oriented construction supply chains. Its originality lies in examining the integration strategies together and distinguishing three complementary analytical functions: consensus-based screening, hierarchical implementation sequencing and driving–dependence classification. This moves beyond the identification or ranking of isolated factors in much of the prior research, which has examined these domains separately or predominantly within manufacturing contexts.