Driving circular economy through business intelligence: managing complexity via innovation culture and effective decision-making

Purpose This article investigates the effect of business intelligence (BI) capacity on the adoption of circular economy (CE) practices. Drawing on the quality of decision-making as a mediator and innovation climate (IC) and continuous improvement (CI) as moderators, it takes the research on open innovation process practices further. Through the resource-based view (RBV)/dynamic capabilities (DC) view, the study explains a conditional-process model that separates the bundles of BI capabilities (sensing, transforming and driving). In this model, decision-making quality (DMQ) is the middle link. IC and CI are the outside conditions that influence the results. Design/methodology/approach The study employed a quantitative research design. The data was derived from a sample of 360 employees in governmental organizations throughout the United Arab Emirates (UAE). Structural equation modeling using partial least squares was employed for data analysis. The model examines three types of pathways: direct effects, indirect effects where BI influences CE outcomes through DMQ, and moderated effects, in which IC shapes the relationship between BI and DMQ, while CI influences the link between DMQ and CE outcomes. This analytical structure provides theory-driven evidence that extends beyond mere correlation. Findings The results reveal that those BI capabilities, particularly driving and transforming capabilities, positively influence CE implementation by enhancing DMQ. Sensing capability showed no meaningful effect. This result shows that just having good information awareness is not enough. It needs support from action-focused capabilities, like transforming and driving, to produce outcomes linked to CE. Additionally, an innovation-supportive climate strengthens the relationship between BI capabilities and DMQ, while CI practices amplify the link between DMQ and CE implementation. Taken together, the results show a pathway that moves from capability to process to outcome. They also explain where the moderators play a role: IC works at the early stage, while CI acts at the later stage, all within the UAE public sector context. Originality/value This study contributes to the literature by integrating BI capabilities, decision-making processes and organizational climate factors in the context of CE. The new value of this paper comes from three points. First, it separates BI capability bundles from the wider ideas of big data analytics. Second, it identifies DMQ as a small but key foundation that connects BI to CE results. Third, it sets IC and CI as the outside conditions that stretch RBV/DC beyond simple consolidation. All of this is shown with public-sector evidence from the UAE. It underscores the strategic value of aligning technological and cultural enablers to drive sustainable practices in public sector organizations.