Effect of interconnected big data analytics capability on strategic value creation

This study examines how Big Data Analytics Capability (BDAC) creates strategic business value by enabling value-creation mechanisms. Design/methodology/approach This study used a quantitative survey approach via a Chinese research firm with the largest panel database. All questionnaires were translated and back-translated by bilingual experts; ambiguous items were refined following a pilot (n = 55). A pilot study (n = 55) and a main survey (n = 408) were conducted among Chinese firms adopting big data. PLS-SEM with 5,000 bootstraps tested relationships among BDAC, value creation mechanisms (VCMs) and strategic business value. Common method bias was assessed and found to be non-significant. Findings This study finds that BDAC drives strategic value creation through the interconnected effects of its core components – technology, talent and management capabilities. The results reveal that these components work synergistically to enhance VCMs, translating analytics potential into tangible strategic benefits and strengthening firms' competitive advantage in dynamic business environments. Research limitations/implications Prior research applying OIPT to BDAC emphasised resources or direct performance effects. This study adopts a process-oriented view, framing BDAC as an enabler of VCMs like transparency, predictive modelling and adaptation. By testing mediating VCM, it validates BDAC interdependence and distinguishes functional versus symbolic outcomes, extending OIPT-BDAC understanding. The study's sample is limited to Chinese firms, restricting generalisability. Additionally, cross-sectional data limits insights into the long-term impact of strategic business value. Practical implications The study shows that investing in analytics talent and innovating value-creating mechanisms produces the largest returns from BDAC; technology investments alone are insufficient. Managers should operationalise value-creation mechanisms – data transparency, predictive modelling and proactive adaptation – and track both functional and symbolic KPIs. Originality/value This study advances the understanding of BDAC by positioning it as an essential enabler of value-creating processes rather than a direct source of value. Drawing on organisational information processing theory (OIPT), the research highlights how BDAC supports value-creation processes — data transparency, predictive modelling and proactive adaptation – that improve a firm's ability to respond in complex environments. Additionally, the study offers practical guidance for firms adopting big data analytics, stressing that the strategic value of BDAC lies in addressing organisational information processing needs to reduce uncertainty and improve decision-making outcomes.