Data-driven agility in the UK retail sector: How SMEs innovate in dynamic environments through experimental evidence

This study examines how Big Data Analytics Capabilities (BDAC) drive innovation in UK retail SMEs through the mediating role of market agility and the contingent roles of environmental dynamism and learning orientation. Drawing on the resource-based view (RBV) and dynamic capabilities view (DCV), we employ a sequential mixed-method design comprising a qualitative pre-study of 26 SMEs and two experiments. The qualitative phase contextualises BDAC and market agility and informs sector-authentic experimental stimuli. Study 1 (N = 248 SME decision-makers) provides causal evidence that stronger BDAC increase market agility, which in turn increases both innovation adoption and innovation generation, with a stronger effect on adoption. Study 2 (N = 96 individuals/48 two-person teams) tests boundary conditions and reveals an asymmetric contingency: environmental dynamism amplifies the agility-adoption link, whereas learning orientation strengthens the agility-generation link. By distinguishing adoption from generation and by demonstrating this asymmetric moderation pattern under controlled conditions, the study clarifies why data-rich SMEs may become responsive adopters yet struggle to generate novel offerings unless learning routines are institutionalised. For practitioners and policymakers, the findings indicate that digital investment must be complemented by agile decision cycles and learning-oriented practices that convert data into timely, innovative action in dynamic retail markets.