Advanced digital technology adoption under risk and uncertainty: A multi-method study of retail firms

This study examines how financial, technological and institutional risk, together with market and ecosystem uncertainty, shape advanced digital technology adoption in retail firms. Drawing on the distinction between risk as identifiable adoption barriers and uncertainty as ambiguity about future market and ecosystem conditions, the study analyses firm-level data from 1,256 retail firms in EU Member States. The empirical strategy combines logit and probit models, XGBoost, LightGBM, SHapley Additive exPlanations (SHAP) and fuzzy-set qualitative comparative analysis (fsQCA). The results show that risk is negatively associated with advanced digital technology adoption, whereas uncertainty is positively associated with adoption. However, the interaction between risk and uncertainty is negative, indicating that identifiable barriers weaken the positive association between uncertainty and adoption. The machine-learning models provide similar predictive performance to the regression models and confirm the relevance of uncertainty, risk, firm size, innovation intensity and contextual conditions. The fsQCA results further show that adoption can occur through multiple configurational pathways involving risk, uncertainty, firm size, finance access, digital growth orientation and ecosystem embeddedness. The study contributes to digital transformation research by showing that uncertainty may stimulate digital adoption, but only when firms have sufficient capacity to respond and risk does not excessively constrain action.