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Purpose This study investigates the role of big data analytics and artificial intelligence (BDA-AI) as an integrated digital sensing capability that enables logistics firms to enhance operational performance in risk-intensive environments. Drawing on dynamic capabilities theory and contingency theory, this research explains how BDA-AI capabilities enhance organisational resilience through service innovation and distribution efficiency, and how organisational resilience, in turn, improves operational performance, while also examining the moderating role of BDA-AI risk concerns. Design/methodology/approach Survey data were collected from 296 logistics firms in China and analysed using partial least squares structural equation modelling. Findings The results show that BDA-AI capabilities significantly enhance service innovation and distribution efficiency, which in turn strengthen organisational resilience. Organisational resilience also positively influences operational performance. In addition, BDA-AI risk concerns negatively moderate the relationship between BDA-AI capabilities and organisational resilience, indicating that heightened risk concerns weaken the extent to which BDA-AI capabilities are translated into resilience outcomes. Originality/value This study advances research on digital transformation and logistics by clarifying the theoretical positioning of BDA-AI and developing a process-oriented, capability-based explanation of digital value creation. It conceptualises BDA-AI as an integrated digital resource infrastructure that remains analytically distinct from the sensing–seizing–reconfiguring processes of dynamic capabilities theory. The findings demonstrate that service innovation, distribution efficiency and organisational resilience function as interdependent capability outcomes, and that BDA-AI risk concerns serve as a negative contingency condition that shapes capability development.
Tan et al. (Tue,) studied this question.