How Does Big Data Analytics Drive Supply Chain Resilience in Pharmaceuticals? Exploring the Roles of Supply Chain Risk and Ambidexterity

Background: The primary objective of this study is to investigate the influence of big data analytics (BDA) on supply chain (SC) risk, SC ambidexterity, and SC resilience. It further examines the effects of SC risk and SC ambidexterity on SC resilience and explores their mediating roles in the BDA–SC resilience relationship. Despite growing interest in BDA and resilience, limited empirical research has addressed these linkages in pharmaceutical distribution, particularly in emerging economies such as Jordan. Methods: A quantitative research strategy was adopted, employing a survey-based methodology. Data were obtained from 204 managers in pharmaceutical distribution companies in Jordan. Results: The findings indicate that BDA reduces SC risk and positively influences SC ambidexterity and SC resilience. Furthermore, SC risk and SC ambidexterity positively affect SC resilience. Notably, both variables partially mediate the BDA–SC resilience relationship, with ambidexterity showing a stronger effect. Conclusions: Grounded in the resource-based view and the dynamic capability view, this study provides empirical evidence that BDA enhances SC resilience primarily by fostering ambidexterity and mitigating risks. By clarifying the distinct mediating roles of SC risk and SC ambidexterity, the research extends theory and offers practical insights for managers seeking to build more resilient pharmaceutical SCs.