Achieving manufacturing supply chain resilience: the role of paradoxical leadership and big data analytics capability

Purpose Despite the escalating significance and intricate nature of supply chains, there has been limited scholarly attention devoted to exploring the cognitive processes that underlie supply chain management. Drawing on cognitive-behavioral theory, the authors propose a moderated-mediation model to investigate how paradoxical leadership impacts manufacturing supply chain resilience. Design/methodology/approach By conducting a two-wave study encompassing 164 supply chain managers from Chinese manufacturing firms, the authors employ partial least squares structural equation modeling (PLS-SEM) to empirically examine and validate the proposed hypotheses. Findings The findings indicate that managers' paradoxical cognition significantly affects supply chain resilience, with supply chain ambidexterity acting as a mediating mechanism. Surprisingly, the study findings suggest that big data analytics negatively moderate the effect of paradoxical cognition on supply chain ambidexterity and supply chain resilience, while positively moderating the effect of supply chain ambidexterity on supply chain resilience. Research limitations/implications These findings shed light on the importance of considering cognitive factors and the potential role of big data analytics in enhancing manufacturing supply chain resilience, which enriches the study of behavioral operations. Practical implications The results offer managerial guidance for leaders to use paradoxical cognition frames and big data analytics properly, offering theoretical insight for future research in manufacturing supply chain resilience. Originality/value This is the first empirical research examining the impact of paradoxical leadership on supply chain resilience by considering the role of big data analytics and supply chain ambidexterity.