AI capabilities and sustainable competitiveness in logistics: a mediated moderation model of resilience, government support and intervention

Abstract

Purpose – Grounded in dynamic capabilities theory and institutional theory, this study investigates how AI capabilities enhance organisational resilience and sustainable competitiveness in the logistics sector. Moreover, it explores the role of government institutional support and government regulatory intervention in shaping these relationships. Design/methodology/approach – Data collected from a sample of 296 logistics managers in China were analysed using the PLS-SEM technique to empirically test the proposed hypotheses. Findings – AI capabilities play a pivotal role in fostering both resilience and competitiveness, with resilience serving as a crucial mechanism in this process. Additionally, supportive policies strengthen these effects, while excessive intervention can weaken the positive relationship between AI and resilience. Research limitations/implications – This study highlights the importance of government support in fostering AI-driven competitiveness, suggesting that further research is needed on these influences within the AI landscape. Practical implications – The findings guide logistics managers in leveraging AI capabilities to strengthen resilience and achieve competitiveness. They also show that government support amplifies these benefits, whereas overly restrictive regulations can weaken them. Originality/value – The findings significantly enrich the academic discourse by underscoring the critical relevance of dynamic capabilities theory and institutional theory within the distinct institutional and technological environments prevalent in the logistics firms. This research highlights the crucial role that AI capabilities and proactive governmental frameworks play in promoting resilience and ensuring sustainable competitiveness. It offers valuable insights for managers and policymakers aiming to navigate the complexities of this evolving industry.