Trust Mechanisms in Amazon’s Supply Chain

Abstract

Drawing on social capital theory, this study explores the trust mechanisms within Amazon's supply chain, focusing on the significant impact of information sharing and relationship governance on collaborative efficiency. In a globalized economy, supply chain networks are becoming increasingly complex, involving multinational suppliers, logistics networks, and multi-tiered distribution systems. Trust has become a core driver of stable and efficient collaboration. Using Amazon as a case study, this study examines how trust can improve demand forecast accuracy by optimizing data quality, reducing inventory overhang, stock-out risks, and operational costs, while also enhancing supply chain resilience and agility in dynamic markets. The study demonstrates that Amazon, through its transparent data-sharing platform, vendor-managed inventory (VMI) system, and long-term partnerships, not only effectively mitigates the amplification effect of demand fluctuations but also significantly improves market responsiveness and collaborative stability. It recommends that companies further adopt blockchain technology to enhance data transparency and trustworthiness, and deepen long-term partnerships through shared performance incentives. By integrating theory and practice, this study provides important theoretical and practical guidance for companies to build efficient and stable supply chains in a complex and volatile global market, laying the foundation for subsequent research.