Impact of Automation on Supply Chain Efficiency in Amazon Warehouses

2026-06-02T06:51:52+00:00

Technological advancements in warehouse operations have fundamentally changed how large-scale e-commerce enterprises manage their supply chains. As global digital commerce continues to expand at an unprecedented pace, the pressure on fulfillment infrastructure to deliver greater speed, precision, and scalability has intensified considerably. This research paper examines the influence of automation technologies — including robotics, Artificial Intelligence (AI), and the Internet of Things (IoT) — on the operational effectiveness of Amazon's fulfillment network. Through an analysis of key performance dimensions such as processing speed, order accuracy, workforce productivity, and cost management, the study demonstrates that automation is central to Amazon's competitive edge in delivering fast and dependable logistics services. The research draws on secondary data sources, industry reports, and academic literature to build a comprehensive picture of how integrated automation ecosystems operate in high-throughput warehouse environments. Key quantitative findings include: robotic picking systems reduced order cycle times by 30–50%, autonomous mobile robots (AMRs) decreased picker travel distances by up to 60%, AI-driven demand forecasting improved inventory accuracy above 99%, and IoT-enabled monitoring enhanced real-time supply chain visibility across all nodes. Per-worker productivity increased by 20–35%, and return on investment was achieved within a 3–5-year horizon for highly automated facilities. While acknowledging challenges such as substantial capital requirements, cybersecurity considerations, and workforce transitions, the research concludes that automation is a foundational pillar of modern supply chain strategy. The insights presented in this study carry broader implications for logistics professionals and organisations seeking to enhance operational resilience and long-term competitiveness through intelligent warehouse technologies.

BorrowBox: The Local Tool and Gear Library

2026-06-20T09:43:30+00:00

Urban India has a large number of underutilized private tools, leading to inefficient resource usage, as many tools are purchased for one-time use and then remain idle. This paper presents BorrowBox, a peer-to-peer tool rental platform that connects tool owners, renters, and delivery partners. The platform includes OTP-based identity verification, escrow payment processing, dynamic delivery pricing, and a bilateral rating system to ensure trust and security. BorrowBox follows a dual commission model, charging 10% from both owners and renters, supported by a mathematical framework for rental costs, delivery charges, and owner earnings. A pilot study involving 35 participants from four groups—students, household owners, small contractors, and domain experts—was conducted. Results showed an average usability score of 4.3/5, exceeding the benchmark of 4.0 across all usability dimensions. Cost analysis suggests savings of up to 90% compared to purchasing tools for one-time use. The platform supports SDGs 8, 10, 11, and 12.

Journal of Purchasing, Logistics and Supply Chain Management system (e-ISSN: 3048-6254)

Impact of Automation on Supply Chain Efficiency in Amazon Warehouses

BorrowBox: The Local Tool and Gear Library