Influence of Autonomous Systems on Supply Chain Optimization in Real-Time Logistics in Ethiopia

Purpose: The purpose of this article was to analyze the influence of autonomous systems on supply chain optimization in real-time logistics in Ethiopia. Methodology: This study adopted a desk methodology. A desk study research design is commonly known as secondary data collection. This is basically collecting data from existing resources preferably because of its low cost advantage as compared to a field research. Our current study looked into already published studies and reports as the data was easily accessed through online journals and libraries. Findings: The influence of autonomous systems on supply chain optimization in Ethiopia is still emerging, with early applications like drones for rural delivery showing potential to improve efficiency. These systems could reduce delivery times, lower costs, and enhance accuracy. However, challenges such as infrastructure gaps and regulatory issues need to be addressed for full implementation. Continued research and investment are crucial to unlocking the potential of autonomous logistics in Ethiopia. Unique Contribution to Theory, Practice and Policy: The technology acceptance model (TAM), resource-based view (RBV) & lean supply chain theory may be used to anchor future studies on the influence of autonomous systems on supply chain optimization in real-time logistics in Ethiopia. Logistics companies should consider adopting hybrid models that integrate autonomous systems with existing human-operated processes. This Governments must create and enforce clear regulatory frameworks that allow for the safe and efficient integration of autonomous systems into logistics.