Enhancing E-commerce Efficiency: AI Solutions for Last-Mile Delivery in Johannesburg.

Abstract

In the South African context, Johannesburg has become the hub of economic activities and the case of e-commerce expansion comes with a problem of last mile delivery. The challenges caused by the void in artificial intelligence (AI) literature are well known, but such application in Johannesburg’s logistical environment where there is a high level of traffic, poor infrastructure and even laws is lacking.This study seeks to bridge that gap by employing a quantitative approach, drawing on statistical data from a variety of sources, including academic journals, industry reports, and case studies of AI in last-mile delivery. Key findings demonstrate that AI technologies including dynamic routing, predictive analytics, and autonomous delivery vehicles significantly enhance delivery performance by reducing times and costs and improving reliability and customer satisfaction metrics. Particularly, the adoption of AI-driven route optimization and scheduling has led to measurable improvements in delivery efficiency and reductions in operational costs. These results have substantial implications for e-commerce logistics, suggesting that targeted AI implementations could mitigate many of the current delivery inefficiencies in Johannesburg, thereby enhancing overall business competitiveness and sustainability in the e-commerce sector.. As a result, the application of AI algorithms in path finding is expected to greatly reduce costs, giving rise to better and more efficient last-mile delivery services in Johannesburg and other regions.

Keywords: E-commerce, Last-mile delivery, Artificial(AI), Johannesburg logistics, Dynamic routing, Predictive analytics, Autonomous delivery vehicles.

DOI: 10.54941/ahfe1006451