Analysis reveals reduced delivery times and operational costs in last-mile logistics using crowdsourcing and AI.
The study conducted an analysis and systematization of approaches to reducing delivery time in the final stage of logistics through the implementation and integration of modern digital platforms. The aim of the work is to conduct an analysis and systematization of methods for reducing temporal and resource indicators of last-mile delivery through the deployment of integrated logistics platforms, as well as to develop a conceptual model of such a solution. The methodology is based on a systems analysis of specialized publications devoted to the application of artificial intelligence, crowdsourcing schemes and alternative delivery methods. As a result, a platform architecture has been formed that integrates modules for adaptive routing, crowdsourcing resource management, organization of a parcel locker network and real-time analytics. It has been shown that the synergistic combination of these technologies ensures a significant reduction in average delivery times, a decrease in operational costs and an increase in end-user satisfaction. The scientific novelty lies in the development of a comprehensive model adapted to the characteristics and constraints of traditional postal operators. The work will be of interest to researchers in the field of logistics, managers of postal and courier services, as well as developers of software solutions for supply chain management.
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Natalia Maliarchuk (2025) studied this question.
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