Reducing Last-Mile Delivery Time in Postal Services through the Use of Logistics Platforms

Natalia Maliarchuk

Citation: Natalia Maliarchuk, "Reducing Last-Mile Delivery Time in Postal Services through the Use of Logistics Platforms", Universal Library of Innovative Research and Studies, Volume 02, Issue 03.

Copyright: This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

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.


Keywords: Last Mile, Postal Services, Logistics Platform, Delivery Optimization, Dynamic Routing, Crowdsourcing, E-Commerce, Supply Chain Management, Artificial Intelligence in Logistics, Parcel Lockers.

Download doi https://doi.org/10.70315/uloap.ulirs.2025.0203010