Delivery Service Management System Using Google Maps for SMEs in Emerging Countries
Source abstract
Abstract
This paper proposes a Delivery Service Management (DSM) system for Small and Medium Enterprises (SMEs) that own a delivery fleet of pickup trucks to manage Business-to-Business (B2B) delivery services. The proposed DSM system integrates four systems: Delivery Location Positioning (DLP), Delivery Route Planning (DRP), Arrival Time Prediction (ATP), and Communication and Data Sharing (CDS) systems. These systems are used to pinpoint the delivery locations of customers, plan the delivery route of each truck, predict arrival time (with an interval) at each delivery location, and communicate and share information among stakeholders, respectively. The DSM system deploys Google applications, a GPS tracking system, Google Map APIs, ATP algorithms (embedded in Excel Macros), Line, and Telegram as supporting tools. To improve the accuracy of the ATP system, three techniques are applied considering driver behaviors. The proposed DSM system has been implemented in a Thai SME. From the process perspective, the DSM system is a systematic procedure for end-to-end delivery services. It allows the interactions between planner-driver decisions and supporting tools. The supporting tools are simple, can be easily used with little training, and require low capital expenditure. The statistical analysis shows that the ATP algorithm with the three techniques provides high accuracy. Thus, the proposed DSM system is beneficial for practitioners to manage delivery services, especially for SMEs in emerging countries.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Urban and Freight Transport Logistics · Transportation and Mobility Innovations · Transportation Planning and Optimization
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (50)
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