A Study on the Application of Machine Learning Optimization Models in Last-Mile Delivery among SME Logistics Companies in Malaysia

Abstract

The rapid growth of e-commerce and increasing customer expectations for fast and reliable delivery have intensified the complexity of last-mile logistics, particularly among small and medium-sized enterprise (SME) logistics companies in Malaysia. Despite their critical role in the supply chain, many SMEs face challenges in optimizing delivery routes, reducing operational costs, and maintaining service quality due to limited technological capabilities and resource constraints. In this context, machine learning (ML) optimization models have emerged as a promising solution to enhance decision-making and operational efficiency in last-mile delivery.
This study aims to investigate the application of machine learning-based optimization models in improving last-mile delivery performance among SME logistics companies in Malaysia, with a focus on identifying key factors influencing adoption and evaluating their impact on delivery efficiency, cost reduction, and service reliability. Drawing upon relevant theoretical perspectives, the study proposes a conceptual framework that integrates technological, organizational, and environmental factors in explaining ML adoption and its effectiveness. A quantitative research approach will be employed, involving data collection from SME logistics providers through structured questionnaires, and the data will be analyzed using appropriate statistical techniques to examine the relationships between ML adoption and performance outcomes.
The expected findings will provide empirical insights into how ML-driven optimization can support SMEs in overcoming logistical challenges and achieving competitive advantage. This study contributes to both theory and practice by advancing the understanding of advanced analytics adoption in SME logistics and offering practical recommendations for industry stakeholders and policymakers to support digital transformation in last-mile delivery operations in Malaysia.