Factors determining the adoption of automation in the last-mile delivery in Penang

• Main Author: Kamalleswary, Baskaran
• Format: Thesis
• Language: English; English
• Published: 2025
• Subjects: TS155-194 Production management. Operations management
• Online Access: https://etd.uum.edu.my/11887/1/depositpermission.pdf; https://etd.uum.edu.my/11887/2/s828671_01.pdf; https://etd.uum.edu.my/11887/

Customer satisfaction, operational effectiveness, and service quality are all significantly impacted by last-mile delivery, the last phase of the logistics chain where products are delivered to ultimate customers. The swift expansion of e-commerce and rising urbanization in Penang, Malaysia, has intensified the demand for new solutions to improve last-mile operations. Automation technologies, including route optimization systems, autonomous delivery vehicles, and robotic handling equipment, present considerable promise to enhance speed, precision, and scalability in last-mile delivery operations. Nevertheless, the integration of automation in Penang's logistics sector is varying, necessitating a study of the factors which influence its acceptance. This study aims to examine the major factors influencing the adoption of automation in last-mile delivery operations across in Penang. The study analyses four key independent variable which is perceived usefulness, perceived ease of use, regulatory restrictions, and workforce readiness. A quantitative methodology was used, and data were gathered using standardised questionnaires given to 147 logistics professionals. Its reliability was tested by a pilot test, with Cronbach’s alpha values surpassing the acceptable threshold for all constructs. Pearson correlation, multiple regression analysis, and descriptive statistics are used in the methodology to carry out the analysis. The findings show that the most important factors influencing the adoption of automation are workforce readiness and regulatory constraints, whereas perceived usefulness and perceived ease of use, despite having a positive correlation, did not reach statistical significance in the regression model. These results highlight how crucial regulatory constraint and workforce readiness are to the success of adoption of automation. For logistics companies, policymakers, and technology providers looking to improve operational efficiency while enabling digital transformation in Penang's logistics sector, this study provides useful insights