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DOI 10.35609/jber.2024.9.1(3)

Reference to this paper should be made as follows: Nopparit, O; Saenchaiyathon, K. (2024). Efficient Container Logistics System Model, J. Bus. Econ. Review, 9(1), 63–72. https://doi.org/10.35609/jber.2024.9.1(3)

Received: April 10, 2024 | Accepted: June 30, 2024

Efficient Container Logistics System Model
Oraya Nopparit, Krittapha Saenchaiyathon
Faculty of Business Administration and Accountancy,Khon Kaen University, No.123, M.16, Mittraphap Road, Nai Mueang, Amphoe Mueang, 40002, Khon Kaen City, Thailand Abstract

Objective - Although there has been much research on containers and yard operations at the port, it has remained a fascinating subject of study on the logistics side because modernity, education, industries, and human behavior have changed and developed all the time. Moreover, they have continued to play significant roles in the international shipping industry and have affected the dependent economy and trade globally. The aims of this study were (1) to study container management systems and (2) to analyze the factors affecting an efficient container yard management system.

Methodology - This research is classified as applied research, which consists of field surveys using the case record/report form (CRF) and data gathered through observation. A sample frame of 400 vehicles was chosen for a specific case study of an empty container terminal operation area in Bangkok port.

Findings - Performance metrics for container terminal management or yard operations based on truck turnaround time were calculated by applying the Confidence Interval Theory. The data were analyzed using the SPSS program's binary logistic regression method to consider the relationship between the independent and dependent variables. The results of the research have been found. The inbound container management system has been better delivered in time than the outbound, which has implemented a total operation within 16.12 minutes. Additionally, some factors have significantly impacted container yard performance, such as activity type, route, container size, distance, and tools.

Novelty - This might be incurred by multifarious reasons, such as operational stages, waiting time, data transmission, task and tool allocation, areas, traffic congestion, searching the container in blocks, etc.

Type of Paper - Empirical research

Keywords: Empty Container Terminal, Container Yard, Container Management System, Binary logistic regression.

JEL Classification: E2, E3.

URI: http://gatrenterprise.com/GATRJournals/JBER/vol9.1_3.html

DOI: https://doi.org/10.35609/jber.2024.9.1(3)

Pages 63–72

Price: USD 25