IDEAS home Printed from https://ideas.repec.org/p/gtr/gatrjs/jber248.html
   My bibliography  Save this paper

Efficient Container Logistics System Model

Author

Listed:
  • Oraya Nopparit

    (Faculty of Business Administration and Accountancy,Khon Kaen University, No.123, M.16, Mittraphap Road, Nai Mueang, Amphoe Mueang, 40002, Khon Kaen City, Thailand Author-2-Name: Krittapha Saenchaiyathon Author-2-Workplace-Name: Faculty of Business Administration and Accountancy,Khon Kaen University, No.123, M.16, Mittraphap Road, Nai Mueang, Amphoe Mueang, 40002, Khon Kaen City, Thailand Author-3-Name: Author-3-Workplace-Name: Author-4-Name: Author-4-Workplace-Name: Author-5-Name: Author-5-Workplace-Name: Author-6-Name: Author-6-Workplace-Name: Author-7-Name: Author-7-Workplace-Name: Author-8-Name: Author-8-Workplace-Name:)

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"

Suggested Citation

  • Oraya Nopparit, 2024. "Efficient Container Logistics System Model," GATR Journals jber248, Global Academy of Training and Research (GATR) Enterprise.
    • Handle: RePEc:gtr:gatrjs:jber248
    DOI: https://doi.org/10.35609/jber.2024.9.1(3)
    as

    Download full text from publisher

    File URL: http://gatrenterprise.com/GATRJournals/JBER/pdf_files/JBERVol-9(1)2024/3.Oraya%20Nopparit.pdf
    Download Restriction: http://gatrenterprise.com/GATRJournals/online_submission.html
    File URL: https://libkey.io/https://doi.org/10.35609/jber.2024.9.1(3)?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Chen, Lu & Lu, Zhiqiang, 2012. "The storage location assignment problem for outbound containers in a maritime terminal," International Journal of Production Economics, Elsevier, vol. 135(1), pages 73-80.
    2. Mar-Ortiz, Julio & Castillo-García, Norberto & Gracia, María D., 2020. "A decision support system for a capacity management problem at a container terminal," International Journal of Production Economics, Elsevier, vol. 222(C).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Lange, Ann-Kathrin & Kreuz, Felix & Langkau, Sven & Jahn, Carlos & Clausen, Uwe, 2020. "Defining the quota of truck appointment systems," Chapters from the Proceedings of the Hamburg International Conference of Logistics (HICL), in: Jahn, Carlos & Kersten, Wolfgang & Ringle, Christian M. (ed.), Data Science in Maritime and City Logistics: Data-driven Solutions for Logistics and Sustainability. Proceedings of the Hamburg International Conferen, volume 30, pages 211-246, Hamburg University of Technology (TUHH), Institute of Business Logistics and General Management.
    2. Youn Ju Woo & Jang-Ho Song & Kap Hwan Kim, 2016. "Pricing storage of outbound containers in container terminals," Flexible Services and Manufacturing Journal, Springer, vol. 28(4), pages 644-668, December.
    3. Zhang, Canrong & Wu, Tao & Kim, Kap Hwan & Miao, Lixin, 2014. "Conservative allocation models for outbound containers in container terminals," European Journal of Operational Research, Elsevier, vol. 238(1), pages 155-165.
    4. Roberto Guerra-Olivares & Neale R. Smith & Rosa G. González-Ramírez & Leopoldo Eduardo Cárdenas-Barrón, 2018. "A study of the sensitivity of sequence stacking strategies for the storage location assignment problem for out-bound containers in a maritime terminal," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 9(5), pages 1057-1062, October.
    5. Zhang, Canrong & Wang, Qi & Yuan, Guoping, 2023. "Novel models and algorithms for location assignment for outbound containers in container terminals," European Journal of Operational Research, Elsevier, vol. 308(2), pages 722-737.
    6. Mar-Ortiz, Julio & Castillo-García, Norberto & Gracia, María D., 2020. "A decision support system for a capacity management problem at a container terminal," International Journal of Production Economics, Elsevier, vol. 222(C).
    7. Julian Neugebauer & Leonard Heilig & Stefan Voß, 2024. "Digital Twins in the Context of Seaports and Terminal Facilities," Flexible Services and Manufacturing Journal, Springer, vol. 36(3), pages 821-917, September.
    8. Facchini, F. & Digiesi, S. & Mossa, G., 2020. "Optimal dry port configuration for container terminals: A non-linear model for sustainable decision making," International Journal of Production Economics, Elsevier, vol. 219(C), pages 164-178.
    9. Roy, Debjit & van Ommeren, Jan-Kees & de Koster, René & Gharehgozli, Amir, 2022. "Modeling landside container terminal queues: Exact analysis and approximations," Transportation Research Part B: Methodological, Elsevier, vol. 162(C), pages 73-102.
    10. Damla Kizilay & Deniz Türsel Eliiyi, 2021. "A comprehensive review of quay crane scheduling, yard operations and integrations thereof in container terminals," Flexible Services and Manufacturing Journal, Springer, vol. 33(1), pages 1-42, March.
    11. Liu, Changchun, 2020. "Iterative heuristic for simultaneous allocations of berths, quay cranes, and yards under practical situations," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 133(C).
    12. Chenhao Zhou & Ek Peng Chew & Loo Hay Lee, 2018. "Information-Based Allocation Strategy for GRID-Based Transshipment Automated Container Terminal," Transportation Science, INFORMS, vol. 52(3), pages 707-721, June.
    13. Bouzekri, Hamza & Bara, Najat & Alpan, Gülgün & Giard, Vincent, 2022. "An integrated Decision Support System for planning production, storage and bulk port operations in a fertilizer supply chain," International Journal of Production Economics, Elsevier, vol. 252(C).
    14. Lange, Ann-Kathrin & Nellen, Nicole & Jahn, Carlos, 2022. "Truck appointment systems: How can they be improved and what are their limits?," Chapters from the Proceedings of the Hamburg International Conference of Logistics (HICL), in: Kersten, Wolfgang & Jahn, Carlos & Blecker, Thorsten & Ringle, Christian M. (ed.), Changing Tides: The New Role of Resilience and Sustainability in Logistics and Supply Chain Management – Innovative Approaches for the Shift to a New , volume 33, pages 615-655, Hamburg University of Technology (TUHH), Institute of Business Logistics and General Management.
    15. Bajomo, Mary & Ogbeyemi, Akinola & Zhang, Wenjun, 2022. "A systems dynamics approach to the management of material procurement for Engineering, Procurement and Construction industry," International Journal of Production Economics, Elsevier, vol. 244(C).
    16. Ahmed Talaat & Mohamed Gheith & Amr Eltawil, 2023. "A Multi-Stage Approach for External Trucks and Yard Cranes Scheduling with CO 2 Emissions Considerations in Container Terminals," Logistics, MDPI, vol. 7(4), pages 1-23, November.
    17. Ya Xu & Kelei Xue & Yuquan Du, 2018. "Berth Scheduling Problem Considering Traffic Limitations in the Navigation Channel," Sustainability, MDPI, vol. 10(12), pages 1-22, December.
    18. Mehdi Mazloumi & Edwin van Hassel, 2021. "Improvement of Container Terminal Productivity with Knowledge about Future Transport Modes: A Theoretical Agent-Based Modelling Approach," Sustainability, MDPI, vol. 13(17), pages 1-17, August.
    19. Carlo, Héctor J. & Vis, Iris F.A. & Roodbergen, Kees Jan, 2014. "Storage yard operations in container terminals: Literature overview, trends, and research directions," European Journal of Operational Research, Elsevier, vol. 235(2), pages 412-430.
    20. Qingcheng Zeng & Yuanjun Feng & Zigen Chen, 2017. "Optimizing berth allocation and storage space in direct transshipment operations at container terminals," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 19(3), pages 474-503, August.

    More about this item

    Keywords

    Empty Container Terminal; Container Yard; Container Management System; Binary logistic regression.;
    All these keywords.

    JEL classification:

    • E2 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment
    • E3 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gtr:gatrjs:jber248. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Prof. Dr. Abd Rahim Mohamad (email available below). General contact details of provider: http://gatrenterprise.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.