IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i22p15686-d1275474.html
   My bibliography  Save this article

Blockchain-Powered Incentive System for JIT Arrival Operations and Decarbonization in Maritime Shipping

Author

Listed:
  • Son Nguyen

    (Institute of High Performance Computing (IHPC), Agency for Science, Technology and Research (A*STAR), 1 Fusionopolis Way, #16-16 Connexis, Singapore 138632, Singapore
    These authors contributed equally to this work.)

  • Aengus Leman

    (Faculty of Science, National University of Singapore, 6 Science Drive 2, Singapore 117546, Singapore
    These authors contributed equally to this work.)

  • Zhe Xiao

    (Institute of High Performance Computing (IHPC), Agency for Science, Technology and Research (A*STAR), 1 Fusionopolis Way, #16-16 Connexis, Singapore 138632, Singapore)

  • Xiuju Fu

    (Institute of High Performance Computing (IHPC), Agency for Science, Technology and Research (A*STAR), 1 Fusionopolis Way, #16-16 Connexis, Singapore 138632, Singapore)

  • Xiaocai Zhang

    (Institute of High Performance Computing (IHPC), Agency for Science, Technology and Research (A*STAR), 1 Fusionopolis Way, #16-16 Connexis, Singapore 138632, Singapore)

  • Xiaoyang Wei

    (Institute of High Performance Computing (IHPC), Agency for Science, Technology and Research (A*STAR), 1 Fusionopolis Way, #16-16 Connexis, Singapore 138632, Singapore)

  • Wanbing Zhang

    (Institute of High Performance Computing (IHPC), Agency for Science, Technology and Research (A*STAR), 1 Fusionopolis Way, #16-16 Connexis, Singapore 138632, Singapore)

  • Ning Li

    (Institute of High Performance Computing (IHPC), Agency for Science, Technology and Research (A*STAR), 1 Fusionopolis Way, #16-16 Connexis, Singapore 138632, Singapore)

  • Wei Zhang

    (Institute of High Performance Computing (IHPC), Agency for Science, Technology and Research (A*STAR), 1 Fusionopolis Way, #16-16 Connexis, Singapore 138632, Singapore)

  • Zheng Qin

    (Institute of High Performance Computing (IHPC), Agency for Science, Technology and Research (A*STAR), 1 Fusionopolis Way, #16-16 Connexis, Singapore 138632, Singapore)

Abstract

Efficiency and sustainability are undisputedly the most critical objectives for modern ports. Current exercises for port services still lack performance profiling for arriving vessels regarding their arrival punctuality and compliance with port resource schedule for Just-in-time (JIT) service, as well as their efforts contributing towards less emission through reduced turnaround time within port. As a result, a performance-based incentive is missing. Bringing in the incentive component may facilitate the objectives of achieving both port efficiency and sustainability. Blockchain technology, owning to its intrinsic features like immutability, traceability, governance and provenance, and in-built tokens (for most public chain platforms), allow for the establishment of system solutions to record key performance indicators (KPIs) and distribute incentives to good performers. This paper is the first to propose a blockchain-based system to incentivize JIT and green operations in ports. The platform system design and operating mechanisms are elaborated in detail, and a prototype system has been implemented based on the Solana blockchain to demonstrate the core features. The current system’s potential is substantial, considering the industry’s increasing awareness about its environmental footprint. Continuous developments can be facilitated by connecting to market-based measures such as carbon pricing and emission trading in the maritime sector.

Suggested Citation

  • Son Nguyen & Aengus Leman & Zhe Xiao & Xiuju Fu & Xiaocai Zhang & Xiaoyang Wei & Wanbing Zhang & Ning Li & Wei Zhang & Zheng Qin, 2023. "Blockchain-Powered Incentive System for JIT Arrival Operations and Decarbonization in Maritime Shipping," Sustainability, MDPI, vol. 15(22), pages 1-22, November.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:22:p:15686-:d:1275474
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/22/15686/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/15/22/15686/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Albert W. Veenstra & Rogier L. A. Harmelink, 2022. "Process mining ship arrivals in port: the case of the Port of Antwerp," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 24(3), pages 584-601, September.
    2. Meng, Qiang & Du, Yuquan & Wang, Yadong, 2016. "Shipping log data based container ship fuel efficiency modeling," Transportation Research Part B: Methodological, Elsevier, vol. 83(C), pages 207-229.
    3. Yang, Chung-Shan, 2019. "Maritime shipping digitalization: Blockchain-based technology applications, future improvements, and intention to use," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 131(C), pages 108-117.
    4. Simon Wong & John Kun-Woon Yeung & Yui-Yip Lau & Tomoya Kawasaki, 2023. "A Case Study of How Maersk Adopts Cloud-Based Blockchain Integrated with Machine Learning for Sustainable Practices," Sustainability, MDPI, vol. 15(9), pages 1-17, April.
    5. Alexander Senss & Onder Canbulat & Dogancan Uzun & Sefer Anil Gunbeyaz & Osman Turan, 2023. "Just in time vessel arrival system for dry bulk carriers," Journal of Shipping and Trade, Springer, vol. 8(1), pages 1-37, December.
    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. Vincenzo Varriale & Antonello Cammarano & Francesca Michelino & Mauro Caputo, 2021. "Sustainable Supply Chains with Blockchain, IoT and RFID: A Simulation on Order Management," Sustainability, MDPI, vol. 13(11), pages 1-23, June.
    2. Liu Jiaguo & Zhang Huimin & Zhao Huida, 2021. "Blockchain Technology Investment and Sharing Strategy of Port Supply Chain Under Competitive Environment," Journal of Systems Science and Information, De Gruyter, vol. 9(3), pages 280-309, June.
    3. Dehghani, Milad & William Kennedy, Ryan & Mashatan, Atefeh & Rese, Alexandra & Karavidas, Dionysios, 2022. "High interest, low adoption. A mixed-method investigation into the factors influencing organisational adoption of blockchain technology," Journal of Business Research, Elsevier, vol. 149(C), pages 393-411.
    4. Petri Helo & Henri Paukku & Tero Sairanen, 2021. "Containership cargo profiles, cargo systems, and stowage capacity: key performance indicators," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 23(1), pages 28-48, March.
    5. Fink, Alexander A. & Klöckner, Maximilian & Räder, Tobias & Wagner, Stephan M., 2022. "Supply chain management accelerators: Types, objectives, and key design features," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 164(C).
    6. Muen Uddin & Shitharth Selvarajan & Muath Obaidat & Shams Ul Arfeen & Alaa O. Khadidos & Adil O. Khadidos & Maha Abdelhaq, 2023. "From Hype to Reality: Unveiling the Promises, Challenges and Opportunities of Blockchain in Supply Chain Systems," Sustainability, MDPI, vol. 15(16), pages 1-24, August.
    7. Önder Çağlayan & Murat Aymelek, 2024. "An Integrated Multi-Criteria Decision Support Model for Sustainable Ship Queuing Policy Application via Vessel Traffic Service (VTS)," Sustainability, MDPI, vol. 16(11), pages 1-33, May.
    8. Suneet Singh & Ashish Dwivedi & Saurabh Pratap, 2023. "Sustainable Maritime Freight Transportation: Current Status and Future Directions," Sustainability, MDPI, vol. 15(8), pages 1-23, April.
    9. Nguyen, Son & Fu, Xiuju & Ogawa, Daichi & Zheng, Qin, 2023. "An application-oriented testing regime and multi-ship predictive modeling for vessel fuel consumption prediction," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 177(C).
    10. Yan, Ran & Wang, Shuaian & Du, Yuquan, 2020. "Development of a two-stage ship fuel consumption prediction and reduction model for a dry bulk ship," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 138(C).
    11. Zhen, Lu & Wang, Shuaian & Zhuge, Dan, 2017. "Dynamic programming for optimal ship refueling decision," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 100(C), pages 63-74.
    12. Zheng, Shiyuan & Jiang, Changmin, 2024. "Consortium blockchain in Shipping: Impacts on industry and social welfare," Transportation Research Part A: Policy and Practice, Elsevier, vol. 183(C).
    13. Arim Park & Huan Li, 2021. "The Effect of Blockchain Technology on Supply Chain Sustainability Performances," Sustainability, MDPI, vol. 13(4), pages 1-18, February.
    14. Benjamin Mosses Sakita & Berit Irene Helgheim & Svein Bråthen, 2024. "The Principal-Agent Theoretical Ramifications on Digital Transformation of Ports in Emerging Economies," Logistics, MDPI, vol. 8(2), pages 1-39, May.
    15. Lavaei Adaryani, Rasool & Palouj, Mojtaba & Karbasioun, Mostafa & Asadi, Ali & Gholami, Hesamedin & Kianirad, Ali & Joodi Damirchi, Milad, 2024. "Antecedents of blockchain adoption in the poultry supply chain: An extended UTAUT model," Technological Forecasting and Social Change, Elsevier, vol. 202(C).
    16. Vincenzo Varriale & Antonello Cammarano & Francesca Michelino & Mauro Caputo, 2020. "The Unknown Potential of Blockchain for Sustainable Supply Chains," Sustainability, MDPI, vol. 12(22), pages 1-16, November.
    17. Wang, Yadong & Wang, Shuaian, 2021. "Deploying, scheduling, and sequencing heterogeneous vessels in a liner container shipping route," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 151(C).
    18. Zhijia Tan & Yadong Wang & Qiang Meng & Zhixue Liu, 2018. "Joint Ship Schedule Design and Sailing Speed Optimization for a Single Inland Shipping Service with Uncertain Dam Transit Time," Service Science, INFORMS, vol. 52(6), pages 1570-1588, December.
    19. Zhu, Qingyun & Bai, Chunguang & Sarkis, Joseph, 2022. "Blockchain technology and supply chains: The paradox of the atheoretical research discourse," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 164(C).
    20. Wang, Yangjun & Liu, Kefeng & Zhang, Ren & Qian, Longxia & Shan, Yulong, 2021. "Feasibility of the Northeast Passage: The role of vessel speed, route planning, and icebreaking assistance determined by sea-ice conditions for the container shipping market during 2020–2030," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 149(C).

    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:gam:jsusta:v:15:y:2023:i:22:p:15686-:d:1275474. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.