Skip to main content
Log in

Theoretical and Practical Aspects of Data Asset Monetization in Maritime Enterprises

  • Original Paper
  • Published:
Fudan Journal of the Humanities and Social Sciences Aims and scope Submit manuscript

Abstract

This paper explores the challenges and opportunities related to the activation of data assets in the maritime industry. This study sheds light on the evolving landscape of data asset monetization in the maritime sector. The successful activation of these data assets has the potential to generate substantial economic benefits. By addressing ownership, pricing, and security concerns, maritime enterprises can unlock the true potential of their data assets and contribute to the growth and development of the industry. Maritime enterprises possess extensive and long-standing data assets, which have the potential for substantial value extraction. The first part highlights the global trend of data asset monetization and provides an overview of data accumulation by leading maritime companies. It also underscores the unique characteristics of maritime data, including relatively straightforward ownership and ease of utilization. The second part delves into the practical experiences and pros and cons of data asset monetization in various regions. The third part examines the main risks associated with data asset monetization in maritime enterprises. These risks include issues related to ownership and profit distribution after data rights are established, the possibility of data idling leading to a bubble effect, and escalating concerns about data security. In the fourth part, the paper offers specific regulatory pathways and recommendations to address these challenges. This includes resolving ownership attribution issues, implementing market-oriented pricing strategies with legal safeguards, and embracing technological measures for robust data security, such as distinguishing between information and raw data and ensuring the anonymization of original data.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

Data availability

The data that support the findings of this study are available.

Code availability

The code used for analysis in this study is available.

Notes

  1. https://www.legislation.gov.uk/primary+secondary/1991?title=data%20protection.

  2. https://www.marinedataexchange.co.uk.

References

  • Alindayu, Ricardo, Lance Licnachan, Ramgem L. Luzadas, Paul Samuel Ignacio, P. Onda, and L. Deo Florence. 2023. Moving towards open data, public access, and information sharing to combat marine plastics pollution in the Philippines and the Southeast Asian region. Ocean & Coastal Management,. https://doi.org/10.1016/j.ocecoaman.2023.106771.

    Article  Google Scholar 

  • Anderson, S.B., and D.P. Mitchell. 2019. Challenges and opportunities in the monetizaiton of maritime data in the United States: A case study of port operations. Journal of Transportation Research 45 (2): 123–138.

    Google Scholar 

  • Bals, L., E. Hartmann, and J. Uhr. 2018. Integrating information systems: A framework and application to intermodal transport. Computers & Industrial Engineering 125: 1015–1026.

    Google Scholar 

  • Bian, Cheng. 2022. Data as assets in foreign direct investment: Is China’s national data governance compatible with its international investment agreements? Asian Journal of International Law. https://doi.org/10.1017/S2044251322000595.

    Article  Google Scholar 

  • Birch, Kean, Margaret Chiappetta, and Anna Artyushina. 2020. The problem of innovation in technoscientific capitalism: Data rentiership and the policy implications of turning personal digital data into a private asset. Policy Studies 24 (5): 468–487.

    Article  Google Scholar 

  • Brown, L.K., and R.J. Garcia. 2020. Leveraging big data and IoT for enhanced maritime data monetizaiton in the United States. International Journal of Maritime Engineering 162 (3): 197–213.

    Google Scholar 

  • Carriço, N., B. Ferreira, R. Barreira, A. Antunes, C. Grueau, A. Mendes, D. Covas, L. Monteiro, J. Santos, and I.S. Brito. 2020. Data monetization for infrastructure asset management in small to medium-sized water utilities. Water Science and Technology 82 (12): 2737–2744. https://doi.org/10.2166/wst.2020.377.

    Article  Google Scholar 

  • Christopher, M., and D.R. Towill. 2000. Supply chain migration from lean and functional to agile and customized. Supply Chain Management: An International Journal 5 (4): 206–213.

    Article  Google Scholar 

  • Closs, D.J., C. Speier, and N. Meacham. 2011. Sustainability to support end-to-end value chains: The role of supply chain management. Journal of the Academy of Marketing Science 39 (1): 101–119.

    Article  Google Scholar 

  • de Juan, Silvia, Andres Ospina-Alvarez, Antonio J. Castro, Emilio Fernández, Gonzalo Méndez-Martínez, Jone Molina, Pablo Pita, Ana Ruiz-Frau, Gabriela de Abreu, and Sebastian Villasante. 2023. Understanding socioecological interaction networks in marine protected areas to inform management. Ocean & Coastal Management. https://doi.org/10.1016/j.ocecoaman.2023.106854.

    Article  Google Scholar 

  • Du, Peilin, and Yu. Ni. 2023. Higher hierarchical growth through country’s blue economy strategies. Ocean & Coastal Management. https://doi.org/10.1016/j.ocecoaman.2022.106467.

    Article  Google Scholar 

  • Duru, O., L. Oyedele, K. Munir, and M. Gunduz. 2017. Big data and predictive analytics for supply chain digitalization: A conceptual framework for construction supply chains. Procedia Engineering 196: 144–151.

    Google Scholar 

  • Fosso Wamba, S., S. Akter, A. Edwards, G. Chopin, and D. Gnanzou. 2015. How “big data” can make big impact: Findings from a systematic review and a longitudinal case study. International Journal of Production Economics 165: 234–246.

    Article  Google Scholar 

  • Han, H., and H. Moon. 2021. Data monetizaiton and analytics for sustainable maritime supply chains. Ocean & Coastal Management 211: 105743.

    Google Scholar 

  • Hiriyannaiah, Srinidhi, G.M. Siddesh, and K.G. Srinivasa. 2020. Predictive analytical model for microblogging data using asset bubble modelling. International Journal of Cognitive Informatics and Natural Intelligence 14 (2): 108–118. https://doi.org/10.4018/IJCINI.2020040107.

    Article  Google Scholar 

  • Kotzab, H., and C. Teller. 2005. The value of supply chain management in third party logistics services. Transportation Research Part e: Logistics and Transportation Review 41 (2): 147–167.

    Google Scholar 

  • Lee, H.L., V. Padmanabhan, and S. Whang. 1997. Information distortion in a supply chain: The bullwhip effect. Management Science 43 (4): 546–558.

    Article  Google Scholar 

  • Lehavi, A. 2019. Intellectual property, data, and digital assets. In Property law in a globalizing world, ed. A. Lehavi, 172–216. Cambridge University Press.

    Chapter  Google Scholar 

  • Leonelli, S. 2019. Data - from objects to assets. Nature 574 (7778): 317–320. https://doi.org/10.1038/d41586-019-03062-w.

    Article  Google Scholar 

  • Min, H., and H.J. Ko. 2008. Risk and risk management in the supply chain. Journal of Purchasing and Supply Management 14 (3): 159–172.

    Google Scholar 

  • Monostori, L. 2014. Cyber-physical production systems: Roots, expectations and R&D challenges. Procedia CIRP 17: 9–13.

    Article  Google Scholar 

  • Park, Sangchul. 2022. designing legal frameworks for cryptoassets and other cryptographic key-controlled data: Property, contract, and asset-backing. Korean Journal of Law and Economics 19 (3): 455–486.

    Article  Google Scholar 

  • Ruiz, M.C., and L. Svensson. 2018. Maritime data monetizaiton and the digital single window in the european union: Progress and challenges. Maritime Policy & Management 45 (7): 899–915.

    Google Scholar 

  • Simatupang, T.M., and R. Sridharan. 2002. The collaborative supply chain. The International Journal of Logistics Management 13 (1): 15–30.

    Article  Google Scholar 

  • Smith, J.A., and M.R. Johnson. 2021. Maritime data monetizaiton for improved safety and efficiency in U.S. ports. Journal of Maritime Technology and Management 12 (3): 153–167.

    Google Scholar 

  • Stavroulakis, G., and C. Dimitriou. 2017. Towards seamless maritime data monetizaiton in the european union: An overview of initiatives and developments. International Journal of Maritime Engineering 169 (2): 131–147.

    Google Scholar 

  • Stephenson, Robert L., et al. 2023. Integrating management of marine activities in Australia. Ocean & Coastal Management. https://doi.org/10.1016/j.ocecoaman.2022.106465.

    Article  Google Scholar 

  • Sun, X., M.K. Lim, J. Gu, and E.P. Chew. 2017. A framework for evaluating the impact of data monetizaiton on enterprise performance. Information Systems Frontiers 19 (6): 1283–1295.

    Google Scholar 

  • Sun, J., Y. Zhang, D. Zhou, and Y. Zhang. 2020. A novel data monetizaiton framework for sustainable supply chain management in maritime transportation. Sustainability 12 (3): 1202.

    Google Scholar 

  • Tan, K.C., V.R. Kannan, and R. Handfield. 1998. Supply chain management: Supplier performance and firm performance. International Journal of Purchasing and Materials Management 34 (3): 2–9.

    Google Scholar 

  • Tavares, P., and P. Carreira. 2020. Challenges and opportunities for maritime data monetizaiton in the european union: A review. European Journal of Maritime and Transportation Research 46 (3): 351–368.

    Google Scholar 

  • Tetteh, E.S., and J.B. Adu. 2016. The role of big data in enhancing maritime logistics: A review. Computers in Industry 82: 96–104.

    Google Scholar 

  • van den Hoek, J., and S.W. Verstegen. 2020. An interoperable and scalable data monetizaiton platform for the maritime domain. Future Generation Computer Systems 111: 640–652.

    Google Scholar 

  • Wang, L., and Z. Liu. 2018. Big data analytics in maritime and shipping: Contemporary practices, opportunities and challenges. Transportation Research Part e: Logistics and Transportation Review 114: 416–431.

    Google Scholar 

  • Wang, Y., L. Chen, and L. Yang. 2019. an integrated data sharing framework for port logistics in smart ports. IEEE Access 7: 10033–10041.

    Google Scholar 

  • Xiaolan, Yu. 2021. Allocating personal data rights: toward resolving conficts of interest over personal data. Fudan Journal of the Humanities and Social Sciences. https://doi.org/10.1007/s40647-021-00330-w.

    Article  Google Scholar 

  • Yu, Xiaolan. 2022. The three legal dimensions of China’s big data governance. Journal of Chinese Governance. https://doi.org/10.1080/23812346.2021.1988267.

    Article  Google Scholar 

  • Yu, Xiaolan, and Yun Zhao. 2019. Dualism in data protection: Balancing the right to personal data and the data property. Computer Law & Security Review. https://doi.org/10.1016/j.clsr.2019.04.001.

    Article  Google Scholar 

  • Yu, Xiaolan, and Yun Zhao. 2019. Dualism in data protection: Balancing the right to personal data and the data property right. Computer Law & Security Review 35 (5): 105318. https://doi.org/10.1016/j.clsr.2019.04.001.

    Article  Google Scholar 

  • Yuan, Zen. 2023. Legal regulation of data scalability utilization. Local Legislation Journal 8 (5): 71–84.

    Google Scholar 

  • Zhang, Y., and J. Liu. 2021. A data-driven approach for improving maritime logistics management using big data analytics. IEEE Access 9: 21529–21542.

    Google Scholar 

  • Zhao, H., S. Zheng, L. Tang, and Y. Hu. 2019. A data monetizaiton framework for maritime internet of things. Sustainability 11 (20): 5570.

    Google Scholar 

Download references

Acknowledgements

This paper is funded by the National Social Science Foundation- “Research on the Private Law Resolution Path of Conflicts of Interest among Stakeholders in the Use of Data” (21BFX077). The authors also thank to the China Scholarship Council (CSC) .

Funding

National Social Science Fund of China, 21BFX077, Xiaolan Yu

Author information

Authors and Affiliations

Authors

Contributions

The authors equally contributed to this manuscript.

Corresponding author

Correspondence to Xiaolan Yu.

Ethics declarations

Conflict of interest

All authors declare that no conflict of interest exists. The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Jiang, Y., Yu, X. Theoretical and Practical Aspects of Data Asset Monetization in Maritime Enterprises. Fudan J. Hum. Soc. Sci. (2024). https://doi.org/10.1007/s40647-024-00415-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s40647-024-00415-2

Keywords

Navigation