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Identifying the Optimal Valuation Model for Maritime Data Assets with the Analytic Hierarchy Process (AHP)

Author

Listed:
  • Sangseop Lim

    (College of Maritime Sciences, Korea Maritime & Ocean University, Busan 49112, Republic of Korea)

  • Chang-Hee Lee

    (College of Maritime Sciences, Korea Maritime & Ocean University, Busan 49112, Republic of Korea)

  • Jae-Hwan Bae

    (Fuel Gas Technology Center Computational Engineering Research Team, Busan Headquarters, Korea Marine Equipment Research Institute, Busan 49111, Republic of Korea)

  • Young-Hun Jeon

    (Fuel Gas Technology Center Computational Engineering Research Team, Busan Headquarters, Korea Marine Equipment Research Institute, Busan 49111, Republic of Korea)

Abstract

Data are becoming the most important factor in the development of the socio-economy, and data can be reevaluated as the owner’s valuable asset, which can increase the owner’s value. Therefore, each company is fiercely competing to secure data. Even in the marine field, maritime data are being produced exponentially, but it is difficult to expect more value creation because data are only stored rather than being used. This study used the analytic hierarchy process (AHP) methodology to select a suitable valuation model necessary to discover new values for maritime data. As a result of AHP analysis of 33 experts based on the stratified factors extracted from previous studies and expert opinions, the market approach (A2) was found to be the most suitable model. In addition, the most important factors to consider when selecting a valuation model were in the order of the characteristics of the maritime data (M1), the features of the maritime data market (M2), and the features of the maritime data valuation model (M3). The potential impact of this implementation could contribute to the establishment of an intelligent technology market by estimating the value of data and developing a platform for maritime data trading, allowing for more efficient data sharing and utilization by maritime autonomous surface ships (MASSs).

Suggested Citation

  • Sangseop Lim & Chang-Hee Lee & Jae-Hwan Bae & Young-Hun Jeon, 2024. "Identifying the Optimal Valuation Model for Maritime Data Assets with the Analytic Hierarchy Process (AHP)," Sustainability, MDPI, vol. 16(8), pages 1-18, April.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:8:p:3284-:d:1375931
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    References listed on IDEAS

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    Cited by:

    1. Kaiyuan Yang & Yuning Luo & Qiao Zou & Alfredo Jimenez, 2026. "Does data assetization enhance corporate innovation performance? A quasi-natural experiment based on the integration of informatization and industrialization in China," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 53(1), pages 253-283, February.
    2. Markus Hafner & Miguel Mira da Silva & Henderik Alex Proper, 2025. "Data valuation as a business capability: from research to practice," Information Systems and e-Business Management, Springer, vol. 23(3), pages 745-784, September.

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