The International Maritime Organization has strengthened global environmental regulations related to sulfur and nitrogen oxides contained in ship fuel oil since the beginning of 2020. One strategy to comply with the regulations is to fuel ships with liquefied natural gas (LNG) rather than with traditional heavy fuel oil. China and Japan are both developing a business structure for the bunkering of LNG through public–private partnerships to expand their leadership in the field in Northeast Asia and secure a competitive advantage. Compared to China and Japan, Korea has relatively inadequate laws, policy support, and best practices for safe and efficient LNG bunkering for ships. This article provides a comprehensive overview of the LNG bunkering regulation systems in China and Japan and addresses how these systems can be mirrored by Korea to improve the Korean system. It compares the legislative and normative rules of China and Japan regarding the complex global scenario of maritime transportation. The results show that Korea must revise its guidelines and create the advanced institutional framework required for the LNG bunkering market to support an eco-friendly shipping industry and maintain a competitive edge against China and Japan.

A rapid transition toward a decarbonized economy is underway, following the Paris Agreement and the International Maritime Organization 2030 decarbonization goals. However, due to the high cost of the rapid transition to eco-friendly energy and the geopolitical conflict in eastern Europe, liquefied natural gas (LNG), which emits less carbon than other fossil fuels, is gaining popularity. As the spot market grows due to increased LNG demand, the usage of period extension options in time charter (T/C) contracts is increasing; however, these options are generally provided free of charge in practice, without economic evaluation; this is because some shipowners want to make their time charter contracts more attractive to the more credible charterers. Essentially, the reason for why this option has not been evaluated is because there is no reliable evaluation model currently used in practice. That is, research on the evaluation model for the T/C extension option has been insufficient. Therefore, this study evaluates the economic value of the extended period option in LNG time charter contracts using machine learning models, such as artificial neural networks, support vector machines, and random forest, and then compares them with the Black–Scholes model that is used for option valuations in financial markets. The results indicate superior valuation performance of the random forest model compared with the other models; particularly, its performance was significantly better than the Black–Scholes model. Since T/C extension options involve significant sums in the balance sheets of both shipowners and charterers, the fair value of these options should be assessed. In this regard, this paper has meaning in proposing valid machine models to efficiently reflect the fair value of period extension options that are provided at no charge in the LNG market.

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