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Forecasting shipbuilding demand using shipping market modeling: A case study of LNGC

우종훈|곽동훈|한승우|변건웅
대한조선학회 (The Society Of Naval Architects Of Korea)|2024.12|International Journal of Naval Architecture and Ocean Engineering|제16권 |pp. 1-14|DOI 10.1016/j.ijnaoe.2024.100616

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참고문헌

키워드

Time series analysisDemand forecastingSystem dynamicsShipbuilding industryMaritime economy
주제분류조선공학

초록

Volatile and cyclical shipbuilding demand has consistently been a risk for the shipbuilding industry. This study analyzes the shipping market from a macro perspective and proposes a model capable of long-term shipbuilding demand forecasting. Initially, a system dynamics model representing the shipping market based on maritime economy theory is presented, comprising five main components: external variables, the freight market, shipyards, fleet productivity, and demolition. Based on this system dynamics model, a case study was conducted using LNG carrier market data. The prediction results of the model were compared with seven other time series forecasting models, demonstrating its validity. Finally, scenario analyses evaluated the impact of changes in cargo transport demand, shipyard supply capacity, and carbon regulations. The findings indicated that while increases in transport demand and stricter regulations enhance the amplitude of the shipbuilding demand cycle, increased shipyard supply capacity mitigates these cycles, raising both the period and trough of the cycle.

Abstract

Volatile and cyclical shipbuilding demand has consistently been a risk for the shipbuilding industry. This study analyzes the shipping market from a macro perspective and proposes a model capable of long-term shipbuilding demand forecasting. Initially, a system dynamics model representing the shipping market based on maritime economy theory is presented, comprising five main components: external variables, the freight market, shipyards, fleet productivity, and demolition. Based on this system dynamics model, a case study was conducted using LNG carrier market data. The prediction results of the model were compared with seven other time series forecasting models, demonstrating its validity. Finally, scenario analyses evaluated the impact of changes in cargo transport demand, shipyard supply capacity, and carbon regulations. The findings indicated that while increases in transport demand and stricter regulations enhance the amplitude of the shipbuilding demand cycle, increased shipyard supply capacity mitigates these cycles, raising both the period and trough of the cycle.

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