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포아송 및 음이항 회귀분석을 이용한 해상운임 결정요인이 해운선사의 블랭크 세일링에 미치는 영향 분석 연구

A Study on Impact of Factors Influencing Maritime Freight Rates Using Poisson and Negative Binomial Regression Analysis on Blank Sailings of Shipping Companies

  • 류원형 (국립한국해양대학교 KMI학연협동과정) ;
  • 남형식 (국립한국해양대학교 물류시스템공학과 )
  • Won-Hyeong Ryu (KMI-KMOU Cooperation Course, National Korea Maritime and Ocean University) ;
  • Hyung-Sik Nam (Logistics System Engineering, National Korea Maritime and Ocean University)
  • 투고 : 2023.11.02
  • 심사 : 2024.02.08
  • 발행 : 2024.02.29

초록

해상운송 산업에서는 공급과 수요의 불균형이 지속적으로 증가하면서 세계 주요 해운선사들이 해운 시황에 따른 선복량을 탄력적으로 조절하기 위해 블랭크 세일링을 주요 수단으로 사용하고 있다. 일반적으로 블랭크 세일링은 중국의 춘절 기간에 맞추어 많이 실시되어 왔지만, 2020년부터 시작된 글로벌 팬데믹과 미국·중국 간 무역 전쟁 등과 같은 특수한 상황으로 인해 최근 해운선사들은 기존 대비 큰 규모의 블랭크 세일링을 실시하였다. 이러한 블랭크 세일링은 화물 운송 지연에 직접적 영향을 미치기 때문에 기업과 소비자의 측면에서 부정적인 영향을 초래할 수 있다. 따라서 본 연구는 이에 선제적으로 대응하기 위해 포아송 회귀모형과 음이항 회귀모형을 활용하여 해상운임 결정요인이 해운선사의 블랭크 세일링에 미치는 영향력을 분석하였다. 분석 결과, 포아송 회귀분석의 2M의 경우 유의한 변수로 글로벌 컨테이너 해상물동량, 컨테이너 선복량, 컨테이너선 해체량, 컨테이너선 신조선가지수, OECD 인플레이션을 도출하였고, 음이항 회귀분석의 Ocean Alliance의 경우 글로벌 컨테이너 해상물동량과 컨테이너선 발주량을, THE Alliance의 경우 컨테이너선 선복량과 금리를, Non-Alliance의 경우 국제유가, 글로벌 공급망 압력지수, 컨테이너선 선복량, OECD 인플레이션을, Total Alliance의 경우 컨테이너선 선복량과 금리를 유의한 변수로 도출할 수 있었다.

In the maritime shipping industry, imbalance between supply and demand has persistently increased, leading to the utilization of blank sailings by major shipping companies worldwide as a key means of flexibly adjusting vessel capacity in response to shipping market conditions. Traditionally, blank sailings have been frequently implemented around the Chinese New Year period. However, due to unique circumstances such as the global pandemic starting in 2020 and trade tensions between the United States and China, shipping companies have recently conducted larger-scale blank sailings compared to the past. As blank sailings directly impact freight transport delays, they can have negative repercussions from perspectives of both businesses and consumers. Therefore, this study employed Poisson regression models and negative binomial regression models to analyze the influence of maritime freight rate determinants on shipping companies' decisions regarding blank sailings, aiming to proactively address potential consequences. Results of the analysis indicated that, in Poisson regression analysis for 2M, significant variables included global container shipping volume, container vessel capacity, container ship scrapping volume, container ship newbuilding index, and OECD inflation. In negative binomial regression analysis, ocean alliance showed significance with global container shipping volume and container ship order volume, the alliance with container ship capacity and interest rates, non-alliance with international oil prices, global supply chain pressure index, container ship capacity, OECD inflation, and total alliance with container ship capacity and interest rates.

키워드

과제정보

본 논문은 한국해양수산개발원이 후원한 해양수산 미래 리스크 논문 공모전 수상작임을 밝힙니다.

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