한국산업정보학회논문지 (Journal of Korea Society of Industrial Information Systems)

한국산업정보학회 (Korea Society of Industrial Information Systems)
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텍스트 마이닝을 활용한 항공 화물 운임에 영향을 미치는 요인 분석: L.A. 및 프랑크푸르트 노선을 중심으로

Analysis of factors affecting air freight rates using text mining: focusing on the L.A. and Frankfurt routes

  • 최동현 (중앙대학교 국제물류학과) ;
  • 박다현 (중앙대학교 무역물류학과)
  • 투고 : 2023.03.23
  • 심사 : 2023.05.03
  • 발행 : 2023.06.30
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초록

본 연구는 2015년 1월부터 2021년 9월까지의 뉴스 기사를 분기별로 수집하여 토픽 모델링 분석 후 인천 출발 LA와 프랑크푸르트 노선의 항공 화물 운임과 회귀분석을 하여 항공 화물 운임 변동 예측에 영향을 미치는 요인을 분석하였다. 그 결과, 국내 물류 대비 LA 노선은 'Oil Price', 'Shipping' 토픽이 영향 있다는 점을 예측하였고, 프랑크푸르트 노선은 'Oil Price' 토픽이 영향을 미친다는 점을 결과로 제시하였다. 본 연구는 온라인 뉴스 기사 텍스트로부터 수집한 비정형 데이터를 활용하여 시장 참여자의 '보이지 않는 심리'에 영향을 주는 특정 키워드의 빈도 분석을 하고, 항공 화물 운임 사이의 동태적 관계를 파악하고자 하였다. 항공 화물 운임 예측은 항공사와 항공 산업 관련 다양한 분야에서 의사결정에 기초자료로 활용할 수 있을 것이다.

In this study, news articles from January 2015 to September 2021 were collected and analyzed to identify the topics that affect air freight rates through regression analysis based on freight rates and quarterly key topics for the Incheon to Los Angeles and Frankfurt routes. As a result, it was predicted that the "fuel" and "shipping" topics have an impact on the LA route compared to domestic logistics, and that the "fuel" topic has an impact on the Frankfurt route. This study aims the topics that influence the "invisible psychology" of market participants by analyzing the frequency of specific keywords in unstructured data collected from online news articles, and their relationship with air freight rates at specific times. Predicting air freight fares can serve as a foundational data for decision-making in various fields related to airlines and the aviation industry.

키워드

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