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Article

Development of a Simultaneous Equations Model Integrating Structured and Unstructured Data for Air Travel Demand Forecasting: South Korea–Vietnam Route

정형·비정형 데이터 통합과 연립방정식을 활용한 한국: 베트남 노선 항공 수요 예측 모형 설계

Chanwon Park1
,
Wonha Lee2
,
Kihan Song3*
박 찬원1
,
이 원하2
,
송 기한3*
1Bachelor’s Degree, Department of Civil Engineering, Seoul National University of Science and Technology
2Master’s and Ph.D. Integration Course, Department of Civil Engineering, Seoul National University of Science and Technology
3Professor, Department of Civil Engineering, Seoul National University of Science and Technology
1서울과학기술대학교 건설시스템공학과 학부과정
2서울과학기술대학교 건설시스템공학과 석·박사통합과정
3서울과학기술대학교 건설시스템공학과 교수
*Corresponding Author
31 December 2025. pp. 132-149
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Abstract

This study develops a simultaneous equations model that integrates structured and unstructured data to forecast air travel demand on the South Korea–Vietnam route. Covering the period from 2015 to 2024, this study analyzes news data using text-mining techniques and constructs an online interest variable by integrating a frequency-based index and a semantic-similarity index. To account for the structural interdependence among demand, supply, and price, as well as price endogeneity, the model is estimated using two-stage least squares (2SLS). The results show that GDP significantly increased demand, expanded supply lowered prices, and both oil prices and the COVID-19 pandemic raised prices. The online interest indicator did not achieve statistical significance, which we interpret as a consequence of the small sample size (n = 9) inherent in annual data. This study empirically demonstrates the feasibility of incorporating unstructured data into econometric analysis and provides actionable insights for airlines, airport operators, and policymakers to enhance demand forecasting and develop early-warning systems.

Keywords
Air Travel Demand Forecasting
Simultaneous Equations
Unstructured Data
Text Mining
Korea–Vietnam Route

본 연구는 한국–베트남 노선의 항공 수요 예측을 위해 정형 데이터와 비정형 데이터를 결합한 연립방정식 모형을 구축하였다. 분석 기간은 2015–2024년이며, 뉴스 데이터를 텍스트마이닝 기법으로 분석하여 빈도 지표와 의미 유사도 지표를 통합한 온라인 관심도 변수를 생성하였다. 수요–가격–공급 간 구조적 상호작용과 가격 내생성을 반영하기 위해 2단계 최소자승법을 적용하였다. 분석 결과, GDP는 수요에 유의한 양의 영향을 미쳤으며, 공급 확대는 가격을 낮추고, 유가와 팬데믹은 가격을 상승시키는 것으로 나타났다. 온라인 관심도 지표는 통계적 유의성을 확보하지 못하였는데, 이는 연간 데이터를 활용한 소표본(n = 9)의 한계로 해석된다. 본 연구는 비정형 데이터의 계량경제학적 활용 가능성을 실증적으로 검증하고, 항공사·공항 운영기관·정책 당국의 수요 예측과 조기경보 체계 구축에 실질적 시사점을 제공한다.

키워드
항공 수요 예측
연립방정식
비정형 데이터
텍스트마이닝
한국–베트남 노선
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Information
  • Publisher :The Korean Society of Airport
  • Publisher(Ko) :한국공항학회
  • Journal Title :Journal of the Korean Society of Airport
  • Journal Title(Ko) :한국공항학회지
  • Volume : 1
  • No :2
  • Pages :132-149
  • Received Date : 2025-08-08
  • Revised Date : 2025-12-08
  • Accepted Date : 2025-12-19
  • DOI :https://doi.org/10.23379/jkosap.1.2.132
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