학술논문
중국 국내 주요 도시 노선의 항공화물 흐름 분석 / Analyzing air cargo flows of China domestic major city routes
Document Type
Dissertation/ Thesis
Source
Subject
Language
Korean
Abstract
본 연구는 2009년부터 2020년까지 중국 주요 도시의 국내 항공화물량을 연구하여 항공화물에 영향을 미치는 여러 요인을 조사하였다. 본 연구에서는 중력 모델을 적용하였다. 본 연구는 중력모형의 경험적 분석에 어떤 접근방식이 더 적합한지를 입증하기 위해 균형패널 자료모형을 활용하여 일반 최소제곱법(OLS), 고정효과(FE), 랜덤효과(RE), 시간고정효과, 이중고정효과 등 다양한 방법으로 종합적인 분석을 하였다.. 본 연구는 중국 국내 주요 도시 간 화물 운송량에 영향을 미치는 요인을 파악하여 선행연구의 공백을 메우려 한다. 또한, 화물량에 영향을 미치는 요인의 분석을 더욱 확장하기 위해 다양한 영향 요인을 도입한다. 이 연구는 다음과 같은 연구 질문에 답한다. '중국에서 선택된 주요 노선의 항공 화물량(주요 세그먼트 볼륨)의 흐름에 영향을 미치는 요소는 무엇입니까?' 결과는 인구, 1인당 GDP, 거리와 같은 근본적인 영향 요인이 항공 화물 운송량에 긍정적이고 통계적으로 유의미한 영향을 미친다는 것을 보여준다. 그리고 이용 가능한 톤수를 넘어서, 비행 스케줄과 예정된 교대 하중 요소들은 또한 총 화물량과 양의 상관관계가 있다. 중력 모형 패널 자료의 실증 결과는 출발도시 인구가 도착도시 인구보다 두 도시 간 항공 화물 부피에 더 큰 영향을 미치는 것으로 나타났다.
This research investigated different factors affecting air cargo by studying the domestic air cargo volumes of major cities in China from 2009 to 2020. The gravity model was adopted in this study. In order to testify which approach is more appropriate for the empirical analysis of gravity model, the study utilized balanced panel data models and made a comprehensive analysis in terms of an array of methods including ordinary least squares (OLS), fixed effects (FE), random effects (RE), time-fixed effects, and double-fixed effects. This research determines to fill the gaps of previous studies by identifying the factors influencing the volume of cargo transported between major domestic cities in China. In addition, different influencing factors are introduced to extend factor the analysis of the factors influencing freight volumes. This study answers the research question: What factors influence the flow of air cargo volumes (major segment volumes) on selected major routes in China? The results show that the underlying influencing factors such as population, GDP per capita and distance have positive and statistically significant effects on the amount of air cargo carried. And then beyond that available tonnage, flight schedules and scheduled shift load factors are positively correlated to total cargo volume. The empirical results from the panel data of the gravity model indicated that the population of the departure city has a more significant on the volume of air cargo between the two cities than the population of the arrival city.
This research investigated different factors affecting air cargo by studying the domestic air cargo volumes of major cities in China from 2009 to 2020. The gravity model was adopted in this study. In order to testify which approach is more appropriate for the empirical analysis of gravity model, the study utilized balanced panel data models and made a comprehensive analysis in terms of an array of methods including ordinary least squares (OLS), fixed effects (FE), random effects (RE), time-fixed effects, and double-fixed effects. This research determines to fill the gaps of previous studies by identifying the factors influencing the volume of cargo transported between major domestic cities in China. In addition, different influencing factors are introduced to extend factor the analysis of the factors influencing freight volumes. This study answers the research question: What factors influence the flow of air cargo volumes (major segment volumes) on selected major routes in China? The results show that the underlying influencing factors such as population, GDP per capita and distance have positive and statistically significant effects on the amount of air cargo carried. And then beyond that available tonnage, flight schedules and scheduled shift load factors are positively correlated to total cargo volume. The empirical results from the panel data of the gravity model indicated that the population of the departure city has a more significant on the volume of air cargo between the two cities than the population of the arrival city.