[논문]네트워크 분석방법을 활용한 중국 공항터미널 연구 동향분석에 관한 연구

박성훈; 여기태

doi:10.14400/jdc.2020.18.11.137

네트워크 분석방법을 활용한 중국 공항터미널 연구 동향분석에 관한 연구
Research trend of Chinese airport terminal using the Network Analysis 원문보기

디지털융복합연구 = Journal of digital convergence, v.18 no.11, 2020년, pp.137 - 147

(인천대학교 동북아 물류대학원) , (인천대학교 동북아 물류대학원) , 박성훈 (인천대학교 동북아 물류대학원) , 여기태 (인천대학교 동북아 물류대학원)

초록
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글로벌 경제의 가속화와 더불어 물류산업에 있어서 항공물류는 점차 중요한 역할을 담당하고 있다. 항공물류산업의 기초로서 공항터미널은 큰 주목의 대상이 되고 있다. 본 연구는 중국 공항터미널의 연구동향을 분석하는 것을 연구의 목적으로 하였으며, 2003년부터 2020년까지 65개 해외 논문의 키워드를 추출하고 SNA방법을 이용하여 분석하였다. 첫 번째 기간 (2003-2008)은 "Airport Terminal", "Boned" 및 "Chinese Mainland"와 같은 키워드가 상위 키워드로 도출되었다. 두 번째 기간 (2009-2014)의 결과는 "China", "DEA", "Airport" 및 "Flight Delay"와 같은 키워드들이 도출되었고, 세 번째 기간(2015-2020)에는 "Airport Competitiveness"와 "Aviation Network"등의 키워드가 상위로 나타났다. 본 연구의 결과는 경제의 성장에 따라 중국 공항터미널의 연구동향은 공항시설 건설에서 네트워크 개발로 점차 확대되는 것을 확인할 수 있다. 본 연구는 중국 공항터미널의 연구동향을 분석하였으며, 향후 한국을 포함한 인근국가의 정책입안자, 학계, 실무자에게 시사점을 제공한다.

Abstract ▼ AI-Helper

With the acceleration of economic globalization, the development of aviation logistics plays an increasingly significant role in the logistics industry. As the foundation of aviation logistics development, airport terminals are attracting increasing attention. In this respect, the aim of this research is to analyze 65 academic papers on Chinese airport terminals from 2003 to 2020 by utilizing analytic keywords of academic papers and suggest the research trend of Chinese airport terminals. The SNA was adopted as research methodology. Airport Terminal, Boned, and Chinese Mainland were the keywords for the first period (2003-2008), while the second period (2009-2014) included the keywords such as China, DEA, Airport, and Flight Delay. For the third period (2015-2020), Airport Competitiveness and Aviation Network were also highly connected keywords. This indicates that with the growth of the economy, the research trend of China's airport terminals has been gradually expanding from infrastructure construction to network development. The results have implications on suggesting the research trend of Chinese airport terminals, and providing insights to the policy makers, academics, and practitioners in neighboring countries including Korea.

주제어

표/그림 (9)

그림 Fig. 1. Research flow
표 Table 1. Structure of information of selected papers
표 Table 2. Resources of keyworkds used
그림 Fig. 2. Result of visualizing in first period (2003-2008)
표 Table 3. Keyword sequencing of the three centralities from 2003-2008
그림 Fig. 3. Results of visualizing the second period (2009-2014)
표 Table 4. Keyword sequencing of the three centralities from 2009-2014
그림 Fig. 4. Results of visualizing the third period (2015-2020)
표 Table 5. Keyword sequencing of the three centralities from 2015-2020)

AI 본문요약
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* AI 자동 식별 결과로 적합하지 않은 문장이 있을 수 있으니, 이용에 유의하시기 바랍니다.

문제 정의

In this respect, the aim of this research is to analyze the research trend of Chinese airports. First, keywords were collected from various academic papers related to Chinese airports, and then SNA (Social Network Analysis) was used to construct an aviation logistics web to analyze the degree centrality, betweenness centrality, and the closeness centrality of each keyword.

제안 방법

In this respect, the aim of this research is to analyze the research trend of Chinese airports. First, keywords were collected from various academic papers related to Chinese airports, and then SNA (Social Network Analysis) was used to construct an aviation logistics web to analyze the degree centrality, betweenness centrality, and the closeness centrality of each keyword. Through the visual matrix diagram, some correlation points of the development trend of Chinese airports in different periods have been identified.
They considered business hour, runway as input variables, and movement, passengers and mail/cargo as outputs variables. In addition, this analysis included city level, the distance to CBD(Central Business District), flight area, number of destinations, number of airlines served and number of international routes to compare each other. The result showed that the city of level 1 had the highest pure technical efficiency and the distance to CBD is not effect to efficiency.
The results presented in this paper clearly show that the research trend of Chinese airports is closely related to the development of China’ s economy. The SNA method was applied to analyze the research trend of Chinese airports, and the time span from 2003 to 2020 was divided into three stages for a specific analysis. In accordance with the sequence of keywords in the first stages, the keywords with high relevance are “Airport terminal,” “Boned,” “Chinese mainland,” and “Economic effect.
As the result, Beiging-Capital, Shanghai- Pudong, and Guangzhou-Baiyun are appeared as a high hub airport, and they show that they can be considered to provide indirect connectivity to passengers. The study can be extended to the whole region network analysis. Zhang et al.
[15] conducted an annual passenger flow survey of an airport in China. Then they used a prediction model to accurately estimate the total occupant numbers in the departure process.
By analyzing the connection of each node, the centrality of each node can be found. This study focused on three centralities: degree centrality, betweenness centrality, and closeness centrality (Freeman,1978)[27]. Through these centralities, the network of Chinese airports and the relationship between the research and the keywords can be discovered.
But, about freight area, 4F, 4E flight area grades are more efficient than other flight area. This study present considering divers method of approach utilizing modified DEA.
As airports are the material basis of aviation logistics, the development trend of China’ s airports would surely be affected by this plan. To conduct more accurate research, this study was divided into three periods with 2008 and 2014 as the reference boundary points, i.e., from 2003 to 2008, from 2009 to 2014, and from 2015 to 2020.

대상 데이터

[20] adopted SNA to grasp scientific research trends. Authors found out 106 papers of journal and 20 of conferences paper. And nodes degree, local clustering coefficient, eigenvector centrality and community score are presented.
The data presented mainly originated from Science Direct, Scopus, Springer eJournals, Emerald Journal, and Taylor & Francis, and some data were collected from the China National Knowledge Internet (CNKI) and the National Science and Technology Library (NSTL).

이론/모형

And about Chinese airport research, in general, some researchers have analyzed the development of Chinese airports using different methods and different views however, there is scant research focusing on analyzing the research trend of Chinese airports. Hence, this study fills a research gap by using the SNA approach for analysis.
[11] adopted the DEA method to analyze the efficiency of 27 Chinese airports during the period from 2014 to 2018. It was found that it is feasible and reliable to consider the weighted variables using the CFPR method.

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