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SNA 분석을 활용한 항만배후지 연구동향 분석에 관한 연구

Research Trends Analysis on Port Hinterland Using SNA Method

  • 송시성 (인천대학교 동북아 물류대학원) ;
  • 완준협 (인천대학교 동북아 물류대학원) ;
  • 박성훈 (인천대학교 동북아 물류대학원) ;
  • 여기태 (인천대학교 동북아 물류대학원)
  • Song, Shi-cheng (Graduate school of Logistics, Incheon National University) ;
  • Nguyen, Tuan-hiep (Graduate school of Logistics, Incheon National University) ;
  • Park, Sung-hoon (Graduate school of Logistics, Incheon National University) ;
  • Yeo, Gi-Tae (Graduate school of Logistics, Incheon National University)
  • 투고 : 2018.08.20
  • 심사 : 2018.11.20
  • 발행 : 2018.11.28

초록

본 연구는 1990년부터 2018년까지 기간 동안의 항만배후지에 대한 연구동향을 사회네트워크 방법론을 이용하여 분석하는 것을 목적으로 하였다. 연구에 사용된 자료는 전 세계 116개 관련 학술논문 자료에서 추출하였다. 10년 단위로 분석된 연구결과를 살펴보면, 먼저 1990-1999년 사이에는 컨테이너화, 수송 기반시설 및 선진물류 국가에 관련된 이탈리아, 독일, 캐나다 등이 분석지표상 상위에 위치하였다. 2000-2009년 사이에는 지역화, 경쟁력, 아시아국가 화물유치 및 물류기술 등이 중심적인 위치를 점하였다. 마지막으로 2010-2018년 사이에는 복합운송, 내륙거점, 컨테이너 및 관련 키워드, 해운 및 연관 키워드가 중요하게 연구되었다. 항만배후지 연구동향은 시대가 변화함에 따라 체계화되고 통합적으로 진행되었음을 확인할 수 있으며. 본 연구결과는 항만배후지와 관련된 학계와 산업계의 산업발전에 대한 이해도 및 연구 집중도에 대한 시사점을 제공한다.

In this paper, the research trends of port hinterland from 1990 to 2018 were analyzed periodically using the Social Network Analysis (SNA) method. The data were collected from major academic journals and totally 116 papers were identified for analysis. The results of the analysis showed that in the first period (1990-1999), keywords can be listed as "containerization", "transport infrastructure" and developed countries related keywords like "Italy", "Canada" and "Germany". The results of the second period (2000-2009) were originated from keywords such as "regionalization", "competitiveness", "Asian consolidation" and "technology". In the third period (2010-2018), the results were derived from keywords such as "intermodal transport", "dry port", "container" and container related keywords and "shipping" and shipping related keywords. We could see the studies of port hinterland are becoming more systematic and integrated. This study provides some important implications for both academic, and industrial viewpoints, and it is helpful to understand the research concentration.

키워드

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Fig. 1. Research Flow

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Fig. 2. Result of visualizing keywords in 1990-1999

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Fig. 3. Result of visualizing keywords in 2000-2009

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Fig. 4. Result of visualizing keywords in 2010-2018

Table 1. Normalized data of 3 centrality (1990-1999)

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Table 2. Normalized data of 3 centrality 2000-2009

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Table 3. Normalized data of 3 centrality 2010-2018

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