Abstract

본 연구는 물류연구가 균형 있게 발전할 수 있는 기반을 마련하기 위해 한국학술지인용색인(Korea Citation Index, KCI)에서 2001년부터 2019년 4월까지 검색어『물류󰡕로 검색된 국내 학술지 논문 1,799편의 키워드와 국문초록 등을 통해 연구 동향을 분석하였다. 분석내용은 1,799편의 학술지 논문을 Python을 사용하여 키워드 빈도분석과 Word Embedding(Word2vec), Document Embedding(Doc2vec)을 수행하였다. 분석결과를 정리하면 다음과 같다. 첫째, 물류연구는 지난 19년 동안 58개의 주제분야, 173개의 학술지에서 연구되는 등 다양한 학문 분야와 융합하여 발전하고 있다. 둘째, 1,799편의 키워드 4,431개를 빈도 분석한 결과, “물류(96회)”, “제3자물류(95회)”, “물류성과(87회)”등이 많은 연구자의 관심 대상이 되었음이 나타났다. 셋째, Word Embedding 분석에서는 키워드 Top 5의 상관관계 분석을 통해 각 키워드와 높은 상관관계를 보이는 단어들을 제시하였고, 전체 초록의 단어들 사이에서 키워드 Top 30의 연구적 연결성을 시각적으로 나타내었다. 본 연구는 국내 학술지 논문을 중심으로 물류연구 분야에 대한 빅 데이터 접근방법을 적용하여 초록 키워드분석을 통해 학문적인 발전을 위한 시사점을 도출한 첫 연구이다. 이와 같은 연구결과를 통해 텍스트 자료의 데이터화 등 물류연구의 발전을 다양한 측면에서 분석하고 향후 여러 국가의 물류연구를 비교 연구하는 등 심층적인 접근이 요구된다.Purpose : This study analyzes the research trends through keywords and abstracts of 1,799 papers listed in Korean academic journals, which were searched by the keyword 󰡔Logistics』from 2001 to April 2019, to lay the foundation for balanced growth of logistics research. Research design, data, methodology : For the analysis, 1,799 papers were analyzed using Keyword Frequency Analysis, Word Embedding (Word2vec), Document Embedding(Doc2vec) based on Python. Results : The analysis results are as follows: First, logistics research has been developed in a total of 58 subject areas with 173 academic journals published over the past 19 years by converging with various academic fields. Second, according to the results of frequency analysis of 4,431 keywords in 1,799 papers, “logistics (96 times)”, “third party logistics (95 times)” and “logistics performance (87 times)” are found to be the top three keywords of interest from various researchers. Third, Word Embedding Analysis pointed out five nouns that showed high correlation with each keyword, and visually illustrated the research connection of top 30 keywords among the nouns of the whole abstracts. Conclusions : This study is the first study conducted to derive implications for academic development through the analysis of keywords in the abstracts of papers by applying big data approach to the logistics research field, focusing on Korean papers in academic journals. Based on our research results, it can be concluded that more in-depth approaches – such as analyzing the development of logistics research from various aspects by turning text materials into digital data or researching logistics research of various countries – are required in the future.

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.