사회네트워크분석을 이용한 ‘인터넷전자상거래연구’의 연구특성 분석 : 2011년-2020년A Social Network Analysis of ‘The Journal of Internet Electronic Commerce Research’ : from 2011 to 2020
- Other Titles
- A Social Network Analysis of ‘The Journal of Internet Electronic Commerce Research’ : from 2011 to 2020
- Authors
- 이동호
- Issue Date
- Jun-2024
- Publisher
- 한국인터넷전자상거래학회
- Keywords
- SNA(Social Network Analysis); Internet e-Business Research; Research Topics; Contents Analysis; Research Trend
- Citation
- 인터넷전자상거래연구, v.24, no.3, pp 273 - 290
- Pages
- 18
- Indexed
- KCI
- Journal Title
- 인터넷전자상거래연구
- Volume
- 24
- Number
- 3
- Start Page
- 273
- End Page
- 290
- URI
- https://scholarworks.gnu.ac.kr/handle/sw.gnu/71128
- DOI
- 10.37272/JIECR.2024.06.24.3.273
- ISSN
- 1598-1983
- Abstract
- The objective of this study is to find and analyze the characteristics of Internet e-business research social network analysis(SNA). With the perspective of continuity from a previous study conducted 10 years ago, this study examining all of the papers in ‘the Journal of Internet Electronic Commerce Research’ from 2011 to 2020.
Based on frequency analysis and SNA method with a network matrix, most of the bibliographical characteristics were founded. And the following is a summary of the key findings from the content analysis.
1) The total number of authors increased, and the number of authors who published two or more papers also increased. 2) The average number of references per research paper was 43, and the average number of citations was 5.7. 3) The top keywords used in the sample papers included SNS(Social Network Service), satisfaction, purchase intention, continuous usage intention, TAM(technology acceptance model), and trust. 4) on the cluster analysis results with VOSViewer application for keywords, SNS was identified as the center concept of the strongest cluster, and they were largely divided into four clusters. 5) In terms of the authors' affiliations, university affiliations were still overwhelmingly high, and compared to previous studies, there was a relative increase in the clustering of collaborative research.
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