• The Journal of Information Systems
• /
• v.28 no.3
• /
• pp.39-58
• /
• 2019

Purpose A digital twin is a digital replication of a physical system. Gartner identified the digital twin as one of the Gartner Top 10 Strategic Technology Trend for three years from 2017. The rapid development of the digital twin market is expected to bring about innovation and change throughout society, and much research has been done recently in academia. In this research, we tried to explore the main research trends for digital twin research. Design/methodology/approach We collected the digital twin research from Web of Science, and analyzed 804 articles that was published during time span of 2010-2018. A total of 41 key authors were selected based on the frequency of citation. We created a co-citation matrix for the core authors, and performed multivariate analysis such as cluster analysis and multidimensional scaling. We also conducted social network analysis to find the influential researchers in digital twin research. Findings We identified four major sub- areas of digital twin research: "Infrastructure", "Prospects and Challenges", "Security", and "Smart Manufacturing". We also identified the most influential researchers in digital twin research: Lee EA, Rajkumar R, Wan J, Karnouskos S, Kim K, and Cardenas AA. Limitation and further research suggestion were also discussed as a concluding remarks.

• Journal of the Korean Society for information Management
• /
• v.39 no.1
• /
• pp.1-15
• /
• 2022

This study analyzes the relationship of citations appearing in the patent data to understand knowledge transfers and impacts between patent documents in the field of pharmaceutical research. Patent data were collected from a website, Google Patents. The top 25 assignees were selected by searching for patent documents related to pharmaceutical research. We identify the citation relationships between assignees, then calculate and compare the values of h-index and derived indicators by using the number of citations and rank for each document of each assignee. As a result, in the case of pharmaceutical research, the assignee, such as 'Pfizer, MIT, and Abbott' shows a high impact. Among the five bibliometric indicators, the g-index and hS-index show similar results, and the indicators are the most related to the rankings of Total Citation Frequency, Cites per Patents, and Maximum Citation Frequency. In addition, it is highly related to the five indicators in the order of Total Citation Frequency, Cites per Patents, and Maximum Citation Frequency. In some cases, it is difficult to make an accurate comparison with Cites per Patents alone, which is previously known to indicate the technological influence of patent assignees.

• The Journal of Information Systems
• /
• v.33 no.2
• /
• pp.81-103
• /
• 2024

Purpose The purposes of the study are to explore the overall theories used in e-commerce adoption research for small enterprises, to demonstrate the research topics and the growth of the research topics in e-commerce adoption for small businesses over twenty years by co-word analysis and to suggest future directions on e-commerce adoption research in small enterprises. Design/methodology/approach This study used bibliometrics approach to systematically review electronic commerce adoption in small enterprises. More specifically, the study used co-citation to reveal the structure and theoretical foundations and keyword network analysis to understand the changes of research themes in small business e-commerce adoption research from 1999 to 2023. Findings According to the bibliometrics analysis result, this study revealed the nine research topics in small enterprise e-commerce adoption. In addition, this study can be applied to start e-commerce adoption research on small enterprises with a theoretical framework.

• Journal of Convergence for Information Technology
• /
• v.12 no.4
• /
• pp.239-259
• /
• 2022

Since 2019, research on microplastics has been actively conducted around the world, so analyzing the differences between domestic and foreign microplastics research can be a milestone in establishing the direction of domestic research. In this study, microplastic papers from KCI and WoS were extracted and the differences between domestic and foreign studies were analyzed using a network analysis methodology based on big data such as author keyword co-occurrence word analysis, thesis co-citation analysis, and author co-citation analysis. As a result of the analysis, the analysis of the research topic confirmed that studies that could affect the human body and the treatment of microplastics in daily life were additionally needed in Korea. In the analysis of the depth of thesis citation that examines the quality of research, it was found that Korea was still insufficient at 2.25 overseas and 1.39 in Korea. In the analysis of the composition of the joint research front, where various researchers participate and share information, 3 out of 22 clusters in Korea are Star type. In the case of overseas, all 19 clusters have a mesh structure, so it was confirmed that information flow and sharing were insufficient in specific research fields in Korea. These research results confirmed the need to expand the research topic of microplastics, improve the quality of research, and improve the research promotion system in which various researchers participate. In addition, if the automation program is developed based on topic modeling, it will be possible to build a system capable of real-time analysis.

• Journal of the Korean BIBLIA Society for library and Information Science
• /
• v.23 no.2
• /
• pp.109-132
• /
• 2012

This study examines the social network of scholars in the field of communication by using author cocitation data. A matrix containing the number of cocited documents between pairs of authors is created for social network analysis of scholars who are on the editorial board of Journal of Communication, and the networked map of the scholars is used to visualize the knowledge structure of the field by identifying groups of authors who are more central than others. In addition, the study compares the previous analysis performed in 2008 and the current analysis on the editorial board of the journal, which increased from 146 to 254 scholars in numbers. Author cocitation data was collected using Social Science Citation Index (SSCI) through the Web of Science database, and UCInet was used to create and visualize the author cocitation network and to analyze the correlation between the cocitation network and the factors that may have affected the structure of the cocitation network.

• Journal of Technology Innovation
• /
• v.22 no.4
• /
• pp.117-143
• /
• 2014

Tracing an evolutionary technological trajectory in the macroscopic viewpoint is useful for technology policy, but not for corporate technology and intellectual property strategy. Tackling this issue, recent bibliometric studies using patents and papers have made efforts to identify more specific and detailed technological trajectory. However, these studies cannot go beyond simple description of the past trajectory. Also, identification of technology fusion and evolution relies on experts judgments. We suggest a way of identifying microscopic evolutionary technological trajectories by combining patent citation network analysis with dynamic technology tree. Also, using new indicators of generality, diversity and novelty, we can detect key technologies that can be a starting point of next generation technology and derivative technology. HVDC(High Voltage DC transmission) system technology is exemplified.

• Journal of the Korean Society for Library and Information Science
• /
• v.53 no.4
• /
• pp.373-397
• /
• 2019

Recent disasters are a complex and growing trend. In order to effectively prepare for and respond to disasters that occur without notice, it is very important to use scientific information related to disaster and safety in addition to the standardized disaster safety information that is used. In this paper, we searched and selected major journals in the field of disaster & safety and conducted various network analysis studies using the classification scheme for development of integrated metadata for disaster & safety information developed through Disaster & Safety Information Sharing Platform R&D project as well as KSCD. Also, we have constructed and analyzed citation network, co-authorship network and keyword network through data identification and preprocessing of research paper contents. As a result of this study, based on the network constructed by information analysis unit, the network structure between core domestic and foreign journals, major research institutes, core keywords and individual information by disaster & safety type was identified in detail, and the analysis results were presented on a case-by-case basis.

• Journal of the Korean Society for information Management
• /
• v.32 no.1
• /
• pp.153-169
• /
• 2015

The combined approach of using ego-centric network analysis and dynamic citation network analysis for refining the result of LDA-based topic modeling was suggested and examined in this study. Tow datasets were constructed by collecting Web of Science bibliographic records of White LED and topic modeling was performed by setting a different number of topics on each dataset. The multi-assigned top keywords of each topic were re-assigned to one specific topic by applying an ego-centric network analysis algorithm. It was found that the topical cohesion of the result of topic modeling with the number of topic corresponding to the lowest value of perplexity to the dataset extracted by SPLC network analysis was the strongest with the best values of internal clustering evaluation indices. Furthermore, it demonstrates the possibility of developing the suggested approach as a method of multi-faceted research trend detection.

• Journal of the Korean Society for information Management
• /
• v.37 no.1
• /
• pp.153-177
• /
• 2020

In the context of open science, data sharing and reuse are becoming important researchers' activities. Among the discussions about data sharing and reuse, data journals and data papers shows visible results. Data journals are published in many academic fields, and the number of papers is increasing. Unlike the data itself, data papers contain activities that cite and receive citations, thus creating their own intellectual structures. This study analyzed 14 data journals indexed by Web of Science, 6,086 data papers and 84,908 cited references to examine the intellectual structure of data journals and data papers in academic community. Along with the author's details, the co-citation analysis and bibliographic coupling analysis were visualized in network to identify the detailed subject areas. The results of the analysis show that the frequent authors, affiliated institutions, and countries are different from that of traditional journal papers. These results can be interpreted as mainly because the authors who can easily produce data publish data papers. In both co-citation and bibliographic analysis, analytical tools, databases, and genome composition were the main subtopic areas. The co-citation analysis resulted in nine clusters, with specific subject areas being water quality and climate. The bibliographic analysis consisted of a total of 27 components, and detailed subject areas such as ocean and atmosphere were identified in addition to water quality and climate. Notably, the subject areas of the social sciences have also emerged.

• Journal of the Korean Society for information Management
• /
• v.31 no.3
• /
• pp.227-247
• /
• 2014

This paper examines the characteristics of the JASIST (Journal of the Association for Information Science and Technology) editorial board members and their research areas through author co-citation analysis, and investigates whether the editorial board members' research areas are related with keywords frequently appeared in the journal's research articles. In the process, research areas of the central members and those appeared most frequently as keywords will be identified. Research areas of the 36 members on the JASIST editorial board are collected and categorized to compare with the categorization of keywords extracted from 169 research articles published in JASIST, 2013. The result shows that members with higher centrality in the co-citation network are related with research areas that are also dominant in the distribution of article keywords. The areas include information behavior and searching, information retrieval, information system design, and bibliometrics.