Song-Kyoo Kim

756 citations
60 papers · 400 indexed · h-index 10
Topics
Blockchain Technology Applications and Security (8 papers)Advanced Queuing Theory Analysis (6 papers)Complex Systems and Time Series Analysis (5 papers)

In The Last Decade

Song-Kyoo Kim

49 papers receiving 380 citations

Peers

Song-Kyoo Kim
Comparison fields: 5 of 78
  • Information Systems 108
  • Artificial Intelligence 63
  • Computer Networks and Communications 58
  • Management Information Systems 49
  • Cognitive Neuroscience 49
Replace Hanane Allioui with:
Hanane Allioui Morocco
Amélie Gyrard United States
Madjid Khalilian Iran
Mehul Bhatt Germany
Yassine Maleh Morocco
Burairah Hussin Malaysia
Borja Ramis Ferrer Finland
Omar Santos United Kingdom
Javad Mohammadzadeh Iran
Song-Kyoo Kim relative to Hanane Allioui Morocco Hanane Allioui's profile →
Citations per field
00.5×8.2×
Hanane Allioui · 1×
Citations per year

Countries citing papers authored by Song-Kyoo Kim

Since Specialization
Citations

This map shows the geographic impact of Song-Kyoo Kim's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Song-Kyoo Kim with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Song-Kyoo Kim more than expected).

Fields of papers citing papers by Song-Kyoo Kim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Song-Kyoo Kim. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Song-Kyoo Kim. The network helps show where Song-Kyoo Kim may publish in the future.

Co-authorship network of co-authors of Song-Kyoo Kim

This figure shows the co-authorship network connecting the top 25 collaborators of Song-Kyoo Kim. A scholar is included among the top collaborators of Song-Kyoo Kim based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Song-Kyoo Kim. Song-Kyoo Kim is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 0
2 0
3 0
4 1
5 2
6 2
7 11
8 3
9 6
10 3
11 2
12 30
13 18
14 47
15 60
16 49
17 1
18 1
19 7
20 8

About Song-Kyoo Kim

Song-Kyoo Kim is a scholar working on Management Information Systems, Management Science and Operations Research and Management of Technology and Innovation, having authored 60 papers that have together received 400 indexed citations. Recurring topics across this work include Blockchain Technology Applications and Security (8 papers), Advanced Queuing Theory Analysis (6 papers) and Complex Systems and Time Series Analysis (5 papers). The work is most often cited by research in Management Information Systems (49 citations), Information Systems (108 citations) and Radiological and Ultrasound Technology (21 citations). Song-Kyoo Kim has collaborated with scholars based in Macao, South Korea and United Arab Emirates. Frequent co-authors include Chan Yeob Yeun, Paul D. Yoo, Ernesto Damiani, Nai‐Wei Lo, Mohamed Jamal Zemerly, Jewgeni H. Dshalalow, Gabriele Gianini, Tae‐Yeon Kim, Young-Ji Byon and Chung-Suk Cho. Their work appears in journals such as IEEE Access, ACM Computing Surveys and Computers & Industrial Engineering.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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