Hee Seok Song
- Information Systems top 5%
- Artificial Intelligence top 10%
- Marketing top 10%
- Sociology and Political Science
- Management Science and Operations Research top 10%
- Co-authors
- Jae Kyeong KimYoung Ae KimSoung Hie KimHyea Kyeong KimYoung‐Wook KimHye-On YoonTaewan KimTae-Han Kim
- Topics
- Bone Tissue Engineering Materials (6 papers)Customer churn and segmentation (5 papers)Dental Implant Techniques and Outcomes (4 papers)
- Partner nations
- South KoreaUnited StatesEthiopia
In The Last Decade
Hee Seok Song
19 papers receiving 306 citations
Peers
Comparison fields: 5 of 68
- Information Systems 152
- Artificial Intelligence 108
- Marketing 97
- Sociology and Political Science 76
- Management Science and Operations Research 44
Countries citing papers authored by Hee Seok Song
This map shows the geographic impact of Hee Seok Song'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 Hee Seok Song with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hee Seok Song more than expected).
Fields of papers citing papers by Hee Seok Song
This network shows the impact of papers produced by Hee Seok Song. 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 Hee Seok Song. The network helps show where Hee Seok Song may publish in the future.
Co-authorship network of co-authors of Hee Seok Song
This figure shows the co-authorship network connecting the top 25 collaborators of Hee Seok Song. A scholar is included among the top collaborators of Hee Seok Song 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 Hee Seok Song. Hee Seok Song is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 6 | |
| 3 | 7 | |
| 4 | 1 | |
| 5 | 90 | |
| 6 | 36 | |
| 7 | 12 | |
| 8 | 1 | |
| 9 | 1 | |
| 10 | 1 | |
| 11 | 38 | |
| 12 | 8 | |
| 13 | 6 | |
| 14 | 1 | |
| 15 | 11 | |
| 16 | A study on fitness of ERP template standardization methodology for medium and small-sized enterprises | 1 |
| 17 | 1 | |
| 18 | 3 | |
| 19 | A Personalized Customer Retention Procedure For Internet Game Site Based on the Self-Organizing Map and Association Rule Mining | 1 |
| 20 | 115 |
About Hee Seok Song
Hee Seok Song is a scholar working on Marketing, Oral Surgery and General Materials Science, having authored 22 papers that have together received 342 indexed citations. Recurring topics across this work include Bone Tissue Engineering Materials (6 papers), Customer churn and segmentation (5 papers) and Dental Implant Techniques and Outcomes (4 papers). The work is most often cited by research in Marketing (97 citations), Tourism, Leisure and Hospitality Management (11 citations) and Information Systems (152 citations). Hee Seok Song has collaborated with scholars based in South Korea, United States and Ethiopia. Frequent co-authors include Jae Kyeong Kim, Young Ae Kim, Soung Hie Kim, Hyea Kyeong Kim, Young Ae Kim, Young‐Wook Kim, Hye-On Yoon, Taewan Kim, Tae-Han Kim and Youdan Kim. Their work appears in journals such as Expert Systems with Applications, Knowledge-Based Systems and Artificial Intelligence Review.
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.