Keeheon Lee
Impact in
-
- Technology Adoption and User Behaviour
- Marketing top 10%
- Consumer Retail Behavior Studies
Papers in
-
- Complex Network Analysis Techniques 3
- Co-authors
- Sang Yup Lee (1 shared paper)Hosang Jung (1 shared paper)Neil Thompson (1 shared paper)Kristjan Greenewald (1 shared paper)Chang Ouk Kim (3 shared papers)Min Song (6 shared papers)Younah Kang (3 shared papers)Dain Kim (1 shared paper)
- Journals
- Journal of the Association for Information Science and Technology (2 papers)Journal of the Association for Information Systems (2 papers)Journal of Artificial Societies and Social Simulation (2 papers)International Journal of Production Research (1 paper)Proceedings of the ACM on Human-Computer Interaction (1 paper)
- Partner nations
- South KoreaUnited States
In The Last Decade
Keeheon Lee
21 papers receiving 486 citations
Peers
Comparison fields: 5 of 111
- Information Systems and Management 59
- Marketing 74
- Applied Psychology 31
- Management Science and Operations Research 72
- Computer Science Applications 26
Countries citing papers authored by Keeheon Lee
This map shows the geographic impact of Keeheon Lee'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 Keeheon Lee with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Keeheon Lee more than expected).
Fields of papers citing papers by Keeheon Lee
This network shows the impact of papers produced by Keeheon Lee. 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 Keeheon Lee. The network helps show where Keeheon Lee may publish in the future.
Co-authors
The 17 scholars most cited alongside Keeheon Lee, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 21 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 114 | |
| 2 | 2021 | 80 | |
| 3 | 2010 | 58 | |
| 4 | 2019 | 49 | |
| 5 | 2020 | 42 | |
| 6 | 2016 | 31 | |
| 7 | 2021 | 27 | |
| 8 | 2020 | 22 | |
| 9 | 2022 | 21 | |
| 10 | 2013 | 15 | |
| 11 | 2017 | 10 | |
| 12 | 2014 | 8 | |
| 13 | 2016 | 8 | |
| 14 | 2018 | 6 | |
| 15 | 2016 | 5 | |
| 16 | 2024 | 4 | |
| 17 | 2020 | 2 | |
| 18 | 2019 | 2 | |
| 19 | 2015 | 2 | |
| 20 | 2014 | 1 |
About Keeheon Lee
Keeheon Lee is a scholar working on Statistical and Nonlinear Physics, Artificial Intelligence, Molecular Biology, Marketing and Management Science and Operations Research, having authored 21 papers that have together received 508 indexed citations. Recurring topics across this work include Innovation Diffusion and Forecasting (4 papers), Complex Network Analysis Techniques (3 papers), Environmental Sustainability in Business (2 papers), Digital Marketing and Social Media (2 papers), Teaching and Learning Programming (2 papers), Computational and Text Analysis Methods (2 papers), Bioinformatics and Genomic Networks (2 papers) and Biomedical Text Mining and Ontologies (2 papers). The work is most often cited by research in Information Systems and Management (59 citations), Marketing (74 citations), Applied Psychology (31 citations), Management Science and Operations Research (72 citations) and Computer Science Applications (26 citations). Keeheon Lee has collaborated with scholars based in South Korea and United States. Frequent co-authors include Sang Yup Lee, Hosang Jung, Neil Thompson, Kristjan Greenewald, Chang Ouk Kim, Min Song, Younah Kang, Dain Kim, Soyeon Kim and Hoyeop Lee. Their work appears in journals such as Journal of the Association for Information Science and Technology, Journal of the Association for Information Systems, Journal of Artificial Societies and Social Simulation, International Journal of Production Research and Proceedings of the ACM on Human-Computer Interaction.
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.