Tae Hee Moon
Impact in
- Strategy and Management top 5%
- Innovation and Knowledge Management
- Accounting top 10%
- Financial Distress and Bankruptcy Prediction
Papers in
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- Technology Adoption and User Behaviour 7
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- Innovation Diffusion and Forecasting 3
- Co-authors
- So Young Sohn (15 shared papers)Hong‐Sik Kim (1 shared paper)Joon Mo Ahn (1 shared paper)David Probert (1 shared paper)Tim Minshall (1 shared paper)Letizia Mortara (1 shared paper)Sang-Hoon Kim (1 shared paper)Yong Wook Kim (1 shared paper)
- Journals
- Expert Systems with Applications (7 papers)Journal of the Operational Research Society (3 papers)European Journal of Operational Research (2 papers)Applied Artificial Intelligence (1 paper)Technology Analysis and Strategic Management (1 paper)
- Partner nations
- South KoreaUnited Kingdom
In The Last Decade
Tae Hee Moon
16 papers receiving 444 citations
Peers
Comparison fields: 5 of 65
- Strategy and Management 158
- Accounting 113
- Management of Technology and Innovation 64
- Management Science and Operations Research 108
- Management Information Systems 72
Countries citing papers authored by Tae Hee Moon
This map shows the geographic impact of Tae Hee Moon'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 Tae Hee Moon with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tae Hee Moon more than expected).
Fields of papers citing papers by Tae Hee Moon
This network shows the impact of papers produced by Tae Hee Moon. 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 Tae Hee Moon. The network helps show where Tae Hee Moon may publish in the future.
Co-authors
The 8 scholars most cited alongside Tae Hee Moon, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2016 | 97 | |
| 2 | 2003 | 89 | |
| 3 | 2003 | 57 | |
| 4 | 2006 | 46 | |
| 5 | 2004 | 39 | |
| 6 | 2009 | 26 | |
| 7 | 2010 | 19 | |
| 8 | 2006 | 18 | |
| 9 | 2005 | 17 | |
| 10 | 2007 | 14 | |
| 11 | 2008 | 12 | |
| 12 | 2008 | 10 | |
| 13 | 2008 | 9 | |
| 14 | 2007 | 9 | |
| 15 | 2010 | 6 | |
| 16 | 2008 | 5 |
About Tae Hee Moon
Tae Hee Moon is a scholar working on Information Systems and Management, Management Science and Operations Research, Accounting, Strategy and Management and Economics and Econometrics, having authored 16 papers that have together received 473 indexed citations. Recurring topics across this work include Technology Adoption and User Behaviour (7 papers), Innovation Diffusion and Forecasting (3 papers), Customer Service Quality and Loyalty (3 papers), Financial Distress and Bankruptcy Prediction (3 papers), Firm Innovation and Growth (3 papers), Innovation Policy and R&D (2 papers), Intellectual Capital and Performance Analysis (2 papers) and Innovation and Knowledge Management (2 papers). The work is most often cited by research in Strategy and Management (158 citations), Accounting (113 citations), Management of Technology and Innovation (64 citations), Management Science and Operations Research (108 citations) and Management Information Systems (72 citations). Tae Hee Moon has collaborated with scholars based in South Korea and United Kingdom. Frequent co-authors include So Young Sohn, Hong‐Sik Kim, Joon Mo Ahn, David Probert, Tim Minshall, Letizia Mortara, Sang-Hoon Kim and Yong Wook Kim. Their work appears in journals such as Expert Systems with Applications, Journal of the Operational Research Society, European Journal of Operational Research, Applied Artificial Intelligence and Technology Analysis and Strategic Management.
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.