Tinglong Dai
Impact in
- Health Informatics top 2%
-
- Supply Chain and Inventory Management
Papers in
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- Supply Chain and Inventory Management 16
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- Healthcare Policy and Management 9
- Game Theory and Voting Systems 5
- Co-authors
- Sridhar Tayur (8 shared papers)Christopher S. Tang (7 shared papers)Kinshuk Jerath (6 shared papers)Fuqiang Zhang (2 shared papers)Soo-Haeng Cho (2 shared papers)Ying‐Ju Chen (2 shared papers)C. Gizem Korpeoglu (2 shared papers)Özge Şahin (2 shared papers)
- Journals
- Manufacturing & Service Operations Management (7 papers)npj Digital Medicine (5 papers)Management Science (5 papers)Production and Operations Management (3 papers)Marketing Science (3 papers)
- Partner nations
- United StatesChinaHong Kong
In The Last Decade
Tinglong Dai
70 papers receiving 1.2k citations
Peers
Comparison fields: 5 of 110
- Health Informatics 76
- Management Information Systems 378
- Marketing 252
- Modeling and Simulation 84
- Strategy and Management 282
Countries citing papers authored by Tinglong Dai
This map shows the geographic impact of Tinglong Dai'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 Tinglong Dai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tinglong Dai more than expected).
Fields of papers citing papers by Tinglong Dai
This network shows the impact of papers produced by Tinglong Dai. 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 Tinglong Dai. The network helps show where Tinglong Dai may publish in the future.
Co-authors
The 25 scholars most cited alongside Tinglong Dai, 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 79 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 160 | |
| 2 | 2019 | 98 | |
| 3 | 2016 | 88 | |
| 4 | 2021 | 67 | |
| 5 | 2013 | 66 | |
| 6 | 2016 | 54 | |
| 7 | 2023 | 40 | |
| 8 | 2019 | 39 | |
| 9 | 2022 | 37 | |
| 10 | 2020 | 36 | |
| 11 | 2020 | 36 | |
| 12 | 2022 | 34 | |
| 13 | 2016 | 27 | |
| 14 | 2019 | 26 | |
| 15 | 2005 | 23 | |
| 16 | 2019 | 22 | |
| 17 | 2020 | 18 | |
| 18 | 2025 | 18 | |
| 19 | 2010 | 16 | |
| 20 | 2016 | 15 |
About Tinglong Dai
Tinglong Dai is a scholar working on Management Information Systems, Economics and Econometrics, Management Science and Operations Research, Marketing and Health Informatics, having authored 79 papers that have together received 1.2k indexed citations. Recurring topics across this work include Auction Theory and Applications (17 papers), Supply Chain and Inventory Management (16 papers), Artificial Intelligence in Healthcare and Education (13 papers), Consumer Market Behavior and Pricing (11 papers), Healthcare Policy and Management (9 papers), COVID-19 epidemiological studies (6 papers), Healthcare Operations and Scheduling Optimization (6 papers) and Game Theory and Voting Systems (5 papers). The work is most often cited by research in Health Informatics (76 citations), Management Information Systems (378 citations), Marketing (252 citations), Modeling and Simulation (84 citations) and Strategy and Management (282 citations). Tinglong Dai has collaborated with scholars based in United States, China and Hong Kong. Frequent co-authors include Sridhar Tayur, Christopher S. Tang, Kinshuk Jerath, Fuqiang Zhang, Soo-Haeng Cho, Ying‐Ju Chen, C. Gizem Korpeoglu, Özge Şahin, Ersin Körpeoğlu and Ronghuo Zheng. Their work appears in journals such as Manufacturing & Service Operations Management, npj Digital Medicine, Management Science, Production and Operations Management and Marketing Science.
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.