Xiaojing Cai
Impact in
-
- scientometrics and bibliometrics research
- Modeling and Simulation top 5%
- COVID-19 epidemiological studies
Papers in
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- Market Dynamics and Volatility 12
- COVID-19 Pandemic Impacts 4
- Energy, Environment, Economic Growth 3
- Finance 10
- Financial Risk and Volatility Modeling 4
- Global Financial Crisis and Policies 4
- Co-authors
- Caroline S. Wagner (8 shared papers)Caroline Fry (7 shared papers)Yi Zhang (5 shared papers)Shigeyuki Hamori (6 shared papers)Zhou Ping (3 shared papers)Lu Yang (3 shared papers)Mengjia Wu (1 shared paper)Wei Yang (1 shared paper)
- Journals
- Scientometrics (4 papers)PLoS ONE (2 papers)Energies (2 papers)Plant Biology (1 paper)Journal of Forecasting (1 paper)
- Partner nations
- ChinaJapanUnited States
In The Last Decade
Xiaojing Cai
35 papers receiving 452 citations
Peers
Comparison fields: 5 of 114
- Statistics, Probability and Uncertainty 71
- Modeling and Simulation 45
- Health Informatics 12
- Information Systems and Management 41
- General Energy 5
Countries citing papers authored by Xiaojing Cai
This map shows the geographic impact of Xiaojing Cai'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 Xiaojing Cai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xiaojing Cai more than expected).
Fields of papers citing papers by Xiaojing Cai
This network shows the impact of papers produced by Xiaojing Cai. 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 Xiaojing Cai. The network helps show where Xiaojing Cai may publish in the future.
Co-authors
The 25 scholars most cited alongside Xiaojing Cai, 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 38 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 103 | |
| 2 | 2021 | 76 | |
| 3 | 2021 | 41 | |
| 4 | 2020 | 35 | |
| 5 | 2021 | 33 | |
| 6 | 2019 | 19 | |
| 7 | 2022 | 17 | |
| 8 | 2020 | 13 | |
| 9 | 2022 | 13 | |
| 10 | 2020 | 12 | |
| 11 | 2020 | 12 | |
| 12 | 2019 | 9 | |
| 13 | 2022 | 8 | |
| 14 | 2023 | 7 | |
| 15 | 2025 | 7 | |
| 16 | 2022 | 7 | |
| 17 | 2023 | 6 | |
| 18 | 2020 | 6 | |
| 19 | 2020 | 6 | |
| 20 | 2023 | 5 |
About Xiaojing Cai
Xiaojing Cai is a scholar working on Economics and Econometrics, Finance, General Economics, Econometrics and Finance, Statistics, Probability and Uncertainty and Modeling and Simulation, having authored 38 papers that have together received 463 indexed citations. Recurring topics across this work include Market Dynamics and Volatility (12 papers), COVID-19 epidemiological studies (7 papers), scientometrics and bibliometrics research (7 papers), Monetary Policy and Economic Impact (7 papers), Financial Risk and Volatility Modeling (4 papers), COVID-19 Pandemic Impacts (4 papers), Global Financial Crisis and Policies (4 papers) and Energy, Environment, Economic Growth (3 papers). The work is most often cited by research in Statistics, Probability and Uncertainty (71 citations), Modeling and Simulation (45 citations), Health Informatics (12 citations), Information Systems and Management (41 citations) and General Energy (5 citations). Xiaojing Cai has collaborated with scholars based in China, Japan and United States. Frequent co-authors include Caroline S. Wagner, Caroline Fry, Yi Zhang, Shigeyuki Hamori, Zhou Ping, Lu Yang, Mengjia Wu, Wei Yang, Shuairu Tian and Zhaojie Luo. Their work appears in journals such as Scientometrics, PLoS ONE, Energies, Plant Biology and Journal of Forecasting.
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.