Yan Meng
- Accounting top 2%
- Finance top 2%
- Economics and Econometrics top 5%
- Strategy and Management top 10%
- Artificial Intelligence
- Co-authors
- Emma Y. PengRobert DeYoungBill B. FrancisQiang WuIftekhar HasanYuan XieMarlene PlumleeJeff Jiewei Yu
- Topics
- Corporate Finance and Governance (15 papers)Banking stability, regulation, efficiency (7 papers)Auditing, Earnings Management, Governance (5 papers)
- Partner nations
- United StatesChinaFinland
In The Last Decade
Yan Meng
37 papers receiving 726 citations
Peers
Comparison fields: 5 of 67
- Accounting 529
- Finance 302
- Economics and Econometrics 226
- Strategy and Management 117
- Artificial Intelligence 86
Countries citing papers authored by Yan Meng
This map shows the geographic impact of Yan Meng'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 Yan Meng with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yan Meng more than expected).
Fields of papers citing papers by Yan Meng
This network shows the impact of papers produced by Yan Meng. 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 Yan Meng. The network helps show where Yan Meng may publish in the future.
Co-authorship network of co-authors of Yan Meng
This figure shows the co-authorship network connecting the top 25 collaborators of Yan Meng. A scholar is included among the top collaborators of Yan Meng 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 Yan Meng. Yan Meng is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 3 | |
| 3 | 0 | |
| 4 | 1 | |
| 5 | 3 | |
| 6 | 1 | |
| 7 | 4 | |
| 8 | Radical or Incremental Innovations – R&D Investment Around CEO Retirement | 2 |
| 9 | R&D Cuts and Subsequent Reversals: Meeting or Beating Quarterly Analyst Forecasts | 0 |
| 10 | 155 | |
| 11 | 23 | |
| 12 | 14 | |
| 13 | 5 | |
| 14 | 1 | |
| 15 | 2 | |
| 16 | The value and indicator function of patents | 14 |
| 17 | Pending Approval Patents, Proprietary Information, and Bank Loan Spread | 1 |
| 18 | Executive Compensation and Policy Choices at U.S. Commercial Banks | 7 |
| 19 | Toward Evolving Neural Networks using Bio-Inspired Algorithms. | 16 |
| 20 | 8 |
About Yan Meng
Yan Meng is a scholar working on Accounting, Finance and Artificial Intelligence, having authored 42 papers that have together received 777 indexed citations. Recurring topics across this work include Corporate Finance and Governance (15 papers), Banking stability, regulation, efficiency (7 papers) and Auditing, Earnings Management, Governance (5 papers). The work is most often cited by research in Accounting (529 citations), Finance (302 citations) and Economics and Econometrics (226 citations). Yan Meng has collaborated with scholars based in United States, China and Finland. Frequent co-authors include Emma Y. Peng, Robert DeYoung, Bill B. Francis, Qiang Wu, Iftekhar Hasan, Yuan Xie, Marlene Plumlee, Jeff Jiewei Yu, Jun Yin and Hongliang Guo. Their work appears in journals such as Bioinformatics, IEEE Access and Neurocomputing.
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.