Mark Cecchini
Impact in
- Accounting top 2%
- Auditing, Earnings Management, Governance
- Financial Distress and Bankruptcy Prediction
- Corporate Finance and Governance
- Corporate Taxation and Avoidance
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- Stock Market Forecasting Methods
Papers in
- Accounting 11
- Auditing, Earnings Management, Governance 6
- Corporate Taxation and Avoidance 4
- Corporate Finance and Governance 3
- Financial Distress and Bankruptcy Prediction 2
- Islamic Finance and Banking Studies 2
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- Financial Reporting and Valuation Research 4
- Co-authors
- Gary J. Kœhler (3 shared papers)Haldun Aytuğ (2 shared papers)Praveen Pathak (2 shared papers)Robert A. Leitch (3 shared papers)Anna M. Cianci (2 shared papers)Scott B. Jackson (2 shared papers)Xiaotao Liu (2 shared papers)John L. Campbell (2 shared papers)
- Journals
- Review of Accounting Studies (2 papers)Decision Support Systems (1 paper)Management Science (1 paper)European Journal of Operational Research (1 paper)Accounting Organizations and Society (1 paper)
- Partner nations
- United States
In The Last Decade
Mark Cecchini
10 papers receiving 520 citations
Peers
Comparison fields: 5 of 63
- Accounting 362
- Management Science and Operations Research 120
- Finance 82
- Artificial Intelligence 234
- Management Information Systems 59
Countries citing papers authored by Mark Cecchini
This map shows the geographic impact of Mark Cecchini'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 Mark Cecchini with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mark Cecchini more than expected).
Fields of papers citing papers by Mark Cecchini
This network shows the impact of papers produced by Mark Cecchini. 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 Mark Cecchini. The network helps show where Mark Cecchini may publish in the future.
Co-authors
The 12 scholars most cited alongside Mark Cecchini, 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 | 2010 | 238 | |
| 2 | 2010 | 184 | |
| 3 | 2018 | 41 | |
| 4 | 2013 | 26 | |
| 5 | 2013 | 25 | |
| 6 | 2009 | 14 | |
| 7 | 2017 | 11 | |
| 8 | 2011 | 10 | |
| 9 | Quantifying the risk of financial events using kernel methods and information retrieval | 2005 | 6 |
| 10 | 2015 | 1 | |
| 11 | 2023 | 0 | |
| 12 | 2016 | 0 |
About Mark Cecchini
Mark Cecchini is a scholar working on Accounting, Strategy and Management, Management Science and Operations Research, Artificial Intelligence and Economics and Econometrics, having authored 12 papers that have together received 556 indexed citations. Recurring topics across this work include Auditing, Earnings Management, Governance (6 papers), Corporate Taxation and Avoidance (4 papers), Financial Reporting and Valuation Research (4 papers), Stock Market Forecasting Methods (3 papers), Corporate Finance and Governance (3 papers), Financial Distress and Bankruptcy Prediction (2 papers), Taxation and Compliance Studies (2 papers) and Islamic Finance and Banking Studies (2 papers). The work is most often cited by research in Accounting (362 citations), Management Science and Operations Research (120 citations), Finance (82 citations), Artificial Intelligence (234 citations) and Management Information Systems (59 citations). Mark Cecchini has collaborated with scholars based in United States. Frequent co-authors include Gary J. Kœhler, Haldun Aytuğ, Praveen Pathak, Robert A. Leitch, Anna M. Cianci, Scott B. Jackson, Xiaotao Liu, John L. Campbell, J. G. Ecker and Marcus L. Caylor. Their work appears in journals such as Review of Accounting Studies, Decision Support Systems, Management Science, European Journal of Operational Research and Accounting Organizations and Society.
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.