Pavol Ďurana
- Accounting top 2%
- Strategy and Management top 5%
- Economics and Econometrics top 5%
- Management Science and Operations Research top 5%
- Management, Monitoring, Policy and Law top 5%
- Co-authors
- Katarína ValáškováTomáš KlieštikPeter AdamkoElvira NicaPavol KráľLucia MichalkovaGeorge LăzăroiuAndrej Přívara
- Topics
- Impact of AI and Big Data on Business and Society (25 papers)Financial Reporting and Valuation Research (14 papers)Auditing, Earnings Management, Governance (14 papers)
In The Last Decade
Pavol Ďurana
52 papers receiving 1.2k citations
Hit Papers
Peers
Comparison fields: 5 of 111
- Accounting 436
- Strategy and Management 368
- Economics and Econometrics 335
- Management Science and Operations Research 207
- Management, Monitoring, Policy and Law 112
Countries citing papers authored by Pavol Ďurana
This map shows the geographic impact of Pavol Ďurana'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 Pavol Ďurana with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pavol Ďurana more than expected).
Fields of papers citing papers by Pavol Ďurana
This network shows the impact of papers produced by Pavol Ďurana. 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 Pavol Ďurana. The network helps show where Pavol Ďurana may publish in the future.
Co-authorship network of co-authors of Pavol Ďurana
This figure shows the co-authorship network connecting the top 25 collaborators of Pavol Ďurana. A scholar is included among the top collaborators of Pavol Ďurana 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 Pavol Ďurana. Pavol Ďurana 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 | 1 | |
| 3 | 12 | |
| 4 | Generative artificial intelligence of things systems, multisensory immersive extended reality technologies, and algorithmic big data simulation and modelling tools in digital twin industrial metaversebreakdown → | 60 |
| 5 | 1 | |
| 6 | 4 | |
| 7 | Artificial intelligence-based predictive maintenance, time-sensitive networking, and big data-driven algorithmic decision-making in the economics of Industrial Internet of Thingsbreakdown → | 88 |
| 8 | 6 | |
| 9 | 2 | |
| 10 | 1 | |
| 11 | 8 | |
| 12 | 7 | |
| 13 | 32 | |
| 14 | 46 | |
| 15 | 18 | |
| 16 | 19 | |
| 17 | 66 | |
| 18 | 74 | |
| 19 | 5 | |
| 20 | 0 |
About Pavol Ďurana
Pavol Ďurana is a scholar working on Management Science and Operations Research, Accounting and Strategy and Management, having authored 57 papers that have together received 1.3k indexed citations. Recurring topics across this work include Impact of AI and Big Data on Business and Society (25 papers), Financial Reporting and Valuation Research (14 papers) and Auditing, Earnings Management, Governance (14 papers). The work is most often cited by research in Accounting (436 citations), Strategy and Management (368 citations) and Management Science and Operations Research (207 citations). Pavol Ďurana has collaborated with scholars based in Slovakia, Czechia and Romania. Frequent co-authors include Katarína Valášková, Tomáš Klieštik, Peter Adamko, Elvira Nica, Pavol Kráľ, Lucia Michalkova, George Lăzăroiu, Andrej Přívara, Josef Maroušek and Gheorghe H. Popescu. Their work appears in journals such as SHILAP Revista de lepidopterología, Sensors and Energies.
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.