Gianfranco d’Atri
Impact in
- Theoretical Computer Science top 5%
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- Supply Chain and Inventory Management
Papers in
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- Mathematical and Theoretical Analysis 7
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- History and Theory of Mathematics 4
- Co-authors
- Francesco Longo (1 shared paper)Antonio Padovano (1 shared paper)Letizia Nicoletti (1 shared paper)Fabio Caldarola (8 shared papers)Claude P. Puech (1 shared paper)Mario Maiolo (3 shared papers)Giuseppe Pirillo (2 shared papers)
In The Last Decade
Gianfranco d’Atri
12 papers receiving 378 citations
Gianfranco d’Atri's Hit Papers
Peers
Comparison fields: 5 of 56
- Theoretical Computer Science 23
- Management Information Systems 116
- Information Systems 258
- Strategy and Management 118
- Mathematical Physics 48
Countries citing papers authored by Gianfranco d’Atri
This map shows the geographic impact of Gianfranco d’Atri'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 Gianfranco d’Atri with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gianfranco d’Atri more than expected).
Fields of papers citing papers by Gianfranco d’Atri
This network shows the impact of papers produced by Gianfranco d’Atri. 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 Gianfranco d’Atri. The network helps show where Gianfranco d’Atri may publish in the future.
Co-authors
The 7 scholars most cited alongside Gianfranco d’Atri, 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 | Blockchain-enabled supply chain: An experimental study Hit paper breakdown → | 2019 | 302 |
| 2 | 1982 | 17 | |
| 3 | 2020 | 15 | |
| 4 | 2020 | 14 | |
| 5 | 2020 | 13 | |
| 6 | 2022 | 13 | |
| 7 | 2020 | 9 | |
| 8 | 2022 | 6 | |
| 9 | 2020 | 6 | |
| 10 | 1980 | 2 | |
| 11 | 2024 | 2 | |
| 12 | 2020 | 1 | |
| 13 | 2020 | 1 | |
| 14 | 1978 | 0 |
About Gianfranco d’Atri
Gianfranco d’Atri is a scholar working on Mathematical Physics, Theoretical Computer Science, Computational Theory and Mathematics, Industrial and Manufacturing Engineering and Statistical and Nonlinear Physics, having authored 14 papers that have together received 401 indexed citations. Recurring topics across this work include Mathematical and Theoretical Analysis (7 papers), History and Theory of Mathematics (4 papers), Computability, Logic, AI Algorithms (3 papers), Numerical Methods and Algorithms (3 papers), Rough Sets and Fuzzy Logic (2 papers), Blockchain Technology Applications and Security (2 papers), Advanced Mathematical Theories and Applications (2 papers) and Vehicle Routing Optimization Methods (2 papers). The work is most often cited by research in Theoretical Computer Science (23 citations), Management Information Systems (116 citations), Information Systems (258 citations), Strategy and Management (118 citations) and Mathematical Physics (48 citations). Gianfranco d’Atri has collaborated with scholars based in Italy, France and Cyprus. Frequent co-authors include Francesco Longo, Antonio Padovano, Letizia Nicoletti, Fabio Caldarola, Claude P. Puech, Mario Maiolo and Giuseppe Pirillo. Their work appears in journals such as Soft Computing, Discrete Applied Mathematics, Mathematical Programming, Computers & Industrial Engineering and Lecture notes in computer 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.