Alexander Sigov
Impact in
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- Digital Transformation in Industry
- Manufacturing Process and Optimization
- Management Information Systems top 10%
- Big Data and Business Intelligence
Papers in
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- Quantum Computing Algorithms and Architecture 3
- Quantum Information and Cryptography 2
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- Cloud Computing and Resource Management 2
- Blockchain Technology Applications and Security 2
- Co-authors
- Leonid Ratkin (7 shared papers)L.A. Ivanov (7 shared papers)Li Da Xu (1 shared paper)Yang Lu (2 shared papers)Ling Li (1 shared paper)Wei Lü (1 shared paper)Jin Li (1 shared paper)Junfang Fan (1 shared paper)
- Journals
- Journal of Industrial Information Integration (4 papers)Journal of Management Analytics (1 paper)Information Systems Frontiers (1 paper)Future Generation Computer Systems (1 paper)
- Partner nations
- RussiaChinaUnited States
In The Last Decade
Alexander Sigov
7 papers receiving 240 citations
Alexander Sigov's Hit Papers
Peers
Comparison fields: 5 of 72
- Industrial and Manufacturing Engineering 85
- Management Information Systems 39
- Management of Technology and Innovation 20
- Health Informatics 3
- Artificial Intelligence 59
Countries citing papers authored by Alexander Sigov
This map shows the geographic impact of Alexander Sigov'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 Alexander Sigov with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Alexander Sigov more than expected).
Fields of papers citing papers by Alexander Sigov
This network shows the impact of papers produced by Alexander Sigov. 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 Alexander Sigov. The network helps show where Alexander Sigov may publish in the future.
Co-authors
The 10 scholars most cited alongside Alexander Sigov, 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 | Emerging Enabling Technologies for Industry 4.0 and Beyond Hit paper breakdown → | 2022 | 146 |
| 2 | 2023 | 33 | |
| 3 | 2023 | 29 | |
| 4 | 2022 | 24 | |
| 5 | 2024 | 10 | |
| 6 | 2024 | 2 | |
| 7 | 2022 | 2 |
About Alexander Sigov
Alexander Sigov is a scholar working on Artificial Intelligence, Information Systems, Computer Networks and Communications, Industrial and Manufacturing Engineering and Atomic and Molecular Physics, and Optics, having authored 7 papers that have together received 246 indexed citations. Recurring topics across this work include Quantum Computing Algorithms and Architecture (3 papers), IoT and Edge/Fog Computing (2 papers), Cloud Computing and Resource Management (2 papers), Blockchain Technology Applications and Security (2 papers), Digital Transformation in Industry (2 papers), Quantum Information and Cryptography (2 papers), Machine Learning in Materials Science (1 paper) and Financial Distress and Bankruptcy Prediction (1 paper). The work is most often cited by research in Industrial and Manufacturing Engineering (85 citations), Management Information Systems (39 citations), Management of Technology and Innovation (20 citations), Health Informatics (3 citations) and Artificial Intelligence (59 citations). Alexander Sigov has collaborated with scholars based in Russia, China and United States. Frequent co-authors include Leonid Ratkin, L.A. Ivanov, Li Da Xu, Yang Lu, Ling Li, Wei Lü, Jin Li, Junfang Fan, Li Da Xu and Caiming Zhang. Their work appears in journals such as Journal of Industrial Information Integration, Journal of Management Analytics, Information Systems Frontiers and Future Generation Computer Systems.
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.