Pasumarti V. Kamesam
Impact in
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- Supply Chain and Inventory Management
- Quality and Supply Management
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- Risk and Portfolio Optimization
- Forecasting Techniques and Applications
- Multi-Criteria Decision Making
Papers in
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- Biomedical Text Mining and Ontologies 2
- Gene expression and cancer classification 1
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- Supply Chain and Inventory Management 2
- Advanced Queuing Theory Analysis 1
- Co-authors
- Laureano F. Escudero (2 shared papers)Alan J. King (1 shared paper)Roger J.‐B. Wets (1 shared paper)Paul R. Kleindorfer (1 shared paper)Hau L. Lee (1 shared paper)Morris A. Cohen (1 shared paper)Paul B. Chou (1 shared paper)Dimitrios Gunopulos (1 shared paper)
- Journals
- Top (1 paper)Production and Operations Management (1 paper)INFORMS Journal on Applied Analytics (1 paper)Annals of Operations Research (1 paper)
- Partner nations
- United StatesIndiaSpain
In The Last Decade
Pasumarti V. Kamesam
7 papers receiving 355 citations
Peers
Comparison fields: 5 of 66
- Management Information Systems 192
- Management Science and Operations Research 126
- Industrial and Manufacturing Engineering 97
- Strategy and Management 73
- Marketing 32
Countries citing papers authored by Pasumarti V. Kamesam
This map shows the geographic impact of Pasumarti V. Kamesam'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 Pasumarti V. Kamesam with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pasumarti V. Kamesam more than expected).
Fields of papers citing papers by Pasumarti V. Kamesam
This network shows the impact of papers produced by Pasumarti V. Kamesam. 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 Pasumarti V. Kamesam. The network helps show where Pasumarti V. Kamesam may publish in the future.
Co-authors
The 17 scholars most cited alongside Pasumarti V. Kamesam, 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 | 1993 | 147 | |
| 2 | 1990 | 146 | |
| 3 | 2000 | 31 | |
| 4 | 2003 | 30 | |
| 5 | 1995 | 22 | |
| 6 | 2003 | 7 | |
| 7 | 2002 | 4 |
About Pasumarti V. Kamesam
Pasumarti V. Kamesam is a scholar working on Molecular Biology, Management Information Systems, Control and Systems Engineering, Management Science and Operations Research and Numerical Analysis, having authored 7 papers that have together received 387 indexed citations. Recurring topics across this work include Supply Chain and Inventory Management (2 papers), Optimization and Mathematical Programming (2 papers), Biomedical Text Mining and Ontologies (2 papers), Risk and Portfolio Optimization (2 papers), Advanced Queuing Theory Analysis (1 paper), Insurance and Financial Risk Management (1 paper), Web Data Mining and Analysis (1 paper) and Gene expression and cancer classification (1 paper). The work is most often cited by research in Management Information Systems (192 citations), Management Science and Operations Research (126 citations), Industrial and Manufacturing Engineering (97 citations), Strategy and Management (73 citations) and Marketing (32 citations). Pasumarti V. Kamesam has collaborated with scholars based in United States, India and Spain. Frequent co-authors include Laureano F. Escudero, Alan J. King, Roger J.‐B. Wets, Paul R. Kleindorfer, Hau L. Lee, Morris A. Cohen, Paul B. Chou, Dimitrios Gunopulos, Biplav Srivastava and Vishal Batra. Their work appears in journals such as Top, Production and Operations Management, INFORMS Journal on Applied Analytics and Annals of Operations Research.
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.