Rashmi Malhotra
- Accounting top 5%
- Artificial Intelligence top 5%
- Finance top 5%
- Management Science and Operations Research top 5%
- Management Information Systems top 10%
- Co-authors
- D.K. MalhotraManu MalhotraRonald K. KlimbergSarama SahaSaurabh VarshneyMinakshi DharMonika PathaniaRajani Singh
- Topics
- Financial Distress and Bankruptcy Prediction (6 papers)Credit Risk and Financial Regulations (4 papers)Efficiency Analysis Using DEA (4 papers)
- Journals
- SHILAP Revista de lepidopterologíaEuropean Journal of Operational ResearchKnowledge-Based Systems
- Partner nations
- United StatesIndiaAustralia
In The Last Decade
Rashmi Malhotra
30 papers receiving 482 citations
Peers
Comparison fields: 5 of 81
- Accounting 323
- Artificial Intelligence 297
- Finance 121
- Management Science and Operations Research 112
- Management Information Systems 62
Countries citing papers authored by Rashmi Malhotra
This map shows the geographic impact of Rashmi Malhotra'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 Rashmi Malhotra with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Rashmi Malhotra more than expected).
Fields of papers citing papers by Rashmi Malhotra
This network shows the impact of papers produced by Rashmi Malhotra. 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 Rashmi Malhotra. The network helps show where Rashmi Malhotra may publish in the future.
Co-authorship network of co-authors of Rashmi Malhotra
This figure shows the co-authorship network connecting the top 25 collaborators of Rashmi Malhotra. A scholar is included among the top collaborators of Rashmi Malhotra 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 Rashmi Malhotra. Rashmi Malhotra is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 0 | |
| 3 | 8 | |
| 4 | 4 | |
| 5 | 0 | |
| 6 | 2 | |
| 7 | 2 | |
| 8 | Travel Time Prediction in Ride-Sourcing Networks: A Case Study for Machine Learning Applications | 3 |
| 9 | 1 | |
| 10 | A Modified Technique of Rhinoplasty UsingCortical Bone Graft to Correct Saddle NoseDeformity with Loss of Septal Cartilage | 1 |
| 11 | 1 | |
| 12 | 4 | |
| 13 | 3 | |
| 14 | 13 | |
| 15 | 24 | |
| 16 | 15 | |
| 17 | Extensible Business Reporting Language: The Future of E-Commerce-Driven Accounting | 10 |
| 18 | 208 | |
| 19 | 1 | |
| 20 | 4 |
About Rashmi Malhotra
Rashmi Malhotra is a scholar working on Otorhinolaryngology, Management Information Systems and Management Science and Operations Research, having authored 34 papers that have together received 532 indexed citations. Recurring topics across this work include Financial Distress and Bankruptcy Prediction (6 papers), Credit Risk and Financial Regulations (4 papers) and Efficiency Analysis Using DEA (4 papers). The work is most often cited by research in Accounting (323 citations), Finance (121 citations) and Artificial Intelligence (297 citations). Rashmi Malhotra has collaborated with scholars based in United States, India and Australia. Frequent co-authors include D.K. Malhotra, Manu Malhotra, Ronald K. Klimberg, Sarama Saha, Saurabh Varshney, Minakshi Dhar, Monika Pathania, Rajani Singh, Joseph M. Mellichamp and Kanchan Bisht. Their work appears in journals such as SHILAP Revista de lepidopterología, European Journal of Operational Research and Knowledge-Based 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.