Uma R. Karmarkar
- Cognitive Neuroscience top 2%
- Marketing top 2%
- Experimental and Cognitive Psychology top 5%
- Cellular and Molecular Neuroscience top 5%
- Sociology and Political Science top 5%
- Co-authors
- Dean V. BuonomanoZakary L. TormalaBryan BollingerYang DanHilke PlaßmannBrian KnutsonBaba ShivCarolyn Yoon
- Topics
- Decision-Making and Behavioral Economics (10 papers)Neural and Behavioral Psychology Studies (9 papers)Neural dynamics and brain function (8 papers)
- Partner nations
- United StatesNetherlandsCanada
In The Last Decade
Uma R. Karmarkar
33 papers receiving 2.0k citations
Peers
Comparison fields: 5 of 131
- Cognitive Neuroscience 1.2k
- Marketing 381
- Experimental and Cognitive Psychology 342
- Cellular and Molecular Neuroscience 340
- Sociology and Political Science 304
Countries citing papers authored by Uma R. Karmarkar
This map shows the geographic impact of Uma R. Karmarkar'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 Uma R. Karmarkar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Uma R. Karmarkar more than expected).
Fields of papers citing papers by Uma R. Karmarkar
This network shows the impact of papers produced by Uma R. Karmarkar. 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 Uma R. Karmarkar. The network helps show where Uma R. Karmarkar may publish in the future.
Co-authorship network of co-authors of Uma R. Karmarkar
This figure shows the co-authorship network connecting the top 25 collaborators of Uma R. Karmarkar. A scholar is included among the top collaborators of Uma R. Karmarkar 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 Uma R. Karmarkar. Uma R. Karmarkar is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 12 | |
| 3 | 10 | |
| 4 | 1 | |
| 5 | 4 | |
| 6 | 20 | |
| 7 | 1 | |
| 8 | 11 | |
| 9 | Planning to Binge: How Consumers Choose to Allocate Time to View Sequential Versus Independent Media Content | 3 |
| 10 | 15 | |
| 11 | BYOB: How Bringing Your Own Shopping Bags Leads to Treating Yourself and the Environment | 0 |
| 12 | Note on Neuromarketing | 5 |
| 13 | 3 | |
| 14 | Accept Or Reject?: How Task Valence Interacts With Product Information Processing to Alter Purchase Decisions | 0 |
| 15 | 388 | |
| 16 | 157 | |
| 17 | 87 | |
| 18 | 98 | |
| 19 | 17 | |
| 20 | 13 |
About Uma R. Karmarkar
Uma R. Karmarkar is a scholar working on General Decision Sciences, Marketing and Cognitive Neuroscience, having authored 36 papers that have together received 2.1k indexed citations. Recurring topics across this work include Decision-Making and Behavioral Economics (10 papers), Neural and Behavioral Psychology Studies (9 papers) and Neural dynamics and brain function (8 papers). The work is most often cited by research in Cognitive Neuroscience (1.2k citations), General Decision Sciences (97 citations) and Marketing (381 citations). Uma R. Karmarkar has collaborated with scholars based in United States, Netherlands and Canada. Frequent co-authors include Dean V. Buonomano, Zakary L. Tormala, Bryan Bollinger, Yang Dan, Hilke Plaßmann, Brian Knutson, Baba Shiv, Carolyn Yoon, Alexander Peysakhovich and Rebecca M. C. Spencer. Their work appears in journals such as Neuron, Journal of Marketing and Management 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.