Nina Mažar
- Safety Research top 0.5%
- Sociology and Political Science top 2%
- Marketing top 1%
- Economics and Econometrics top 2%
- Cognitive Neuroscience top 5%
- Co-authors
- Dan ArielyChen‐Bo ZhongUri GneezyGeorge LoewensteinOn AmirPankaj AggarwalJennifer JordanSonya Sachdeva
- Topics
- Experimental Behavioral Economics Studies (19 papers)Decision-Making and Behavioral Economics (17 papers)Psychology of Moral and Emotional Judgment (14 papers)
- Journals
- Proceedings of the National Academy of SciencesJournal of Clinical InvestigationJournal of Marketing
- Partner nations
- United StatesCanadaUnited Kingdom
In The Last Decade
Nina Mažar
52 papers receiving 2.7k citations
Hit Papers
Peers
Comparison fields: 5 of 139
- Safety Research 711
- Sociology and Political Science 692
- Marketing 651
- Economics and Econometrics 604
- Cognitive Neuroscience 558
Countries citing papers authored by Nina Mažar
This map shows the geographic impact of Nina Mažar'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 Nina Mažar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nina Mažar more than expected).
Fields of papers citing papers by Nina Mažar
This network shows the impact of papers produced by Nina Mažar. 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 Nina Mažar. The network helps show where Nina Mažar may publish in the future.
Co-authorship network of co-authors of Nina Mažar
This figure shows the co-authorship network connecting the top 25 collaborators of Nina Mažar. A scholar is included among the top collaborators of Nina Mažar 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 Nina Mažar. Nina Mažar is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 1 | |
| 3 | 1 | |
| 4 | 10 | |
| 5 | 0 | |
| 6 | 15 | |
| 7 | 15 | |
| 8 | 25 | |
| 9 | 13 | |
| 10 | 8 | |
| 11 | Motivating Bureaucrats Through Social Recognition: External Validity — A Tale of Two States | 0 |
| 12 | 18 | |
| 13 | 1 | |
| 14 | Removing Individuals' License to Misbehave | 2 |
| 15 | 12 | |
| 16 | Greasing the Palm: Can Collectivism Promote Bribery? | 5 |
| 17 | Being Hot Or Being Cold: the Influence of Temperature on Judgment and Choice | 3 |
| 18 | Sequential Influences on Dishonest Behavior | 3 |
| 19 | Do Green Products Make Us Better People | 10 |
| 20 | 266 |
About Nina Mažar
Nina Mažar is a scholar working on General Decision Sciences, Safety Research and Information Systems and Management, having authored 62 papers that have together received 2.9k indexed citations. Recurring topics across this work include Experimental Behavioral Economics Studies (19 papers), Decision-Making and Behavioral Economics (17 papers) and Psychology of Moral and Emotional Judgment (14 papers). The work is most often cited by research in General Decision Sciences (459 citations), Safety Research (711 citations) and Marketing (651 citations). Nina Mažar has collaborated with scholars based in United States, Canada and United Kingdom. Frequent co-authors include Dan Ariely, Chen‐Bo Zhong, Uri Gneezy, George Loewenstein, On Amir, Pankaj Aggarwal, Jennifer Jordan, Sonya Sachdeva, Mara Mather and Andrej Schoeke. Their work appears in journals such as Proceedings of the National Academy of Sciences, Journal of Clinical Investigation and Journal of Marketing.
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.