Tamar Avnet

18 papers receiving 436 citations

Peers

Tamar Avnet
Comparison fields: 5 of 58
  • Applied Psychology 203
  • General Decision Sciences 61
  • Marketing 231
  • Information Systems and Management 44
  • Organizational Behavior and Human Resource Management 55
Replace Dengfeng Yan with:
Dengfeng Yan Hong Kong
Adriana Samper United States
Tilottama G. Chowdhury United States
Leilei Gao Hong Kong
Daniella Kupor United States
Anastasiya Pocheptsova United States
Lisa A. Cavanaugh United States
Rod Duclos United States
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Citations per field
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Citations per year

Countries citing papers authored by Tamar Avnet

Since Specialization
Citations

This map shows the geographic impact of Tamar Avnet'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 Tamar Avnet with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tamar Avnet more than expected).

Fields of papers citing papers by Tamar Avnet

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Tamar Avnet. 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 Tamar Avnet. The network helps show where Tamar Avnet may publish in the future.

Co-authors

The 15 scholars most cited alongside Tamar Avnet, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Tamar Avnet Line = papers co-authored together Tamar Avnet links everyone, so they are left out of the graph.

All Works

19 of 19 papers shown
#Work
1 2013130
2 201277
3 201269
4 200464
5 200629
6 200629
7 200319
8 20148
9 20186
10 20086
11 20216
12 20105
13 20044
14
Smiles Lead to More Smiles Unless They Lead to Tears: a Meta-Analytic Integration of Affect Effects
20152
15 20091
16 20211
17 20141
18 20101
19 20230

About Tamar Avnet

Tamar Avnet is a scholar working on Applied Psychology, Sociology and Political Science, Marketing, Social Psychology and General Decision Sciences, having authored 19 papers that have together received 458 indexed citations. Recurring topics across this work include Behavioral Health and Interventions (12 papers), Consumer Behavior in Brand Consumption and Identification (6 papers), Social and Intergroup Psychology (5 papers), Decision-Making and Behavioral Economics (4 papers), Cultural Differences and Values (3 papers), Psychology of Social Influence (2 papers), Psychology of Moral and Emotional Judgment (2 papers) and Creativity in Education and Neuroscience (2 papers). The work is most often cited by research in Applied Psychology (203 citations), General Decision Sciences (61 citations), Marketing (231 citations), Information Systems and Management (44 citations) and Organizational Behavior and Human Resource Management (55 citations). Tamar Avnet has collaborated with scholars based in United States, Canada and New Zealand. Frequent co-authors include E. Tory Higgins, Michel Tuan Pham, Daniel Laufer, Andrew T. Stephen, Nancy M. Puccinelli, Dhruv Grewal, Scott Motyka, Ahmad Daryanto, Anne L. Roggeveen and Ko de Ruyter. Their work appears in journals such as Journal of Consumer Psychology, Journal of Consumer Research, Journal of Marketing Research, Journal of Personality and Social Psychology and Business Horizons.

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.

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