Maya Yankelevich

18 total papers · 544 total citations
7 papers, 378 citations indexed

About

Maya Yankelevich is a scholar working on Organizational Behavior and Human Resource Management, Sociology and Political Science and Social Psychology. According to data from OpenAlex, Maya Yankelevich has authored 7 papers receiving a total of 378 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Organizational Behavior and Human Resource Management, 3 papers in Sociology and Political Science and 2 papers in Social Psychology. Recurrent topics in Maya Yankelevich's work include Job Satisfaction and Organizational Behavior (3 papers), Psychology of Social Influence (2 papers) and Social and Intergroup Psychology (1 paper). Maya Yankelevich is often cited by papers focused on Job Satisfaction and Organizational Behavior (3 papers), Psychology of Social Influence (2 papers) and Social and Intergroup Psychology (1 paper). Maya Yankelevich collaborates with scholars based in United States. Maya Yankelevich's co-authors include Patricia B. Barger, Charlotte Fritz, Scott Highhouse, Michael J. Zickar, Dalia L. Diab, Michael A. Gillespie, Ashley M. Guidroz and Jennifer Z. Gillespie and has published in prestigious journals such as Journal of Applied Psychology, Journal of Vocational Behavior and Stress and Health.

In The Last Decade

Maya Yankelevich

7 papers receiving 341 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Maya Yankelevich 176 163 138 83 54 7 378
Alex J. Barelka 195 1.1× 193 1.2× 119 0.9× 52 0.6× 44 0.8× 12 439
Ralph van den Bosch 204 1.2× 185 1.1× 106 0.8× 51 0.6× 70 1.3× 6 358
Greg A. Chung‐Yan 169 1.0× 134 0.8× 163 1.2× 75 0.9× 40 0.7× 16 386
Ashley Elizabeth Hardin 221 1.3× 153 0.9× 116 0.8× 54 0.7× 114 2.1× 10 442
Sabine Korek 148 0.8× 83 0.5× 67 0.5× 59 0.7× 55 1.0× 11 366
Jenny Liao 215 1.2× 150 0.9× 76 0.6× 66 0.8× 36 0.7× 14 424
Jake Gale 132 0.8× 112 0.7× 142 1.0× 40 0.5× 45 0.8× 7 358
Anna Imus 140 0.8× 109 0.7× 107 0.8× 80 1.0× 100 1.9× 7 413
David Joseph Keating 217 1.2× 111 0.7× 130 0.9× 44 0.5× 60 1.1× 3 381
Joseph T. Liu 209 1.2× 106 0.7× 116 0.8× 62 0.7× 28 0.5× 10 358

Countries citing papers authored by Maya Yankelevich

Since Specialization
Citations

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

Fields of papers citing papers by Maya Yankelevich

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Maya Yankelevich

This figure shows the co-authorship network connecting the top 25 collaborators of Maya Yankelevich. A scholar is included among the top collaborators of Maya Yankelevich 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 Maya Yankelevich. Maya Yankelevich is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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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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