F. Javier Lerch

46 total papers · 1.6k total citations
38 papers, 909 citations indexed

About

F. Javier Lerch is a scholar working on Artificial Intelligence, Management Science and Operations Research and Social Psychology. According to data from OpenAlex, F. Javier Lerch has authored 38 papers receiving a total of 909 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Artificial Intelligence, 8 papers in Management Science and Operations Research and 7 papers in Social Psychology. Recurrent topics in F. Javier Lerch's work include Team Dynamics and Performance (7 papers), Complex Systems and Decision Making (6 papers) and Cognitive Science and Mapping (5 papers). F. Javier Lerch is often cited by papers focused on Team Dynamics and Performance (7 papers), Complex Systems and Decision Making (6 papers) and Cognitive Science and Mapping (5 papers). F. Javier Lerch collaborates with scholars based in United States, Germany and Canada. F. Javier Lerch's co-authors include Mark Fichman, Donald E. Harter, Paul S. Goodman, Robert E. Kraut, Susan R. Fussell, J. J. Cadiz, Jörn Lötsch, Alfred Ultsch, William L. Scherlis and Jinwoo Kim and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of the American Statistical Association and Academy of Management Journal.

In The Last Decade

F. Javier Lerch

35 papers receiving 800 citations

Author Peers

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

Author Last Decade Papers Cites
F. Javier Lerch 155 154 131 127 124 38 909
David W. Conrath 150 1.0× 152 1.0× 113 0.9× 112 0.9× 165 1.3× 48 846
Paweł Korzyński 139 0.9× 229 1.5× 84 0.6× 154 1.2× 272 2.2× 41 1.0k
Ajay Vinzé 220 1.4× 180 1.2× 105 0.8× 94 0.7× 187 1.5× 67 999
Jun-Gi Park 124 0.8× 109 0.7× 104 0.8× 194 1.5× 179 1.4× 28 787
Luca Iandoli 129 0.8× 169 1.1× 66 0.5× 95 0.7× 284 2.3× 54 1.0k
Hind Benbya 229 1.5× 168 1.1× 56 0.4× 74 0.6× 225 1.8× 42 959
Roy Gelbard 83 0.5× 194 1.3× 98 0.7× 270 2.1× 74 0.6× 42 998
Raymond McLeod 290 1.9× 169 1.1× 81 0.6× 148 1.2× 126 1.0× 46 892
Richard T. Herschel 256 1.7× 147 1.0× 76 0.6× 72 0.6× 106 0.9× 23 860
Richard E. Potter 108 0.7× 64 0.4× 227 1.7× 158 1.2× 191 1.5× 28 824

Countries citing papers authored by F. Javier Lerch

Since Specialization
Citations

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

Fields of papers citing papers by F. Javier Lerch

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by F. Javier Lerch. 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 F. Javier Lerch. The network helps show where F. Javier Lerch may publish in the future.

Co-authorship network of co-authors of F. Javier Lerch

This figure shows the co-authorship network connecting the top 25 collaborators of F. Javier Lerch. A scholar is included among the top collaborators of F. Javier Lerch 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 F. Javier Lerch. F. Javier Lerch 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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