F. Javier Lerch
- Management Information Systems top 5%
- Artificial Intelligence top 10%
- Social Psychology top 10%
- Organizational Behavior and Human Resource Management top 5%
- Sociology and Political Science top 10%
- Co-authors
- Mark FichmanDonald E. HarterPaul S. GoodmanSusan R. FussellRobert E. KrautJörn LötschJ. J. CadizAlfred Ultsch
- Topics
- Team Dynamics and Performance (7 papers)Complex Systems and Decision Making (6 papers)Technology Adoption and User Behaviour (5 papers)
- Journals
- SHILAP Revista de lepidopterologíaJournal of the American Statistical AssociationAcademy of Management Journal
- Partner nations
- United StatesGermanyHong Kong
In The Last Decade
F. Javier Lerch
35 papers receiving 807 citations
Peers
Comparison fields: 5 of 131
- Management Information Systems 155
- Artificial Intelligence 155
- Social Psychology 132
- Organizational Behavior and Human Resource Management 127
- Sociology and Political Science 124
Countries citing papers authored by F. Javier Lerch
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
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
| # | Work | Indexed citations |
|---|---|---|
| 1 | 18 | |
| 2 | 56 | |
| 3 | 5 | |
| 4 | 23 | |
| 5 | Visualization and 3D printing of multivariate data of biomarkers | 21 |
| 6 | 0 | |
| 7 | 31 | |
| 8 | 1 | |
| 9 | 15 | |
| 10 | 64 | |
| 11 | 13 | |
| 12 | 23 | |
| 13 | 40 | |
| 14 | 12 | |
| 15 | 1 | |
| 16 | 30 | |
| 17 | 4 | |
| 18 | 1 | |
| 19 | How do we trust machine advice | 9 |
| 20 | A Framework for Computer Support in Managerial Decision Making | 8 |
About F. Javier Lerch
F. Javier Lerch is a scholar working on General Decision Sciences, Information Systems and Management and Management Science and Operations Research, having authored 38 papers that have together received 913 indexed citations. Recurring topics across this work include Team Dynamics and Performance (7 papers), Complex Systems and Decision Making (6 papers) and Technology Adoption and User Behaviour (5 papers). The work is most often cited by research in General Decision Sciences (35 citations), Management Information Systems (155 citations) and Information Systems and Management (114 citations). F. Javier Lerch has collaborated with scholars based in United States, Germany and Hong Kong. Frequent co-authors include Mark Fichman, Donald E. Harter, Paul S. Goodman, Susan R. Fussell, Robert E. Kraut, Jörn Lötsch, J. J. Cadiz, Alfred Ultsch, William L. Scherlis and Jinwoo Kim. Their work appears in journals such as SHILAP Revista de lepidopterología, Journal of the American Statistical Association and Academy of Management Journal.
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.