Wen Lea Pearn

40 total papers · 952 total citations
34 papers, 724 citations indexed

About

Wen Lea Pearn is a scholar working on Management Information Systems, Management Science and Operations Research and Industrial and Manufacturing Engineering. According to data from OpenAlex, Wen Lea Pearn has authored 34 papers receiving a total of 724 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Management Information Systems, 14 papers in Management Science and Operations Research and 13 papers in Industrial and Manufacturing Engineering. Recurrent topics in Wen Lea Pearn's work include Advanced Queuing Theory Analysis (14 papers), Advanced Statistical Process Monitoring (9 papers) and Probability and Risk Models (8 papers). Wen Lea Pearn is often cited by papers focused on Advanced Queuing Theory Analysis (14 papers), Advanced Statistical Process Monitoring (9 papers) and Probability and Risk Models (8 papers). Wen Lea Pearn collaborates with scholars based in Taiwan, United States and Canada. Wen Lea Pearn's co-authors include Chien‐Wei Wu, Jau‐Chuan Ke, Kuo-Hsiung Wang, Norman L. Johnson, Samuel Kotz, Kaibin Huang, Chia‐Huang Wu, Yichun Liu, Dong‐Yuh Yang and Lap‐Ming Wun and has published in prestigious journals such as International Journal of Production Economics, Computers & Operations Research and Omega.

In The Last Decade

Wen Lea Pearn

33 papers receiving 683 citations

Author Peers

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

Author Last Decade Papers Cites
Wen Lea Pearn 276 266 256 230 117 34 724
Chia‐Huang Wu 228 0.8× 549 2.1× 216 0.8× 195 0.8× 84 0.7× 74 881
Si̇mge Küçükyavuz 227 0.8× 252 0.9× 43 0.2× 407 1.8× 75 0.6× 42 859
John E. Kobza 166 0.6× 122 0.5× 140 0.5× 54 0.2× 35 0.3× 44 798
W.J. Kolarik 92 0.3× 119 0.4× 157 0.6× 94 0.4× 102 0.9× 30 722
Ali Salmasnia 221 0.8× 177 0.7× 385 1.5× 185 0.8× 137 1.2× 97 898
Antonio Pievatolo 57 0.2× 115 0.4× 215 0.8× 109 0.5× 143 1.2× 49 863
Eginhard J. Muth 397 1.4× 317 1.2× 51 0.2× 96 0.4× 110 0.9× 34 745
Seyed Mohsen Mousavi 219 0.8× 287 1.1× 62 0.2× 123 0.5× 44 0.4× 19 730
B. D. Sivazlian 120 0.4× 452 1.7× 49 0.2× 166 0.7× 138 1.2× 56 756
Cheng‐Fu Huang 120 0.4× 82 0.3× 259 1.0× 71 0.3× 36 0.3× 74 681

Countries citing papers authored by Wen Lea Pearn

Since Specialization
Citations

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

Fields of papers citing papers by Wen Lea Pearn

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Wen Lea Pearn. 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 Wen Lea Pearn. The network helps show where Wen Lea Pearn may publish in the future.

Co-authorship network of co-authors of Wen Lea Pearn

This figure shows the co-authorship network connecting the top 25 collaborators of Wen Lea Pearn. A scholar is included among the top collaborators of Wen Lea Pearn 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 Wen Lea Pearn. Wen Lea Pearn 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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