John M. Jordan

50 total papers · 1.0k total citations
27 papers, 683 citations indexed

About

John M. Jordan is a scholar working on Sociology and Political Science, Computer Networks and Communications and Management Information Systems. According to data from OpenAlex, John M. Jordan has authored 27 papers receiving a total of 683 indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Sociology and Political Science, 2 papers in Computer Networks and Communications and 2 papers in Management Information Systems. Recurrent topics in John M. Jordan's work include Model-Driven Software Engineering Techniques (1 paper), Innovative Teaching and Learning Methods (1 paper) and Digital Transformation in Industry (1 paper). John M. Jordan is often cited by papers focused on Model-Driven Software Engineering Techniques (1 paper), Innovative Teaching and Learning Methods (1 paper) and Digital Transformation in Industry (1 paper). John M. Jordan collaborates with scholars based in United States, Germany and United Kingdom. John M. Jordan's co-authors include William L. Garrard, Erik Brynjolfsson, Paul Hofmann, David L. Hall, Stephen J. K. Walters, Guy Alchon, Hubert Österle, Henning Kagermann, Drummond Reed and Uwe Sterr and has published in prestigious journals such as Automatica, Communications of the ACM and Industrial & Engineering Chemistry Research.

In The Last Decade

John M. Jordan

24 papers receiving 615 citations

Author Peers

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

Author						Papers	Cites
John M. Jordan	126	121	88	84	78	27	683
Kadir Alpaslan Demir	54 0.4×	128 1.1×	84 1.0×	53 0.6×	38 0.5×	30	650
Yi‐Cheng Chen	27 0.2×	201 1.7×	120 1.4×	90 1.1×	54 0.7×	47	650
Ali Alkhalifah	49 0.4×	226 1.9×	170 1.9×	51 0.6×	35 0.4×	39	711
Ke‐Wei Huang	27 0.2×	89 0.7×	70 0.8×	71 0.8×	35 0.4×	69	685
Nguyen Khoi Tran	98 0.8×	353 2.9×	155 1.8×	37 0.4×	38 0.5×	36	596
John Erickson	33 0.3×	143 1.2×	95 1.1×	107 1.3×	49 0.6×	46	707
Yang Lü	42 0.3×	438 3.6×	221 2.5×	97 1.2×	28 0.4×	46	763
Pankaj Agarwal	69 0.5×	65 0.5×	133 1.5×	33 0.4×	80 1.0×	55	743
Richard G. Mathieu	87 0.7×	147 1.2×	83 0.9×	170 2.0×	6 0.1×	40	659
Michael Henshaw	198 1.6×	39 0.3×	39 0.4×	65 0.8×	87 1.1×	59	665

Countries citing papers authored by John M. Jordan

Since Specialization

Citations

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

Fields of papers citing papers by John M. Jordan

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by John M. Jordan. 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 John M. Jordan. The network helps show where John M. Jordan may publish in the future.

Co-authorship network of co-authors of John M. Jordan

This figure shows the co-authorship network connecting the top 25 collaborators of John M. Jordan. A scholar is included among the top collaborators of John M. Jordan 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 John M. Jordan. John M. Jordan 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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