Ken R. McNaught

29 total papers · 569 total citations
20 papers, 408 citations indexed

About

Ken R. McNaught is a scholar working on Management Science and Operations Research, Software and Statistics, Probability and Uncertainty. According to data from OpenAlex, Ken R. McNaught has authored 20 papers receiving a total of 408 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Management Science and Operations Research, 5 papers in Software and 5 papers in Statistics, Probability and Uncertainty. Recurrent topics in Ken R. McNaught's work include Simulation Techniques and Applications (4 papers), Software Reliability and Analysis Research (4 papers) and Bayesian Modeling and Causal Inference (4 papers). Ken R. McNaught is often cited by papers focused on Simulation Techniques and Applications (4 papers), Software Reliability and Analysis Research (4 papers) and Bayesian Modeling and Causal Inference (4 papers). Ken R. McNaught collaborates with scholars based in United Kingdom, United States and Russia. Ken R. McNaught's co-authors include M Fasihul Alam, Trevor J. Ringrose, Adam Zagorecki, Peter Šutovský, A. J. Saddington, Richard Critchley and Rachael Hazael and has published in prestigious journals such as International Journal of Production Economics, Journal of the Operational Research Society and Technological Forecasting and Social Change.

In The Last Decade

Ken R. McNaught

18 papers receiving 378 citations

Author Peers

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

Author Last Decade Papers Cites
Ken R. McNaught 167 77 67 57 50 20 408
Luis Asunción Pérez-Domínguez 236 1.4× 38 0.5× 82 1.2× 52 0.9× 61 1.2× 49 484
Soumava Boral 247 1.5× 111 1.4× 63 0.9× 61 1.1× 33 0.7× 14 453
Arash Alizadeh 287 1.7× 72 0.9× 64 1.0× 29 0.5× 31 0.6× 14 494
Burak Efe 216 1.3× 68 0.9× 48 0.7× 38 0.7× 37 0.7× 25 383
Zhiying Zhang 206 1.2× 28 0.4× 77 1.1× 30 0.5× 63 1.3× 26 409
H. H. Chang 121 0.7× 78 1.0× 32 0.5× 88 1.5× 44 0.9× 32 467
Ching‐Liang Chang 241 1.4× 141 1.8× 50 0.7× 47 0.8× 31 0.6× 8 438
François Pérès 77 0.5× 63 0.8× 50 0.7× 64 1.1× 40 0.8× 50 445
Mingshun Song 163 1.0× 143 1.9× 35 0.5× 41 0.7× 39 0.8× 13 374
Zhanwen Niu 121 0.7× 84 1.1× 55 0.8× 70 1.2× 38 0.8× 47 441

Countries citing papers authored by Ken R. McNaught

Since Specialization
Citations

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

Fields of papers citing papers by Ken R. McNaught

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ken R. McNaught. 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 Ken R. McNaught. The network helps show where Ken R. McNaught may publish in the future.

Co-authorship network of co-authors of Ken R. McNaught

This figure shows the co-authorship network connecting the top 25 collaborators of Ken R. McNaught. A scholar is included among the top collaborators of Ken R. McNaught 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 Ken R. McNaught. Ken R. McNaught 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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