Tom Magerman

409 citations
17 papers · 330 · h-index 9

Impact in

Papers in

Tom Magerman

17 papers receiving 303 citations

Peers

Tom Magerman
Comparison fields: 5 of 58
  • Management of Technology and Innovation 189
  • Economics and Econometrics 169
  • Strategy and Management 90
  • Statistics, Probability and Uncertainty 39
  • Management Science and Operations Research 37
Replace Ryan Lampe with:
Ryan Lampe United States
Kyle Higham Switzerland
Zhiyun Zhao China
Jeffrey M. Kuhn United States
H. Grupp Germany
Markus Nordberg Switzerland
Pascal Billand France
Ted M. Sichelman United States
Dyuti Banerjee Australia
In‐Uck Park United Kingdom
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Citations per field
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Citations per year

Countries citing papers authored by Tom Magerman

Since Specialization
Citations

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

Fields of papers citing papers by Tom Magerman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Tom Magerman. 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 Tom Magerman. The network helps show where Tom Magerman may publish in the future.

Co-authors

The 11 scholars most cited alongside Tom Magerman, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Tom Magerman Line = papers co-authored together Tom Magerman links everyone, so they are left out of the graph.

All Works

17 of 17 papers shown
#Work
1 200978
2 201547
3 200644
4 200740
5 200638
6 201114
7
Patent statistics at Eurostat: Methods for regionalisation, sector allocation and name harmonisation
201113
8 201911
9 20148
10
Assessment of Latent Semantic Analysis (LSA) text mining algorithms for large scale mapping of patent and scientific publication documents
20117
11 20067
12
Vlaams indicatorenboek wetenschap, technologie en innovatie
20055
13
In search of anti-commons, patent-paper pairs in biotechnology, an analysis of citation flows
20115
14 20084
15
Assessing academic patent activity: the case of Flanders
20054
16
Impact and consequences of science-intensive patenting: In search of anti-commons evidence using Latent Semantic Analysis (LSA) text mining techniques.
20113
17
Domain Study 'Biotechnology'
20032

About Tom Magerman

Tom Magerman is a scholar working on Management of Technology and Innovation, Molecular Biology, Artificial Intelligence, Economics and Econometrics and Statistics, Probability and Uncertainty, having authored 17 papers that have together received 330 indexed citations. Recurring topics across this work include Intellectual Property and Patents (9 papers), Innovation Policy and R&D (5 papers), Advanced Text Analysis Techniques (4 papers), Biomedical Text Mining and Ontologies (4 papers), scientometrics and bibliometrics research (3 papers), Entrepreneurship Studies and Influences (2 papers), Biotechnology and Related Fields (2 papers) and Cognitive Computing and Networks (1 paper). The work is most often cited by research in Management of Technology and Innovation (189 citations), Economics and Econometrics (169 citations), Strategy and Management (90 citations), Statistics, Probability and Uncertainty (39 citations) and Management Science and Operations Research (37 citations). Tom Magerman has collaborated with scholars based in Belgium, China and Spain. Frequent co-authors include Bart Van Looy, Koenraad Debackere, Bart Baesens, Julie Callaert, Bart Peeters, Kris Aerts, Wolfgang Glänzel, Reinhilde Veugelers, Bart Thijs and Arnold Verbeek. Their work appears in journals such as Scientometrics, Research Policy, SSRN Electronic Journal, Data Archiving and Networked Services (DANS) and Springer handbooks.

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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