Laurent Gourvès

28 papers receiving 213 citations

Peers

Laurent Gourvès
Comparison fields: 5 of 44
  • Computational Theory and Mathematics 120
  • Management Science and Operations Research 70
  • Industrial and Manufacturing Engineering 66
  • Computer Networks and Communications 61
  • Economics and Econometrics 51
Replace Naoyuki Kamiyama with:
Naoyuki Kamiyama Japan
László A. Végh United Kingdom
F. Margot Switzerland
Anureet Saxena United States
H.-C. Wirth Germany
Olivier Spanjaard France
Matthias Englert United Kingdom
Mikhail Batsyn Russia
Miyuki Koshimura Japan
Giorgio Lucarelli France
Laurent Gourvès relative to Naoyuki Kamiyama Japan Naoyuki Kamiyama's profile →
Citations per field
00.5×3.7×
Naoyuki Kamiyama · 1×
Citations per year

Countries citing papers authored by Laurent Gourvès

Since Specialization
Citations

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

Fields of papers citing papers by Laurent Gourvès

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Laurent Gourvès

This figure shows the co-authorship network connecting the top 25 collaborators of Laurent Gourvès. A scholar is included among the top collaborators of Laurent Gourvès 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 Laurent Gourvès. Laurent Gourvès is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 1
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3 22
4 16
5 1
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8 1
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13 7
14 21
15 27
16 4
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18
Scheduling Selfish Tasks: About the Performance of Truthful Algorithms
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19 10
20 40

About Laurent Gourvès

Laurent Gourvès is a scholar working on Computer Graphics and Computer-Aided Design, Management Science and Operations Research and Industrial and Manufacturing Engineering, having authored 30 papers that have together received 223 indexed citations. Recurring topics across this work include Auction Theory and Applications (11 papers), Game Theory and Voting Systems (11 papers) and Advanced Graph Theory Research (10 papers). The work is most often cited by research in Computational Theory and Mathematics (120 citations), Industrial and Manufacturing Engineering (66 citations) and Management Science and Operations Research (70 citations). Laurent Gourvès has collaborated with scholars based in France, Brazil and Argentina. Frequent co-authors include Jérôme Monnot, Éric Angel, Evripidis Bampis, Bruno Escoffier, Yann Chevaleyre, Olivier Spanjaard, Nicolas Maudet, Cristina Bazgan, Orestis Telelis and Stefano Moretti. Their work appears in journals such as European Journal of Operational Research, Theoretical Computer Science and Discrete Applied Mathematics.

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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