Jean‐François Laslier

96 papers receiving 1.6k citations

Peers

Jean‐François Laslier
Comparison fields: 5 of 87
  • Economics and Econometrics 1.2k
  • Management Science and Operations Research 733
  • Political Science and International Relations 549
  • Safety Research 287
  • Artificial Intelligence 221
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Countries citing papers authored by Jean‐François Laslier

Since Specialization
Citations

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

Fields of papers citing papers by Jean‐François Laslier

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jean‐François Laslier. 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 Jean‐François Laslier. The network helps show where Jean‐François Laslier may publish in the future.

Co-authorship network of co-authors of Jean‐François Laslier

This figure shows the co-authorship network connecting the top 25 collaborators of Jean‐François Laslier. A scholar is included among the top collaborators of Jean‐François Laslier 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 Jean‐François Laslier. Jean‐François Laslier 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
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The Future of Economic Design: The Continuing Development of a Field as Envisioned by Its Researchers
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Strategic Voting in Multiwinner Elections with Approval Balloting: An Application to the 2011 Regional Government Election in Zurich
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7 11
8 28
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Sincere Voting, Strategic Voting a Laboratory Experiment Using Alternative Proportional Systems
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Approval Voting in the French 2002 Presidential Election: A Live Experiment
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Leçons de microéconomie évolutionniste
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Social-choice mediators
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More on the tournament equilibrium set
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About Jean‐François Laslier

Jean‐François Laslier is a scholar working on Economics and Econometrics, Management Science and Operations Research and General Decision Sciences, having authored 103 papers that have together received 1.7k indexed citations. Recurring topics across this work include Game Theory and Voting Systems (61 papers), Electoral Systems and Political Participation (36 papers) and Game Theory and Applications (18 papers). The work is most often cited by research in General Decision Sciences (127 citations), Management Science and Operations Research (733 citations) and Economics and Econometrics (1.2k citations). Jean‐François Laslier has collaborated with scholars based in France, Canada and United Kingdom. Frequent co-authors include Karine Van der Straeten, Gilbert Laffond, M. Remzi Sanver, Michel Le Breton, André Blais, Bhaskar Dutta, Nathalie Picard, Bernard Walliser, Piotr Skowron and Luc Arrondel. Their work appears in journals such as American Economic Review, Journal of Political Economy and European Journal of Operational Research.

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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