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Game Theory and Applications

Game Theory and Applications is a research topic within Management Science and Operations Research. Science Explorer counts 21k research works in it since 1950. 26.9% of them reached the world's top 10% most cited for their field and year.

This cluster of papers focuses on network formation, game dynamics, and strategic interactions in social and economic networks. It explores topics such as selfish routing, Bayesian learning, information design, reputation, coordination games, and the price of anarchy in network environments.

  • Network Formation
  • Game Theory
  • Social Networks
  • Nash Equilibrium
  • Bayesian Learning
  • Information Design
  • Selfish Routing
  • Reputation
  • Coordination Games
  • Price of Anarchy
Research works
21k
fractional, since 1950
In the world top 10%
5.6k
per year above
Top-10% rate
26.9%
share of its works in the world top 10%
Growth, 2013–17 → 2018–22
-11%
the tick is no change

Which countries lead Game Theory and Applications research?

By volume, the United States and China publish the most (651 and 483 works in 2022–2025).

By volume, 2022–2025

  1. 1 United States 651 works
  2. 2 China 483 works
  3. 3 United Kingdom 156 works
  4. 4 Germany 131 works
  5. 5 France 128 works
  6. 6 Italy 116 works
  7. 7 Japan 110 works
  8. 8 India 87 works
  9. 9 Canada 81 works
  10. 10 Russia 77 works

How concentrated that is

The same countries as shares of everything the list above accounts for. A node where two countries do two thirds of the work and one spread evenly across twelve read alike as a ranking and not at all alike here.

United States: 32.2%China: 23.9%United Kingdom: 7.7%Germany: 6.5%6 others listed: 29.6%32%largest
United States651 · 32.2%China483 · 23.9%United Kingdom156 · 7.7%Germany131 · 6.5%6 others listed599 · 29.6%

Shares of the rows listed above, not of the whole node.

Which institutions lead Game Theory and Applications research?

By volume in 2022–2025, St Petersburg University publishes the most Game Theory and Applications research, followed by University of Illinois Urbana-Champaign and New York University.

By volume, 2022–2025

  1. 1 St Petersburg UniversityRussia 21 works
  2. 2 University of Illinois Urbana-ChampaignUnited States 20 works
  3. 3 New York UniversityUnited States 19 works
  4. 4 Cornell UniversityUnited States 17 works
  5. 5 Centre National de la Recherche ScientifiqueFrance 16 works
  6. 6 University of OxfordUnited Kingdom 16 works
  7. 7 Tel Aviv UniversityIsrael 15 works
  8. 8 National Research University Higher School of EconomicsRussia 14 works
  9. 9 University of ChicagoUnited States 14 works
  10. 10 Yale UniversityUnited States 14 works

Who are the leading researchers in Game Theory and Applications?

The most-cited researchers publishing on Game Theory and Applications include Daron Acemoğlu, Zhu Han and A. Charnes.

  1. 1 Daron Acemoğlu United States 5.7k citations
  2. 2 Zhu Han United States 4.7k citations
  3. 3 A. Charnes United States 4.5k citations
  4. 4 Jean Tirole France 4.4k citations
  5. 5 Mérouane Debbah France 4.3k citations

Ranked by citations received across their whole record, among researchers with at least three works on this topic.

Where is Game Theory and Applications research done?

The largest centres of Game Theory and Applications research in 2022–2025 are Beijing (China), Shanghai (China), London (United Kingdom) and Tokyo (Japan).

Largest cities, 2022–2025

  1. 1 Beijing China 96 works
  2. 2 Shanghai China 63 works
  3. 3 London United Kingdom 51 works
  4. 4 Tokyo Japan 49 works
  5. 5 Paris France 46 works
  6. 6 New York United States 41 works
  7. 7 Nanjing China 34 works
  8. 8 Moscow Russia 34 works
  9. 9 Singapore Singapore 27 works
  10. 10 Hong Kong China 27 works
See Game Theory and Applications on the map

Where is the best place to study Game Theory and Applications?

Among universities, judged by research, St Petersburg University, Shanghai University of Finance and Economics and New York University score highest, combining excellence, specialisation, size, growth and international reach. Research strength is one signal when choosing where to study; it does not measure teaching.

0%20%40%mean 18.03%fractional works in this node (log) →share in the world top 10% →St Petersburg University: 21, 15.5%Shanghai University of Finance and Economics: 12, 15.2%New York University: 19, 16.1%Columbia University: 13, 30.8%University of Illinois Urbana-Champaign: 20, 13.4%National Research University Higher School of Economics: 14, 16.6%University of Oxford: 16, 20.2%Carnegie Mellon University: 12, 17.1%Massachusetts Institute of Technology: 13, 20.6%University of California, Santa Barbara: 9, 14.8%Columbia UniversityNew York UniversitySt Petersburg Univer…Shanghai University …
above the meannear itbelow it

One dot per university in the table below. The upper left is the interesting corner: small places doing unusually strong work.

#UniversityScoreTop 10%SpecialisationWorksGrowth
1 St Petersburg UniversityRussia 73.115.5%16.6×21 +230.6%
2 Shanghai University of Finance and EconomicsChina 61.915.2%44.0×12 +246.9%
3 New York UniversityUnited States 60.416.1%9.2×19 +18.9%
4 Columbia UniversityUnited States 59.530.8%6.2×13 +4.4%
5 University of Illinois Urbana-ChampaignUnited States 58.313.4%8.9×20 +29.5%
6 National Research University Higher School of EconomicsRussia 57.716.6%13.2×14 +52.2%
7 University of OxfordUnited Kingdom 54.620.2%4.8×16 +56.4%
8 Carnegie Mellon UniversityUnited States 54.217.1%11.7×12 +5.8%
9 Massachusetts Institute of TechnologyUnited States 54.020.6%8.3×13 -28.1%
10 University of California, Santa BarbaraUnited States 52.514.8%10.9×9 +136.5%

Universities only. Score blends excellence (30%), specialisation (25%), size (20%), growth (15%) and international reach (10%), 2015–2022; growth compares 2010–14 with 2015–19.

Is Game Theory and Applications research growing?

Output in 2018–2022 was 11% lower than in 2013–2017, peaking in 2015. The fastest-growing topics are Game Theory and Applications.

19801990200020102020
grewheldshrank

The same series as a ribbon — one cell per year, darker for more. The line above answers how much; this answers when.

Which topics inside it are moving

Growth and decline on one axis around a shared zero. Two lists side by side hide the thing that matters: whether the growth dwarfs the decline, or the other way round.