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Efficiency Analysis Using DEA

Efficiency Analysis Using DEA is a research topic within Management Science and Operations Research. Science Explorer counts 19k research works in it since 1956. 24.4% of them reached the world's top 10% most cited for their field and year.

This cluster of papers focuses on the analysis of efficiency, productivity growth, and resource allocation in various sectors such as production processes, energy, banking, healthcare, and education. The papers employ methods like Data Envelopment Analysis (DEA) and non-parametric frontier models to measure technical, environmental, and energy efficiency, as well as to evaluate the performance of different organizations and industries.

  • Data Envelopment Analysis
  • Efficiency Measurement
  • Productivity Growth
  • Environmental Efficiency
  • DEA Models
  • Technical Efficiency
  • Energy Efficiency
  • Banking Efficiency
  • Non-parametric Frontier Models
  • DEA Applications
Research works
19k
fractional, since 1956
In the world top 10%
4.6k
per year above
Top-10% rate
24.4%
share of its works in the world top 10%
Growth, 2013–17 → 2018–22
+19%
the tick is no change

Which countries lead Efficiency Analysis Using DEA research?

By volume, China and Türkiye publish the most (872 and 272 works in 2022–2025).

By volume, 2022–2025

  1. 1 China 872 works
  2. 2 Türkiye 272 works
  3. 3 India 237 works
  4. 4 Iran 190 works
  5. 5 United States 181 works
  6. 6 Brazil 110 works
  7. 7 Indonesia 93 works
  8. 8 Spain 88 works
  9. 9 Taiwan 85 works
  10. 10 United Kingdom 76 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.

China: 39.6%Türkiye: 12.3%India: 10.7%Iran: 8.6%6 others listed: 28.7%40%largest
China872 · 39.6%Türkiye272 · 12.3%India237 · 10.7%Iran190 · 8.6%6 others listed633 · 28.7%

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

Which institutions lead Efficiency Analysis Using DEA research?

By volume in 2022–2025, Islamic Azad University, Science and Research Branch publishes the most Efficiency Analysis Using DEA research, followed by Hefei University of Technology and Fuzhou University.

By volume, 2022–2025

  1. 1 Islamic Azad University, Science and Research Branch Iran 17 works
  2. 2 Hefei University of Technology China 16 works
  3. 3 Fuzhou University China 14 works
  4. 4 University of Macedonia Greece 14 works
  5. 5 National Cheng Kung University Taiwan 13 works
  6. 6 Universitat de Miguel Hernández d'Elx Spain 12 works
  7. 7 Universiti Teknologi MARA Malaysia 12 works
  8. 8 University of Science and Technology of China China 11 works
  9. 9 Shandong University China 11 works
  10. 10 Istinye University Türkiye 11 works

Who are the leading researchers in Efficiency Analysis Using DEA?

The most-cited researchers publishing on Efficiency Analysis Using DEA include Witold Pedrycz, W. W. Cooper and Rajiv D. Banker.

  1. 1 Witold Pedrycz 5.4k citations
  2. 2 W. W. Cooper 4.6k citations
  3. 3 Rajiv D. Banker 4.6k citations
  4. 4 A. Charnes 4.5k citations
  5. 5 Allen N. Berger 3.4k citations
  6. 6 C. A. Knox Lovell 2.7k citations

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

Where is Efficiency Analysis Using DEA research done?

The largest centres of Efficiency Analysis Using DEA research in 2022–2025 are Beijing (China), Tehran (Iran), Nanjing (China) and Istanbul (Türkiye).

Largest cities, 2022–2025

  1. 1 Beijing China 144 works
  2. 2 Tehran Iran 80 works
  3. 3 Nanjing China 54 works
  4. 4 Istanbul Türkiye 46 works
  5. 5 Wuhan China 44 works
  6. 6 Shanghai China 44 works
  7. 7 Hefei China 39 works
  8. 8 Ankara Türkiye 38 works
  9. 9 Jinan China 35 works
  10. 10 Fuzhou China 34 works
See Efficiency Analysis Using DEA on the map

Where is the best place to study Efficiency Analysis Using DEA?

Among universities, judged by research, Hefei University of Technology, Southwestern University of Finance and Economics and Istinye 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%60%mean 35.13%fractional works in this node (log) →share in the world top 10% →Hefei University of Technology: 16, 46.6%Southwestern University of Finance and Economics: 10, 44.3%Istinye University: 11, 37.4%Islamic Azad University, Science and Research Branch: 17, 22.2%Soochow University: 9, 33.3%Universitat de Miguel Hernández d'Elx: 12, 27.6%Fuzhou University: 14, 26.1%Sultan Qaboos University: 8, 33.6%Sivas Cumhuriyet Üniversitesi: 9, 32.1%Shandong University: 11, 48.1%Hefei University of …Southwestern Univers…Istinye UniversityIslamic Azad Univers…
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
1Hefei University of Technology China 75.246.6%8.6×16 +55.8%
2Southwestern University of Finance and Economics China 70.044.3%19.9×10 +131.1%
3Istinye University Türkiye 69.737.4%40.1×11
4Islamic Azad University, Science and Research Branch Iran 63.022.2%30.3×17 +14.6%
5Soochow University Taiwan 62.933.3%70.1×9 +65.1%
6Universitat de Miguel Hernández d'Elx Spain 59.627.6%33.4×12 +17.9%
7Fuzhou University China 58.626.1%7.7×14 +90.2%
8Sultan Qaboos University Oman 57.033.6%15.8×8 -1.9%
9Sivas Cumhuriyet Üniversitesi Türkiye 53.432.1%11.2×9
10Shandong University China 51.848.1%2.8×11 +105.9%

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 Efficiency Analysis Using DEA research growing?

Output in 2018–2022 was 19% higher than in 2013–2017, peaking in 2020. The fastest-growing topics are Efficiency Analysis Using DEA.

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.