---
title: "Companies publishing research papers, 2023–2025"
description: "Of the 168,221 papers the 400 tracked journals published in 2023–2025, 4,810 (3%) have at least one author at a company; 93% of those also have a university author. The corporate share of papers went from 2% in 2017 to 3% in 2025."
url: https://scholar4ai.com/rankings/companies
markdown_url: https://scholar4ai.com/rankings/companies.md
license: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/)
share_text: "Of the 168,221 papers the 400 tracked journals published in 2023–2025, 4,810 (3%) have at least one author at a company; 93% of those also have a university author. (as of 2026-10-31)"
data_url: https://scholar4ai.com/data/rankings.json
updated: 2026-10-31T19:11:11+09:00
window: 2026-10-02 to 2026-10-31
source: OpenAlex (CC0)
---

# Corporate research: companies publishing in the tracked journals, 2023–2025

Companies whose researchers publish in the 400 tracked journals, ranked by their papers in each year from 2023 to 2025, and how much of the research has corporate authors. A paper counts as corporate when at least one of its authors is affiliated with an institution that OpenAlex classifies as a company; it counts once for each company among its authors' affiliations. Universities are the institutions OpenAlex classifies as education.

By category: [Finance](https://scholar4ai.com/rankings/companies/finance.md) · [Accounting](https://scholar4ai.com/rankings/companies/accounting.md) · [Economics](https://scholar4ai.com/rankings/companies/economics.md) · [Health Economics and Policy](https://scholar4ai.com/rankings/companies/health-economics-and-policy.md) · [Management](https://scholar4ai.com/rankings/companies/management.md) · [Marketing](https://scholar4ai.com/rankings/companies/marketing.md) · [Information Systems](https://scholar4ai.com/rankings/companies/information-systems.md) · [Tourism and Hospitality](https://scholar4ai.com/rankings/companies/tourism-and-hospitality.md) · [Higher Education and Research](https://scholar4ai.com/rankings/companies/higher-education-and-research.md) · [Operations Research](https://scholar4ai.com/rankings/companies/operations-research.md) · [Statistics](https://scholar4ai.com/rankings/companies/statistics.md) · [AI](https://scholar4ai.com/rankings/companies/ai.md)

## Key findings

- Of the 168,221 papers the 400 tracked journals published in 2023–2025, 4,810 (3%) have at least one author at a company; 93% of those also have a university author.
- The corporate share of papers went from 2% in 2017 to 3% in 2025.
- Tencent (China) took part in the most papers (244), followed by Huawei Technologies (China) (194) and Alibaba Group (China) (180).
- Companies take part most in health economics and policy papers (7%) and least in tourism and hospitality (0%).
- By the companies' countries: China (2,997), United States (1,254), United Kingdom (278) and Germany (238).
- Keywords with the highest corporate share: “quality-adjusted life years” (24%), “text-to-image generation” (22%) and “economic burden” (20%).

## Companies

*Companies with the most papers, 2023–2025*

| # | Company | Country | 2023 | 2024 | 2025 | 2023–2025 |
|---:|---|---|---:|---:|---:|---:|
| 1 | [Tencent (China)](https://scholar4ai.com/companies/tencent-china.md) | China | 72 | 88 | 84 | 244 |
| 2 | [Huawei Technologies (China)](https://scholar4ai.com/companies/huawei-technologies-china.md) | China | 72 | 56 | 66 | 194 |
| 3 | [Alibaba Group (China)](https://scholar4ai.com/companies/alibaba-group-china.md) | China | 56 | 66 | 58 | 180 |
| 4 | [Jingdong (China)](https://scholar4ai.com/companies/jingdong-china.md) | China | 61 | 34 | 35 | 130 |
| 5 | [Amazon (United States)](https://scholar4ai.com/companies/amazon-united-states.md) | United States | 47 | 37 | 41 | 125 |
| 6 | [China Telecom](https://scholar4ai.com/companies/china-telecom.md) | China | 13 | 33 | 73 | 119 |
| 7 | [Baidu (China)](https://scholar4ai.com/companies/baidu-china.md) | China | 30 | 33 | 32 | 95 |
| 8 | [ByteDance (China)](https://scholar4ai.com/companies/bytedance-china.md) | China | 23 | 22 | 35 | 80 |
| 9 | [Meta (United States)](https://scholar4ai.com/companies/meta-united-states.md) | United States | 33 | 23 | 19 | 75 |
| 10 | [China Telecom (China)](https://scholar4ai.com/companies/china-telecom-china.md) | China | 7 | 20 | 45 | 72 |
| 11 | [State Grid Corporation of China (China)](https://scholar4ai.com/companies/state-grid-corporation-of-china-china.md) | China | 21 | 15 | 36 | 72 |
| 12 | [Microsoft (United States)](https://scholar4ai.com/companies/microsoft-united-states.md) | United States | 17 | 22 | 25 | 64 |
| 13 | [China Mobile (China)](https://scholar4ai.com/companies/china-mobile-china.md) | China | 12 | 22 | 27 | 61 |
| 14 | [Sensetime (China)](https://scholar4ai.com/companies/sensetime-china.md) | China | 21 | 20 | 20 | 61 |
| 15 | [Ant Group (China)](https://scholar4ai.com/companies/ant-group-china.md) | China | 20 | 20 | 20 | 60 |
| 16 | [Microsoft Research Asia (China)](https://scholar4ai.com/companies/microsoft-research-asia-china.md) | China | 21 | 20 | 19 | 60 |
| 17 | [China Electronics Technology Group Corporation](https://scholar4ai.com/companies/china-electronics-technology-group-corporation.md) | China | 17 | 14 | 18 | 49 |
| 18 | [Google (United States)](https://scholar4ai.com/companies/google-united-states.md) | United States | 28 | 12 | 8 | 48 |
| 19 | [Samsung (South Korea)](https://scholar4ai.com/companies/samsung-south-korea.md) | South Korea | 10 | 16 | 22 | 48 |
| 20 | [Meituan (China)](https://scholar4ai.com/companies/meituan-china.md) | China | 12 | 21 | 13 | 46 |
| 21 | [Inspur (China)](https://scholar4ai.com/companies/inspur-china.md) | China | 7 | 8 | 26 | 41 |
| 22 | [IBM (United States)](https://scholar4ai.com/companies/ibm-united-states.md) | United States | 15 | 12 | 8 | 35 |
| 23 | [Alibaba DAMO Academy (China)](https://scholar4ai.com/companies/alibaba-damo-academy-china.md) | China | 11 | 14 | 9 | 34 |
| 24 | [China United Network Communications Group (China)](https://scholar4ai.com/companies/china-united-network-communications-group-china.md) | China | 3 | 9 | 22 | 34 |
| 25 | [Nvidia (United States)](https://scholar4ai.com/companies/nvidia-united-states.md) | United States | 8 | 13 | 11 | 32 |
| 26 | [Lenovo (China)](https://scholar4ai.com/companies/lenovo-china.md) | China | 10 | 9 | 12 | 31 |
| 27 | [Kuaishou (China)](https://scholar4ai.com/companies/kuaishou-china.md) | – | 7 | 10 | 13 | 30 |
| 28 | [Intel (United States)](https://scholar4ai.com/companies/intel-united-states.md) | United States | 9 | 8 | 12 | 29 |
| 29 | [Samsung Electronics (South Korea)](https://scholar4ai.com/companies/samsung-electronics-south-korea.md) | South Korea | 4 | 11 | 14 | 29 |
| 30 | [China Mobile Research Institute](https://scholar4ai.com/companies/china-mobile-research-institute.md) | China | 3 | 13 | 12 | 28 |
| 31 | [IFlyTek (China)](https://scholar4ai.com/companies/iflytek-china.md) | – | 4 | 9 | 14 | 27 |
| 32 | [Sinopec (China)](https://scholar4ai.com/companies/sinopec-china.md) | China | 6 | 8 | 12 | 26 |
| 33 | [Électricité de France (France)](https://scholar4ai.com/companies/electricite-de-france-france.md) | France | 10 | 12 | 4 | 26 |
| 34 | [Analysis Group (United States)](https://scholar4ai.com/companies/analysis-group-united-states.md) | United States | 6 | 8 | 8 | 22 |
| 35 | [BMW (Germany)](https://scholar4ai.com/companies/bmw-germany.md) | Germany | 8 | 5 | 9 | 22 |
| 36 | [Bristol-Myers Squibb (United States)](https://scholar4ai.com/companies/bristol-myers-squibb-united-states.md) | United States | 7 | 11 | 4 | 22 |
| 37 | [F. Hoffmann-La Roche AG](https://scholar4ai.com/companies/f-hoffmann-la-roche-ag.md) | Switzerland | 7 | 7 | 7 | 21 |
| 38 | [Google DeepMind (United Kingdom)](https://scholar4ai.com/companies/google-deepmind-united-kingdom.md) | United Kingdom | 5 | 7 | 9 | 21 |
| 39 | [LG (South Korea)](https://scholar4ai.com/companies/lg-south-korea.md) | South Korea | 4 | 9 | 7 | 20 |
| 40 | [China Aerospace Science and Industry Corporation (China)](https://scholar4ai.com/companies/china-aerospace-science-and-industry-corporation-china.md) | China | 3 | 7 | 9 | 19 |
| 41 | [China National Petroleum Corporation (China)](https://scholar4ai.com/companies/china-national-petroleum-corporation-china.md) | China | 7 | 4 | 8 | 19 |
| 42 | Ping An (China) | – | 7 | 5 | 7 | 19 |
| 43 | Adobe Systems (United States) | United States | 5 | 7 | 6 | 18 |
| 44 | China North Industries Group Corporation (China) | China | 6 | 4 | 8 | 18 |
| 45 | BYD (China) | China | 2 | 6 | 9 | 17 |
| 46 | [Boston Consulting Group (United States)](https://scholar4ai.com/companies/boston-consulting-group-united-states.md) | United States | 9 | 3 | 5 | 17 |
| 47 | [Charles River Associates](https://scholar4ai.com/companies/charles-river-associates.md) | United States | 5 | 5 | 7 | 17 |
| 48 | Didi Chuxing (China) | – | 4 | 9 | 4 | 17 |
| 49 | [Flanders Make (Belgium)](https://scholar4ai.com/companies/flanders-make-belgium.md) | Belgium | 6 | 8 | 3 | 17 |
| 50 | [Prometeia (Italy)](https://scholar4ai.com/companies/prometeia-italy.md) | Italy | 4 | 4 | 9 | 17 |

## By category and year

*Share of papers with an author at a company, per category and year*

| Category | 2017 | 2018 | 2019 | 2020 | 2021 | 2022 | 2023 | 2024 | 2025 | 2026 (so far) |
|---|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|
| [Finance](https://scholar4ai.com/rankings/companies/finance.md) | 1% | 1% | 1% | 1% | 2% | 1% | 1% | 1% | 1% | 1% |
| [Accounting](https://scholar4ai.com/rankings/companies/accounting.md) | 1% | 1% | 0% | 0% | 0% | 0% | 0% | 1% | 0% | 0% |
| [Economics](https://scholar4ai.com/rankings/companies/economics.md) | 1% | 1% | 1% | 1% | 1% | 1% | 1% | 1% | 1% | 1% |
| [Health Economics and Policy](https://scholar4ai.com/rankings/companies/health-economics-and-policy.md) | 6% | 8% | 8% | 8% | 9% | 9% | 8% | 7% | 7% | 6% |
| [Management](https://scholar4ai.com/rankings/companies/management.md) | 1% | 1% | 1% | 1% | 1% | 1% | 1% | 1% | 1% | 1% |
| [Marketing](https://scholar4ai.com/rankings/companies/marketing.md) | 1% | 0% | 1% | 2% | 1% | 0% | 1% | 1% | 1% | 1% |
| [Information Systems](https://scholar4ai.com/rankings/companies/information-systems.md) | 3% | 3% | 2% | 2% | 2% | 2% | 2% | 2% | 2% | 2% |
| [Tourism and Hospitality](https://scholar4ai.com/rankings/companies/tourism-and-hospitality.md) | 0% | 0% | 0% | 0% | 0% | 1% | 0% | 0% | 1% | 0% |
| [Higher Education and Research](https://scholar4ai.com/rankings/companies/higher-education-and-research.md) | 2% | 1% | 1% | 1% | 0% | 0% | 1% | 1% | 1% | 1% |
| [Operations Research](https://scholar4ai.com/rankings/companies/operations-research.md) | 3% | 3% | 3% | 3% | 3% | 3% | 3% | 2% | 2% | 2% |
| [Statistics](https://scholar4ai.com/rankings/companies/statistics.md) | 1% | 2% | 3% | 3% | 3% | 2% | 2% | 2% | 2% | 2% |
| [AI](https://scholar4ai.com/rankings/companies/ai.md) | 4% | 5% | 6% | 6% | 6% | 6% | 6% | 6% | 6% | 5% |
| All categories | 2% | 2% | 3% | 3% | 3% | 3% | 3% | 3% | 3% | 2% |

## Countries

*Countries of the companies, by papers with an author at a company there, 2023–2025*

| # | Country | Papers |
|---:|---|---:|
| 1 | China | 2,997 |
| 2 | United States | 1,254 |
| 3 | United Kingdom | 278 |
| 4 | Germany | 238 |
| 5 | South Korea | 196 |
| 6 | Japan | 195 |
| 7 | France | 171 |
| 8 | Switzerland | 101 |
| 9 | Italy | 91 |
| 10 | Spain | 78 |
| 11 | Belgium | 71 |
| 12 | Netherlands | 69 |
| 13 | India | 68 |
| 14 | Sweden | 63 |
| 15 | Canada | 54 |
| 16 | Austria | 34 |
| 17 | Turkey | 33 |
| 18 | Denmark | 33 |
| 19 | Brazil | 31 |
| 20 | Norway | 30 |
| 21 | Hungary | 28 |
| 22 | Taiwan | 23 |
| 23 | Singapore | 22 |
| 24 | Australia | 17 |
| 25 | Ireland | 16 |

## Topics

*Keywords with the highest corporate share (at least 100 papers), 2023–2025*

| # | Keyword | Share | Corporate papers | All papers |
|---:|---|---:|---:|---:|
| 1 | quality-adjusted life years | 24% | 118 | 487 |
| 2 | text-to-image generation | 22% | 31 | 141 |
| 3 | economic burden | 20% | 31 | 152 |
| 4 | neural radiance fields | 19% | 20 | 104 |
| 5 | health-related quality of life | 19% | 36 | 189 |
| 6 | incremental cost-effectiveness ratio | 19% | 24 | 128 |
| 7 | health technology assessment | 18% | 58 | 314 |
| 8 | pre-training | 18% | 24 | 130 |
| 9 | hospitalization | 18% | 22 | 124 |
| 10 | instance segmentation | 17% | 24 | 142 |
| 11 | Markov model | 16% | 26 | 164 |
| 12 | [cost-effectiveness](https://scholar4ai.com/keywords/cost-effectiveness.md) | 16% | 133 | 855 |
| 13 | autonomous driving perception | 15% | 15 | 100 |
| 14 | parameter-efficient fine-tuning | 15% | 33 | 221 |
| 15 | multimodal large language models | 14% | 37 | 257 |
| 16 | end-to-end learning | 14% | 21 | 146 |
| 17 | object detection | 14% | 91 | 656 |
| 18 | cost-utility analysis | 13% | 17 | 126 |
| 19 | semantic segmentation | 13% | 87 | 646 |
| 20 | foundation models | 13% | 25 | 188 |
| 21 | memory efficiency | 13% | 17 | 128 |
| 22 | 3D object detection | 13% | 21 | 159 |
| 23 | image restoration | 13% | 32 | 250 |
| 24 | inference efficiency | 13% | 21 | 165 |
| 25 | 3D Gaussian Splatting | 13% | 16 | 127 |
| 26 | depth estimation | 12% | 19 | 152 |
| 27 | human action recognition | 12% | 14 | 113 |
| 28 | health care costs | 12% | 58 | 476 |
| 29 | domain gap | 12% | 13 | 107 |
| 30 | image captioning | 12% | 14 | 116 |
| 31 | benchmark | 12% | 15 | 125 |
| 32 | self-distillation | 12% | 14 | 117 |
| 33 | CLIP | 12% | 46 | 385 |
| 34 | multivariate time series | 12% | 27 | 228 |
| 35 | in-context learning | 11% | 12 | 105 |
| 36 | sequential recommendation | 11% | 17 | 151 |
| 37 | quality of life | 11% | 21 | 187 |
| 38 | prompt learning | 11% | 23 | 205 |
| 39 | out-of-distribution generalization | 11% | 23 | 205 |
| 40 | image enhancement | 11% | 11 | 101 |

## Keywords of corporate papers

*Keywords of the most corporate papers, 2023–2025*

| # | Keyword | Corporate papers | All papers | Share |
|---:|---|---:|---:|---:|
| 1 | [large language models](https://scholar4ai.com/keywords/large-language-models.md) | 216 | 3,166 | 7% |
| 2 | [graph neural networks](https://scholar4ai.com/keywords/graph-neural-networks.md) | 149 | 2,102 | 7% |
| 3 | [cost-effectiveness](https://scholar4ai.com/keywords/cost-effectiveness.md) | 133 | 855 | 16% |
| 4 | [contrastive learning](https://scholar4ai.com/keywords/contrastive-learning.md) | 130 | 1,644 | 8% |
| 5 | quality-adjusted life years | 118 | 487 | 24% |
| 6 | self-supervised learning | 91 | 1,032 | 9% |
| 7 | object detection | 91 | 656 | 14% |
| 8 | semantic segmentation | 87 | 646 | 13% |
| 9 | image classification | 87 | 846 | 10% |
| 10 | attention mechanism | 80 | 1,667 | 5% |
| 11 | [knowledge distillation](https://scholar4ai.com/keywords/knowledge-distillation.md) | 79 | 1,021 | 8% |
| 12 | diffusion models | 76 | 791 | 10% |
| 13 | [COVID-19 pandemic](https://scholar4ai.com/keywords/covid-19-pandemic.md) | 76 | 5,530 | 1% |
| 14 | [class imbalance](https://scholar4ai.com/keywords/class-imbalance.md) | 74 | 1,675 | 4% |
| 15 | data augmentation | 70 | 1,078 | 6% |
| 16 | transformer models | 70 | 1,144 | 6% |
| 17 | [multimodal fusion](https://scholar4ai.com/keywords/multimodal-fusion.md) | 70 | 1,225 | 6% |
| 18 | pseudo-labeling | 65 | 761 | 9% |
| 19 | interpretability | 65 | 1,246 | 5% |
| 20 | self-attention | 58 | 733 | 8% |
| 21 | health technology assessment | 58 | 314 | 18% |
| 22 | health care costs | 58 | 476 | 12% |
| 23 | computational efficiency | 57 | 1,278 | 4% |
| 24 | semi-supervised learning | 57 | 732 | 8% |
| 25 | [China](https://scholar4ai.com/keywords/china.md) | 56 | 6,654 | 1% |
| 26 | transfer learning | 55 | 985 | 6% |
| 27 | [vision-language models](https://scholar4ai.com/keywords/vision-language-models.md) | 54 | 568 | 10% |
| 28 | autonomous driving | 54 | 563 | 10% |
| 29 | domain adaptation | 53 | 695 | 8% |
| 30 | [reinforcement learning](https://scholar4ai.com/keywords/reinforcement-learning.md) | 53 | 1,018 | 5% |
| 31 | domain generalization | 53 | 543 | 10% |
| 32 | catastrophic forgetting | 51 | 555 | 9% |
| 33 | [federated learning](https://scholar4ai.com/keywords/federated-learning.md) | 50 | 987 | 5% |
| 34 | vision transformer | 50 | 670 | 7% |
| 35 | few-shot learning | 50 | 655 | 8% |
| 36 | [explainable AI](https://scholar4ai.com/keywords/explainable-ai.md) | 47 | 1,307 | 4% |
| 37 | CLIP | 46 | 385 | 12% |
| 38 | convolutional neural networks | 45 | 1,257 | 4% |
| 39 | overfitting | 45 | 529 | 9% |
| 40 | [mixed-integer linear programming](https://scholar4ai.com/keywords/mixed-integer-linear-programming.md) | 44 | 1,121 | 4% |

## Cite this page

Scholar4AI. (2026). Corporate research: companies publishing in the tracked journals, 2023–2025. Journal Research Rankings. Retrieved October 31, 2026, from https://scholar4ai.com/rankings/companies

```bibtex
@misc{scholar4ai-rankings-companies,
  author = {{Scholar4AI}},
  title = {Corporate research: companies publishing in the tracked journals, 2023–2025},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/rankings/companies}},
  urldate = {2026-10-31},
  note = {Journal Research Rankings; data from OpenAlex (CC0); licensed CC BY-NC 4.0}
}
```

License: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/).