Innovation Diffusion and Forecasting
Innovation Diffusion and Forecasting is a research topic within Management Science and Operations Research. Science Explorer counts 17k research works in it since 1951. 27.4% of them reached the world's top 10% most cited for their field and year.
This cluster of papers focuses on the models, dynamics, and factors influencing the diffusion of technology and innovation across different markets and countries. It explores concepts such as innovation diffusion, agent-based modeling, market penetration, global technology spillover, forecasting models like S-curves and long-wave theory, and the impact of technological paradigms on adoption.
- Innovation Diffusion
- Agent-Based Modeling
- New Product Growth
- Market Penetration
- Global Technology Spillover
- Forecasting Models
- S-Curves
- Long-Wave Theory
- Mobile Telephony
- Technological Paradigms
- Research works
- 17k fractional, since 1951
- In the world top 10%
- 4.6k per year above
- Top-10% rate
- 27.4% share of its works in the world top 10%
- Growth, 2013–17 → 2018–22
- +13% the tick is no change
Which countries lead Innovation Diffusion and Forecasting research?
By volume, China and the United States publish the most (1.2k and 414 works in 2022–2025).
By volume, 2022–2025
- 1 China 1.2k works
- 2 United States 414 works
- 3 India 196 works
- 4 United Kingdom 130 works
- 5 Germany 126 works
- 6 Russia 112 works
- 7 Italy 95 works
- 8 South Korea 93 works
- 9 Indonesia 86 works
- 10 Japan 69 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.
Shares of the rows listed above, not of the whole node.
Which institutions lead Innovation Diffusion and Forecasting research?
By volume in 2022–2025, Wuhan University publishes the most Innovation Diffusion and Forecasting research, followed by Wuhan University of Technology and Shanghai University.
By volume, 2022–2025
- 1 Wuhan UniversityChina 16 works
- 2 Wuhan University of TechnologyChina 14 works
- 3 Shanghai UniversityChina 13 works
- 4 Tianjin UniversityChina 12 works
- 5 Xiamen UniversityChina 11 works
- 6 Shanghai Jiao Tong UniversityChina 11 works
- 7 Jiangsu UniversityChina 11 works
- 8 Tsinghua UniversityChina 11 works
- 9 Beijing Jiaotong UniversityChina 11 works
- 10 Sichuan UniversityChina 10 works
Who are the leading researchers in Innovation Diffusion and Forecasting?
The most-cited researchers publishing on Innovation Diffusion and Forecasting include H. Eugene Stanley.
- 1 H. Eugene Stanley United States 5.5k citations
Ranked by citations received across their whole record, among researchers with at least three works on this topic.
Where is Innovation Diffusion and Forecasting research done?
The largest centres of Innovation Diffusion and Forecasting research in 2022–2025 are Beijing (China), Shanghai (China), Wuhan (China) and Nanjing (China). Among places with at least 20 works in it, it is an unusually large share of all research in Tianjin and Wuhan.
Largest cities, 2022–2025
Where it is the local speciality
- TianjinCN · 41.9 works2.6×
- WuhanCN · 67.8 works2.4×
Location quotient: how much more of its research is in Innovation Diffusion and Forecasting than the world average.
Where is the best place to study Innovation Diffusion and Forecasting?
Among universities, judged by research, Tianjin University, Zhejiang University of Finance and Economics and Wuhan 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.
One dot per university in the table below. The upper left is the interesting corner: small places doing unusually strong work.
| # | University | Score | Top 10% | Specialisation | Works | Growth |
|---|---|---|---|---|---|---|
| 1 | Tianjin UniversityChina | 58.2 | 53.7% | 2.8× | 12 | +6.6% |
| 2 | Zhejiang University of Finance and EconomicsChina | 55.4 | 41.4% | 31.2× | 8 | +9.0% |
| 3 | Wuhan UniversityChina | 53.4 | 49.9% | 3.7× | 16 | -46.4% |
| 4 | Harbin Engineering UniversityChina | 45.8 | 53.6% | 5.1× | 9 | -31.0% |
| 5 | Jiangsu UniversityChina | 45.7 | 47.2% | 4.2× | 11 | -33.2% |
| 6 | South China University of TechnologyChina | 44.7 | 44.8% | 2.5× | 10 | +18.7% |
| 7 | Central University of Finance and EconomicsChina | 40.3 | 33.3% | 22.3× | 9 | -42.9% |
| 8 | Renmin University of ChinaChina | 40.3 | 44.2% | 7.1× | 8 | -45.1% |
| 9 | Wuhan University of TechnologyChina | 40.0 | 37.5% | 5.0× | 14 | -68.2% |
| 10 | Nanjing UniversityChina | 39.5 | 46.1% | 3.6× | 10 | -37.3% |
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 Innovation Diffusion and Forecasting research growing?
Output in 2018–2022 was 13% higher than in 2013–2017, peaking in 2025. The fastest-growing topics are Innovation Diffusion and Forecasting.
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.