Title |
Quantitative Determination of Technological Improvement from Patent Data
|
---|---|
Published in |
PLOS ONE, April 2015
|
DOI | 10.1371/journal.pone.0121635 |
Pubmed ID | |
Authors |
Christopher L. Benson, Christopher L. Magee |
Abstract |
The results in this paper establish that information contained in patents in a technological domain is strongly correlated with the rate of technological progress in that domain. The importance of patents in a domain, the recency of patents in a domain and the immediacy of patents in a domain are all strongly correlated with increases in the rate of performance improvement in the domain of interest. A patent metric that combines both importance and immediacy is not only highly correlated (r = 0.76, p = 2.6*10-6) with the performance improvement rate but the correlation is also very robust to domain selection and appears to have good predictive power for more than ten years into the future. Linear regressions with all three causal concepts indicate realistic value in practical use to estimate the important performance improvement rate of a technological domain. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 4 | 17% |
United Kingdom | 2 | 9% |
Australia | 2 | 9% |
Japan | 1 | 4% |
France | 1 | 4% |
India | 1 | 4% |
Costa Rica | 1 | 4% |
Finland | 1 | 4% |
Unknown | 10 | 43% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 20 | 87% |
Scientists | 2 | 9% |
Science communicators (journalists, bloggers, editors) | 1 | 4% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 3 | 2% |
Netherlands | 2 | 2% |
United Kingdom | 1 | <1% |
Unknown | 116 | 95% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 32 | 26% |
Researcher | 20 | 16% |
Student > Master | 18 | 15% |
Other | 10 | 8% |
Student > Doctoral Student | 5 | 4% |
Other | 15 | 12% |
Unknown | 22 | 18% |
Readers by discipline | Count | As % |
---|---|---|
Engineering | 24 | 20% |
Business, Management and Accounting | 17 | 14% |
Computer Science | 13 | 11% |
Economics, Econometrics and Finance | 13 | 11% |
Agricultural and Biological Sciences | 4 | 3% |
Other | 21 | 17% |
Unknown | 30 | 25% |