Phys.org comments on MIT method to use patent citation statistics
Work of Chris Benson and Chris Magee using patent citation statistics was recently published in PLoS ONE.
link to phys.org article
http://phys.org/news/2015-04-method-patent-technology-future.html
link to phys.org article
http://phys.org/news/2015-04-method-patent-technology-future.html
The team devised a
simple equation incorporating forward citation and publication date, and
used the method to predict improvement rates for 28 technologies. The
researchers then compared the rates with those they previously obtained
using their more time-intensive, historical data-based approach, and
found the results from both methods matched closely.
They then used their more efficient approach to predict the improvement rates of 11 emerging technologies in the next 10 years. Among these, the fastest-growing domains appear to be online learning and digital representation, while slower technologies include food engineering and nuclear fusion.
Magee hopes the method may be used much like a rating system, similar to Standard & Poor's and other stock-market indices. Such ratings could be useful for investors looking for the next big breakthrough, as well as scientific labs that are contemplating new research directions. Magee says knowing how various technologies may improve in the next decade could give innovators an idea of when "feeder technologies" may mature, and enable more pie-in-the-sky ideas, like mass-produced hoverboards and flying cars.
"We can help reduce the uncertainty of the capabilities of a technology in the future, not to zero, but to a more manageable number," Benson says. "I believe that's valuable in a lot of different ways."
Read more at: http://phys.org/news/2015-04-method-patent-technology-future.html#jCp
They then used their more efficient approach to predict the improvement rates of 11 emerging technologies in the next 10 years. Among these, the fastest-growing domains appear to be online learning and digital representation, while slower technologies include food engineering and nuclear fusion.
Magee hopes the method may be used much like a rating system, similar to Standard & Poor's and other stock-market indices. Such ratings could be useful for investors looking for the next big breakthrough, as well as scientific labs that are contemplating new research directions. Magee says knowing how various technologies may improve in the next decade could give innovators an idea of when "feeder technologies" may mature, and enable more pie-in-the-sky ideas, like mass-produced hoverboards and flying cars.
"We can help reduce the uncertainty of the capabilities of a technology in the future, not to zero, but to a more manageable number," Benson says. "I believe that's valuable in a lot of different ways."
Read more at: http://phys.org/news/2015-04-method-patent-technology-future.html#jCp
Now engineers at
MIT have devised a formula for estimating how fast a technology is
advancing, based on information gleaned from relevant patents.
The researchers determined the improvement rates of 28 different technologies, including solar photovoltaics, 3-D printing, fuel-cell technology, and genome sequencing. They searched through the U.S. Patent Office database for patents associated with each domain—more than 500,000 total—by developing a novel method to quickly and accurately select the patents that best represent each technology.
Once these were identified, the researchers analyzed certain metrics across patents in each domain, and found that some were more likely to predict a technology's improvement rate than others. In particular, forward citations—the number of times a patent is cited by subsequent patents—is a good predictor, as is the date of a patent's publication: Technologies with more recent patents are likely innovating at a faster rate than those with older patents.
The team devised an equation incorporating a patent set's average forward citation and average publication date, and calculated the rate of improvement for each technology domain. Their results matched closely with the rates determined through the more labor-intensive approach of finding numerous historical performance data points for each technology.
Among the 28 domains analyzed, the researchers found the fastest-developing technologies include optical and wireless communications, 3-D printing, and MRI technology, while domains such as batteries, wind turbines, and combustion engines appear to be improving at slower rates.
Chris Benson, a former graduate student in MIT's Department of Mechanical Engineering, says the new prediction tool may be of interest to venture capitalists, startups, and government and industry labs looking to explore new technology.
Read more at: http://phys.org/news/2015-04-method-patent-technology-future.html#jCp
The researchers determined the improvement rates of 28 different technologies, including solar photovoltaics, 3-D printing, fuel-cell technology, and genome sequencing. They searched through the U.S. Patent Office database for patents associated with each domain—more than 500,000 total—by developing a novel method to quickly and accurately select the patents that best represent each technology.
Once these were identified, the researchers analyzed certain metrics across patents in each domain, and found that some were more likely to predict a technology's improvement rate than others. In particular, forward citations—the number of times a patent is cited by subsequent patents—is a good predictor, as is the date of a patent's publication: Technologies with more recent patents are likely innovating at a faster rate than those with older patents.
The team devised an equation incorporating a patent set's average forward citation and average publication date, and calculated the rate of improvement for each technology domain. Their results matched closely with the rates determined through the more labor-intensive approach of finding numerous historical performance data points for each technology.
Among the 28 domains analyzed, the researchers found the fastest-developing technologies include optical and wireless communications, 3-D printing, and MRI technology, while domains such as batteries, wind turbines, and combustion engines appear to be improving at slower rates.
Chris Benson, a former graduate student in MIT's Department of Mechanical Engineering, says the new prediction tool may be of interest to venture capitalists, startups, and government and industry labs looking to explore new technology.
Read more at: http://phys.org/news/2015-04-method-patent-technology-future.html#jCp
Now engineers at
MIT have devised a formula for estimating how fast a technology is
advancing, based on information gleaned from relevant patents.
The researchers determined the improvement rates of 28 different technologies, including solar photovoltaics, 3-D printing, fuel-cell technology, and genome sequencing. They searched through the U.S. Patent Office database for patents associated with each domain—more than 500,000 total—by developing a novel method to quickly and accurately select the patents that best represent each technology.
Once these were identified, the researchers analyzed certain metrics across patents in each domain, and found that some were more likely to predict a technology's improvement rate than others. In particular, forward citations—the number of times a patent is cited by subsequent patents—is a good predictor, as is the date of a patent's publication: Technologies with more recent patents are likely innovating at a faster rate than those with older patents.
The team devised an equation incorporating a patent set's average forward citation and average publication date, and calculated the rate of improvement for each technology domain. Their results matched closely with the rates determined through the more labor-intensive approach of finding numerous historical performance data points for each technology.
Among the 28 domains analyzed, the researchers found the fastest-developing technologies include optical and wireless communications, 3-D printing, and MRI technology, while domains such as batteries, wind turbines, and combustion engines appear to be improving at slower rates.
Chris Benson, a former graduate student in MIT's Department of Mechanical Engineering, says the new prediction tool may be of interest to venture capitalists, startups, and government and industry labs looking to explore new technology.
Read more at: http://phys.org/news/2015-04-method-patent-technology-future.html#jCp
The researchers determined the improvement rates of 28 different technologies, including solar photovoltaics, 3-D printing, fuel-cell technology, and genome sequencing. They searched through the U.S. Patent Office database for patents associated with each domain—more than 500,000 total—by developing a novel method to quickly and accurately select the patents that best represent each technology.
Once these were identified, the researchers analyzed certain metrics across patents in each domain, and found that some were more likely to predict a technology's improvement rate than others. In particular, forward citations—the number of times a patent is cited by subsequent patents—is a good predictor, as is the date of a patent's publication: Technologies with more recent patents are likely innovating at a faster rate than those with older patents.
The team devised an equation incorporating a patent set's average forward citation and average publication date, and calculated the rate of improvement for each technology domain. Their results matched closely with the rates determined through the more labor-intensive approach of finding numerous historical performance data points for each technology.
Among the 28 domains analyzed, the researchers found the fastest-developing technologies include optical and wireless communications, 3-D printing, and MRI technology, while domains such as batteries, wind turbines, and combustion engines appear to be improving at slower rates.
Chris Benson, a former graduate student in MIT's Department of Mechanical Engineering, says the new prediction tool may be of interest to venture capitalists, startups, and government and industry labs looking to explore new technology.
Read more at: http://phys.org/news/2015-04-method-patent-technology-future.html#jCp
Now engineers at
MIT have devised a formula for estimating how fast a technology is
advancing, based on information gleaned from relevant patents.
The researchers determined the improvement rates of 28 different technologies, including solar photovoltaics, 3-D printing, fuel-cell technology, and genome sequencing. They searched through the U.S. Patent Office database for patents associated with each domain—more than 500,000 total—by developing a novel method to quickly and accurately select the patents that best represent each technology.
Once these were identified, the researchers analyzed certain metrics across patents in each domain, and found that some were more likely to predict a technology's improvement rate than others. In particular, forward citations—the number of times a patent is cited by subsequent patents—is a good predictor, as is the date of a patent's publication: Technologies with more recent patents are likely innovating at a faster rate than those with older patents.
The team devised an equation incorporating a patent set's average forward citation and average publication date, and calculated the rate of improvement for each technology domain. Their results matched closely with the rates determined through the more labor-intensive approach of finding numerous historical performance data points for each technology.
Among the 28 domains analyzed, the researchers found the fastest-developing technologies include optical and wireless communications, 3-D printing, and MRI technology, while domains such as batteries, wind turbines, and combustion engines appear to be improving at slower rates.
Chris Benson, a former graduate student in MIT's Department of Mechanical Engineering, says the new prediction tool may be of interest to venture capitalists, startups, and government and industry labs looking to explore new technology.
Read more at: http://phys.org/news/2015-04-method-patent-technology-future.html#jCp
The researchers determined the improvement rates of 28 different technologies, including solar photovoltaics, 3-D printing, fuel-cell technology, and genome sequencing. They searched through the U.S. Patent Office database for patents associated with each domain—more than 500,000 total—by developing a novel method to quickly and accurately select the patents that best represent each technology.
Once these were identified, the researchers analyzed certain metrics across patents in each domain, and found that some were more likely to predict a technology's improvement rate than others. In particular, forward citations—the number of times a patent is cited by subsequent patents—is a good predictor, as is the date of a patent's publication: Technologies with more recent patents are likely innovating at a faster rate than those with older patents.
The team devised an equation incorporating a patent set's average forward citation and average publication date, and calculated the rate of improvement for each technology domain. Their results matched closely with the rates determined through the more labor-intensive approach of finding numerous historical performance data points for each technology.
Among the 28 domains analyzed, the researchers found the fastest-developing technologies include optical and wireless communications, 3-D printing, and MRI technology, while domains such as batteries, wind turbines, and combustion engines appear to be improving at slower rates.
Chris Benson, a former graduate student in MIT's Department of Mechanical Engineering, says the new prediction tool may be of interest to venture capitalists, startups, and government and industry labs looking to explore new technology.
Read more at: http://phys.org/news/2015-04-method-patent-technology-future.html#jCp
Now engineers at
MIT have devised a formula for estimating how fast a technology is
advancing, based on information gleaned from relevant patents.
The researchers determined the improvement rates of 28 different technologies, including solar photovoltaics, 3-D printing, fuel-cell technology, and genome sequencing. They searched through the U.S. Patent Office database for patents associated with each domain—more than 500,000 total—by developing a novel method to quickly and accurately select the patents that best represent each technology.
Once these were identified, the researchers analyzed certain metrics across patents in each domain, and found that some were more likely to predict a technology's improvement rate than others. In particular, forward citations—the number of times a patent is cited by subsequent patents—is a good predictor, as is the date of a patent's publication: Technologies with more recent patents are likely innovating at a faster rate than those with older patents.
The team devised an equation incorporating a patent set's average forward citation and average publication date, and calculated the rate of improvement for each technology domain. Their results matched closely with the rates determined through the more labor-intensive approach of finding numerous historical performance data points for each technology.
Among the 28 domains analyzed, the researchers found the fastest-developing technologies include optical and wireless communications, 3-D printing, and MRI technology, while domains such as batteries, wind turbines, and combustion engines appear to be improving at slower rates.
Chris Benson, a former graduate student in MIT's Department of Mechanical Engineering, says the new prediction tool may be of interest to venture capitalists, startups, and government and industry labs looking to explore new technology.
Read more at: http://phys.org/news/2015-04-method-patent-technology-future.html#jCp
The researchers determined the improvement rates of 28 different technologies, including solar photovoltaics, 3-D printing, fuel-cell technology, and genome sequencing. They searched through the U.S. Patent Office database for patents associated with each domain—more than 500,000 total—by developing a novel method to quickly and accurately select the patents that best represent each technology.
Once these were identified, the researchers analyzed certain metrics across patents in each domain, and found that some were more likely to predict a technology's improvement rate than others. In particular, forward citations—the number of times a patent is cited by subsequent patents—is a good predictor, as is the date of a patent's publication: Technologies with more recent patents are likely innovating at a faster rate than those with older patents.
The team devised an equation incorporating a patent set's average forward citation and average publication date, and calculated the rate of improvement for each technology domain. Their results matched closely with the rates determined through the more labor-intensive approach of finding numerous historical performance data points for each technology.
Among the 28 domains analyzed, the researchers found the fastest-developing technologies include optical and wireless communications, 3-D printing, and MRI technology, while domains such as batteries, wind turbines, and combustion engines appear to be improving at slower rates.
Chris Benson, a former graduate student in MIT's Department of Mechanical Engineering, says the new prediction tool may be of interest to venture capitalists, startups, and government and industry labs looking to explore new technology.
Read more at: http://phys.org/news/2015-04-method-patent-technology-future.html#jCp
Now engineers at
MIT have devised a formula for estimating how fast a technology is
advancing, based on information gleaned from relevant patents.
The researchers determined the improvement rates of 28 different technologies, including solar photovoltaics, 3-D printing, fuel-cell technology, and genome sequencing. They searched through the U.S. Patent Office database for patents associated with each domain—more than 500,000 total—by developing a novel method to quickly and accurately select the patents that best represent each technology.
Once these were identified, the researchers analyzed certain metrics across patents in each domain, and found that some were more likely to predict a technology's improvement rate than others. In particular, forward citations—the number of times a patent is cited by subsequent patents—is a good predictor, as is the date of a patent's publication: Technologies with more recent patents are likely innovating at a faster rate than those with older patents.
The team devised an equation incorporating a patent set's average forward citation and average publication date, and calculated the rate of improvement for each technology domain. Their results matched closely with the rates determined through the more labor-intensive approach of finding numerous historical performance data points for each technology.
Among the 28 domains analyzed, the researchers found the fastest-developing technologies include optical and wireless communications, 3-D printing, and MRI technology, while domains such as batteries, wind turbines, and combustion engines appear to be improving at slower rates.
Chris Benson, a former graduate student in MIT's Department of Mechanical Engineering, says the new prediction tool may be of interest to venture capitalists, startups, and government and industry labs looking to explore new technology.
Read more at: http://phys.org/news/2015-04-method-patent-technology-future.html#jCp
The researchers determined the improvement rates of 28 different technologies, including solar photovoltaics, 3-D printing, fuel-cell technology, and genome sequencing. They searched through the U.S. Patent Office database for patents associated with each domain—more than 500,000 total—by developing a novel method to quickly and accurately select the patents that best represent each technology.
Once these were identified, the researchers analyzed certain metrics across patents in each domain, and found that some were more likely to predict a technology's improvement rate than others. In particular, forward citations—the number of times a patent is cited by subsequent patents—is a good predictor, as is the date of a patent's publication: Technologies with more recent patents are likely innovating at a faster rate than those with older patents.
The team devised an equation incorporating a patent set's average forward citation and average publication date, and calculated the rate of improvement for each technology domain. Their results matched closely with the rates determined through the more labor-intensive approach of finding numerous historical performance data points for each technology.
Among the 28 domains analyzed, the researchers found the fastest-developing technologies include optical and wireless communications, 3-D printing, and MRI technology, while domains such as batteries, wind turbines, and combustion engines appear to be improving at slower rates.
Chris Benson, a former graduate student in MIT's Department of Mechanical Engineering, says the new prediction tool may be of interest to venture capitalists, startups, and government and industry labs looking to explore new technology.
Read more at: http://phys.org/news/2015-04-method-patent-technology-future.html#jCp
Now engineers at
MIT have devised a formula for estimating how fast a technology is
advancing, based on information gleaned from relevant patents.
The researchers determined the improvement rates of 28 different technologies, including solar photovoltaics, 3-D printing, fuel-cell technology, and genome sequencing. They searched through the U.S. Patent Office database for patents associated with each domain—more than 500,000 total—by developing a novel method to quickly and accurately select the patents that best represent each technology.
Once these were identified, the researchers analyzed certain metrics across patents in each domain, and found that some were more likely to predict a technology's improvement rate than others. In particular, forward citations—the number of times a patent is cited by subsequent patents—is a good predictor, as is the date of a patent's publication: Technologies with more recent patents are likely innovating at a faster rate than those with older patents.
The team devised an equation incorporating a patent set's average forward citation and average publication date, and calculated the rate of improvement for each technology domain. Their results matched closely with the rates determined through the more labor-intensive approach of finding numerous historical performance data points for each technology.
Among the 28 domains analyzed, the researchers found the fastest-developing technologies include optical and wireless communications, 3-D printing, and MRI technology, while domains such as batteries, wind turbines, and combustion engines appear to be improving at slower rates.
Chris Benson, a former graduate student in MIT's Department of Mechanical Engineering, says the new prediction tool may be of interest to venture capitalists, startups, and government and industry labs looking to explore new technology.
Read more at: http://phys.org/news/2015-04-method-patent-technology-future.html#jCp
The researchers determined the improvement rates of 28 different technologies, including solar photovoltaics, 3-D printing, fuel-cell technology, and genome sequencing. They searched through the U.S. Patent Office database for patents associated with each domain—more than 500,000 total—by developing a novel method to quickly and accurately select the patents that best represent each technology.
Once these were identified, the researchers analyzed certain metrics across patents in each domain, and found that some were more likely to predict a technology's improvement rate than others. In particular, forward citations—the number of times a patent is cited by subsequent patents—is a good predictor, as is the date of a patent's publication: Technologies with more recent patents are likely innovating at a faster rate than those with older patents.
The team devised an equation incorporating a patent set's average forward citation and average publication date, and calculated the rate of improvement for each technology domain. Their results matched closely with the rates determined through the more labor-intensive approach of finding numerous historical performance data points for each technology.
Among the 28 domains analyzed, the researchers found the fastest-developing technologies include optical and wireless communications, 3-D printing, and MRI technology, while domains such as batteries, wind turbines, and combustion engines appear to be improving at slower rates.
Chris Benson, a former graduate student in MIT's Department of Mechanical Engineering, says the new prediction tool may be of interest to venture capitalists, startups, and government and industry labs looking to explore new technology.
Read more at: http://phys.org/news/2015-04-method-patent-technology-future.html#jCp
Now engineers at
MIT have devised a formula for estimating how fast a technology is
advancing, based on information gleaned from relevant patents.
The researchers determined the improvement rates of 28 different technologies, including solar photovoltaics, 3-D printing, fuel-cell technology, and genome sequencing. They searched through the U.S. Patent Office database for patents associated with each domain—more than 500,000 total—by developing a novel method to quickly and accurately select the patents that best represent each technology.
Once these were identified, the researchers analyzed certain metrics across patents in each domain, and found that some were more likely to predict a technology's improvement rate than others. In particular, forward citations—the number of times a patent is cited by subsequent patents—is a good predictor, as is the date of a patent's publication: Technologies with more recent patents are likely innovating at a faster rate than those with older patents.
The team devised an equation incorporating a patent set's average forward citation and average publication date, and calculated the rate of improvement for each technology domain. Their results matched closely with the rates determined through the more labor-intensive approach of finding numerous historical performance data points for each technology.
Among the 28 domains analyzed, the researchers found the fastest-developing technologies include optical and wireless communications, 3-D printing, and MRI technology, while domains such as batteries, wind turbines, and combustion engines appear to be improving at slower rates.
Chris Benson, a former graduate student in MIT's Department of Mechanical Engineering, says the new prediction tool may be of interest to venture capitalists, startups, and government and industry labs looking to explore new technology.
Read more at: http://phys.org/news/2015-04-method-patent-technology-future.html#jCp
The researchers determined the improvement rates of 28 different technologies, including solar photovoltaics, 3-D printing, fuel-cell technology, and genome sequencing. They searched through the U.S. Patent Office database for patents associated with each domain—more than 500,000 total—by developing a novel method to quickly and accurately select the patents that best represent each technology.
Once these were identified, the researchers analyzed certain metrics across patents in each domain, and found that some were more likely to predict a technology's improvement rate than others. In particular, forward citations—the number of times a patent is cited by subsequent patents—is a good predictor, as is the date of a patent's publication: Technologies with more recent patents are likely innovating at a faster rate than those with older patents.
The team devised an equation incorporating a patent set's average forward citation and average publication date, and calculated the rate of improvement for each technology domain. Their results matched closely with the rates determined through the more labor-intensive approach of finding numerous historical performance data points for each technology.
Among the 28 domains analyzed, the researchers found the fastest-developing technologies include optical and wireless communications, 3-D printing, and MRI technology, while domains such as batteries, wind turbines, and combustion engines appear to be improving at slower rates.
Chris Benson, a former graduate student in MIT's Department of Mechanical Engineering, says the new prediction tool may be of interest to venture capitalists, startups, and government and industry labs looking to explore new technology.
Read more at: http://phys.org/news/2015-04-method-patent-technology-future.html#jCp
Now engineers at MIT
have devised a formula for estimating how fast a technology is
advancing, based on information gleaned from relevant patents.
The researchers determined the improvement rates of 28 different technologies, including solar photovoltaics, 3-D printing, fuel-cell technology, and genome sequencing. They searched through the U.S. Patent Office database for patents associated with each domain—more than 500,000 total—by developing a novel method to quickly and accurately select the patents that best represent each technology.
Once these were identified, the researchers analyzed certain metrics across patents in each domain, and found that some were more likely to predict a technology's improvement rate than others. In particular, forward citations—the number of times a patent is cited by subsequent patents—is a good predictor, as is the date of a patent's publication: Technologies with more recent patents are likely innovating at a faster rate than those with older patents.
The team devised an equation incorporating a patent set's average forward citation and average publication date, and calculated the rate of improvement for each technology domain. Their results matched closely with the rates determined through the more labor-intensive approach of finding numerous historical performance data points for each technology.
Among the 28 domains analyzed, the researchers found the fastest-developing technologies include optical and wireless communications, 3-D printing, and MRI technology, while domains such as batteries, wind turbines, and combustion engines appear to be improving at slower rates.
Chris Benson, a former graduate student in MIT's Department of Mechanical Engineering, says the new prediction tool may be of interest to venture capitalists, startups, and government and industry labs looking to explore new technology.
Read more at: http://phys.org/news/2015-04-method-patent-technology-future.html#jCp
The researchers determined the improvement rates of 28 different technologies, including solar photovoltaics, 3-D printing, fuel-cell technology, and genome sequencing. They searched through the U.S. Patent Office database for patents associated with each domain—more than 500,000 total—by developing a novel method to quickly and accurately select the patents that best represent each technology.
Once these were identified, the researchers analyzed certain metrics across patents in each domain, and found that some were more likely to predict a technology's improvement rate than others. In particular, forward citations—the number of times a patent is cited by subsequent patents—is a good predictor, as is the date of a patent's publication: Technologies with more recent patents are likely innovating at a faster rate than those with older patents.
The team devised an equation incorporating a patent set's average forward citation and average publication date, and calculated the rate of improvement for each technology domain. Their results matched closely with the rates determined through the more labor-intensive approach of finding numerous historical performance data points for each technology.
Among the 28 domains analyzed, the researchers found the fastest-developing technologies include optical and wireless communications, 3-D printing, and MRI technology, while domains such as batteries, wind turbines, and combustion engines appear to be improving at slower rates.
Chris Benson, a former graduate student in MIT's Department of Mechanical Engineering, says the new prediction tool may be of interest to venture capitalists, startups, and government and industry labs looking to explore new technology.
Read more at: http://phys.org/news/2015-04-method-patent-technology-future.html#jCp
Now engineers at MIT
have devised a formula for estimating how fast a technology is
advancing, based on information gleaned from relevant patents.
The researchers determined the improvement rates of 28 different technologies, including solar photovoltaics, 3-D printing, fuel-cell technology, and genome sequencing. They searched through the U.S. Patent Office database for patents associated with each domain—more than 500,000 total—by developing a novel method to quickly and accurately select the patents that best represent each technology.
Once these were identified, the researchers analyzed certain metrics across patents in each domain, and found that some were more likely to predict a technology's improvement rate than others. In particular, forward citations—the number of times a patent is cited by subsequent patents—is a good predictor, as is the date of a patent's publication: Technologies with more recent patents are likely innovating at a faster rate than those with older patents.
The team devised an equation incorporating a patent set's average forward citation and average publication date, and calculated the rate of improvement for each technology domain. Their results matched closely with the rates determined through the more labor-intensive approach of finding numerous historical performance data points for each technology.
Among the 28 domains analyzed, the researchers found the fastest-developing technologies include optical and wireless communications, 3-D printing, and MRI technology, while domains such as batteries, wind turbines, and combustion engines appear to be improving at slower rates.
Chris Benson, a former graduate student in MIT's Department of Mechanical Engineering, says the new prediction tool may be of interest to venture capitalists, startups, and government and industry labs looking to explore new technology.
Read more at: http://phys.org/news/2015-04-method-patent-technology-future.html#j
The researchers determined the improvement rates of 28 different technologies, including solar photovoltaics, 3-D printing, fuel-cell technology, and genome sequencing. They searched through the U.S. Patent Office database for patents associated with each domain—more than 500,000 total—by developing a novel method to quickly and accurately select the patents that best represent each technology.
Once these were identified, the researchers analyzed certain metrics across patents in each domain, and found that some were more likely to predict a technology's improvement rate than others. In particular, forward citations—the number of times a patent is cited by subsequent patents—is a good predictor, as is the date of a patent's publication: Technologies with more recent patents are likely innovating at a faster rate than those with older patents.
The team devised an equation incorporating a patent set's average forward citation and average publication date, and calculated the rate of improvement for each technology domain. Their results matched closely with the rates determined through the more labor-intensive approach of finding numerous historical performance data points for each technology.
Among the 28 domains analyzed, the researchers found the fastest-developing technologies include optical and wireless communications, 3-D printing, and MRI technology, while domains such as batteries, wind turbines, and combustion engines appear to be improving at slower rates.
Chris Benson, a former graduate student in MIT's Department of Mechanical Engineering, says the new prediction tool may be of interest to venture capitalists, startups, and government and industry labs looking to explore new technology.
Read more at: http://phys.org/news/2015-04-method-patent-technology-future.html#j
Now engineers at MIT
have devised a formula for estimating how fast a technology is
advancing, based on information gleaned from relevant patents.
The researchers determined the improvement rates of 28 different technologies, including solar photovoltaics, 3-D printing, fuel-cell technology, and genome sequencing. They searched through the U.S. Patent Office database for patents associated with each domain—more than 500,000 total—by developing a novel method to quickly and accurately select the patents that best represent each technology.
Once these were identified, the researchers analyzed certain metrics across patents in each domain, and found that some were more likely to predict a technology's improvement rate than others. In particular, forward citations—the number of times a patent is cited by subsequent patents—is a good predictor, as is the date of a patent's publication: Technologies with more recent patents are likely innovating at a faster rate than those with older patents.
The team devised an equation incorporating a patent set's average forward citation and average publication date, and calculated the rate of improvement for each technology domain. Their results matched closely with the rates determined through the more labor-intensive approach of finding numerous historical performance data points for each technology.
Among the 28 domains analyzed, the researchers found the fastest-developing technologies include optical and wireless communications, 3-D printing, and MRI technology, while domains such as batteries, wind turbines, and combustion engines appear to be improving at slower rates.
Chris Benson, a former graduate student in MIT's Department of Mechanical Engineering, says the new prediction tool may be of interest to venture capitalists, startups, and government and industry labs looking to explore new technology.
Read more at: http://phys.org/news/2015-04-method-patent-technology-future.html#jCp
The researchers determined the improvement rates of 28 different technologies, including solar photovoltaics, 3-D printing, fuel-cell technology, and genome sequencing. They searched through the U.S. Patent Office database for patents associated with each domain—more than 500,000 total—by developing a novel method to quickly and accurately select the patents that best represent each technology.
Once these were identified, the researchers analyzed certain metrics across patents in each domain, and found that some were more likely to predict a technology's improvement rate than others. In particular, forward citations—the number of times a patent is cited by subsequent patents—is a good predictor, as is the date of a patent's publication: Technologies with more recent patents are likely innovating at a faster rate than those with older patents.
The team devised an equation incorporating a patent set's average forward citation and average publication date, and calculated the rate of improvement for each technology domain. Their results matched closely with the rates determined through the more labor-intensive approach of finding numerous historical performance data points for each technology.
Among the 28 domains analyzed, the researchers found the fastest-developing technologies include optical and wireless communications, 3-D printing, and MRI technology, while domains such as batteries, wind turbines, and combustion engines appear to be improving at slower rates.
Chris Benson, a former graduate student in MIT's Department of Mechanical Engineering, says the new prediction tool may be of interest to venture capitalists, startups, and government and industry labs looking to explore new technology.
Read more at: http://phys.org/news/2015-04-method-patent-technology-future.html#jCp
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