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How well do experience curves predict technological progress? A method for making distributional forecasts

Overview of attention for article published in Technological Forecasting and Social Change, March 2018
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#45 of 2,486)
  • High Attention Score compared to outputs of the same age (95th percentile)
  • High Attention Score compared to outputs of the same age and source (92nd percentile)

Mentioned by

news
4 news outlets
blogs
1 blog
policy
1 policy source
twitter
31 X users

Citations

dimensions_citation
47 Dimensions

Readers on

mendeley
157 Mendeley
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Title
How well do experience curves predict technological progress? A method for making distributional forecasts
Published in
Technological Forecasting and Social Change, March 2018
DOI 10.1016/j.techfore.2017.11.001
Authors

François Lafond, Aimee Gotway Bailey, Jan David Bakker, Dylan Rebois, Rubina Zadourian, Patrick McSharry, J. Doyne Farmer

Timeline

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X Demographics

X Demographics

The data shown below were collected from the profiles of 31 X users who shared this research output. Click here to find out more about how the information was compiled.
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 157 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Estonia 1 <1%
Unknown 156 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 27 17%
Student > Master 24 15%
Researcher 17 11%
Student > Doctoral Student 8 5%
Student > Bachelor 7 4%
Other 24 15%
Unknown 50 32%
Readers by discipline Count As %
Engineering 21 13%
Energy 18 11%
Economics, Econometrics and Finance 13 8%
Business, Management and Accounting 9 6%
Environmental Science 7 4%
Other 31 20%
Unknown 58 37%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 58. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 24 October 2023.
All research outputs
#792,488
of 26,571,932 outputs
Outputs from Technological Forecasting and Social Change
#45
of 2,486 outputs
Outputs of similar age
#17,038
of 348,680 outputs
Outputs of similar age from Technological Forecasting and Social Change
#3
of 40 outputs
Altmetric has tracked 26,571,932 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 97th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,486 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.0. This one has done particularly well, scoring higher than 98% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 348,680 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 95% of its contemporaries.
We're also able to compare this research output to 40 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 92% of its contemporaries.