TechNext’s research, initially conducted at MIT, showcases the regularity of improvement rate (from generalized Moore’s law) which lies at the heart of integrating objective data into decision processes affected by the timing of technological change.
Source- Magee, C. L., Basnet, S., Funk, J. L., & Benson, C. L. (2016). Quantitative empirical trends in technical performance. Technological Forecasting and Social Change, 104, 237–246. https://doi.org/10.1016/j.techfore.2015.12.011
The computation of centrality of cited patents in the overall patent citation network is illustrated above. Nodes are patents and arrows are citations. Patents depicted in blue are the most central in each filing year. These centralities are computed before the green and the red patents are filed.
Source- Triulzi, G., Alstott, J., & Magee, C. L. (2020). Estimating technology performance improvement rates by mining patent data. Technological Forecasting and Social Change, 158, 120100. https://doi.org/10.1016/j.techfore.2020.120100