Max Planck Institute for Innovation and Competition, Munich, Room 313
This talk will review the speaker’s and other researchers’ efforts to quantify technological change. Some challenges have been at least partially met but others are still outstanding. The important issues include what to measure (the dependent variable) and a variety of economic and technical measures will be considered with the conclusion that functional performance metrics are the most informative about what we want to learn. To quantify change, we also need to decide what the performance metrics theoretically depend upon (the independent variable). One obvious candidate is time but given work by Wright and many others, the presentation will also consider whether an effort variable such as cumulative demand/production or R&D spending improves the understanding of technological change. After making contestable decisions on the variables, the result for a wide variety of technological domains appears to be a generalization of Moore’s Law. However, this exponential relationship with time is quite noisy but more importantly, many (probably most) researchers of technological change do not find the generalized Moore’s Law (GML) acceptable. The final part of the presentation will be discussion and speculation about various reasons for this reality including practical utility, quantitative theoretical foundations and deep qualitative reasoning.
Contact Person: Dr. Fabian Gaessler