Transcript Slide 1
Economics 124/PP 190-5/290-5
Innovation and Technical
Change
Science, invention, and innovation
Prof. Bronwyn H. Hall
UC Berkeley
Today
Science, invention and innovation
The linear model
Deviations from the linear model
Technology driving science
Learning by using
Chance and unexpected innovations
Lessons for policy
Fall 2004 (C) B H Hall
Econ 124/PP 190-5/290-5
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The linear model of innovation
A useful conceptualization, but not the
whole story. The idea:
science base → basic research → applied
research → invention → prototype →
development → commercialization →
diffusion → technical progress →
economic growth
Sometimes the entire process in red is
referred to as innovation
Which stages need funding, and how?
Fall 2004 (C) B H Hall
Econ 124/PP 190-5/290-5
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Example – new drug
Basic research – microbiology, etc.
Applied research – screening compounds in
test tubes; testing on animals
Invention – successful in laboratory
Development – Phase I and II clinical trials
Commercialization – packaging; marketing;
dosage info
Diffusion – spread throughout the
patient/doctor population
Fall 2004 (C) B H Hall
Econ 124/PP 190-5/290-5
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Example – new software
Basic research – mathematics, queuing
theory
Applied research – cryptography, sorting
algorithms, data storage systems
Invention – idea of program, design, basic
features
Development – programming, detailed
specifications, alpha testing
Commercialization – beta testing, marketing,
sale
Diffusion – adoption by consumers; large
market share
Fall 2004 (C) B H Hall
Econ 124/PP 190-5/290-5
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Modifying the linear model
Importance of backward links (reverse the
arrows)
Commercialization and diffusion → new innovation
& development
Invention/innovation → science base/basic research
Rosenberg emphasizes this point in a series
of papers
“How exogenous is science?” (1981)
“Learning by using” (1978)
Both published in Inside the Black Box (CUP
1982)
Fall 2004 (C) B H Hall
Econ 124/PP 190-5/290-5
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Backward links in the linear model
"How Exogenous is Science?"
how applied research and innovation have yielded
new scientific knowledge and created new scientific
fields, both accidentally and purposefully
=> feedback from applied research, innovation, and
development to the science base.
"Learning by Using"
a term modeled on learning by doing
describes how products are improved and developed
in both embodied and disembodied ways, based on
experience of the product in use
=> feedback from diffusion to development
Fall 2004 (C) B H Hall
Econ 124/PP 190-5/290-5
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How exogenous is science?
exogenous means determined outside the
system
in this case, the innovation system
Technological knowledge often precedes
scientific knowledge
Scientific progress can be an accidental byproduct of
searching for an answer to a technological puzzle
A technological discovery can dictate the direction in
which subsequent scientific research should go
Improvements in instrumentation (technology)
A major determinant of subsequent scientific progress
nanotechnology (1910) and the electron microscope
Fall 2004 (C) B H Hall
Econ 124/PP 190-5/290-5
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Science from technology (1)
Inventor/s
cientist
Technological
source
Years Scientific field
developed
Toricelli
improved pump –
explored the weight
of the atmosphere
1600s Atmospheric/pressure
science/barometer
Watt/Carnot
steam engines
1830s Thermodynamics
Pasteur
wine industry/
fermentation
1850s Bacteriology/germ
theories
Perkin
/Hoffman
Synthesis of mauve,
first aniline dye
1870s Organic chemistry
Wilm
Bessemer process;
age-hardening of
duraluminum
1850- Metallurgy/
1900s materials science
Fall 2004 (C) B H Hall
Econ 124/PP 190-5/290-5
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Science from technology (2)
Inventor/
scientist
Technological source Years
Scientific field
developed
Davisson
vacuum tubes –
patterns of emission
from nickel crystal due
to electrons
1920s
Wave nature of
matter/ Nobel prize
1937
Jansky/
Bell labs
radio noise
1932
Radio astronomy
(star noise)
Townes/
Bell labs
Laser technology for
optic fiber cables
1950s
Optics resurgence
Shockley
Transistor/
semiconductor
1948
Solid state physics
Fall 2004 (C) B H Hall
Econ 124/PP 190-5/290-5
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Innovation and learning
During the R&D process
Knowledge concerning laws of nature (basic R)
Knowledge with useful applications (applied R)
Knowledge directed towards optimal design
characteristics and satisfying consumer wants
(development)
After the R&D process
During manufacturing – learning by doing
During the use of the product – learning by
using
Fall 2004 (C) B H Hall
Econ 124/PP 190-5/290-5
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Learning by doing
Widespread phenomenon in the repeated
manufacture of a good (airframes,
chemicals, semiconductors)
First measured for aircraft in the 1930s-1940s
labor = N-1/3 where N=N airplanes produced
Observed in a number of industries by the
Boston Consulting Group – plotted learning
curves with downward slope ~ 0.3
A major feature of semiconductor manufacturing
as the number of rejected chips falls over time
Fall 2004 (C) B H Hall
Econ 124/PP 190-5/290-5
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Learning in chemicals
25000
Unit Cost
20000
15000
10000
5000
.15
.2
.25
.3
.35
.4
.45
.5
.55
Cumulative Production
Fall 2004 (C) B H Hall
Econ 124/PP 190-5/290-5
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Learning by using
Technological change does not end after the
technology is diffused
Technologies continue to improve due to
feedback from use and users
software; skateboards
Some improvements embodied
learning how to stretch a Boeing 747
Some disembodied
learning the maintenance frequency necessary
for aircraft
learning that a drug good for one condition
actually works for another
Fall 2004 (C) B H Hall
Econ 124/PP 190-5/290-5
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Learning by using
Performance of complex capital goods
not fully understood until they are
used
Technological knowledge required highly
specialized, includes user knowledge
Product differentiation valuable to users,
can be achieved by them
e.g., skateboard innovations from users
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Econ 124/PP 190-5/290-5
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Aircraft example
Embodied learning
Uncertainty in aircraft design, plus
caution in first use
As time goes by, experience leads to
stretched aircraft, larger payloads
Disembodied learning
Extensive maintenance and overhaul
requirements of jet engines
Over time, service intervals lengthened
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Econ 124/PP 190-5/290-5
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Boeing 737-100,737-600/900
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Boeing 747-100,747-300,747-500
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Uncertainty and chance
History of innovation replete with
examples of discoveries that
Were a side effect of a completely
different investigation, as in technology>science examples
were unappreciated at the time they
were made (consequences or usefulness
unforeseen)
Examples: laser, radio, computer
Fall 2004 (C) B H Hall
Econ 124/PP 190-5/290-5
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Examples of forecasting failure
Laser (Light Amplification by Stimulated
Emission of Radiation)
invented by Townes at Bell Labs around 1960
now used in navigation, precision measurement,
chemical research, surgery, compact discs and
printing
most important and widespread use is probably
fiber-optic cable for telecommunications
But…..lawyers at Bell labs did not apply for a
patent, thinking it not relevant for their industry,
which was the telephone industry!
Fall 2004 (C) B H Hall
Econ 124/PP 190-5/290-5
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Examples of forecasting failure
Radio
invented by Marconi to be useful when wire
communication impossible, such as ship-to-ship,
that is, narrowcasting, not broadcasting
Computers
Watson, Sr. (head of IBM) saw a need for only
one computer to solve all the world’s scientific
problems
In 1949, IBM forecast world demand at 10-15
computers
(ENIAC contained 18,000 vacuum tubes and was
100 feet long, so this is understandable)
Fall 2004 (C) B H Hall
Econ 124/PP 190-5/290-5
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Some lessons for policy
Macro-inventions (scarce ideas?; radical innovation)
Unexpected sources and consequences
May require a broad science base
Micro-inventions (well-known needs?; incremental
innovation)
More predictable
Often a result of natural evolution of a technology
Easier to pay for
Distinction does not necessarily correspond to the
increment in economic welfare (e.g. malaria vaccine)
Fall 2004 (C) B H Hall
Econ 124/PP 190-5/290-5
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