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
Fall 2004 (C) B H Hall
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
Fall 2004 (C) B H Hall
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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