Economics 124/PP 190-5/290-5
Innovation and Technical
Change
Diffusion of innovations
Prof. Bronwyn H. Hall
Outline – Diffusion (Oct. 26,28)
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Introduction
Economic determinants of diffusion
Overview of some models
Factors affecting the pace of diffusion
Example: the dynamo and the
computer
Fall 2004 (C) B H Hall
Econ 124/PP 190-5/290-5
2
Diffusion
 Dictionary definition: The spread of linguistic
or cultural practices or innovations within a
community or from one community to
another
 Course definition: The spread of an
innovation throughout the economy or the
relevant set of potential users – examples:
 Almost all consumers – TV, indoor plumbing
 ATM machines – banks and retail stores
 Sometimes referred to as “adoption”
 When looked at from the point of view of individual
choice by consumers or firms
Fall 2004 (C) B H Hall
Econ 124/PP 190-5/290-5
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The historical view
“in the history of diffusion of many
innovations, one cannot help
being struck by two characteristics
of the diffusion process: its
apparent overall slowness on the
one hand, and the wide variations
in the rates of acceptance of
different inventions, on the other.”
(Rosenberg, 1976, p. 191).
Fall 2004 (C) B H Hall
Econ 124/PP 190-5/290-5
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The s-curve for diffusion
 Shows how the number of users of a new technology
grows over time (usually measured as a share of
potential users).
 Begins trending upward very slowly
 At some point becomes much steeper (as the
technology spreads rapidly)
 Eventually flattens out because there are fewer and
fewer potential users that have not already adopted
 Graph shows the diffusion of some major consumer
inventions in the United States during the past 100
years.
Fall 2004 (C) B H Hall
Econ 124/PP 190-5/290-5
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U.S. diffusion of major inventions
100
90
80
Telephone
Share (%)
70
Refrigerator
60
Washing machine
50
40
VCR
30
20
10
0
1900
Electric Service
1910
1920
Fall 2004 (C) B H Hall
1930
1940
1950
Year
1960
Econ 124/PP 190-5/290-5
1970
1980
1990
2000
6
Bottom-up view
 Adoption from the point of view of
adopter:
 Investment under uncertainty
 Once done, costs are sunk
 Like an option
 Adoption from the point of view of the
innovator or supplier:
 Marketing goal – reaching a new customer
 Focus on network effects, either
technological or social
Fall 2004 (C) B H Hall
Econ 124/PP 190-5/290-5
7
Top-down view
 Channel from innovation to economic growth
mediated by diffusion, which can be
surprisingly slow
 need to understand process to understand why
 Some examples
 Diffusion of electricity required complete factory
redesign; infrastructure
 Diffusion of computing technology and internet
 Productivity growth sometimes surges 20-30
years after initial introduction of new general
purpose technology (GPT)
Fall 2004 (C) B H Hall
Econ 124/PP 190-5/290-5
8
Economic determinants
The adoption decision will depend on
the factors that usually affect
investment decisions:
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Benefits
Costs
Risk and uncertainty/information
Environment and institutions – market
and/or regulatory
Fall 2004 (C) B H Hall
Econ 124/PP 190-5/290-5
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Benefits depend on
 Closeness of substitute technologies
 Radio versus automatic clotheswasher
 Mobile and landline telephones
 Networks and standards (more later)
 ATM adoption by banks
 VHS/Beta
 Wireless computing and 802.11b
 Experience and Learning
 Investment in adopter skills
Fall 2004 (C) B H Hall
Econ 124/PP 190-5/290-5
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Costs depend on
 Price of new technology
 Complementary investments
 Infrastructure and other capital equipment
 Training/skills
 Scale
 Due to fixed cost nature of adoption in many
cases
 Mechanical reaper in 19C (David on UK)
 Cost of finance
 Large body of literature on innovation
investment where there is uncertainty
Fall 2004 (C) B H Hall
Econ 124/PP 190-5/290-5
11
Uncertainty/information
 New technology – less understood, more
uncertainty about how well it works
 Uncertainty about whether it will be
successful (standards)
 Benefits are a flow, costs are upfront =>
benefits may be more uncertain
 The option to delay decision in order to
acquire more information may cause delay
in adoption
 Luque (2002) – new manufacturing technology
adopted more quickly in industries with lower
sunk costs, lower uncertainty
Fall 2004 (C) B H Hall
Econ 124/PP 190-5/290-5
12
Environment – market structure
Size and/or market power of adopters:
 Accelerates diffusion
 Scale economies
 Delays diffusion
 Slower and less flexible
Size and/or market power of suppliers:
 Accelerates diffusion
 Sponsoring a standard (e.g., IBM and the personal
computer) – mobile telephone evidence
 Delays diffusion
 Higher prices
 Less fear of market share loss to entry (see ATT in
1960s)
Fall 2004 (C) B H Hall
Econ 124/PP 190-5/290-5
13
Environment - regulatory
 Accelerates adoption
 mandates pollution or safety standards
 solves coordination problems in network
industries
 Delays adoption
 Safety regulation, e.g., new pharmaceuticals
and medical instruments, PVC pipe
 Standard-setting process - telecommunications
(ATT again)
 New California law and lighting innovation?
Fall 2004 (C) B H Hall
Econ 124/PP 190-5/290-5
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Some empirical examples
Date Authors
Technology
1957
1968
1975
1984
1995
hybrid corn
diesel locomotives
mechanical reaper
ATMs
ATMs
Griliches
Mansfield
David
Hannan/MacDowell
Saloner/Shepard
1995 Helper
Observations Factors
Midwest farms
US railways
US,UK farms
US banks
US banks
US auto
CNC machine tools component firms
1997 Kennickell/kwast
electronic banking US consumers
Majumdar/Vankatara
1998 man
elec switching tech US telecomms
1998 Gray/Shadbegian
new tech in paper US paper plants
1998 Hubbard
on-board IT
2000 Stoneman/Toivanen
robot technology
2001 Caselli/Coleman
computers
2001 Gruber and Verboven mobile telephones
Fall 2004 (C) B H Hall
US trucking
firms crosscountry
profitability; need to specialize product
liquidity (financial factors)
minimum efficient scale
regulation; concentration;firmsize;holding co. (risk);cost of
network size;customer deposits (size)
prod worker wage;tech complexity;size;stable customer
relationshp
education; assets; learning (older services versus newer)
network effect and scale (weaker over time)
environmental regulation
on-time benefits;stable customer relationship - helps
monitoring
real options; volatility in uncertain investments?
education level of workers;openness;overall investment
OECD countries rate
European
consumers
concentration of providers;tech improvements
Econ 124/PP 190-5/290-5
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Models – the s-curve
 Heterogeneous adopters
 Benefits have a unimodal distribution
 Costs decline monotonically
 Adopt when benefit>cost
 Epidemics (spread of information)
 Small share adopt
 They encounter the remainder randomly; those
contacted adopt
 Implies 3-parameter logistic
Both models => s-shaped curve for diffusion
Fall 2004 (C) B H Hall
Econ 124/PP 190-5/290-5
16
Models - sunk costs
 Adoption is investment under uncertainty
 Compare an upfront cost with a stream of future
benefits
 =>adoption an absorbing state in the sense that
once costs incurred, they are sunk
 Decision is
 Not “adopt or do not adopt”
 But instead “adopt now or wait to decide later”
 Real options models (Stoneman 2001)
 Uncertain payoff is modelled as a stochastic process
 If it reaches a high enough value (strike price), the
option to invest is exercised.
Fall 2004 (C) B H Hall
Econ 124/PP 190-5/290-5
17
Internet diffusion in Econ 124
 Computer ownership:
 1997, 80% of class
 2003, 100% of class
 Internet use 1997 to 2003
 Total use increased
 Recreational use relatively more important in
2003
 More classwork done at home
 Web surfing increased more than email
 University service improved a lot
 => WTP (Willingness To Pay) decreased
Fall 2004 (C) B H Hall
Econ 124/PP 190-5/290-5
18
Hours Per Day Online
Economics 124 Students
25
20
Number
15
10
5
0
0
<1 hour
1 to 2 hours
2-3 hours
>3 hours
Rating
1997
Fall 2004 (C) B H Hall
2003
Econ 124/PP 190-5/290-5
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Hours Per Day Email for Class
Economics 124 Students
45
40
35
Number
30
25
20
15
10
5
0
0
<1 hour
1 to 2 hours
2-3 hours
>3 hours
Rating
1997
Fall 2004 (C) B H Hall
2003
Econ 124/PP 190-5/290-5
20
Hours Per Day Web for Class
Economics 124 Students
35
30
Number
25
20
15
10
5
0
0
<1 hour
1 to 2 hours
2-3 hours
>3 hours
Rating
1997
Fall 2004 (C) B H Hall
2003
Econ 124/PP 190-5/290-5
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Rating UC Berkeley Online Service
Economics 124 Students
30
25
Number
20
15
10
5
0
NA
Very poor
Poor
Fair
Good
Excellent
Rating
1997
Fall 2004 (C) B H Hall
2003
Econ 124/PP 190-5/290-5
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Willingness-to-pay for Online Access
Economics 124 Students
40
35
30
Number
25
20
15
10
5
0
Nothing
<$5 per month
$5-9.99 per mo
$10+ per mo.
Rating
1997
Fall 2004 (C) B H Hall
2003
Econ 124/PP 190-5/290-5
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