economics 124/pp 190-5/290-5 innovation and technical change

Economics 124/PP 190-5/290-5 Innovation and Technical Change

Diffusion of innovationsProf. Bronwyn H. Hall

Fall 2004 (C) B H Hall Econ 124/PP 190-5/290-5 2

Outline – Diffusion (Oct. 26,28)

Introduction Economic determinants of diffusion Overview of some models Factors affecting the pace of diffusion Example: the dynamo and the

computer


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


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).


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.


U.S. diffusion of major inventions

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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


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)


Economic determinants

The adoption decision will depend on the factors that usually affect investment decisions: Benefits Costs Risk and uncertainty/information Environment and institutions – market

and/or regulatory


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


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


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


Environment – market structureSize and/or market power of adopters: Accelerates diffusion

Scale economies Delays diffusion

Slower and less flexibleSize 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)


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?


Some empirical examplesDate Authors Technology Observations Factors1957 Griliches hybrid corn Midwest farms profitability; need to specialize product1968 Mansfield diesel locomotives US railways liquidity (financial factors)1975 David mechanical reaper US,UK farms minimum efficient scale1984 Hannan/MacDowell ATMs US banks regulation; concentration;firmsize;holding co. (risk);cost of 1995 Saloner/Shepard ATMs US banks network size;customer deposits (size)

1995 Helper CNC machine toolsUS auto component firms

prod worker wage;tech complexity;size;stable customer relationshp

1997 Kennickell/kwast electronic banking US consumers education; assets; learning (older services versus newer)

1998Majumdar/Vankataraman elec switching tech US telecomms network effect and scale (weaker over time)

1998 Gray/Shadbegian new tech in paper US paper plants environmental regulation

1998 Hubbard on-board IT US truckingon-time benefits;stable customer relationship - helps monitoring

2000 Stoneman/Toivanen robot technologyfirms cross-country real options; volatility in uncertain investments?

2001 Caselli/Coleman computers OECD countrieseducation level of workers;openness;overall investment rate

2001 Gruber and Verboven mobile telephonesEuropean consumers concentration of providers;tech improvements


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


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.


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


Hours Per Day OnlineEconomics 124 Students

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Hours Per Day Web for ClassEconomics 124 Students

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Rating UC Berkeley Online ServiceEconomics 124 Students

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Willingness-to-pay for Online AccessEconomics 124 Students

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Nothing <$5 per month $5-9.99 per mo $10+ per mo.

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economics 124/pp 190-5/290-5 innovation and technical change

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