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History-Friendly Models of Industrial Evolution


History-Friendly Models of Industrial Evolution Luigi Orsenigo University of Brescia KITeS CESPRI, Universit Bocconi L. Orsenigo, Pecs. July 2010 – PowerPoint PPT presentation

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Title: History-Friendly Models of Industrial Evolution

History-Friendly Models of Industrial Evolution
  • Luigi Orsenigo
  • University of Brescia
  • KITeS CESPRI, Università Bocconi

The Principles (from S. Winter)
  • 1.      Realism!
  • It may not be a necessity for good theory, but it
    is often a virtue at least at the prevailing
    margin. There is no need to take off one head and
    put on another one when you step reading the
    business page and start doing economics
  • 2.      Dynamics first!
  • To impose on dynamic theory the burden of
    supporting a pre-existing static equilibrium
    analysis, is essentially to put on blinders,
    making it inevitable that obviously significant
    issues will be overlooked
  • 3.      No free calculation!
  • It is an abiding scandal that the
    self-proclaimed science of scarcity routinely
    treats all forms of deliberation and information
    processing as free. This scandal reaches
    Monica-gate proportions in rational expectations
    and other sophisticated equilibrium concepts that
    implicitly endow each actor with the ability
    solve every actors problem many times over.
  • 4.      Firms are profit seeking!
  • It is a true fact of nature that firms are
    typically profit seeking, but it is not a true
    fact of nature that they are typically profit
    maximizing. Profit maximization is a theorists
    crutch and ought to be abandoned when it is too
    stark to capture the reality of profit seeking or
    too cumbersome to permit analysis of any but the
    most extremely stylized models

  • .5.      Innovation is always an option!
  • One thing a profit-seeking firm can do rather
    than optimize over a given set of possibilities
    is to think of some new possibilities. Hence,
    every analysis of such optimizing behavior
    deserves an asterisk leading to a footnote that
    says unless, of course, there is a better idea.
  • 6.      Firms are historical entities!
  • They typically display pronounced inertial or
    quasi-genetic traits (e.g. scale/ routines) that
    are clearly persistent enough to shape their
    actions over interesting prediction periods.
    They ought to be represented that way in theory,
    positioned in model history the way real firms
    are positioned in real history.
  • 7.      Firms are repositories of productive
  • In most contemporary societies they are in fact
    the key repositories of technological and
    organizational knowledge and among the key agents
    of historical change. The storage and advance of
    knowledge, the maintenance and improvement of
    organizational capabilities, are complementary

  • 8.      Progress is co-evolutionary!
  • Technological and organizational innovation is
    generated by a variety of firm-level search
    processes. But firms do not search independently,
    they look to rivals, suppliers and customers for
    ideas, technologies and practices. And these
    firm and industry processes go forward in the
    context of a variety of public and private
    institutions and programs, which in turn are
    shaped by the firms. I could tell you that itís
    really simpler than that, but That Would be
  • 9.      Anything can happen for a while!
  • As Schumpeter said, only when things have had
    time to hammer logic into men is it safe to
    assume that some level of rationality will
    characterize economic outcomes. Market discipline
    and economic natural selection constrain outcomes
    over time, but in the short run anything can
  • 10. Feedback, not foresight, drives economic

The Evolutionary Approach
  • Analysis of changing systems
  • Change is partly exogenous, but partly
  • Change is partly stochastic and partly
  • Agents are different, do not understand perfectly
    the world and cannot look too far ahead
  • Selection
  • Learning
  • Institutions
  • Methodological commitments
  • start from stylized facts
  • empirically-based assumptions
  • appreciative theorizing
  • models

Evolutionary Models of Industrial Change
  • Build a formal argument to reproduce and
    explain specific stylized facts
  • The argument is derived from appreciative
  • Dynamic stochastic systems when analytic
    treatment is impossible, simulate the model
  • Derive simplified, compact versions of the model
    and solve it analytically

  • Heuristic technique, widely used in other
  • Inductive approach
  • Theory-driven and disciplined
  • Problems of validation robustness, sensitivity
    analysis, ability to reproduce facts, calibration

A. Evolutionary models à la Nelson-Winter 1982
  • Micro learning processes
  • selection with heterogeneous population of firms
    destrategising conjectures
  • processes of experimentation and imperfect trial
    and error (Nelson and Winter, 1982 Silverberg,
    Dosi and Orsenigo, 1989, Dosi, Kaniovski and
    Winter, 1999
  • Recognition of some stylized facts and
    development of an evolutionary model able to
    reproduce those phenomena (i.e. the relationship
    between innovation and concentration)
  • Very abstract models Focus on some generic basic
    properties of industrial structure and dynamics

B. Industry life cycle models
  • Focus on the relationship between product and
    process innovation, entry and firm growth, exit,
    industrial concentration
  • Basic model of industry life cycle derived from
    the evidence of the auto industry (Klepper, 1996)
  • Different industry life cycles and divergence
    from the standard model due to factors such as
    the characteristics of demand, technological
    discontinuities, the type of competition and
    innovation, as from the several models by Klepper
    and associates

  • From the empirical cases and the historical
    analyses of semiconductors, computers,
    pharmaceuticals, aircraft, chemicals it is
    evident that
  • the evolution of industries presents a wide
    variety of patterns
  • a richer set of factors and variables than those
    examined by evolutionary and industry life cycle
    models can be identified various types of
    capabilities, innovative users, vertical and
    horizontal boundaries of firms, actors such as
    universities or government, specific
    institutions, and so on.
  • In sum, except for some versions of the standard
    industry life cycle model, there are no models
    which focus on the evolution of industries and on
    the factors that have been identified and
    examined by historical analyses and case studies

History Friendly Models
    industrial leadership)

  • HFMs play a bridging role between general and
    abstract theories and detailed case studies
  • To the theorists, HFMs suggest that abstract and
    general modeling should take into account some
    degree of realism and contain empirical
    foundations in their models
  • To the historian/empirical scholars, HFMs suggest
    some degree of formal discipline and modeling of
    the empirical analyses and historical works, so
    that rigorous and consistent explanations of
    industry evolution could be developed

Empirical validation
  • It is not the purpose of history-friendly
    modeling to produce simulations that closely
    match the quantitative values observed in the
    histories under investigation.
  • The goal is to match overall patterns in
    qualitative features, in particular the trend
    behaviour of the key descriptors of industry
    structure and performance of a sector
  • In a sense, HFMs represent also an abstraction
    from the specific motivating historical episode
  • The goal is to feature some particular causal
    mechanisms that have been proposed by the
    appreciative theories for the empirical phenomena
    under examination
  • So, HFMs do not attempt detailed quantitative
    matching to historical data, nor detailed
    calibration of the parameters

Empirical validation (ctd)
  • There is some common sense guidance and some
    basic learning from the case studies in the
    choice of the plausible orders of magnitude of
    the parameters
  • Moreover some of the dimensions known as relevant
    are not easily measurable, for example some rules
    and behaviors
  • Some value choices for parameters involve
    implicit unit choices for variables, which means
    that the quantitative variables are at the end
    somewhat arbitrary. However the relations among
    parameters have to be made with a view to
  • So the methodology is different from the one by
    Werker and Brenner (2004) in which models are
    constructed using detailed empirical data on
    assumptions and on implications

  • The computer industry (1950-1985) (Malerba,
    Nelson, Orsenigo and Winter, 1999)
  • The pharmaceutical industry (from the early
    period to molecular biology)(Malerba and
    Orsenigo, 2002)
  • The synthetic dye industry (late XIX-early XX
    century) (Brenner and Murmann, 2003)
  • The DRAM industry (early 1970s- late 1980s) (Kim
    and Lee, 2003)
  • The recent evolution of the semiconductor
    industry (1985-2010)(Yoon and Malerba, 2009)
  • The coevolution of the semiconductor and computer
    industries (1950s-1985). (Malerba,Nelson,Orsenigo
    and Winter,2008)

  • Technological bifurcation between US and Britain
    in the XIX century (Fontana,Guerzoni and
  • The dynamics of environmental technologies (Oltra
    and Saint Jean, 2003)
  • The dynamics of Korean and Taiwanese national
    innovation systems and their international
    specialization (Yoon, 2009)

  • Demand and industry evolution(Malerba,Nelson,Orsen
    igo and Winter, JEE 2007)
  • Public policy, innovation and industry evolution
    (Malerba, Nelson, Orsenigo and Winter, IJIO 2001
    and JEBO,2008)
  • Entry and the dynamics of concentration
    (Garavaglia, Malerba and Orsenigo, 2006)
  • IPR (Garavaglia, Malerba, Orsenigo and Pezzoni

The Evolution of the Computer Industry
  • Four eras
  • early experimentation and mainframes
  • introduction of integrated circuits and
    subsequent development of minicomputers.
  • personal computer, made possible by the invention
    of the microprocessor.
  • networked PCs and the Internet.
  • Discontinuities concerning both components
    technology (transistors, integrated circuits, and
    microprocessors) and the opening of new markets
    (minicomputers, PCs).
  • One firm - IBM - emerges as a leader in the first
    era and keeps its leadership also in the
    successive ones, surviving every potential
    "competence-destroying" technological
  • In each era, however, new firms have been the
    vehicles through which new technologies opened up
    new market segments.
  • The old established leaders have been able to
    adopt the new technologies and - not always and
    often facing some difficulties - to enter in the
    new market segments, where they gained
    significant market shares but did not acquired
    the dominant position they previously had.

  • What determines the emergence of a dominant
    leader in the mainframe segment?
  • What are the conditions that explain the
    persistence of one firm's leadership in mainframe
    computer, despite a series of big technological
  • What allowed IBM to enter profitably into new
    markets (PCs) but not to achieve dominance?

The era of transistors, entry and the mainframe
  • At the beginning, the only available technology
    for computer designs is transistors.
  • N firms engage in efforts to design a computer,
    using funds provided by "venture capitalists" to
    finance their RD expenditures.
  • Some firms succeed in achieving a computer that
    meets a positive demand and begin to sell. This
    way they first break into the mainframe market.
    Some other firms exhaust their capital endowment
    and fail.
  • Firms with positive sales uses their profits to
    pay back their initial debt, to invest in RD and
    in marketing.
  • With RD activity firms acquire technological
    competencies and become able to design better
    computers. Different firms gain different market
    shares, according to their profits and their
    decision rules concerning pricing, RD and
    advertising expenditure.
  • Over time firms come closer to the technological
    frontier defined by transistor technology, and
    technical advance becomes slower.

The introduction of microprocessors
  • After a period t', microprocessors become
    exogenously available. This shifts the
    technological frontier, so that it is possible to
    achieve better computer designs.
  • A new group of firms tries to design new
    computers exploiting the new technology, in the
    same way it happened for transistors.
  • Some of these firms fail. Some enter the
    mainframe market and compete with the incumbents.
  • Some others open up the PC market.
  • Incumbents may choose to adopt the new technology
    to achieve more powerful mainframe computers.
  • Diversification in the PC market

Computers in the space of characteristics
Customers and Markets
  • Computers are offered to two quite separate
    groups of potential customers.
  • "large firms", greatly values performance and
    wants to buy mainframes.
  • "individuals", or "small users", has less need
    for high performance but values cheapness. It
    provides a potential market for personal
  • Each of the two user groups requires a minimum
    level" of performance and cheapness before they
    are enticed to buy any computer at all. Then, the
    value that customers place on a computer design
    is an increasing function of its performance and
    its cheapness.

  • The probability, Pi, that a particular submarket
    will buy a computer i is
  • c0 is specified so that the sum of the
    probabilities adds to one.
  • Mi denotes the "value" of computer i.
  • "mi" is the market share of the firm who produces
    computer i
  • the market share variable can be interpreted
    either in terms of a "bandwagon" effect, or a
    (probabilistical) lock-in of consumers who
    previously had bought products of a particular
  • The constant parameter d1 assures that even
    computers that have just broken into the market,
    and have no previous sales, can attract some
  • "A" is the advertising expenditure of a firm.
  • The constant parameter d2 performs here a similar
    role to d1 for firms who have just broken into
    the market and have not yet invested in
  • If consumers in a particular submarket decide to
    buy computer i, then M is the number of machines
    they buy.

  • In every period the "merit " of the computer each
    firm is able to achieve along its technological
    trajectory --performance and cheapness improves
    according to
  • R, is the firm's RD expenditure, where i1 is
    performance and i2 is cheapness.
  • T represents the number of periods that a firm
    has been working with a particular technology.
  • Li-Xi, measures the distance of the achieved
    design from the technological frontier. The
    closer one gets to the frontier, the more
    technological progress slows down, for every
    given level of RD expenditure. There is also a
    random element to what firm achieves, given by e.

Profits, prices, RD
  • Profits ?t Mp Mk,
  • Price pt k (1?t)
  • Mark-up ?t 0.9?t-1 0.1(mi/( ?- mi ),
  • Where ? is demand elasticity
  • RD expenditures Rt, ? ?t (1- ?)
  • Advertising

The dynamics of concentration
Counterfactuals 2
Policy experiments
Theoretical experiments failed adoption
Experimental Users
  • Innovation as a quasi random process
  • Innovation and imitation
  • Market fragmentation
  • Low concentration, despite high RD and marketing

  • Random search, patent
  • Development
  • Product launch and marketing
  • Imitation

An (evolutionary) model of the pharmaceutical
  • We use a history-friendly model of the evolution
    of the bio-pharmaceutical industry
  • Might be used to explore the logic and the
    effects of alternative policies
  • The technological and market environment in which
    pharmaceutical firms are active is composed by
    several therapeutic areas or fields (TA).
  • Each therapeutic areas (TA) has a different
    economic size (nr of patients)
  • Within each TA there are a certain number of
    molecules M, which firms aim to discover and
    which are at the base of pharmaceutical products
    that later on are introduced in the market.
  • Each molecule M has a certain quality Q. Q is
    expressed in terms of height of a certain
    molecule and it is set randomly. In most of the
    cases, it is equal to zero in few cases, it has
    a positive value drawn from a normal

1.b TA markets
  • In each TA (each characterized by a fixed number
    of patients, i.e. the value of this market) firms
    may sell products.
  • The patients in each TA are grouped in a fixed
    number of submarkets), where products can be sold
    if they reach an exogenous minimum level of
    quality (this means that low-quality products
    catch few patients, even if they are the only
    available drug).

The firms
  • Firms are born with a given budget
  • Firms are characterized by three activities
    -search, development and marketing- but with
    different propensities in these activities.
  • In each period, firms can be innovators or

The landscape
  • Figure 1 Therapeutic areas and molecules
  • Firms do not know the height Q of a molecule
    they only know whether Q is greater than zero or
    not a lottery model
  • Firms engage in a search process in a specific
    therapeutic area and may (or may not) discover
    a molecule. Discovery means that the firm knows
    whether that search has found a potentially
    interesting molecule (Q gt 0). If Q gt 0, the
    firm patents the molecule and start a research
    process. If successful, they invest in marketing
    and sell it

  • Firms randomly screen the molecules, spending a
    given amount of money (a fixed share of their
    initial budget is used for the search activity,
  • The firm draws from the environment n molecules
    and adds them to the array of (potential)
  • n is given by

NB Imitative firm doesnt draw and doesnt pay
the cost of draw
  • A patent has a specific duration and width
    (extension). Once patent duration expires, the
    molecule becomes free for all the firms. A patent
    gives the firm also the right to extend the
    protection on the molecules situated in the
    neighbourhood of the molecule that has been
    patented. Competing firms are blocked in the
    developments of potential molecules near the
    patented one.

  • Firms may also imitate already discovered
    molecules when patent has expired
  • Search and development if a drug is less
    esxpensive for imitators

  • Choice of TA (and Molecule) in each period
  • Firms own a portfolio of potential projects.
  • In each period, according to budget
    availability, firms start some new parallel
  • Projects are selected according to the value
    of their TA i.e. firms will select more likely a
    project whose TA is high valued (congestion
  • BUT if the patent of the Molecule of the
    project is close to expiration, then firms are
    less attracted by this project and will not chose
    it very likely.

  • All projects have the same number of steps (i.e.
    Same cost of development)
  • Firms, developing a project (i) of an innovative
    or imitative product (or both), pay a fixed
    number of steps each period (In this way the
    periods needed to develop a product are fixed).
  • A firm starts a new project if it thinks it has,
    in advance, enough money to finish it.
  • Hence, it is possible to develop multiple
    projects at the same time (innovative and
    imitative too) (i.e. in this model we have firms
    developing parallel projects).

  • If the development phase is successul, the firm
    has a product
  • But its quality must be higher that a minimum
    level (FDA approval) otherwise,the drug cannot
    be launched
  • Once the product is developed and approved, the
    firm commercializes it spending money for
    advertising this amount has been saved up during
    the development period.
  • The higher the value of a TA, the higher the
    amount spent in marketing for the product in that

LEGEND S share of patients in a submarket
(sub) and total share in a TC (TC) caught by a
product n.sub number of submarkets
reached STCtotal share of firm in the
TC iproduct
  • firms products compete within each submarket.
  • Each product has its own UTILITY Uf(quality,
    price, advertising)

LEGEND PQ products quality P products
price A expenditures in advertising Usubtotal
utility in a submarket
  • Products market share is then

LEGEND S share of patients in a submarket
(sub) and total share in a TC (TC) caught by a
product n.sub number of submarkets reached
That is to say totalNumberOf Patents/Patients
  • All firms start their research activity at
    time 0.
  • When a firm successfully develops its first
    product, then it enters the market
  • All firms start as innovators.
  • After the first patent expired, then firms behave
    as innovators or imitators accordingly to their
    own firm-specific propensity.

Products with a market share lower than 5 exit
the market. i.e. Firms that own more than one
product, then, might stop producing some of them
without exiting the market. If Firms have no more
products and are not researching anymore,
obviously exit the market.
LEGEND Ef fixed level to exit F number of
firms at the beginning of the simulation r
weight factor Stottotal share of the firm in the
Firms exit rules
2) If number of draw n is 0 more than ? times
  • The model does a good job in generating
    qualitively a series of stylised facts
  • Low overall concentration
  • Concentration is higher in individual TAs, but it
    declines over time
  • Patterns of competition within individual markets
  • Dynamics of drug prices
  • As time goes by, an increasing number of TAs is
  • Skewed distributions of firms size, products
    quality, firms innovative performance
  • Firms growth is basically consistent with
    empirical evidence (deviations form Gibrats Law)
  • Relationships between profits and innovation

(No Transcript)
  • Costs and economies of scale
  • Market size and demand growth
  • Market fragmentation
  • Innovative opportunities
  • Patent protection

Understanding the determinants of specialization
and vertical integration in related industries
in uncertain and dynamic environments,
characterized by technological
discontinuities. Major factors capabilities,
technical change and market size Co-evolutionary
  • A capability-based, dynamic theory of vertical
    integration and specialization
  • Competence accumulation in specific technological
    and market domains
  • Competence destroying technological change
  • Coordination and integration capabilities
  • Capabilities take time to develop
  • Decisions to specialize and vertically integrate
    are not symmetrical
  • The distribution of capabilities among all
    industry participants are relevant
  • Market selection amplifies the effects of
    capabilities on the vertical scope of firms
  • The identity of firms affects the development of

  • VERTICAL INTEGRATION decision is led by
  • - the relative size of the computer firm compared
    to the largest SC component producer
    (capabilities, RD, innovation)
  • - the age of the SC component technology
  • SPECIALIZATION decision is led by
  • Comparison between the quality of SC components
    produced in-house and the quality of SC
    components available on the market

Market for components
  • Specifically, a specialized computer producer
    will sign a contract with a component producer
    selected by using a probability function that
    considers the technical quality of the
    components the higher the quality of the
    component , the higher the probability of signing
    a contract with a computer producer.
  • (5)
  • where LitCOMP is the propensity of component
    producer i to be selected and Pri,t is the
    probability of a supplier to be selected.
  • A component firm which signs a contract sells a
    number of components which is related to the
    proportion to which components and systems
    combine in order to build a computer (in the
    current parametrization, the proportion is one to
    one). After signing the contract the computer
    firm is tied to the component supplier for a
    certain number of periods. When this period
    expires, a new supplier might be selected, using
    the same procedure, if the firm still decides to
    buy component on the open market.

Firms behaviour and technical progress
  • Firms start with a given (randomly drawn) mod and
    they start to sell make profits and invest in
    RD spending.
  • Price is obtained by adding a mark-up, m , to
    costs which in turn are derived from the merit of
    design achieved by a computer. The price of
    components charged by component suppliers is
    determined symmetrically by adding a fixed
    mark-up to unit production costs.
  • RD expenditures are calculated as . a constant
    fraction of profits
  • Technical progress double draw scheme. In each
    period firms draw the value of their Mod from a
    normal distribution. The number of draws that any
    one firm can take is set proportional to its RD
  • In each period, the values of the Mod obtained
    through the firms draws are compared with the
    current Mod, and the higher among these values is
    kept. Thus, more draws increase the likelihood to
    get a higher Mod for both systems and components.

Public knowledge
  • The extent to which technical progress is
    possible for each firm, given their RD
    investment depends in turn on two variables the
    level of publicly available knowledge and the
    value of the Mod achieved by the firm in the
    previous period
  • Public knowledge is specific to each basic
    component technology and it grows exogenously
    over time. When a new technology is introduced,
    its corresponding level of public knowledge is
    lower than that reached by current technology,
    but then it grows faster and at a certain time it
    overtakes the public knowledge of the older
    technology. The rate of growth of public
    knowledge starts to slow down as time goes by.
    An integrated computer firm decides to adopt the
    new technology when the mean of its own
    distribution becomes inferior to the level of the
    public knowledge of the new technology.
  • The mean of the normal distribution from which
    the values of the merit of design (Mod) of system
    or component are taken, is a linear combination
    of the Mod at time t-1 of firm i and of the
    level of publicly available knowledge, PK, at
    time t
  • And
  • tgttmcK, lim and nu are parameters and tmck is the
    date of introduction of the new component

  • Integrated producers enjoy some coordination
    advantages as compared to specialized producers
    As a consequence, the productivity of their RD
    efforts on components is enhanced by a spillover
  • cCOMPm is the difference between the price of
    component in the open market and its actual cost
    for the producer it represents savings gained by
    self-production. An integrated computer firm
    allocate these resources to component RD.
  • Specialized computer producers invest all their
    RD on systems and obviously do not enjoy the
    coordination advantages.
  • Component suppliers spend all their RD on the
    development of components.

Vertical Integration
  • Probability of integration
  • Let
  • where
  • AgeOfTechK ( K TR,IC,MP) t (Starting time of
    Technology K) Qit is the sales of the computer
    producer biggestQt COMP is the sales of the
    largest component producers and w is a parameter
  • Then
  • where B is a parameter. If the probability of
    integration is bigger than a number drawn from a
    uniform distribution (0-1), integration occurs.

  • The probability of specialization for each firm
  • where maxModCOMP is the higher component Mod
    available on the market.
  • Then
  • A is a parameter and if Prob(Specialize) is
    bigger than a number randomly drawn by a uniform
    distribution, specialization will occur.
  • A specialized computer firm may also decide to
    change its supplier, if a better producer has
    emerged in the market. The procedure for changing
    supplier follows the same rule for the
    specialization process.

  • Computer firms the variable
  • Eit (1-e)lshr eshareit
  • is computed, where lshr is the inverse of the
    number of firms active in the market at the
    beginning of the simulation (i.e. the market
    share that would have been held by n equal
    firms), shareit is the market share of firm i
    at time t and 0ltelt1 is a parameter. Then, if Eit
    lt E, where E is a constant threshold, the firm
  • The rule governing the exit of the semiconductor
    producers is different and simpler. The
    probability of exiting of any one firm is an
    increasing function of the number of consecutive
    periods in which it doesnt sell to a computer

Standard simulation
  • Assumptions
  • the size of the external market is relatively
    small in the case of transistors and integrated
    circuits and significantly higher for
  • lock-in effects in demand are very important for
    mainframes and much less so for both PCs and
  • the introduction of microprocessors allows much
    higher improvements in component designs as
    compared to the older technology this
    technological discontinuity is much sharper than
    the previous one.

The Standard Simulation Results
  • A dominant firm emerges quickly in the mainframe
    industry and becomes vertically integrated.
  • In the semiconductor industry, concentration
    first rises as demand from computer producers
    exert strong selective pressures and firms leave
    the market. The decrease of the number of
    mainframe producers gradually softens competition
    and the Herfindahl index declines in the
    component market. Concentration begins to grow
    again as a vertically integrated monopolist comes
    to dominate the computer market component
    suppliers are left with no demand from the
    mainframe firms and exit continues.
  • At the time of the introduction of integrated
    circuits, new semiconductor companies enter the
    market and concentration drops sharply.
  • The dominant mainframe firm remains vertically
    integrated, because the external market is not
    large enough to sustain a significant growth of
    the new entrants and of the quality of their
    components. The absence of a demand from the
    mainframe producer induces a shakeout and
    concentration gradually increases in the
    semiconductor market

The age of microprocessors
  • Microprocessors constitute a major technological
    advance as compared to integrated circuit and a
    large external market supports a significant
    improvement in the quality of the new components.
  • the PC market opens up, generating a substantial
    new demand and fuelling further advances in the
    merit of the components.
  • The computer leader decides to specialize
  • Competition in components large external market
  • The establishment of a monopoly in the supply of
    components contributes however to maintaining
    competition in the PC market, since all firms get
    their microprocessors from the same source.
  • In the last periods of the simulation, as the
    microprocessors technology matures, the
    incentives towards specialization become slightly
    less compelling and, in some simulations, the
    mainframe firm and some PC producers decide to
    vertically integrate

History Friendly Simulation
  • Does lack of external markets lead to more
    vertical integration?
  • Do no demand lock-ins in mainframes lead to more
    specialization ?
  • Do no demand lock-ins in semiconductors lead to
    more vertical integration ?
  • Does a minor technological discontinuity in
    microprocessors lead to more vertical integration?

No external market for SC
Policy exercises
  • Antitrust
  • Public procurement
  • Investment in basic research
  • Unintended consequences
  • - The creation of open standards in computers
    may lead to the emergence of concentration in
  • - Antitrust policy in computers may lead to the
    emergence of a monopolist in the PC market and
    the disappearance of a the merchant component
  • -Open standards in systems may lead to the
    emergence of a merchant component industry

User- Producer relations
  • Dynamic matching
  • Specific and generic bonus
  • Contract length
  • Exclusive contracts
  • Lead users
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