fJJ.l.T.
LIBRARIES
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DEWEY
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IT
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The International Center for Research on the
Management of Technology
The Death Knells
of Mature Technologies
Carl W.I. Pistorius*
James M. Utterback
WP # 135-95
February 1995
Sloan
WP
# 3859-95
Technological Innovation
University of Pretoria
''Institute for
Will appear in Technological Forecasting and Social
Change
©
1995 Massachusetts Institute of Technology
Sloan School of Management
Massachusetts Institute of Technology
38 Memorial Drive, E56-390
Cambridge,
02139
MA
MASSACHUSETTS INSTITUTE
OF TECHNOLOGY
:T
271995
LIBRARIES
ABSTRACT
The
behavior
oscillatory'
in
the mature phase of
some
technologies' diffusion-related S-curves
are investigated, specifically with regard to the influences that other technologies can have on
the oscillations
The notion of mortality
mature technology
signal that the
structural panels in the
wood
is
indicators
is
raised,
products industry
is
in a
it
is
mature technology's S-curve.
plywood
is
made
Two
interaction
in
mature
It
concluded that
is
for the oscillations in
possible alternative explanations for the
a previously proposed chaos-formulation and a
mathematical model based on modified Lotka-Volterra equations
behavior
a
argued that an emerging technology can also contribute to
oscillatory behavior are also discussed, viz
oscillatory
is
considered as an example, and an updated
macroeconomic business cycles are primarily responsible
plywood's S-curve, although
perturbations
whether such behavior
under attack from an emerging technology The case of
forecast of the substitution of oriented strand board for
factors such as
i.e.
technologies'
S-curves
can
This model shows that
also
from
result
symbiotic
between two technologies under certain circumstances
Introduction
Oscillatory behavior
phenomenon
this
type ot
whether the
in
that has
the mature phase of the diffusion-related S-curves of technologies
been recognized and discussed
oscillatory behavior
is
oscillations signal the
in
the literature.
of more than passing academic
One of
interest,
demise of the mature technologies, ie
indicators of mature technolomes can be useful not
onlv
in
is
a
why
the question
whether thev are
mortality indicators foi mature technologies, as has been proposed previously
Mortality
the reasons
is
the
in
the literature
search tor new
technologies, but also
technologies
In
in
the
paper
this
mortalitv indicators, or
in
development and execution
we
the subject,
the
In
it
the general case, whether they are in
(OSB)/waferboard.
is
it
Although
that
oscillations in
is
this
shown
being
second case,
in
a
in
indeed
triggered b\
\\a\
paper does not attempt to speak the
the
final
in
"attacked"
by
behavior
plywood's S-curye correlates
rather than the
effect
in
oriented
strand
above However,
the S-curve that can be ascribed to the
conceptual model
developed
is
the mature phase of an S-curve
emergence of
board
US, and
OSB
is
it
causes the
to the conclusion that oscillatory behavior per se
the sense described
interaction of one technology with another
behavior
some
the residential fixed investment pattern in the
in
plywood's S-curve This leads
some perturbations
this
that the oscillatory
macroeconomic
not a mortality indicator
In the
plywood
of
very well with the fluctuations
concluded
strategies for mature
adds to the debate by considering two cases
that
case,
first
end-game
address the question whether the oscillations are
interaction with another technology
word on
oi'
it
is
possible to identify
emergence of a new technology
to illustrate the
more general case of
Other authors have argued
may be
a chaotic effect
that
the oscillatory'
However, these arguments
have not taken into account the interaction of another technology with the technology
exhibiting the oscillatory behavior
that
the
In this paper, a
is
symbiotic interaction between two technologies can also give
oscillatory behavior in S-curves
This conceptual model
necessanK the only) possible cause
modified
mathematical model
Lotka-Yolterra equations,
for
and
is
rise
chaos-like
to
offered to illustrate another (but not
the oscillatory behavior
differs
formulated to show
The model
from the chaos formulation
is
in
based on
that
the
interaction
among two
technologies
is
accounted
explicitly
foi
modeling
here, rather than just
one technology competing against the market
Mortality indicators of mature technologies
The
and tracking of emerging technologies have important implications for
identification
company from
a
resources
new
strategies,
ones,
it
New
a timely fashion
in
As major new technological innovations create new
strategic viewpoint
industries and destroy old
essential
is
a
company's
technology obviously can aid
in
R&D
threat
of
a
quoted by
Barbe
new technology,
conclude that
it
is
the
more
important for a
of identifying
the
flexible
company
to
concern to directors of public
competitors and the consequences of the
its
its
that the earlier a
company perceived
range of strategic responses was
to gather
possible before competitors erect barriers to entry
importance
From
have done research to examine the way
et al.
They found
2]
new
of projects, indicate which research directions
companies perceive new technologies vis-a-vis
as
and deplov
strategies
example, earlv warning of an emerging
Similar issues are of
research institutions and policy makers
[1
firms formulate
new measures of competitiveness
effort, for
the selection
pursue and which to stay clear from
companies' responses
that
technologies bring with them the requirements for
organizational structures and
viewpoint of managing
a
They
and process information as soon as
Similar arguments can be
emerging technologies
the
from
a
national
made
rather
to
than
show
the
company
viewpoint
Relying on chance successes
technologies
This
is
is
not a satisfactory
particularly relevant
way of going about
when one
the search for emerging
considers the fact that new technological
innovations very often originate from outside a particular industry which
it
impacts (see for
I
l
'-i-'i,;>-\
)<)
>
example
very
The
[3])
various
that there
is
no obvious place
is
to determine if
something
Once such
emerging technology has been
difficult
"emerging"
implication
ways
weaknesses.
an
that
actually a
is
and furthermore
new technology
which one can keep track of
A
systematic framework for gathering and processing data
its
can be employed to aid
[4-9], to
the wind
all
is
that
is
with their different strengths and
a
is
much more
Several staictured approaches that
emerging technologies have been suggested (see
the search for
in
in
progress,
it
however, there are
identified,
in
rewarding strategy than grasping for straws
example
detected
is
to look
for
mention only a few)
Rather than directing the search
the
at
new emerging technology
however,
itself,
it
may
be
advantageous to use an indirect route by focusing on the demise of mature technologies From
the accumulated
knowledge base on
the processes of technological innovation, especially the
diffusion of technology and the substitution of
rise
of an emerging technology
technology In
this regard,
is
often associated with the demise of an older,
Foster speaks of attackers and defenders [10]
S-shaped growth curves, he shows
new. emerging technology
established technology
in a
In
how
is
emerging
mature technologies can be
technologies
It
will
a
the case
where
the
new technology
hypothesis
is
is
attacking an older,
is
in
is
possible to
may
true, the identification
of mortality indicators of
powerful technique to aid
be particularly useful
it
"dying", such signals
in
indicate thai a new
the identification of emerging
generating clues suggesting where to search for
emerging technologies, since the market niche has now been
indicators which
more mature
Relying heavily on
particular market niche, one can thus argue that if
If this
that the
an older, defending technology can be attacked by a
detect signals that a mature technology'
technology
one technology with another, we know
show when an older technolouy
is
identified
under attack from an
The
abilit)
to identify
emermnu technology
company
can be equally useful from the viewpoint of the
technology, since such a
company
timely response to the attack [11]
will
In
has an interest
in
the older
have to formulate and execute an appropriate and
order to pursue
necessary' to investigate the characteristics of
this line
is
it
thus becomes
being attacked by a new. emerging
be particularly useful
will
of reasoning,
mature technologies, particularly with the aim of
finding signals that indicate that the mature technology
technology Such mortality indicators
that
if
they can be identified
in real
time
To
illustrate the
concept, consider for example
Modis and Debecker's
active service contracts in the mini-computer industry [12]
findings on patterns of
Thev examined
the service
life
cycle of computers and found that the cumulative sales of computers follow S-shaped curves,
but that the service lives of the
same computers follow
take explicit account of the mortality of products
track of the
that
number of
so-called end-of-life curves
active service contracts for certain generations of computers, noting
number of contracts increases
at
the logistic S-curve. the
declining as machines age and
the
same
rate as sales
number of
that "
increases with time, reaching a ceiling
products
///
use.
the total
at
They found
that
obsolescence because of aging per
the end of the product's
is
life
As an explanation
particular product
cycle
The number
oi'
among
a certain mortality
computer generations are replaced due
se.
sales
graph
point out that the
number of units sold of a
however, never reaches the same ceiling as there
the products sold"
Initially the
active contracts reaches a peak and then starts
become obsolete Modis and Debecker
phenomenon, they argue
sales
However, whereas cumulative
depicting active service contracts peaks before the cumulative sales Joes
for this
latter
Modis and Debecker kept
In their analysis
hardware maintenance contracts for computers closely follow systems
follow
The
to technological
and confirmed the notion that computer models are
.,
.,
,
;
phased oui as
individual
generation, as opposed to personal cars, for example, thai are phased out
a
Computer models thus phase
independently of
In the case
when
that
is
becomes
generation
outdated,
of computer models, the number of service contracts may thus prove to be
characteristics of
shall
their
as
they were sold
mature technologies
that can be investigated as potential mortality indicators,
concentrate on one particular
sometimes detected
in
a
Although there are certainly many aspects and
mortality indicator for mature technologies
we
out
phenomenon
in this
paper, viz
the oscillatory behavior
the mature phase of the diffusion-related
S-curve of some
technologies
Oscillatory behavior in S-curves
The S-curve
is
a verv well
elaborated on here
in
any
known concept
detail,
in
innovation
save to mention that
substitution as well as technological progress
cases, the diffusion
is
the
There
it
is
management and hence
has application
in
it
will not
be
explaining diffusion,
strong empirical evidence that
of a technology over time displays a smooth growth pattern
—
in
many
in fact, that
whole notion underlying the shape of the S-curve. However, the actual data points very
often exhibit erratic behavior in the sense that they deviate
from the smooth curve. Although
some of these deviations can be ascribed
error,
to
therefore must be ascribed to other influences
behavior
in
the mature phase, and
it
is
measurement
The deviations
to these oscillations that
as the rate of diffusion of a technology can be ascribed to
example), one can
growth curves
now
also ask
many of them cannot, and
often exhibit a clear oscillatory
we now
many
turn our attention
Just
factors (see [13-19]. for
what causes the oscillatory behavior
in
the mature phase of
commented on
Several authors have
among them Montrey and Utterback
enter the mature phase,
Debecker
phase of the
Modis
S-curve,
from
deviations
the
fluctuations'" [24]
—
states
At
'
growth
logistic
completion
approaches
With regard
and Modis [23. 24]
[22],
when approaching
appearing
in
saturation
contexts)"
ecological
appearance of oscillations
in
(a
may
old
Referring to the oscillations
in
recent years
is
As
quasilogistics
or
solution of Volterra
some
a
plywood's S-curve, they
production of
a
Figure
1
shows the
sales
curve of plywood gross
oscillations
in
the
s
o\~
if
the
recognized
attacking the
state "...
as
We
shown
in the
mature phase of
a
The
aluminum" [20]
technology's S-
so under which circumstances
phwood
and OSB/waferboard
smoothly (with minor
mature
a
that
waferboard and oriented strand board (OSB)
whether the oscillations
curve are mortality indicators and
become
of the vulnerability of that product to an emerging
charts of sales of several other commodities such as
arise
can
commodity, such
same pattern appears
The questions now
is
new technology
one depicted
in
random
notion
the
substitution such as the
for
into
further and lav the seed for the hypothesis
the mature phase of
a clear sign
substitution
equations often
technologies' S-curves
emergence of
in
the
breaks
pattern
These comments support
[21]
venture to hypothesize that the type of variance
plywood
substitution
observed
logistics
possible
actually indicate the
in
been
trajectorv
phenomenon Montrey and Utterback, however, go
such oscillations
process
these
the mature phase of
that
of the
extremities
the
"
Marchetti notes that
Modis and
mature
have
—
[20], Marchetti [21],
as they
to the oscillatory behavior in the
the
pattern
90%
above
oscillators'
for
some growth curves develop
fluctuations that
phase,
and
in
the
US Note
oscillations), but then
hoss
the
emergence
boss the
growth
breaks into pronounced
of
a
ness
technology
hriinn
!
'')•
coincides with the onset of oscillatory- behavior
(OSB waferboard)
mature technology (plvwood
earlier in tins section
in this
case)
the
Since external factors such as those referred to
in a
have such an important influence on the
to assert that they, or other external factors, will also
this
would weaken
rate
the
of diffusion,
emerging technology For example. Girifalco points out
in
that erratic
discussed later
arises
is
for
in
in this
If so.
behavior from the smooth
Davies has shown that the growth
is
expanding or
is
paper From a mortality indicator viewpoint, however, the question that
oscillations are
some way
the oscillations
1
chaos formulation has also been proposed by Modis and Debecker. and
whether these
technology
reasonable
emergence of an
curve exhibits oscillators- behavior due to the fact that the industry (niche)
A
it
the business, political and social environments or to
the specific differing characteristics of the adopters [25]
contracting [17]
is
cause or influence the oscillations'
the argument that the oscillations are triggered by the
S-curve can be attributed to changes
S-curve
oi'
in
or another
Obviously
if
brought about by the emergence of
If so.
is
this a necessary, sufficient
one can show
that
a challenging
new
and unique condition
the oscillations are triggered
emergence of a new technology {and only by the emergence of a new technology),
extremely powerful and useful indicator with profound implications on the
it
by the
will
be an
ability to identify
and track emerging technologies as well as end-game strategies for mature technologies
Alternatively, the
weaker case where an emerging technologv
responsible for) the oscillatory behavior
in
a
also influences (but
mature technology's S-curve
is
is
not solely
also
useful,
although less so and more complicated to apply operationally
Diffusion of
plywood and OSB/waferboard
Montrey and L'tterback investigated the diffusion of plvwood and
frame construction industry [20.26]
This case
is
OSB
waferboard
in
the light
discussed here as an illustrative example for
.,-;,;;,
,
I-
several reasons, viz
curve,
just
it
is
a
good example of
illustrates the interaction
it
mature technology's S-
oscillatory behavior in a
between two technologies within
one technology competing against the market) and
it
this
context (as opposed to
some discussion
has drawn
the
in
literature
After World
panel
in
II,
and particularly since the 1950s, plywood became the dominant staictural
the industry', having gradually displaced
floor, wall
the
War
lumber as the preferred sheathing material
and roof construction However, since the
appearance of new unveneered
panels
late
(notably
1960s several developments led
waferboard
and
OSB)
that
for
to
started
challenging plywood's dominance [20], viz
Technology related developments There were process advancements for the manufacture
of chip or flake based panels
Raw
material developments The prices of plywood were increasing
depletion of suitable timber supplies for the manufacture of
suitable
new timber
supplies for unveneered panels
Lately there has also been
fast,
due
part to the
plywood On the other hand,
were being exploited
some environmental pressures
in
at
that tend to limit the
lower costs
raw material
supply of plywood
Market developments The remaining raw material supplv
in
for
plvwood had been declining
quality
Political developments
There had been some changes
in
building codes that
made
the
unveneered panels more acceptable
The new
unveneered
Waferboard was
first
structural
produced
in
panels
Canada
were mainly waferboard,
in
COM-PLY
1966 and then spread to the
and
OSB
US COM-PLY was
first
marketed
in
1976. but had not proven to be a very successful product and has almost
disappeared as a serious competitor
been very successful
plvwood
three
All
It
OSB
has been commercially produced since 19S1 and has
has proven to be superior to waferboard and
of the
plywood
substitutes
commodities Montrev and Utterback concluded
at
a severe cost
that
marketed
are
in
some
as
respects also to
structural
sheathing
plywood was. and would continue
that
to be.
disadvantage with regard to the newer panels, and that there was no doubt
plywood was under attack from the newer panels
[20].
OSCILLATORY BEHAVIOR OF THE S-CURVE
Consider
US
now
again Figure
combined
(as well as
1
which shows the
sales) in billions
of plywood and OSBwaferboard
sales
of square
feet,
calculated on a 3/8" basis
in
The data
From
on plywood was obtained from Montrey and Utterback for the period 1940-1975 [20]
1976 onwards both the plywood and
OSB
as in
have been grouped together as
Montrey and Utterback's
unveneered panels
plywood
sales
in
a
OSB
data were obtained from [27]
original
follows
an
Waferboard and
category of unveneered panels competing with plywood
The sharp upturn
paper [20]
in
the earlv 1980s corresponds with the introduction of
generally
the
S-curve
and
has
a
approximately 1970 when the sales curve starts oscillating
relatively
The
fact
the curve for the
OSB
Note how
uneventful
that
life
the
until
these oscillations
correspond with the emergence of the unveneered panels prompts the question whether the
oscillations in
i
e
plywood's S-curve are causally related
whether the fluctuations indicate the presence of
the resulting fluctuations
oscillations
in
in
demand
If so,
it
to the
a
emergence of unveneered
panels,
superior substitute and are triggered by
would lend
credibility
to the hypothesis that
the mature phase of a technologv's diffusion curve indicate that
it
is
under
attack from an emerging technology, and hence that oscillations can be interpreted as mortality
indicators
Montrey and Utterback ascribe the
the
comment
wood
nature of the overall
erratic
'
oscillations in
the steep drop
"
that
in
plywood's curve throughout the 1970s
products economy during that decade"
we now compare
statement,
this
plywood's S-curve. The assumption
They
the mid-1970s coincides with the nation's recession
during that period, during which housing construction sank to very low levels"
test
to
residential
that,
is
investment trends
fixed
In
the
in
order to
US
with
since the light frame construction industry
major contributor to the residential fixed investment and
this
industry
is
is
a
one of plywood's
main markets [28], an examination of the correlation between time series data for residential
fixed investment and
plywood
oscillations in the curve for
plywood
residential fixed investment
from
Statistical
investment
market swings
is
shown
in
we
dollars
in
are
a
comparing
are coupled to
US
Figure
1
the market share,
its
indicator to test the hypothesis that
macroeconomic business
(in
cycles
constant 1982 dollars)
The
The
Data
for
1950-1979, and
[29] for the period
[30] for the period after that'
we
residential
correlation
fixed
between the
are looking specifically at the phases rather than the amplitudes,
sales in billions
of square
the case of residential fixed investment
oscillations in
good
the curve for residential fixed investment and the oscillations in the total sales
remarkable (Note that
since
in
would be
was obtained from Gordon
Abstracts o^ the
also
is
sales
it
would be
fair
to
feet in the
)
case of plywood with billions of
Since plywood constitutes
a
major part of
conclude that sales of plywood, and particularK the
S-curve. are indeed coupled to macroeconomic business cycles, specifically
residential fixed investment
these assumptions
Does
the
One
should, however, be careful about the causality implied
plvwood
sales follow the residential fixed investment curve or
in
is
the residential fixed investment curve driven by the
may be
plvwood curve
the
that
oscillates
plywood
reasons
for
1
sales" If the latter
other
than
the
the case,
is
residential
the residential
that
is
macroeconomic conditions and
this setting
—
sold
demand
that
it
for housing
OSB
o\~
as
the
a
way around Timber products
how
OSB/waferboard curve
technology
It
will
in a
It
if
OSB
fixed investment curve in years to
in
the early eighties
that
in
the
It is
as
that the
was caused by
the
OSB becomes
an established
emergence
dips in the curves around 1990 illustrate this point
come, and
if
the coupling
plywood
between the plywood curve and
loses market share
the previous paragraph leads one to conclude that oscillations
in
OSB/waferboard
triggered by the emergence of
emergence of the new technology contributes
the mature technology's S-curve
To
in
plywood's
the residential fixed investment pattern and
cannot be interpreted to be mortality indicators per se
the
fulfill
fortunes are also linked to residential fixed
its
S-curve are primarily the result of fluctuations
therefore are not
are supplied inter alia to
continues to track the oscillatory behavior of the residential
residential fixed investment decreases as
in
in
amount of timber
which the data are given Recall
would seem, however,
more pronounced way The
be interesting to see
The arguments
determined by
is
both the plywood and OSB/waferboard curves tend to track the
technology and gains significant market share,
investment
US
not determined bv the
is
residential fixed investment in the latest years for
in
the
and hence the plywood curve follows the residential fixed investment
also interesting to note
sharp upturn
in
should be considered as a "demand" curve or driver
Surely decisions to build new housing
rather the other
investment
fixed
fixed
A more
investment and that the residential fixed investment only follows the plywood curve
plausible explanation
it
to
Hence
The question does
some secondary
investigate this question,
the oscillations
arise,
however,
if
or smaller perturbations
we now
concentrate on the
S-cun.es of plywood and OSB/wafcrboard as well as the S-curve of the combined sales Note
that there are three
"hiccups" superimposed on the general oscillatory pattern of plvwood's S-
curve (indicated with small arrows
in
Figure
tracks the S-curve of the total sales very closely
made anv market impact and
sales
At the
1)
the total sales for
At
This could be interpreted to
for a while, but then catches
the
plvwood
One
sales
up again
It is
OSB/waferboard had not
is
mean
in
how
no hiccup
that the
is
that the
for
If this
that
is
shows
the demand/capacity ratios of
to
1989 [27]
If
where the trends
as
shown
in
we now
in
Figure
from
demand capacity
the S-curve
plywood
sales lag total sales
demand
this deviation
for structured
The
panels
was
data
historical
in
1,
S2
why does plywood
after the hiccup 7
A
then recover, as
possible explanation
OSB
plywood and
in
the
US
for the period 1981
focus on the period 1983-1987, which corresponds with the period
plywood
we
S7 (with a high of
increased
in
unveneered structured panels was greater than the capacity and that the
was then taken up by plywood
1
the case,
resumes growth
resulting slack
Table
time
at that
the unveneered panels gained market share at the expense of plywood,
plywood curve
demand
much more
tempting to speculate on the cause of
hypothesis might be that the
lending support this hypothesis-
indicated by the
really
is
plywood's S-curve
being taken up by the unveneered panels rather than by plywood
Figure 2 shows
plywood
practical purposes therefore represents the
all
of plvwood. At the second hiccup, however, the dip
of OSB/waferboard
hiccup, the S-curve of
this point
severe than that of the total sales and furthermore there
in
first
ratio for
seemed
to lag the trend in residential fixed investment cycle
note that the industry demand/capacity ratio increased from
OSS
to
sales
in
re
19S6),
SS°o
0.8-4
(with
OSB
increased from
a
high
of
The demand/capacitv
87
58 to
in
1986),
90 (with
i.e
2
a high
for
ratio
4%
of
SO to
plywood
However,
93
in
the
1986).
nnm
!
i
e
)9*
55°
o
There
than for
is
thus evidence of a
plvwood
This
demand and hence
capacity
was
mav indeed
unfulfilled orders
steeper increase
indicate that
OSB
might have been
in
the
demand/supply
caused short term shortages
in
OSB/waferboard can account
OSB
ratio for
OSB
supplv was harder pushed to meet
filled
by plywood Note that even though
demand, there might have been regional
larger than
still
much
factors, for example, that
This explanation of interaction between plvwood and
for the hiccup in the
plywood curve around 1985, and so
lend
support to the larger hypothesis that an attacking emerging technology can contribute to the
perturbations
would thus
in
mature technology's S-curve
a
typically subtract the sales curve
phenomenon, one
In order to identifv such a
of the contributing technology from the
total sales
curve and isolate irregularities The third hiccup seems to exhibit a similar behavior where both
the total sales and that of
Just as
one
tree
OSB/waferboard
does not make a
forest,
is
growing, but the sales of plwvood
one or two hiccups
in
However, the arguments above support
oscillatory pattern
with
other
oscillations)
factors,
give
rise
to
is
perturbations
Given the arguments advanced
in
that an
in
the
dipping
an S-curve do not constitute an
the general conclusion that an
oscillatory pattern in the S-curve are not necessarily triggered bv the attack
technology What does seem plausible, however,
is
from an emerging
emerging technology can. together
S-curve
(but
not
necessarilv
to
the previous paragraph, this statement should
immediately be qualified bv saving that such perturbations should be carefullv analyzed within
the context of other influences (such as
existence of oscillations or perturbations
of the
difficulties,
fluctuations
As
of course,
is
macroeconomic business cvcles) and
is
that the
not enough to qualify' as a inortalitv indicator
to distinguish
between such indicators and regular
mere
One
statistical
the data on the residential fixed investment shows, the oscillations can be
caused b\ other factors that mav mask or interfere with the siunals that are related to the
effects
o\~
emerging technology
the
Interpreting
the
As
observing an oscillators' pattern or perturbations
thus
signal
entails
more than
example shows, external influences
this
such as the general economic climate and business cycles can play a significant role
into
just
Taking
account measurement errors and other sources of fluctuations and oscillations mentioned,
together with effects caused by business cycles,
processing
it
is
evident that a certain
amount of
signal
have to be done on an S-curve to extract potential signals from emerging
will
technologies
FORECASTING THE SUBSTITUTION PROCESS
Montrey forecasted the
substitution of
OSB
waferboard and
formulated the forecast
as
OSB/waferboard
for
plywood
one product category and using
a
in
1982 [26]
Fisher-Pry
model
Treating
[31],
he
the form
in
/(0 = -[l + tanha(/-/
(1)
)]
where
f(t)
= fraction of takeover of OSB/waferboard
a =
t
(l
half the
= year
in
initial
US
structural panel
the year
2002
specificallv
to
year
t
exponential takeover rate
which the substitution
The constants were found
in
to be
a=0 071
1
is
and
50%
t
completed
=2002.
i.e
the forecast indicated that half the
market would be made up of unveneered panels (waferboard and
In their
19 Q
paper.
the fact that a
Montrey and Utterback
14S°o
substitution
15
refer to the
was predicted
for
OSB)
by
19S2 forecast, and
1985 whilst the true
substitution
would seem
was
in fact
8%
(However, based on
[201
model given
that the
rather than a 14
15%
in their
substitution in
1985
Hence
of updating the forecast again was too great to
plywood
for the period
1976
to
the rate substitution
more years of
resist
in
original forecast,
new
forecast
were found
was assumed here
it
that
OSB
market segments for both plywood and
shown
el al.'s
to be
total
According to the new forecast, the substitution
that at least 15
pan due
new
slightly
plants
to the lack of raw
management
will
worrying. However, there
the expense of plywood.
OSB
[4]
were
forecast
Based on the new
a=0.10S7 and
were
likely to
is
50%
be
stronger current showing for
At the same time there
centuiA [3 2]
in
at
book
new
the
t„
=1995
As
data.
in
the
the
same
is
mutually exclusive
Figure 2 together with the historical data as well as the original
fact that this forecast predicts a
continue to grow
for
similar to the original
[20]
forecast
is
model
state that there are
forecast
current historical trend
retrospect probably against the
market between them This assumption
The new
in
in
a Fisher-Prv
rough approximation, since Montrey and Utterback
is
brisker than
plywood and OSB/waferboard address
market segments and that they account for the
a
was even
historical data, the temptation
The parameters
Utterback.
determined with the software accompanying Porter
the coefficients for the
substitution
a S
Subsequently the substitution data of OSB/waferboard for
1992 was applied
one described bv Montrey and
(and
it
16%
1990 paper actually predicts
they predicted). Having had the benefit of several
present authors' better judgment)
the constants given in their paper,
is
OSB
completed
than
is
in
1995
The
evidenced bv the
strong evidence that
OSB
will
As of September 1994 there were indications
be build
in
North America before the turn of the
also evidence of a falling
plywood production This
is
material, environmental pressures and governmental resource
practices that have resulted in large tracts of forests no longer being available for
this
purpose [33]
the void
filled
left
The statement
as
plywood
New
that
mills shut
oriented strand board mills, meanwhile, have
down because
even more oriented strand board capacity
is
added,
with uncertain and expensive log supplies" [34],
circa late
fast as
1994 The issue
plywood capacity
is
whether capacity
falls
away
As
[35]
to
is
it
they couldn't get big logs to peel
may elbow
typical
plvwood
of opinions expressed
OSB
manufacture
can be
the
in
made
mills
media
available as
plywood
a defensive strategy, one can expect
manufacturers to target niche markets that are not addressed by
A
aside older
As
OSB
chaos formulation
We now
turn our attention to alternative explanations for the oscillatory behavior
introduced by a discussion of a previously proposed chaos formulation, and
by the presentation of a modified Lotka-Volterra model which illustrates
interaction of
two technologies can give
rise to oscillatory
behavior
in
is
how
This part
is
then followed
the symbiotic
the mature phase of an
S-curve
Referring to the oscillatory behavior
Modis comments
that "
logistic
essential in order to analyze data via
it
[24]
some technologies' S-curves,
function
is
in
terms of states of chaos,
becomes
put in discrete form, which
computer programs which employ
iterative techniques,
can also be justified theoretically because populations are discrete quantities after
In another article
population growth into
into fluctuations ol~
[22]
the mature phase of
These deviations have been explained
which are encountered when the
but
in
Modis and Debecker make
a
comment
new niche had often been seen
random character and
Thev then proceed
the
that "
The annual
rate
all"
of
a
to follow a logistic pattern that brakes
sizable amplitude just before reaching the ceiling"
to explain the oscillatory behavior
of the growth curves with chaos
,.
c
,.
r;i
,,..
;
V
n
theory
Modis and Debecker's paper suggests
seemingly chaotic nature of the oscillations
In addition to
over the
of
Modis and Debecker's
The conclusion
contributions, several other articles have been published
that
[36,37],
Bhargava
Bhargava
el al.
come
to
is
[38],
telling
Gordon
which
[39,40] and
(1)
is
is
large (X being a
According
referred to
is
economic and
parameter analogous
to
a
[3S]
The
to
ways
in
which
article [22],
to
when X
is
they happened
upon
the
speed up algorithms to generate S-
in
generating the S-curves, but
mature phases of the curve
the oscillations that are often observed on
investigated the appropriateness of a chaos explanation for the
to investigate the effect
logistic
in (1))
Modis and Debecker's
also fluctuations in both the initial and
were akin
is
for the greater richness of the behavior of the
discretizing the calculation, they not onlv succeeded
the S-curve
social behavior
the solution, and which leads to chaotic and oscillatory behavior
to the narrative in
fluctuations
Modis [23.41])
the discrete difference equation form of the differential equation
chaotic behavior whilst searching for
By
example
for
of the sentiment of many of the papers,
particularly for large values of the nonlineantv parameter X"
equation that
curves
el al.
However, one must be prepared
undeniable
for
the mature phase of S-curves
the importance of the logistic equation in describing
solutions,
an investigation into the
growth models of technologies and technological forecasting (see
Gordon and Greenspan
"...
for
couple of years to show the relevance of chaotic behavior and the associated use
last
fractals to
viz
in
a justification
by changing the nature of parameters
Recognizing that the
growth curves, they
phenomenon Thev proceeded
in
the discrete representation of
Their simulations yielded systems with seemingly chaotic behavior, and hence
their claim that
chaos theory can account
for the
IS
S-shaped growth curve, oscillations
in
the
mature phase of S-curves. as well as similar fluctuations often observed
in
phases of a technology They also suggest that chaotic behavior can exist
period
curve
when one S-curve
is
replaced by another,
is
US
is
growth phase
in a
new market
the mature phase of one growth
when
approached
in
growth phase
perturbations)
is
"
the beginning", and
A
chaotic oscillations should be expected;
In contrast, an entrenched
will start" [22]
One could reasonably
that ".
deserve some
chaos
will reveal
to imply,
however, that there
Gordon
alludes to the
b\
when
in
the next
An
growth
new
that oscillatory behavior (or
chaotic systems,
analyst
What caused them 9
this
being
that indicate a
rise
of an
Modis and
a certain inevitability in the onset
is
of the complex behavior of
is
of the
oscillations
would understandably,
In fact,
no externalities
curve results from within the system
...
search for externalities responsible for the market performance would be misplaced effort,
for in this
to
the ceiling
same notion when he savs of chaotic
the causes for the market swings
all
when
comment The notion of precursors
generated by a simulation of sales as a function of time, "
were responsible,
is
mature phase of technology's growth may indicate the
the
chaotic oscillations
wonder about
it
nothing about
emerging technology Drawing upon the inherent determinism
Debecker seem
well-established S-curve will
noteworthy and lends support to the hypothesis
in
expect that an upcoming
niche will be heralded by precursors and, once installed, will
an accelerated rhythm
at
point to the time
To
the transitionary
held as an example
Modis and Debecker's statements
phase
when
in
growth
blended into the early phase of the next curve The annual production on bituminous
coal in the
proceed
i.e.
the early
example,
all
of the chaotic behavior comes from internal sources" [40] Modis refers
Montrey and Utterback's explanations
stating that
"
From 1970 onward
for the fluctuations in the
a
growth curve of plywood
pattern of significant (plus or minus 20 percent)
hniiir\
[
'j')j
instabilitN
Utterback tried to explain one by one
appeared, which Montrey and
socioeconomic arguments Given
fixed investment did play a
seem
the previous section
in
dominant role
terms of
one can always correlate other phenomena
a pattern
could have been predicted a
This type of pattern, however,
The arguments presented
in
in
pnon by chaos formulations"
to
it
[23]
residential
to indicate, however, that the
determining the oscillatory behavior
plywood's
in
S-curve
The chaos-based model
competes agamst the market,
one or more technologies
technology which
referred to in this section describes a
was
that
i.e.
account for the effects of
the formulation does not explicitly
Often one
finds,
competing or are interacting with one another
however,
in a
that
are
two or more technologies
section a
given market segment In the next
also lead to
interacting technologies and that can
mathematical model which involves two
described
oscillator,
behavior,
interacting
technologies and
technologies
in
the
same vein
The
model
is
applicable
is
technology,
oscillatory
is
case
of two
mature
Debecker
[22], rather as
one
much
that has
of time
behavior with modified Lotka-Volterra equations
mechanisms involved
it
general
presented as a conceptual one, very
the diffusion
differential equation.s) describing
underlying
the
to
emerging and
not restricted to the interaction of
and
as the chaos formulation of Modis
test
Modeling the
is
This
should be stressed that the model
It
withstood the
is
In
order
to
of a technology must be based on the
model
the
diffusion
characteristics
of
a
resources available be taken into
therefore necessary that the extent of the
embodied
account Finite resources are often
in a
market niche of
and competition of
cannot, however, descnbe the growth
finite size
A
single equation
two technologies simultaneously
for
does not account
it
their
for
respective effects on one another
To model
diffusion of one technology into a market [42]
one would need to
set
up
a differential
It
can
at
the competition of
best
model
the
two technologies,
equation for each of the technologies based on the
underlying drivers and inhibitors for that technology, together with coupling coefficients that
reflect the technologies" effect
at
hand,
is
it
on one another's growth rate In order to address the problem
necessary to model both the technologies explicitly, each with
They must then be coupled with coupling
A
them
Such
a
system of
is
own
coefficients to account for the interaction
differential equations rather than a single
system that
its
equation
applicable to this problem has been formulated
ecologists Lotka and Volterra. but until very recently
was
is
equation
between
therefore required
some time ago bv
the
not widely applied to the diffusion
of technology The system of equations that they developed has become
known
as the
Lotka-
Volterra equations
shown or commented on
Several authors have
the fact that the Lotka-Volterra equations can
be successfully applied to model technological diffusion,
[44],
among them Bhargava
[43], Farrell
Marchetti [21,45], Modis [23], Nakicenovic ([46] as quoted by Marchetti [45]) and
Porter
el
al.
Marchetti comments that
[4]
'
I
Volterra developed for ecological systems are vers'
nutshell,
I
suppose
Darwinian way,
their
solution of which
Even though
that
is
the social
am
fairly
convinced that the equations
good descriptors of human
affairs
In a
system can be reduced to structures that compete
in
a
flow and ebb being described bv the Volterra equations, the simplest
a logistic" [21
]
the Lotka-Volterra equations
may be
suitable to
model technological diffusion
and substitution, the question arises however, as to the appropriateness of modeling the
.;'".
.
)
);
with these equations
There are
equations
several references in the literature that suggest that the Lotka-Volterra
may indeed
behavior
oscillatory
in
the mature phase of the S-curve,
lead to a
modeling solution
Porter
a!.,
el
for the oscillatory behavior that
example, state that
for
accommodated by
"
States and
in
logistic start
in
in
overshoots and then oscillates around a
phase of
technology
a
curves can
are interested
become
in,
i.e
The above reference
the 'united
limit
a
The
limit
is
to a logistic equation
indicative
strongly
of the type of
those that are sometimes observed
Recall also Marchetti's
oscillatory
in
as Lotka-Volterra, can represent such behaviors if the
forecaster has correctly surmised their form..." [4]
we
in
These growths often show
Europe
followed by an overshoot and then oscillation around a supposed
oscillations that
of models
commonly found
Periodic behaviors are
consumption and mining patterns
car and transportation systems
more complex population models such
that
class
final
modeled using the Lotka-Volterra equations
natural populations and they can be successfully
have been observed
are concerned with here
Oscillatory models are a
the Lotka-Volterra equations
Oscillators' behaviors
we
comment quoted
when approaching
in
the mature
earlier to the effect that S-
saturation and that this
is
a possible solution
of Lotka-Volterra equations
Consider
now two
technologies which are interacting
ecological term and refers to the association of
two
interaction
growth
among two
rate
A
for the
a
different
other or one within the other to their mutual advantage
mutualism and commensualism, but
in
purpose of
symbiotic
way Symbiosis
is
an
organisms Using attached to each
The term
is
related to the concepts of
this discussion,
it
is
meant
to imply the
technologies such that each has a positive influence on the other's
system of nonlinear differential equations (which
is
based on Lotka-Volterra
equations) that describes symbiotic interaction can be formulated as follows
—
ciN
,
= a n N-bn N- +c nm
dt
—
dKl
where
= am A 1 -
all
This
coefficients are positive
Volterra equations
in
(2)
,
b,„
A I ~ + cim A4N
N(t) and Al(() represent the "populations"
example) and
NM
(
of the two technologies (such as
set
3
for
sales,
of equations differs from traditional Lotka-
the sense that both ^-coefficients are positive, and furthermore has been
modified to depict symbiosis by having positive signs for both the coefficients that regulate the
among
interaction
formulation
indicate
is
shown
where
two technologies
the
in
dN di=0
Figure
3.
and cmn ).
(c nm
The equilibrium
lines
A
generic phase diagram for this
on the associated phase diagram
and dhl dt = Q are respectively given by
N = ^L + ^SL M
b„
M
h "<
KA
lines)
will
where
and
is
"'"
c..
inn
the phase diagram are also equilibrium lines,
A/-0 and dN.dt=0 on
position
(4)
o„
c.. ,„
The axes of
the A/-axis
dN dt =
normally
terminate there
that
e
dM/dt=0 on
where
the yV-axis
where N=0. The equilibrium point (N*,M*) represents the
and dM/dt=0 simultaneously
a stable point, in the
The arrows
i
in
(i
the intersection
e
sense that once
it
between these two
has been reached, the trajectory
the four subregions of the phase diagram indicate the
directional derivatives in those regions
Note
that time
is
a
parameter for
a trajectory
on the
phase diagram
'a,
in
.
i
':
Pielou's
iterative
solution for the set of equations
are
[47]
modified to account
for
the
symbiotic interaction, yielding the solution
N(t +
;v N(t)
(6)
l)
fc
)
\-P n N(,)-\^\P n MU
where
=
?
a
e "
(7)
a
b n (e » -1)
P„
(8)
and
X,„M{t)
M(l +
(9)
1)
C
\
+ p m M{t)-
L
-f
\
where
An "
'
10)
L
b,„(e
a
»<-\)
(11)
p,
In order to illustrate the
dynamics of this formulation, consider
\'{D= .Y(0.1-0.01.V-c„„ A/)
now
the system
(
1
(
24
/y.>
.\/m = A/(0 15-001.\/-c„„,.Y)
with c„„,=0.005 and
c mn =0.005
Let the
(13)
conditions be Af(0)=\ and N(0)=\5
initial
be stressed that the numeric values of the coefficients as well as the
intended to relate to any real situation
randomly chosen with c adjusted
domain
to illustrate the
to the oscillatory behavior in the
interesting
phenomenon occurs when
diagram
Figure
in
equilibrium point
seems
3
As expected,
However,
example were
dynamics conceptually The resultinu time
in
Figures 4 and
Note how
5
show
the time
values
of
domain
plot
b„b„ =0.000]
the
like oscillatory patterns
to
the
note that an
Consider again the phase
subregion
initiates in
we
1
approaches the
domain reminds one of a chaos-like
A
cursory inspection
state
Figures 6 and 7
and phase diagram when c „=0.005 and c
m
nwi =0.0157, yielding
and
growth along S-curves
rise
c mn c mn approaches b„b
m
a trajectory that
c„„,t„„,=0
000025) Both technologies
what gives
mature phase of an S-curve,
to overshoot and then breaks into an oscillatory pattern
oscillators' pattern in the time
regular
this
rather than terminate at the equilibrium point (as in Figure
5), the
of the
c iwi c '>nn = Q
values are not
initial
in
should
on the phase diagram approaches and terminates on the equilibrium point
Coming back
trajectory
the coefficients a and b
and associated phase diagram are shown
plot
trajectory
—
It
until
000079
live fairly
uneventful lives
approximately
By examining
the time
(whereas
/
in
in
the
previous
the time domain, following
= 240 when they both break
domain
sudden burst of oscillations
plot in Figure 6,
in
the
case
into chaos-
one might wonder
mature phase
after
the
two
technologies coexisted for a long time during which both followed normal logistic growth
turns
out
that
there
is
nothing
mystical
about the time when the oscillations
examination of the associated phase diagram
in
Figure 7 reveals that the time
It
start
An
when
the
';,. t r\
'
l
'
when
oscillations start corresponds with the time
the equilibrium point
If the coefficients are
subsequently the time
when
The chaotic
the
that
oscillations
observed here are a
is
commence
far cry
can be predicted
from those shown
in
Figure
Figure 6 break into oscillations simultaneously
in
plywood and OSB/waferboard
system shown here
diagram reaches
known, the phase diagram can be constaicted and
the oscillations will
two technologies simulated
the trajectory in the phase
purely to
in
Figure
do not do Keep
1
the
illustrate
and that
concept,
plywood/OSB/waferboard case cannot be modeled with
in
Note
1
that
— something
mind, however, that the
the
possibility
that
the
model should not be dismissed
this
out of hand without further investigation of the behavioral characteristics of the model
should also be kept
mind
in
that the simulated results presented here
difference equation and the time increments in the
behavior, particularly
when
yields negative values for
sales
A-/,
in
From
the
principle,
(1)
we know
among
depends very strongly on the
in
we
sometimes
N and M represent
in
the real
Nevertheless, the results
in
the
the mature
a
symbiotic
absence of another
can infer that (within the realms
the mature phase of the S-curve can also be caused
multiple technologies,
ratios
that
a
role in the
also
when two technologies have
technology, oscillatory behavior does not occur and hence
of the model), the chaos-like oscillations
if
model
one can expect oscillatory behavior
nature of equation
bv symbiotic interaction
that the
we assume M,N>0.
phase of S-curves under certain circumstances
interaction
Note
something that cannot occur
of the technologies for example, where
obtained here indicate that,
model hence plays an important
a chaotic situation occurs.
N and
were generated with
It
in
of the coefficients
which case the onset of chaos
in
the
underlying
Lotka-Yolterra
equations
•(..•'".
/>
Note
that the
system modeled above changed
of the coefficients changed
ratios
(i
e
its
behavior from stable to oscillatory
change depicted
the
when
the
Figures 4 and 5 versus that
in
in
Figures 6 and 7) In general, one can assume that the coefficients will be time dependent rather
than
constant,
and
furthermore that
with time
dvnamically
It
is
external
forces
can and
influence
will
may
then entirely conceivable that a chaotic solution
values
their
result if the
values of the coefficients change relative to one another to support such a solution This brings
us back to the issue of the pre-determinedness of the chaotic nature that has been discussed
the literature
The
issue boils
technology exhibits
is
down
genetically
to the question whether the
encoded into the technology
animate or organic objects, for example)
If
substitution are social rather than natural
there
is
no predetermined
one takes
the
view
phenomena, there
inevitability in the
growth curve
that a particular
(similar to the
growth of some
that technological diffusion
and
made
that
is
an argument to be
growth of technology The diffusion pattern and
particularly the rate of diffusion, are determined by various external
certainly
acknowledge
that the inherent characteristics
influence these factors
We
growth
may be
the
path, as suggested
forces [43]
may be
possibility
we
that,
from
modeling
a
described by different models along
by Tingyan [48], for example
It is
quite feasible that the
of the equations change with time as they are acted
Depending on the relationship and
ratios
between the
growth
growth cycle These
turn,
are
will
in
be dictated by the ratios of the coefficients
influenced bv external
forces
upon by
external
coefficients, the svstem
then exhibit smooth growth, oscillatory or even chaotic behavior
in
although
described by the general Lotka-Volterra equations as suggested by Bhargava, where
coefficients
thev.
factors,
of the innovation or technology can
must also not exclude the
viewpoint, the growth of a particular technology
its
in
at
may
various phases of the
any given moment as
Even thouuh some technological urowth
/
i
>->;
uar\
;)')'
may
patterns
exhibit chaotic oscillations, the question that should be
system to chaos
"
asked
is.
"What drove
the
[39]
Conclusions
The paper
started
by discussing the notion of mortality indicators that signal the demise of
mature technologies The question was posed whether the oscillations that have been observed
in
the mature phase of
some
technologies' S-curves are indications that such technologies are
being attacked by emerging technologies,
The case of
shown
in
the
US Hence
e
whether the oscillations are mortality indicators
plywood by OSB/waferboard was
the substitution of
investigated, and
plywood's S-curve track the phases of the
that the oscillations in
investment
i
it
is
residential
was
it
fixed
concluded that the residential fixed investment pattern
is
therefore primarily responsible for the oscillations and that the oscillations are not mortality
indicators
The
rise
of OSB/waferboard does, however, seem to contribute to perturbations
A
the mature technology's S-curve
(plywood
made
new technology can have
that
the
perturbations
emergence of
in a
a
in this
case)
in
further conclusion can thus be
a
contributory
influence
on
mature technology's S-curve, although the oscillations can be dominated by
other effects such as macroeconomic business cycles Given the fact that accurate and reliable
mortality indicators can have profound managerial implications and that the surface has only
been scratched
in this
paper with regard to death knells of mature technologies, further pursuit
of the notion of mortality indicators
may be
is
certainly to be
recommended One avenue of research
the application of signal processing techniques to "extract" potential signals that are
caused b\ emeruinu technologies
2S
There have been some comments
related
phenomenon
mathematical
in
the literature that the oscillators' behavior
The chaos formulation was used
model which
is
rate),
and
oscillatory behavior in S-curves
coefficients
It
is
it
is
a
backdrop
to
on modified Lotka-Volterra equations
based
assumes symbiotic interaction among two technologies
on the other's growth
as
may be
shown
(i.e.
that this type
where each has
a
chaos
introduce
a
model
This
a positive effect
of interaction can also give
rise to
under certain circumstances, depending on the ratios of the
suggested that
this
is
another avenue of research which
may
lead
to
interesting and useful results
Acknowledgments
The authors would
like to
acknowledge the inputs of Dr Chris
Pielou's solution to their attention and alerting
inputs of
general
Dr John Crowley of MIT on aspects
them
Farrell
to the usefulness
relating to the
wood
of Baxter
in
bringing
of phase diagrams, the
products industry and the
comments of Mr Schalk Burger of the University of Pretoria
chruun
•
.
O
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3-4
"rutin
>'>:
.
FOOTNOTES
The data from
deflator of
The
1
1
the
US
Statistical
74 was used to convert
historical data in Figure 2
Figure
1,
Abstracts [30]
assuming
that
it
to constant
was obtained by
is
1
given
982
in
constant
A
1987 dollars
dollars [29]
calculating market share from the values
plywood and OSB/waferboard make up the
total
market as
in
in
[20]
-'',..'>,
.
'
)•
FIGURE LEGENDS
Figure
1
US
sales
of plywood and OSB/vvaferboard as well as residential fixed investment
constant
(in
The dark arrows
1982 dollars)
indicate the hiccups discussed
in
the
text
Figure 2 Market share of OSB/waferboard versus plywood
Figure 3
in
the
US
Generic phase diagram for the symbiotic system with an equilibrium point (N*.M*J
in
the region
M,jV>0
(b n b
m > cnm cnm
).
The dark arrows
indicate the directional
derivatives in the various subregions.
Figure 4 Time domain plot for two technologies
Figure 5
Phase diagram for two technologies
Note how the
Figure 6
Time domain
c
w „=0.0157)
trajectory terminates
plot for
Note
in
symbiotic interaction (c tim =~c nm = Q 005)
in
symbiotic interaction {cmiJ =c nin =0.005)
on the equilibrium point
two technologies
in
symbiotic interaction (c /nn ~
005 and
the onset of oscillations in the mature phase in the region of
/=240
Figure 7 Phase diagram for two technologies
mature phase
(c
mn =
in
symbiotic interaction with oscillations
Note
005 and cnfn =0.0\57)
in
the
the onset of the oscillator.'
behavior after the trajectory crosses the equilibrium point
Table
1
Demand/capacity
ratios for
plywood and
(3/8" basis) [27]
jo
OSB
in
the
US
for the period
19S 1-1989
Figure
1:
US
sales of plywood and OSB/waferboard as well as
residential fixed investment (constant
1982 dollars). The dark
arrows indicate the hiccups discussed in the text.
200
30
Total
sales
--
180
--
160
Residential
fixed
--
25
investment
7i
CD
--
140
w
<*
Q.
CD
20
D
CD
CD
CD
**—
Plywood
CD
--
120
X
CD
a
ra
=3
5'
cr
<
CD
15
-
100
c
o
3
CD
D
in
80
_CD
03
5C/1
o
—
10
Q_
+ 60
|
W
5
--
40
--
20
--
OSB/waferboard
1
1
1
1
1
1
1
1
1
1
1940 1945 1950 1955 1950 1965 1970 1975 1980 1985 1990
Year
Figure
1
2:
Market share of OSB/waferboard
versus plywood in the US
00%
1975
1980
1985
1990
1995
Year
2000
2005
2010
30
M(t)
N(t)
20
-
10
100
50
Figure
4:
Time domain
plot for
150
two technologies
in
20 °
Time
250
300
symbiotic interaction (c nm =c mn =0 005)
M
30
25
S
20
dN/dt=0
pi
5
10
H
5
,'
10
FiauiT
5:
Note how
Phase diagram
tor
15
two technologies
in
M(t)
dM/dt=0
20
svmbiottc interaction (c nm
the traiecton. terminates on the equilibrium point
30
25
l
iiw
'I'h'n
400
Table
I:
Demand/capacitv
ratios for
plvwood and
OSB
in
the
US
for the period
1981-1989
[27]
1981
1982
1983
1984
1985
1986
1987
1988
1989
Plywood
0.74
0.69
0.82
0.86
0.84
0.87
0.86
0.86
OSB
0.48
0.49
0.58
0.79
0.76
0.93
0.84
0.90
0.88
0.90
Total
0.71
0.68
0.80
0.82
0.83
0.88
0.87
0.88
0.89
FOOTNOTES
1
The
data from the
deflator of
2
The
.
1
Statistical
74 was used
1,
assuming
that
Abstracts [30]
to convert
historical data in Figure 2
Figure
[20]
1
US
it
to constant
was obtained by
given
is
1
982
in
constant
1987
dollars.
A
dollars [29]
calculating market share
plywood and OSB/waferboard make up the
from the values
in
market as
in
total
The International Center for Research on the Management of Technology
Sloan School of
Management
•
Massachusetts Institute of Technology
Working Paper and Reprint
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1-89
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Youth and Scientific Innovation: The Role
Development of a New Field
55-91R
7/92
Technological Communities and the Diffusion of Knowledge
56-91
The Voice
of
Scientists in the
1/92
58-92R
1993
59-92R
1992
60-92R
9/91
Rappa
Rappa
Rappa
Debackere
of the
Customer
Griffin
Hauser
The Influence
Auto Industry
of Inter-Project Strategy
on Market Performance
in the
Linking International Technology Transfer with Strategy and Management:
A
Literature
Commentary
Nobeoka
Cusumano
Cusumano
Elenkov
Modeling Contribution-spans of Scientists in a
Cochlear Implants
Field:
The Case
of
Rappa
Garud
Technological Progress and the Duration of Contribution Spans
Rappa
Debackere
Garud
1992
61-^2
Debackere
Debackere
Win/93
57-92
Rappa
Debackere
(Rev. 9/92)
A
Socio-Cognitive Model of Technology Evolution: The Case of Cochlear
Garud
Rappa
Implants
(Rev. 2/93)
62-^2R
8/92
b3-^2
1/
,L*2
On
the Persistence of Researchers in Technological
Development
Garud
Rappa
Life
on the
Frontier:
an Emerging Field
An
International
Comparison
ot Scientists in
Debackere
Rappa
Number
Date
The
64-92
Author(s)
Title
Social Construction of Technological Reality:
The Case of Cochlear
65-92
Superseded by 77-92
66-92
Windows Of Opportunity: Temporal Patterns of Technological
Adaptation In Organizations
3/92
Garud
Rappa
Implants
1/92
Tyre
Orlikovvski
(Rev. 9/92)
67-92R
Spr/93
How
Puritan-Bennett Used the
68-92
How
Consumers Allocate Their Time When Searching
2/92
House
Ha user
of Quality
for
Information
(Rev. 5/93)
Moving Ideas
69-92
to
Hauser
Urban
Weinberg
Meyer
Market and Corporate Renewal
Utterback
7/92
70-92
Project
Management
in
Technology Innovation, Application and Transfer
Frankel
5/92
71-92
Pindyck
Investments of Uncertain Cost
9/92
72-92
Identifying Controlling Features of Engineering Design Iteration
Smith
Eppinger
9/92
Objectives and Context of Software Measurement, Analysis
73-92
and Control
Cusumano
10/92
An
74-92
11/92
Empirical Study of Manufacturing
Board Assembly
Flexibility in Printed-Circuit
Suarez
Cusumano
Fine
75-92
11/92
76-92
Japanese Technology Management: Innovations, Transferability, and the
Limitations of "Lean" Production
Customer
11/92
77-92 R
Hauser
Satisfaction Incentives
Simester
Wernerfelt
(Rev. 3/93; 1/94)
The Product Family and
the
Dynamics
of
Core Capability
1 1
/
Multi-Project Strategy and Organizational Coordination in
t)
2
79-92
12/92
80-92
11/42
81-92
1/^:
Meyer
Utterback
Spr/93
78-^2
Cusumano
Automobile Product Development
Patterns of Industrial Evolution,
Dominant Designs, and Firms' Survival
(Rev. 7/93)
Innovation from Differentiation: Pollution Control Departments and
Innovation in the Printed Circuit Industry
Answer Garden and
the Organization of Expertise
Nobeoka
Cusumano
Utterback
Suarez
King
Ackerman
Number
Date
82-92
Author(s)
Title
Skip and Scan: Cleaning
Up Telephone
Resnick
Interfaces
2/92
Virzi
How
83-92R
Fall/92
Voice
84-92
A
to
Succeed
in Business
Comparative Analysis
by Really Trying: Listening
of
to the
Customer's
Roberts
Design Rationale Representations
Lee
Lai
3/92
85-93
1/93
86-93
2/93
An Introductory Note for
Analyze Nodes, Relationships, Partitions
Relational Data in Organizational Settings:
Using AGNI and Netgraphs
and Boundaries
A Knowledge
to
Asset-Based View of Technology Transfer in International
Joint Ventures
George
Allen
Rebentisch
Ferretti
(Rev. 9/93)
87-93
4/93
Managing High Performance
R&D Teams
Katz
(Rev. 6/93; 5/94)
Toward
Handbook
88-93
Tools for Inventing Organizations:
5/93
Processes
89-93
The Impact of Knowledge and Technology Complexity on Decision
Making Software Development
5/93
a
of Organizational
Malone
Crowston
Lee
Pentland
Meyer
Curley
Locating Adaptive Learning: The Situated Nature of Adaptive Learning
in Organizations
von Hippel
91-93R
Fall/93
Exploiting Opportunities for Technological Improvement
Organizations
Tyre
Orlikowski
92-93
Scientific
90-93
5/93
3/93
93-93
7/93
94-93
and Commercial Importance and the Source
in
of Scientific
Inductive System Diagrams:
An
Empirically Based Theory Generation
9/93
97-93
9/93
9S-93
Burchill
Kim
Technique
The Hvpercube
Afuah
of Innovation
Bahram
Managing
the Integration
Problem
in
Concurrent Engineering
McCord
Eppinger
8/93
96-93
RiRRS
von Hippel
Instrument Innovations
7/93
95-93
Tyre
Bevond the Software Factory:
Software Developers
A Comparison
Obstacles to Systemic Innovation:
of "Classic"
and PC
S
m
i
t
h
Cusumano
An
Illustration
from Semiconductor
Kappa
Manufacturing Technology
Radical Innovation
Utterback
Number
Date
Author(s)
Title
Finding Out
99-93
What Goes On
Software Development Organization
in a
Perry
Staudenmayer
11/93
Votta
100-93
11/93
Network
Externalities in
Microcomputer Software:
An
Econometric
Brynjolfsson
Analysis of the Spreadsheet Market
Kemerer
101-94
Superseded by 115-94 and 119-95
102-94
Technological Intensity and Interfirm Cooperation: An Industry Level
Study of Alliance Networks of US Public Firms, 1985-1990
George
Globalization through Interfirm Cooperation: Technological Anchors and
George
3/94
103-94
3/94
104-94
Temporal Nature
of Alliances across
Premarket Forecasting of Really
New
Geographical Boundaries
Urban
Weinberg
Hauser
Products
5/94
105-94
5/94
106-94
5/94
107-94
5/94
108-94
Multi-Project Strategy and Market-Share Growth:
Rapid Design Transfer
in
New
The
Nobeoka
Cusumano
Benefits of
Product Development
Nobeoka
Cusumano
Multi-Project Strategy, Design Transfer, and Project Performance:
A
Survey of Automobile Development Projects
in the U.S.
and Japan
Time versus Market Orientation
in Product Concept Development:
Empiricallv-based Theory Generation
Business Transformation: The Key to Long
Term
Burchill
Fine
Weil
White
Survival and Success
5/94
109-94
6/94
Social
Sword
Comparisons and Cooperative
of Communication
R&D Ventures:
The Double-Edged
Tucci
Lojo
r
110-94
Benefits
and
Pitfalls of International Strategic
Technology Alliances
1 1
1-94
7/94
112-94
10/94
113-94
10/94
1
14-94
9/94
115-94
1 1
/
Identifying the Sources of Market Value for Science-Based Products:
The Case
Integrating
Mechanisms
for
Marketing and
R&D
Griffin
Hauser
(Rev. 7/95)
Multi-Project
Frenkel
Harel
Koschatzky
Grupp
Maital
of Industrial Sensors
Management:
Nobeoka
Cusumano
Interdependencv and
Product Development
Inter-Project
Organizational Coordination
in
New
Global Benchmarking Studs' on the Management of Technology:
The Case of Singapore
Benchmarking the
Strategic
Management
of
Technology
-
-
Roberts
Roberts
I
94
16-9?
12,
Tucci
Cusumano
7/94
*-'4
Managerial Determinants of Industrial R&D Performance:
Chemicals/Materials Industry
of the Global
An
Analysis
Roberts
Bellotti
Number
Date
117-95
12/94
Author(s)
Title
Overcoming Collusion: Using
Moral Hazard
a
Supervisor
to Costlessly
Resolve
Simester
Wernerfelt
Hauser
118-95
1/95
119-95
1/95
120-95
2/95
Internal
Customers and Internal Suppliers
Hauser
(Rev. 6/95)
Benchmarking
R&D
Simester
Wernerfelt
the Strategic
Management
Technology
- - II:
Roberts
Product Development
Morelli
Eppinger
Gulati
of
Performance
Predicting Technical
Communication
in
Organizations
(Rev. 5/95)
121-95
Integration Analysis of Product Decompositions
Pimmler
2/95
122-95
Eppinger
Peace, Trade and Technology in the
New
Maital
Mideast
4/95
123-95
Technology Strategy
in a
Software Products
Company
Meyer
Lopez
4/95
124-95
Metrics for Managing Research and Development
Meyer
Tertzakian
Utterback
4/95
125-95
Metrics to Evaluate
R&D
Groups
-
Phase
I:
Qualitative Interviews
3/95
126-95
S/95
127-95
8/95
128-^5
What We Have Learned and Have Yet to Learn from ManufacturerSupplier Relations in the Auto Industrv
Cusumano
&
Cusumano
Making Large Teams Work Like Small Teams: Microsoft's "Synch
Development
Stabilize" Process for Software Product
Bevond
the Waterfall: Software
Development
at
Microsoft
S/95
12 u - c >5
S/V5
Zettelmeyer
Hauser
Microsofts Competitive Principles:
Mass Markets
Pioneer and Orchestrate Evolving
Takeishi
Selbv
Cusumano
Smith
Cusumano
Selbv
Number
Date
130-95
8/95
131-95
8/95
132-95
Author(s)
Title
New-and-Improved High-Tech Products: Speeding Producer, Meet
the Balking Consumer
A
Studv of Technology Transfer
Venture
in a
Multinational Cooperative
Dhebar
Katz, Allen
Rebentisch
Joint
A German View of Executive Support Systems
Rechkemmer
9/95
133-95
Information Technology and Product Policy (A): "Smart" Products
Dhebar
Information Technology and Product Policy
Dhebar
9/95
134-95
(B):
Information Products
9/95
135-95
The Death Knells
of
Mature Technologies
Paper numbers with the ^uttiv
Pistorius
Utterback
2/95
R
are reprints
2218
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