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Organizations as Adaptive Systems in Complex Environments: The Case of China
Author(s): Max Boisot and John Child
Source: Organization Science, Vol. 10, No. 3, Special Issue: Application of Complexity Theory
to Organization Science, (May - Jun., 1999), pp. 237-252
Published by: INFORMS
Stable URL: http://www.jstor.org/stable/2640330
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Organizations
s
daptive
Systems
in Complex
Environments h e a s e o h i n a
Max
Boisot
*
John Child
Department of Strategic Management, ESADE, P.O. Box 144, 08870,
Sitges, Barcelona, Spain
The
Judge Institute of Management Studies, Cambridge University, TrumpingtonStreet, Cambridge CB2 JAG,
United
Kingdom
Abstract
This paper treats organizations as adaptive systems that have to
match the complexity of
their environments. The nature of this
complexity is analyzed by
linking an institutional Information-
Space (I-Space) framework to the work of complexity theorists.
The I-Space framework
identifies the codification, abstraction,
and diffusion of information
as cultural attributes. Codification
involves the assignment of
data to categories, thus giving them
form. Abstraction involves a reduction in the number of cate-
gories
to which
data needs
to
be assigned for a phenomenon to
be
apprehended. Information is diffused through populations of
data-processing agents, thus
constituting the
diffusion
dimen-
sion. Complexity theorists
have identified the stability and
structure of algorithmic information complexity
in
a way that
corresponds to levels of codification
and
abstraction.
Their
identification of system partsandthe richness of cross-coupling
draws attention to the fabric of
information diffusion.
We
dis-
cuss two modes of adaptation
to complex environments: com-
plexity reduction and complexity absorption. Complexity re-
duction entails
getting
to
understandthe complexity and acting
on it
directly, including attempts
at environmental
enactment.
Complexity absorption entails creating options and risk-
hedging strategies, often
through alliances.
The analysis, and its
practical utility,
is
illustrated
with
ref-
erence to
China,
the
world's largest social system. Historical
factors have
shaped
the
nature
of
complexity
in
China, giving
it very different characteristics than those typical of Western
industrial countries. Its
organizations and other social units have
correspondingly handled
this
complexity through
a
strategy
of
absorption rather than the reduction
strategy characteristic
of
Western
societies. Western firms
operating
in China therefore
face a choice
between
maintaining
their norms of
complexity
reduction
or
adopting a
strategy
of
complexity absorption
that
is
more consistent with Chinese culture. The specifics of these
policy alternatives are
explored, together
with their
advantages
and
disadvantages.
The
paper concludes
with the outlines of a
possible agenda
for
future
research, focusing
on the
investigation
of
complexity-
handlingmodes and the contingencieswhich may bear upon
the choice between hem.
(Adaptation; China; Complexity; Organizations)
Introduction
As a theme for organizational scholars, complexity
has
undergone some important
transformations in recent
years.
It
figures
in
conference headings and, increasingly,
in the popular literature as a managerial topic in its own
right (Waldrop 1992, Lewin
1993, Casti 1994). Organi-
zational complexity was discussed
in
the professional
lit-
erature of the 1960s and 1970s, although not always ex-
plicitly
under that
heading
(Emery and Trist 1969, Etzioni
1961, Perrow 1970, Simon 1969, Bums and Stalker
1961). Organizational complexity circa 1970, however,
has a very different intellectual
flavour than what is of-
fered today.
Developments
in the nonlinear sciences, as well
as
in
biology
and in
physics,
have transformed the
subject.
Much
of the work
coming
out
of
research centres
such as
the
Santa
Fe Institute
in
New Mexico,
for
example,
with
its
emphasis
on
emergence
and far-from-equilibriumphe-
nomena, has radically different implications for
how we
approach complex organizational
processes than the
re-
search of three decades ago, concerned
as it was then with
abberations
from
stability
and predictability.
From the new perspective, organizationsare treated as
instances of adaptive systems (Holland 1975), that is, sys-
tems that have to
match in a
nontrivial
way
the
complex-
ity
of their environment (Ross Ashby 1954,
Wiener
1961), either to
achieve an
appropriate
measure of fit
with
it or to secure for themselves
a
degree of autonomy with
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Copyright
C)
1999, Institute or OperationsResearch ORGANIZATION SCIENCE/Vol. 10, No. 3, May-June 1999
and the ManagementSciences pp. 237-252
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MAX BOISOT AND JOHN CHILD Organizations as Adaptive Systems
respect to whatever constraints it might
impose (Varela
et al. 1991).
Does the fact that human organizations
are also inter-
pretative systems (Weick 1995), that they
function
partly
on the basis of internal representations
of the environ-
ments that they respond to, place them beyond the ana-
lytical reach of the new sciences of complexity? For, they
adapt,
if
at all,
to
the complexity
as their decision
makers
perceive
and
interpret
it rather than to
any objectively
given complexity
in
their environment.
And, given an
appropriate
set of
representational schemata, perceived
complexity
can
often be
significantly
reduced. Further-
more, they
also
have
the
capacity
to enact
some of
the
representations that they construct for themselves, thus
modifying
their
environmentproactively
as well as
adapt-
ing to it (Child 1972, Giddens 1984, Weick 1995). The
joint
effects
of
interpretation
and enactment have in the
past served to distinguish the social
from the natural
sci-
ences (Dilthey 1883/1988, Weber 1964).
The new approach to complexity
is
tending
to blur
that
distinction (Morin 1977).
Both
types
of
science
view
complexity
as
arising
out
of the number of
elements
that
go
to
make
up
a
system-social
or
natural-and the na-
ture of the interactions that
take
place
between the ele-
ments.
An
important
distinction
between
natural and
so-
cial systems resides
in
the tightness
of their
coupling.
Both might
be
open, but
social
systems
are
more
loosely
coupled
than
natural
systems
and thus
inherently
more
complex.
What do we mean
by
this?
Simply
that
in
the
former
case,
the
interaction between
the elements is
pri-
marily informational
rather than
energetic.
The
trade-off
between energy and informationis also visible withinnat-
uralsystems themselves.
The
binding energy
between nu-
clear
particles,
for
example,
is of the order
of
140 million
electronvolts,
that
between
the atoms that make
up
a mol-
ecule is
of the order
of five
million
electronvolts,
and that
between molecules is half an electronvolt. Clearly, the
combinatorial
power
of molecules-and
by implication,
the information content of an
assemblage
of molecules-
is orders of
magnitude greater
than that
of atoms or
sub-
atomic
particles.
The
degree
of
openness
of a
system
is
thus
partly
a reflection of its combinatorial
power
and so
is its
degree
of
complexity.
Finally,
the
complexity
of the environment
that
orga-
nizations are requiredto enact or adaptto reflects human
cultural
activity
and level of
development.
These
shape
both
the forces
that an organization
must
respond
to
as
well as the
representations
and behavioural
dispositions
through
which the
response
is channelled.
Much
evolutionary theorizing points
to
systems
evolv-
ing phylogenetically
to handle ever
more
complexity
over
time
(Schuster 1996).
Thus
in the case of
living systems,
for example, single-cell organisms give way to multicell-
ular structures,
and the cells
themselves grow and acquire
a more complex internal structure-i.e., eukaryotic cells
emerge from prokaryoticones. In this way and over time,
organisms grow
and
differentiate internally, acquiring
so-
phisticated data-processing capabilities as they do so.
With growthand specialization comes an abilityto handle
an ever wider and varied range of internal representations
of the external environment. As evolving organisms en-
hance their capacity
to
match the variety of the environ-
ments
they
encounter-for our
purposes, variety
offers a
good proxy
measure
of
complexity-so
do their survival
chances and reproductive fitness improve (Ross Ashby
1954).
Interpretative systems, however, have two quite dis-
tinct ways of handling the complexity that underlies the
variety:
(a) They
can either reduce it
through getting
to under-
stand it and acting on it directly. That is, they elicit the
most
appropriatesingle representation
of that
variety
and
summon
up
an
adapted response
to
match
it. Such
a strat-
egy
leads to
specialization
informed
by
relevant
codifi-
cation and abstraction
of the
phenomenon.
(b)
Or
they
can absorb it
through
the creation
of
op-
tions and
risk-hedging strategies.
That
is, they
can hold
multiple
and sometimes
conflicting representations
of en-
vironmental
variety, retaining
in their behavioural
rep-
ertoire
a
range
of
responses,
each of which
operates
at a
lower level of specialization. This approach develops be-
havioural plasticity.
There
may be less goodness of fit
between
any given response
and the state
of nature to
which it needs to be
matched,
but the
range
of environ-
mental
contingencies
that
an
organism
can deal with
in
this
way
is
greater
than
in
a
regime
of
specialization.
It
may
endeavour to enhance its
capability
to deal with a
wider
range
of
environmental contingencies by cooper-
ating closely
with a number
of other
organisms,
which
can assist with information and
interpretation
and share
risk.
These
strategies only partially overlap
with
those of
uncertainty
reduction and
absorption (Weick 1995). They
correspond
to two distinct
approaches to learning first
identified
by
Holland
(1975)
in
his work
on
complex
adaptive systems and subsequently elaboratedby March
(1991)
and
March
and
Levinthal (1993)
in an
organiza-
tion context:
exploitative
and
exploratory learning.
Each
of these
two
approaches
to
learning distinctively shapes
the
way
that data is
processed
and shared
among
the data-
processing agents
that make
up
an
organization's
social
system.
Since the
processing
and
sharing
of data are the
constitutive activities that
make
up
a cultural
process
238 ORGANIZATION CIENCE/Vol. 10, No. 3, May-June 1999
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MAX BOISOT AND
JOHN CHILD Organizations as Adaptive Systems
(Boisot 1995, Schein
1992),
we would
expect
to
see or-
ganizations,
and
societies,
with
different cultures
vary
in
the extent to which
they
choose to reduce or absorb the
complexity that confronts them.
In
what follows, we develop the
argument that com-
plexity reduction and
complexity absorption represent
distinct cultural strategies adopted by adaptive systems
(Holland 1975).
This
is first addressed
analytically by ap-
plying an
Information-Space (I-Space) framework
(Boisot 1995) and linking this to the work of
complexity
theorists.
We
then move on to illustrate the
argument
with
reference to
China. China is the world's
largest
social
system, and one whose form of
complexity, and
custom-
ary modes of
handling it,
were
not familiar
to
the Western
firms
now operating there. We
analyze
the
choice these
organizations have faced between
maintaining
Western
norms of
complexity
reduction or
adopting
a
strategy of
complexity absorption that is more consistent with Chi-
nese culture. The
paper
concludes with the outlines of
a
possible agenda for future research, focusing on the in-
vestigation
of
complexity-handling
modes
and the con-
tingencies which
may
bear
upon
the
choice between
them.
Its
contribution is
thereforeby
way
of
an
explora-
tory exercise in
theory-building.
The
Framework
The
I-Space is an augmented
version
of the
framework
that we have used to
analyse different
aspects
of China's
modernization
(Boisot
and Child
1988, 1996).
The
origi-
nal
framework was
labelled
the Culture
Space
or
C-
Space.
The
C-Space
took
the extent to
which
data could
be shared in a
given population to be
a
function of how
far it
could be
codified,
that
is, compressed
into codes
(Boisot 1986).
Financial
information that
is
codified into
prices
and
quantities,
for
example,
can be shared more
readily
in
a
population
of market
players
than
information
that
is
replete
with
qualitative nuance.
Codification, however,
can be
greatly
facilitated
by
an
appreciation
of
structure. Structure abstracts
from
phe-
nomena
those
regularities
that
underpin
the
form
they
adopt, very
much in
keeping
with
Weber's
(1964)
use of
the ideal
type.
The
I-Space, therefore,
takes the
artic-
ulation and
sharing
of
experience
to
be
a
joint product
of
codification and
abstraction,
the twin
poles
of a structur-
ation
process through
which a
world
is first
created and
then
objectified (Giddens 1984).
Codification involves the
assignment
of data to cate-
gories-i.e.,
the
giving
of
form
or
formalization.
A
phe-
nomenon is well codified when the basis of
assignment
is clear
and
it can
be
performed
speedily
and
unproble-
matically-i.e.,
when black is black and
white
is
white
and no shades of
grey
emerge
to
cloud the
judgment.
Abstraction, by contrast, involves a reduction
in the
number of categories to which data needs to be assigned
for
a
phenomenon to
be
apprehended-i.e.,
it
involves a
discernment of the structures that underpin phenomena.
These structuresare multiple and often contradictory,one
of the reasons why the process of structuration has an
irreducibly hypothetical character.
Codification
and abstraction are distinct
strategies
for
economizing on data-processing
efforts.
They are,
how-
ever, mutually reinforcing (see Figure 1). While codifi-
cation-the giving of form to phenomena and catego-
ries-reduces the quantity of data that needs to be
processed in order to assign a given phenomenon to ap-
propriatecategories, abstraction saves on data processing
by reducing the number of categories that need to be con-
sidered
in
the
first
place-i.e., it facilitates the discern-
ment of structure.Both codification and
abstraction
have
the effect of
reducing
the
complexity
of
data-processing
tasks. Mapping Perrow's (1970) two-dimensional frame-
work for analyzing task complexity onto our two dimen-
sions
of codification and
abstraction
makes this
apparent
(see Figure 2).
We can establish an
equivalence
between
Perrow's dimensions
of
task complexity and our own as
follows:
The
Codification Dimension
Few Exceptions
=
Codified-i.e.,
a
speedy assign-
ment of
phenomena
to
categories implies
that the task is
routinizeable and has few
exceptions.
Many Exceptions
=
Uncodified-i.e.,
a slow
assign-
ment
of
phenomena
to
categories implies
that the task has
too
many exceptions
to be
easily
routinizable.
TheAbstraction Dimension
Understood
=
Abstract-i.e.,
one
apprehends
the
structurethat underlies
a
given phenomenon.
Figure
1
Structuring
Information
Codified
Uncodifled
Concrete Abstract
ORGANIZATION CIENCE/Vol. 10, No. 3,
May-June
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MAX
BOISOT AND JOHN CHILD
Organizations s AdaptiveSystems
Figure 2 Locating
Perrow's Typology in the Framework
Few Exceptions
a) Perrows Typology
Many Exceptions
Not Understood Understood
Codified
Few
Exceptions
MINIMUM
COMPLEXITY
Not Understood Understood b) Perrow's Typology in our Framework
MAXIMUM
COMPLEXITY
Uncodified
Many
Exceptions
Concrete
Abstract
Not
understood
=
Concrete-i.e., one does not
appre-
hend the
structurehatunderliesa
given phenomenon.
In
line with the
propositions hat we
earlier
derived
from
theC-Space, he
I-Space
takesthecodification
nd
abstraction f data o facilitate ts
sharing
among
a
popu-
lation of data-processing gents. Populationsof data-
processing gents,
uitably
defined,
make
up
the
diffusion
dimensionof
Figure
3.
Through
what ransactional
truc-
turesthese interact
with each
other
will
be
partlydeter-
mined
by
the
way
thatdataflows
along
the
diffusion
di-
mension.
Transactionaltructures
re
n
fact
implicit
n
Perrow'
typology,structureshat affect
the natureof
connections
possible
among
he
coupled
agents
thatmake
up
the
dif-
fusion
dimensionof the I-Space.The Diffusion
dimen-
sion
allows us to
specify
the
percentage
f
agents
sharing
a
given item of
data. The question that
might
then
be
asked is how
does such
sharing
of data affect the
inter-
actionamongagents?Althoughwe maywish to interpret
the
question
at the level of
social
systems,
the
issue
of
how
interactions
mong
data-processinggents
givesrise
to stable
organized
patterns urnsout
to be a general
one
and can be
addressed
ndependently
f a
given
level
or
area
of
application.
Stable nteraction
atterns
n
neural
networks,
or
example,
may
be the result of
Hebbian
learning Hebb
1949), a process n
which the
strength f
Figure 3 The Diffusion Curve
in the
I-Space
ABSTRAC
T
DIFFUSED
CONCRETE
UNDIFFUSED
connections
etweendata
processing
nodes-at
the
social
level we may call them agents-is a functionof (a)cou-
pling frequency
and
(b) coupling
ime.
In
sum,
n the
I-Space,
codification
ndabstraction
re
mutually reinforcing
activities and
both, working
to-
gether,
facilitate
he
process
of diffusion.
The curve of
Figure
3 thus
establishes
n
a
schematic orm he
founding
proposition
or our
analysis,namely,
hatcodification nd
abstraction
ncrease
he number f
data-processinggents
240
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MAX BOISOT AND JOHN CHILD Organizations as Adaptive Systems
that can be reached,
per unit of time, with a given mes-
sage. The reason s intuitivelyobvious.
Codification
nd
abstraction educe
an agent'sdata-processingoad by
ex-
tracting nformation-about
form and structure-from
data.
Messages
that
are codifiedand abstract re thus
n-
herently aster
to encode and transmit han those
which
arenot. Whether uchmessages
areeffectivelydealtwith
subsequently
y recipientsdepends
on how far they re-
quirea
sharedcontext for their
interpretationShannon
and
Weaver
1949,
Weick
1995).
The
I-Space
thus relates the flow of knowledge
and
informationwithina social system
to the structure f the
data hatact as
their
substrate.Clearly,
he characteristics
of such flows will condition he interactionshatarepos-
sible between agents.
Both the speed and frequencyof
interactionwill
reflect the time and effort required
or
transactionally
elevantknowledge o flow. Figure
4
lo-
cates
four nstitutionalized
ransactionaltructuresn the
I-Space as a functionof the knowledge lows thatchar-
acterizes hem.The cultural haracteristicsf thesetrans-
actional tructures re
summarized
n Table 1.
Our earlier
hypotheses(Boisot
and
Child 1996) sug-
gestedthat there had to be a goodnessof
fit
between
a
culture's
preferred
pproach
o
knowledge
lows andthe
transactionaltructureshat t madeuse
of. We examined
China'sattempt
at
modernizing
rom this
perspective,
noting that
the
country
could
plausibly
be interpreteds
modernizing
n
the lower regions
of the
C-Space.
This
entaileda decentralizationrom fiefs to clans
in
the con-
text of
modernization.
We called the
resulting
cultural
order Network
Capitalism.
We
suggested
hatNetwork
and MarketCapitalismeflect wo distinctwaysin which
Chinese
and
Westerncultures
espectively
deal with the
challenge
of
complexity.
Ourbelief
is that market
api-
talismreflectsa cultural
reference
or complexity
educ-
tion and
thatnetwork
apitalism
s more
strongly
attuned
to
complexityabsorption.
To progress
he discussion,however,
we first need to
explore
how
complexitymight
best be
interpreted
n the
I-Space.We turn o this next
with
reference o the work
of
complexity
heorists.
Complexityin the I-Space
We can
identify
two
quite
different
yet complementary
approaches
o
complexity.
The
first,
associated
with
the
work
of
Kolgomorov
1965)
and Chaitin
1974),
origi-
nates
n the
theory
of
computation
nd
goes by
the
name
of
Algorithmic
Information Complexity
or
AIC.
It mea-
sures
complexity
as
a functionof the
shortest
rogramme
that
will
describe
a
task or a
phenomenon.
Given that
n
Figure
4
Institutions
in the
I-Space
*
Mark
* Bureaucraies_
CODIFIED
ABSTRACT
DIFFUSED
CONCRETE
UNDIFFUSED
the absenceof compressible
egularities,he shortest
ro-
grammes coterminouswiththe phenomenatself, Gell-
Man,
amongothers,has observed hat
AIC equates om-
plexity with randomness.
He suggests nsteada measure
which
he labels effective complexity (Gell-Mann
1995)
and thatequatescomplexity
with the size of the shortest
programme
hatdescribes he regularities
n
a given
phe-
nomenon. The second approach
o complexity
draws
from
biology
and studiesof artificial
ife (Holland1975,
Kauffman
1993,
Langton1992, Ray
1992).
It defines
complexity
n termsof the
density
and variability
f in-
teractions hat take
place
among coupledagents (Varela
et
al.
1991).
The two
approaches omplement
ach
other
in the sense thatthe first ocuses on the
contentof infor-
mation lowsamongagentsand the secondon the struc-
ture of the interactions hat such
flows allow
among
agents.
The
first,
n effect, measures
ognitivecomplex-
ity,
whereas he second
measureswhat we
might
call
re-
lational
complexity.
If
we now
try
to
map
hesetwo measures
f
complexity
on to
the
I-Space,
t becomes clear
that
the
codification
and abstraction
imensionsof the
space
offer a
measure
of
cognitivecomplexity,
whereas
the diffusion dimen-
sion,
through
he
transactional
tructures
hat it
engen-
ders,
allows us to capture
relational
complexity.
Rela-
tional
complexity
is best
understood
hrough
a brief
overviewof the
work of Stuart
Kauffman.
Kauffman, uildingontheworkof Wright 1931),con-
structs itness andscapes-i.e., any
well-defined
roperty
in its distribution
cross
an
ensemble-using
what he
terms NK Boolean
networks,
hat
is,
nodes interlinked
with
varying degrees
of
density.
Boolean networks
are
nonequilibrium
pen thermodynamic
ystems.
In such
networks,
N
refers
to
the
number
of
parts
n
the
system
under
consideration-genes
in a
genotype,
amino acids
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MAX BOISOT AND JOHN CHILD Organizations as Adaptive Systems
Table
1
Institutions
in
the
I-Space
Undiffused Information
Diffused Information
Codified Information
Bureaucracies Markets
*
Informationdiffusion limited and under central control
*
Informationwidely diffused, no control
*
Relationships impersonal and hierarchical
*
Relationships impersonal and competitive
*
Submission to superordinate goals
*
No superordinate goals-each one for himself
*
Hierarchical coordination
*
Horizontal coordination through self-regulation
*
No
necessity to
share values
and beliefs
*
No
necessity
to
share values and beliefs
Uncodified Information
Fiefs Clans
*
Informationdiffusion
limited
by
lack of
codification
to
*
Information s
diffused but still
limited
by
lack
of codification to
face-to-face relationship
face-to-face
relationships
*
Relationships personal and hierarchical (feudal/charismatic)
*
Relationships personal but
nonhierarchical
*
Submission to
superordinate goals
* Goals are
shared
through
a
process
of
negotiation
*
Hierarchical coordination
*
Horizontal
coordination through negotiation
* Necessity to share values and beliefs
*
Necessity to share values and beliefs
in a protein, etc. Each part makes a fitness contribution
which depends upon that part and on
K
other
parts among
the
N. In
effect,
K reflects how
richly
cross-coupled the
system is. A geneticist
would
say that
it measures the
richness of epistatic interactions among system compo-
nents (Kauffman 1993). With K
=
0
for example, there
are
no
epistatic interactions. With
K = N - 1, on the
other hand, each node
in the
network
is
epistatically af-
fected by every other
node and
we obtain
the largest value
for K.
The
behaviour
of the links between nodes can
be
tuned
by employing a control parameter,P.
In
this way they
can be made to exhibit order, chaos, or a phase transition
between those
two states that is labelled the
edge
of
chaos. It is in this phase transition that complex behav-
iour emerges. If,
for
example,
we let P be the fractionof
the
2K
positions
in
the
Boolean function with either
a
1
response or a
0
response, whichever is the larger fraction,
P will
range
from 0.5 to
1.0.
The deviation
of
P
above
0.5 then measures
the internal
homogeneity
of
the
Boolean function.
The critical
value,
PC,
dentifies the lo-
cus of a
phase
transition
in the
behaviour
of a
dynamical
system. In our scheme, a high value for P-i.e., close to
1.0-reflects
a
high degree
of
stability
and structure and
a low
level
of AIC. It thus
corresponds
to
an
information
environment
high
in
codification
and
abstraction.
Low
P,
by contrast,
that
is,
P close to
0.5,
is
low in
stability
and
structure
and
high
in AIC.
It
corresponds
to
an informa-
tion environment
low in codification and
abstraction.
P,
therefore is a
reflection of
cognitive complexity.
The
higher the value
of P, the lower the level of cognitive
complexity.
In
discussing his Boolean
networks, Kauffman ob-
serves:
As systems
with
many parts increase both the
number of these
parts
and the
richness of interactions
among the parts, it is typ-
ical that the number of conflicting
design constraints among the
parts increases
rapidly. These conflicting constraints imply
that
optimization can attain
only
ever
poorer compromises.
Further,
it is clear that conflicting constraints are a very general limit in
adaptive
evolution. Each part
of an
adaptive system costs some-
thing.
For
example,
additional
genes
and
proteins require
met-
abolic
energy (Kauffman 1993, pp. 53-54).
Beyond a certain
point,
Kauffman
points out, total costs
will
exceed total fitness, and
increasing either N or K will
no
longer
be
profitable.
The limits of
complexity
have
been attained.
Beyond the point the
system undergoes
a
phase
transition
into the chaotic regime.
A
high
value
for our control
parameter, P, however,
allows
higher
values to be achieved for
K or N before a
phase
transition occurs than do lower
values of P. An-
otherway
of
saying
this is that there is a
trade-off between
cognitive and relationalcomplexity. A low degree of cog-
nitive
complexity
allows one to handle
a
higher
degree
of
relational
complexity
and vice versa
without under-
going
a
phase
transition
into chaos. In
other
words,
cod-
ification and
abstraction facilitate the orderly
processing
of information
among larger
numbers of
interactingper-
sons.
Table 2
presents
the
complexity
characteristics of our
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MAX BOISOT
AND
JOHN
CHILD
Organizations as
Adaptive Systems
Table
2
The
Complexity
of
Transactional
Structures
Overall
Relational
Cognitive
Transactional
Complexity
Complexity
Complexity
Markets High (High K) Low (High P) Medium
Bureaucracies
Low
(Low
K)
Low
(High P)
Low
Fiefs
Low
(Low K)
High (Low
P)
Medium
Clans
Medium
(Medium
K)
High (Low
P)
High
four
transactional
structures,
relating
these to K and P
in
Kauffman's
scheme. N
specifies the number
of
agents to
be located in a
given
I-Space
and hence
establishes the
size
of
its
diffusion
dimension.
It defines
the
size of
the
agent
population
on
which K and P
will
operate and it is
set
by
identifying those
agents
who
might
be
candidates
for involvement in transactionalarrangements.Once an
I-Space has
been
created,
however,
N
becomes
fixed.
In
Table
2, we
take
markets
to be
characterized
by
high
K,
bureaucraciesand fiefs
by low
K,
and
clans
by medium
K.
It
might
at
first
sight
seem
surprising
to
impute
a
low
K to
bureaucracies.
After
all,
rational-legal
bureaucracies
are
associated with
an
increase in
the size of
organiza-
tions.
While this is
true,
it is
also
the case
that
by
hier-
archically
ordering
reporting
relationships, bureaucracies
severely restrict the
number of
agents that one
is
required
to
interact
with:
one
superior and
usually
a
few
subordi-
nates.
Having
established
some initial
correspondence be-
tween Kauffman's variables and our own, we can now
build
on
his
analysis
to
tentively partition the
I-Space into
the
three
phases
that he
identifies
namely,
the
Ordered,
the
Complex,
and
the
Chaotic.
Since,
in
contrast to
Kauffman, our
partitioningexercise is
not
derived
from
a
series of
simulations or
from
the use
of
Boolean
net-
works, it
must of
necessity remain
schematic. It is
shown
in
Figure 5.
Although it
is not
possible
to
establish
more than
an
approximate
correspondence
between the
location
of
the
three
phases
and those
of the
transactional
structures
of
Figure
4,
it
is at
least
intuitively
plausible to
argue
that
bureaucracies
seek out
the
stabilityof the
ordered
regime
andthatthe otherthreetransactional ormsrepresentthree
distinct
responses to
different
mixes of
cognitive and re-
lational
complexity.
Markets,
for
example,
have
banished
cognitive
complexity by
codifying
everything into an
ab-
stract set
of
prices but
have to
deal
with the
relational
complexity
of
large
numbers
bargaining
(Williamson
1975,
Hayek
1945).
Interactions
between
players
may be
simple (high
P)
but
codified
and
abstract
information
Figure 5
Phase
Transitions
in the
I-Space
CODI'MD
E
REG
9 Bur.atucrscle
CM4O1IC
REGIME
UNCOOPDIF
DIFUSED
flows
favours
epistatic
nteractions n a
large
scale
(high
K). Theassumption f self-regulation ives thistransac-
tional form
homeostatic
tability.
Fiefs, in
contrast o
markets,deal
with
small
numbers
(low
K), and
usuallyon
the
basis of
loyalty
anda
complex
set of
reciprocal
bligations.They
do
so,
however,
n an
environmentn
which
cognitive
complexity s high
(low
P).
Finally,
clans
appear
o
exhibit
the
highest
level of
complexity
of
all
our
transactional
tructures.
Although
the
numbers
nvolvedare
smaller han
hose
required or
efficient
markets
hey
are
higherthan in
fiefs
(medium
K).Cognitive
omplexity,
however,
s
high (low
P).
Here,
overall
transactional
omplexity
is
not
the
product of
largenumbersbargaining ut of a complexset of inter-
actions
among
a
sizeable
numberof
players.When
the
numbers
hat
participate n
clan
transactions
o
up, or
cognitive
andrelational
omplexity
are
increased,
lans
are
prone
to
slip into
chaotic
behaviour.For
that
reason
theymustbe
considered
n
edgeof
chaos
phenomenon
(Langton
1992).
Cultures,
ike
individuals,
ary
in
the
extent to
which
they
need
order
and
stability
n their
commercewith
re-
ality (Hofstede
1980, Boisot
1995). The
seeking
of
order
and
stabilitycan be
interpreted
n
the
I-Space
as a
move
from
whatever
region
one finds
oneself in
towards
he
point
0 of
Figure 5
(top
left-hand
corner).Point 0
thus
acts as an attractorn the I-Spaceandoffers an escape
from
chaos.
But how
far do
individualsor
cultures
actu-
ally
want
to
escape?For
instance,
do
theywantto
move
wholesale
nto the
ordered
egime?
Or
might
they
settle
for
the
excitementsof
the
complex
regime?Much
will
depend
on
how
they
feel
about
complexityand
the un-
certainty
hat
it creates.
Attractorsother
than
point
0
might
be on
offer.
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MAX BOISOT
AND JOHN
CHILD Organizations as Adaptive Systems
Point 0 in the orderedregime is a world in which events
are predictable and
from
which uncertainty has been ban-
ished. It is the preferred location of those who seek tran-
quility, hence its attractiveness to monopolists
for whom
the best of all monopoly profits is a quiet life (Hicks
1935, p. 8). The complex regime is more difficultto man-
age, with the degree of difficulty rising in line
with
the
level
of
complexity. Here, the
world
is perceived
as a
discernible set of alternative possibilities that
can be re-
sponded to but which require a repertoire of flexible re-
sponses. Contingencies
can
be
managed
but
rarely opti-
mally.
In
the
chaotic
regime, nothing
stable can be
discerned and hence
nothing
can be
managed.
It can
only
be allowed for in the hope thatorganized complexity
will
emerge
from chaotic
processes
themselves.
Our discussion
of
Kauffman
suggests
two
ways
of
moving
towards
point
0
in
the
I-Space,
whether from the
chaotic towards the
complex regime,
or
from the
complex
towards the orderedregime:
(1) Reduce cognitive complexity through
acts of cod-
ification and abstraction-i.e.,
aim for
a
high
P.
(2) Reduce relational complexity by keeping
the num-
bers
of
transacting agents down-i.e.,
aim for
a low
K.
Of
course,
it
has
to
be
recognized
that
to
the extent that
relational complexity is a productof the density
of
inter-
action
among agents
as
well as of
the
number
of
partici-
pating agents,
it will be
reduced
both
by keeping cogni-
tive
complexity down-i.e., establishing
codified and
abstract rules of interaction among agents-as
well as
by
limiting the number of agents that
can
interact.
Both
strategies, however,
involve
complexity
reduc-
tion. The first strategymoves one up the I-space towards
greater codification
and
abstraction.
It allows one to
deal
with
large
numbers but
only by keeping
transactions
cog-
nitively simple.
Where the numbers
are
limited
we
find
ourselves
in
the ordered
regimes
characteristicof bureau-
cracies;
where
numbers
are not
limited
we
find
ourselves
in the medium
complex regimes
characteristic of market
processes.
The
second strategy moves one towards
the left
in
the
I-Space by reducing
the number of
agents
that
one has to
deal with. Where
interactions among agents
are
cogni-
tively simple
we find
ourselves
once more in the ordered
regime
of bureaucracies.
Where, however, they
are
cog-
nitively complex, we find ourselves in the medium com-
plex regime characteristic of fiefs.
Yet
as
we have
already argued, reducing complexity
is
only
one of the
ways
available to
us for
dealing
with it.
For it can also be absorbed. This is the transactionalstrat-
egy
we
associate
with a clan order. It can
only
function
under conditions
of trust
and shared values
where
the
risks associated
with
uncertainty
and
ambiguity
can
be
pooled
among agents and where mutual adjustments are
possible.
Clans are higher in entropy production than either the
ordered regime of
bureaucracies
or
the complex regimes
of markets or fiefs-that is, they consume more time and
social resources in order to maintainthemselves in a state
of dynamic equilibrium-but in
compensation, they
offer
a
greater potential
for
adaptation
and renewal.
Ourgeneral
proposition
is that
culturesvary
in
how far
they aim to reduce
complexity as
a
whole, but to the ex-
tent that
they
do so
they
will
reduce
cognitive
and rela-
tional
complexity
to
different degrees. Cultures whose
development
trajectories
have allowed
them
to
build up
an
institutional capacity in the
upper regions
of
the
I-
Space, for example, are more likely to aim for a
reduction
in
cognitive
complexity
and to transact in
large numbers
either
through
bureaucracies or
markets.
By contrast,
cul-
tures
whose institutional investments aremainly confined
to the lower regions of the I-Space may have little choice
but to hold
cognitive complexity constant
and to
reduce
relational
complexity by keeping the
numbers
down to
what can be
managed
in
face-to-face situations.
Clearly,
relational complexity will
be lower
in fiefs than in clans
so
that
in the latter case more
complexity
will
need to
be
absorbed.
Handling Complexity-the
Case
of China
Applying
Kauffman's
parameters,
China is
characterized
by
a
low
P,
a
high N,
and a level of
K that
is
high within
the society's constituentunits, but low (albeit now rising)
between those units.
Low
P
In
China,
social
order
in the
past
has been
precarious
and
unpredictable,
due in
large
measure to the
problem
of
establishing
an
adequate system
of
governance
within
a
country highly
differentiated
by
geography, language,
and
local identities. The
periodic
breakdown and
frequent
arbitrariness of central
authority,
and the
lack
of clear
rights generated considerable
uncertainty.
While the im-
perial bureaucracy
did not
normally
extend
down
beyond
district
capitals,
the
state
could
nevertheless
arbitrarily
intervene in people's lives for financial or military pur-
poses.
As
Fukuyama (1995) notes,
the Chinese
state
pro-
vided
few social services
in
return
for its
demands,
de-
spite
the
injunctions
of Confucius
concerning
the
obligations
of the
paternalistic Emperor:
In
traditional
China,
there were
no
established
property rights.
Through
much
of
Chinese
history,
taxation
was
highly arbitrary;
the state
subcontracted tax collection to local officials or tax
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BOISOT AND
JOHN CHILD
Organizations as Adaptive
Systems
farmers,
who were free to set the level of
taxation at whatever
the local
population could endure.
Peasants could also be
drafted
arbitrarily
or
militaryduty or to
work
on
public works
projects
(Fukuyama 1995, p.
87).
The threat of
disorder, and
consequential
massive un-
certainty,arose from a combination of naturaland official
capriciousness. For
example, Seagrave, in his
study
of
the
Overseas
Chinese,
notes how mass
emigrations from
South
China were
caused by invasion
from the North,
imperial repression and
taxation,
and
natural calamities
both local and in
the North. The
latter led to
furtherpres-
sures from a
movement of
population southwards. The
result, as Seagrave
put it, was that to
the ordinary Chi-
nese,... chaos is
always just
around the corner
(Seagrave
1995, p. 183).
The
institutional
environment has provided
few guar-
antees
for
the
members of
Chinese society. Historically,
the Chinese
have
not been protected
by
a
legal
system
that was independent of the state and
supreme
in its
own
right. In the
absence of a
codified commercial
law, mer-
chants and
producers were at
the mercy of a system in
which
imperial officials and their
acolytes could
exercise
arbitrary
power through taxes,
licensing fees,
and restric-
tions on trade and
travel.
Even
today, despite continued
legal reform
since 1979 which
has begun to evolve a dis-
tinct
body
of
legal
rules and
institutions,
evidence
sug-
gests that the
law
in
China
remains a tool of
state ad-
ministration
and
always
within close
reach
of the
Chinese
Communist
Party (Lubman
1995, p.
2).
Thus little
pro-
gress has been
made
in
the
effective ability
of
China's
laws to provide a means of controlling official arbitrari-
ness
(ibid., p. 11).
Nor
has
China, even
today, developed
a
strong
civil
society
to
constrain,
and hence
modulate,
the
power
of
the
state
(Nevitt,
1996).
High
N
China
as
a
socioeconomic
system
displays
a
high
level
of
Kaufmann's
N.
It
consists of
many
and differentiatedele-
ments. These are
today
manifest
in
the
presence
of
mul-
tiple
business
systems
(state-controlled,
collective,
and
private, each with
different
governance systems and lev-
els of
marketization), many
regions
which
contrast in
wealth, education,
and
culture,
different
provincial and
other local authorities to which much power has now de-
volved,
and
significant
generational
differences
(Child
1999a). Under the new wave
of economic
reform,
state-
owned
enterprises
are
further
differentiating
the nature of
their
governance systems (Child
1999b).
Its internal dif-
ferentiation lends
China the character of a
complex
cel-
lular
society.
Levels of
K
The
cellular nature of China's society gives rise
to ten-
sions within its governance system which in
turn com-
pound the
complexity
of the
system.
The
society
is char-
acterized by
a
high N but low levels of
K between its
constituent units,
a
configuration
which
would of itself
be conducive to a hierarchicalmode of coordination from
the
centre.
Indeed,
Confucian
philosophy legitimized
the
expectation that government should
play an intervention-
ist role in China. It
has, however, always proved
a prob-
lem to coordinate the many
units in the system from the
centre. In the past fifty years,
attempts to do so have
shifted
dramatically,
indeed
sometimes
violently,
from
mechanical
coordination
via
central
planning
to the use
of
personal charisma
by
the
Party Chairman.
The
variable
and uncertain nature of central
authority
has
encouraged
local
powers to make up the
deficiency, and
in
turn strong
local
loyalties
have added
to the
problems
of
securing
effective central governance.
Thus,
levels of
K
are high within the
system's constit-
uent
units,
especially
within local
communities which
have
close-knit networks
embracing administrative, po-
litical,
and
business groups. This combinationcreates ten-
sions between the central and
local levels
in
the
gover-
nance system, and
consequent ambiguities
about their
respective jurisdictions. While laws and
regulations
are
formulated
centrally,
coordination between national
gov-
ernment bodies is
often ineffective
and,
in
addition,
the
laws
and
regulations
are administered
locally.
This
can
give rise to considerable
ambiguityas to who is the
gov-
ernment and behavioural
inconsistencies between dif-
ferent agencies and localities.
Ambiguity
about
governmentaljurisdictions
and
pow-
ers
contributes to
a
low level
of
stability
within the Chi-
nese
system
and hence the low
level
of P
already
noted.
The form of
complexity
in China
(low
overall K com-
bined with
high
local
K
and low
P) poses
far
greater
dif-
ficulties for
those
engaged
in economic
relationships,
than
does a
high
N
per
se. For it describes a situationin which
economic
governance
tends to be
organized
through
in-
tensive relations coordinated
according
to
implicit
rules-in other
words,
at the lower levels of the
I-Space.
Despite the tensions with the
centre,
much of
this socio-
economic
coordination in
present-day
China is
in the
hands of local government and Partyofficials. This is not
to
say,
of
course,
that
any
kind of national
plan
is
being
imposed-indeed,
the
contrary
tends to be true because
of
the
local variation
that this system creates.
The
ability
of local
authorities
to
exercise
significant power
stems in
large part
from the
high
levels of
K
within local com-
munities and the core role
that authorities
play
in them
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even
in relation to nonstate
enterprises. Indeed,
the
prop-
erty rights they enjoy over Chinese enterprises remain
considerable. Despite the objectives
of the economic re-
form, many state and collective enterprises
are
beholden
to governmental bodies (at
the local level with the ex-
ception of certain strategic sectors), especially for work-
ing capital
and the enforcement of transactions. There are
fears that the
current
corporate governance
reforms will
leave governmental agencies largely in control even of
smaller enterprises, despite the declared aim
of
the re-
forms to separate governmental from business functions
(Child 1999b). This dependence on government can ex-
tend to
the
joint
ventures
that
Chinese
enterprises
form
with multinational companies.
The cognitive complexity (low P) which is caused by
ambiguities
as to
the
locus of
power
and initiative in the
Chinese
system,
is added to
by
the lack
of
transparency
of
many
Chinese laws and/or their uncertain
enforcement,
as
is
the case with intellectual property rights. Local gov-
ernmentalagencies have powers to interpretregulations,
issue licences, and impose taxes,
which furnish
ample
scope
for
negotiation
and
corruption.
Even
some national
regulations
and
taxes
have been
imposed retrospectively.
There also continues to be
a
shortage
of two
key
busi-
ness
resources, namely
domestic
working capital (much
of
it
being administratively
redirected
to
propping up
ail-
ing state-owned enterprises),
and
high quality,
well-
trained
managers.
When neither the
availability
of work-
ing capital,
nor
the loyalty
of
key
local
managers,
can be
taken
for
granted,
further elements
of
uncertainty
are in-
jected into the business environment. Infrastructuralim-
itations, especially
in
the transportation
of
goods,
add an-
other source of
uncertainty.
Each of these uncertainties
increases the temptation
for
local agents to act opportun-
istically-for example,
to
renege
on
an
employment
or
supply
contract in order to take
advantage
of available
economic rents.
The wide
range
of
unethical behaviours which the
Chi-
nese
categorize
as
corruption
not
only
create
great
un-
certainty
in business
relationships,
but also most under-
mine
the development
of
trust. The problemis recognized
at the
highest
level. Former
premier
Li
Peng, addressing
the National
People's Congress
in March
1994
stated that
the struggle against corruption is a matter of life and
death for the
nation
(quoted by
McDonald
1995, p. 175).
There are several
specific practices
which
are
quite
com-
mon,
and which are
particularly
nimical
to
the establish-
ment of trust. One
is
product piracy, including
the
illegal
use of their
foreign partners'
brand names
by
Chinese
enterprises.
The chief
executive
of a
global
U.S.
house-
hold
goods company
told the second author that this was
the
single greatest problem
his firm
faced in China. An-
other is
embezzlement,
a
problem
which
has led many
foreign companies
to
insist that
they
control the
appoint-
ment
of chief
financial officers for their China
joint ven-
tures.
A third
practice, and
probably
the most
common,
is thatof bribery.Bribery, of course, implies the threat of
non-cooperation or even reneging on
agreements
if
side-
payments
are not made.
The low level of P in the
Chinese context generates
high levels of cognitive complexity and
uncertainty. This
poses considerable
problems
for local
Chinesepeople, not
just
foreign investors.
Historically,
the
Chinese have
sought
to
adapt
to these
contingencies by
forming
rela-
tional
networks with
lower numbers but
denser
interper-
sonal links than those
typical
of
Western countries. This
represents
a cultural
preference for
absorption,
rather han
reduction, as the means for
dealing with the nature of
complexity
in
China.
The
reliance on dense
interpersonal
links, in which friendship,identity, andtrustoverlay eco-
nomic
transactions, tends by its nature
to
exclude non-
Chinese
participants.
These
specific relationships, based on trust and
implicit
(noncodified)
norms,
fall
into two broad
categories.
The
firstcomprises the
extended family, and to a lesser
degree
relationships
stemming
from
a
common formative
expe-
rience in
hometown
and
school,
all of
which
provide
for
group loyalty and shared
identity. This trust s based
upon
blood and
upbringing,
and
it
often takes on fieflike
qual-
ities. The
foundations
of
trust within these
close social
units
are
those of identification and
affect. It
is
found in
the Chinese
family business,
in
both mainland and over-
seas Chinese communities. It has also provided the basis
on which the directors of
state
enterprises agreed
to form
horizontal
groups,
and on which
many joint ventures be-
tween PRC
enterprises
and overseas
Chinese investors
have
been
established.
The second
category
is
the
network,
which
can some-
times
be
quite extensive, taking
on
clanlike
qualities.
Boisot and Child
(1996) suggested
that the
clan
system
of social
governance
has
been the
appropriate
institu-
tional structure to
adopt
for
economic transactions in
China. Trust within the clanlike
networks
is
based on
what
the
Chinese know as
guanxi. Guanxi refers to the
credit which
a
person
or
a
group
has with
others,
based
on the giving of assistance or favours, or deriving from
personal recommendations. It is
significant
within work
units,
and even more so for
the
development
of
interor-
ganizational
relations in which
the actors have no
other
foundation on which to
establish trust in a
society
where
institutional
guarantees
and
protection
are
weak. There
is
a risk involved in
offering
the
favours
through
which it
is
hoped
to build
up guanxi,
and
the
main
guarantee
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against lack of reciprocity lies in the strong social
norms
by
which the
acceptance
of favours
places
an
obligation
upon
the
recipient.
Personal networks are therefore particularly
significant
modes of economic
transacting
in
China because
of
the
weak
institutional sanctions against reneging on conmit-
ments. Both shared social identityandguanxi can provide
the foundations for
long-standing relationships
which
govern business transactions
and
upon
which
transac-
tional networks are built. To an
important extent,
trans-
actions within the Chinese business system are governed
by
the
relatively
tacit norms and
expectations
which ac-
company
these
trust-based relationships, rather than by
the more codified rules
characteristic
of
transactions
reg-
ulated
either by hierarchical rules
or
by laws of contract
applied
to market
dealings (Boisot
and Child
1996).
This
is the case even within the ostensibly bureaucratic
PRC
state-owned enterprise, where typically key nonns
of
con-
duct remain
implicit
and
where strong fieflike loyalties
exist around
key officeholders (Child 1994).
Thus, whereas we might characterize the Western
or-
ganizational
context as
exhibiting
a low
degree
of
cog-
nitive
complexity
and a
high degree
of
market-based re-
lational
complexity,
the
Chinese organizational context
displays
a
high degree
of
cognitive complexity
and mod-
erate levels of clan-based relational
complexity.
These
differences in
organizational context,
we would
hypoth-
esize,
will be reflected in a
cultural preference by Western
organizations
on
the one hand for
deploying cognitive
strategies that reduce complexity, and a cultural
prefer-
ence
by
Chinese
organizations
on the other hand
for
de-
ploying relational strategies that absorb
complexity.
Two Approaches to Complexity
Management:
Western
Firms
in
China
It
is
clearly
not
easy
for the
managers
of a
foreign
com-
pany
to enter into these close-knit Chinese
relationships,
but without some connection to them it
may
also be dif-
ficult for such
managers
to be able to make
good
sense
of
the
cognitively complex implicit understandings
within
the
system.
It is
virtually impossible
for Western-
ers to
enter
into
the
first
relational
category
based
on
fam-
ily
or
other groupings with
a
strong shared
identity.
It
may, however, be possible though still difficult, for them
to
gain acceptance
as trusted
partners
of somewhat looser
clanlike networks.
This
presents
the
foreign
firm with two alternative
ap-
proaches
towards
handling
the
high complexity
and weak
institutional context in China. The two approaches reflect
the fact that when faced with the
challenge
of
operating
within a system located in
an unfamiliar part of the I-
Space, organizations can endeavour either to maintain
their familiar mode of handling complexity and enact the
environment to permit this, or
to adapt their mode of com-
plexity handling to the local situation with the assistance
of local partners.The first approach s thus familiar to the
firm, but not to the context. The second approach is un-
familiar to the firm,
but
culturally
more attuned to
the
context. These contrasting approaches reflect, according
to our argument, fundamental differences
in
the
nature of
the
complexity
that
respectively
confronts China and
Western countries.
It
will become evident
that
there
is
some parallel between the two approaches and, respec-
tively, the
K'
and
r
strategies identified
in
biogeo-
graphical and evolutionary models. Put simply, the
K-
strategy involves
a focused efficient investment in a given
reproductive attempt and is suited to a slowly-changing,
predictable environment,
while the
r-strategy
involves
many reproductive attempts
spread
over a
range
of
possible environmental situations. The latter are less ef-
ficient in
themselves,
but
offer a
greater
chance
of
species
survival in
complex,
unpredictable environments
(MacArthur and
Wilson
1967,
Hannan and Freeman
1989).
The
first alternative is an
attempt to reduce cognitive
complexity through imposing
familiar routines and stan-
dards
upon
business
in China.
It
approximates
to what
cross-cultural theorists term
a
domination
strategy
(Tung 1993). This imposition attempts to replicate the
structured articulation of
information that in Western
countries
is assisted
by supporting
institutions.
It is
pur-
sued
through
a combination
of
complementary
external
and internalactions. The external approach s to enact the
environment to reduce its
complexity through
measures
such
as
lobbying foreign governments
to
pressure
China
into
creating
a more codified environment, especially
via
legislation
and
its effective
enforcement, deploying big
corporate guns
to
negotiate
Chinese institutional
toler-
ance of
the
foreign
investor's
intentions,
and
using
the
Chinese need
for
technology
and finance as
bargaining
levers for the introduction of Western
norms. Coca-
Cola's
highly publicized policy
of
contributing
to local
economic
development has,
for
example, generated
con-
siderable
goodwill
and tolerance for its
application
of its
preferred global policies
to
China
(cf.,
Nolan
1995). By
enacting
ratherthan
negotiating
the
environment,
this
ap-
proach
endeavours
to
restrict
involvement in the
system'
s
relational
complexity
and hence favours 100% foreign
ownership
and control over
China
operations.
A
major
element
in the internal
approach
is the
impor-
tation
of standardized
systems (accounting, quality, pro-
duction, HRM,
and
so
forth)
which enforce
predictability
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onto Chinese behaviour and lock the China
venture into
a multinational corporation' global network. MNCs
have, for example, preferred to apply their
own environ-
mental protection standards
n the face of unclear expec-
tations from Chinese law enforcers and the high trans-
action costs of negotiating new or modified standards
(Tsai 1997). Other internal features
in
the complexity-
reducing strategy include the establishment
of control
over personnel selection so as to recruit employees, pref-
erably young people, who are untainted by Chinese
work and institutional norms, and a reliance upon a com-
bination
of
training
and attractive rewards to mould Chi-
nese workplace behaviour (Lu and Bjorkman 1997).
This approachhas been advocated by Western consul-
tants (e.g.,
Meier et al.
1995)
and
management
writers
(e.g.,
Vanhonacker
1997).
It relies
on
the
rapid
establish-
ment of codified structuresand
systems,
and
those
adopt-
ing it are prepared o incur short-termcosts in the process.
One cost is that the control has
to
be
secured
through
a
capital
investment sufficient to secure a
large majority
of
joint
venture
equity
or sole
ownership.
Such control nor-
mally requires
a
heavy presence
of
expatriates
n
the
early
life of the Chinese affiliate,
which
imposes
a heavy
fi-
nancial burden,
and there
can
be considerable
conflict
with local
personnel
as
the
foreign parent company's
structures and practices
are
applied.
The
intention
is
to
replace expatriates with homegrown Chinese managers
who can
run
and accept foreign systems as
soon as they
can
be
found and trained.
There
is some
doubt, however,
whether the early re-
placement of expatriatesis going to be feasible with this
approach.
One
reason is that it bases
cooperative
rela-
tionships between the Chinese and foreign parties almost
entirely upon calculation,
and not on
any
firmer bases of
mutual commitment or trust. As
such,
it is
likely
to en-
gender only
the most basic level
cooperation
between the
partners.
The
primary
basis
of
the
relationship
lies
in the
promise
of
favourable
rewards to the Chinese
partner,
n
terms
of
dividends, employment,
and
technology transfer,
and to individual Chinese employees
in
terms
of
high
levels of
personal
income. There is no doubt that this buys
cooperation, but only up
to a
point
and not on
a
basis of
a
commitment to the
joint enterprise.
It
is
not surprising,
therefore, that many foreign managers complain about
their
partners' instrumental,
even
underhand, attitude to-
wards the
protection
of
resources such as
technology
transfer and brand
equity,
as
well
as
about the
difficulty
of
retaining good Chinese managers.
There is a
danger,
then,
with
this
approach
that order is
purchased
within
the China venture or
subsidiary
but at the
expense
of the
external
certainty
that can
be
secured.
Its advocates
argue
that, given time, learning about external complexity can
be achieved and the
level
of external
entropy correspond-
ingly reduced. Despite the strength with which a com-
plexity reduction, go-it-alone, approach is being ad-
vocated
among foreign companies
in China
(Johnstone
1998), the evidence so far available in terms of the rela-
tive
profitability
of
foreign-invested enterprises
with dif-
ferent levels of foreign control does not unequivocally
supportthe argument (Andersen Consulting 1995, Pan et
al.
1999)
The alternative approach to dealing with the complex-
ity
of
the Chinese system
is
one
of
using local Chinese
capabilities
to
absorb
it. This
requires
an
attempt
to
en-
gage
with relevant clans and
to enter
into
more intensive
relationships (i.e., high relational complexity) with Chi-
nese
partners
and other
significant groups.
This is not
easy,
and
may
take
years
rather than months. Clans are
predicated
on
outcomes
from an
iterated prisoner's di-
lemma
relationship
that
are
in favour of
cooperation
ratherthan defection. Resources are secured fromoutsid-
ers
through opportunistic
behaviour and are used to cross-
subsidize transactions between insiders.
For
transactions
between clan
members,
the shadow of the future is
therefore
very positive
and real
(Axelrod 1984).
How-
ever,
the favourable conditions for
benefiting
from co-
operation
are extended
only to
those who
have become
accepted
as
members
of the
clan. An
outsider,
such as a
foreign
firm in
China,
has to find
ways
of
demonstrating
benefit to
prospective partners
and
their
wider
clans
(i.e.,
social
networks)
so as to
buy
its
way into the clan. For-
eigners choosing cooperation with Chinese partnersbe-
fore demonstrating
that
they
are in an iterated
game
will
tend to
confront
defection as the
preferred
Chinese
op-
tion. This
implies
that
they
have to offer
substantialbene-
fits to their
prospective
Chinese
partners
so
that
the
costs
of defection to
the
latter
are
high,
and
that once accepted
it
is
important
to
maintain the
trust
of the Chinese
party.
Again,
there are both external and
internal routes to
doing
this. The external one
includes the co-opting, on
the basis of
mutual
benefit,
of
Chinese
partners
who have
institutional
influence,
and
allowing
them to handle the
external
complexity
which derives
mainly
from
the
bu-
reaucracy
and its manifestations of
arbitrarybehaviour.
The internal route may comprise several measures. First,
an involvement of
Chinese
managers
in the decision
pro-
cesses
of
joint
ventures
or
subsidiaries, appealing
to
the
venture's
collective
identity
and mutual
benefit
in so
do-
ing. Second, adapting procedures such as personnel ap-
praisal
and
the conduct of
meetings
to suit the local
cul-
tural
context, though retaining reporting systems
which
are
compatible
with those of
the
foreign
investor.
Third,
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developing long-term relationships through frequent
con-
tact
between Chinese and foreign board
members,
a
planned
programme of visits between foreign and
Chi-
nese
executives, relatively lengthy assignments of
foreign
executives to China joint
ventures, and emphasizing the
need for
cultural sensitivity.
All
these positive
relationship-building moves have, nevertheless, to build
on
the perception of clear economic advantage by the
Chinese as well as the
foreign partner.
This second
approach attempts
to
absorb
complexity
in
the Chinese
context by giving primacy to
establishing
a
set
of
enduring relationships
both with