organizations as adaptive systems in complex environments: the case of china

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Organizations as Adaptive Systems in ComplexEnvironments: The Case of ChinaMax Boisot, John Child,

To cite this article:Max Boisot, John Child, (1999) Organizations as Adaptive Systems in Complex Environments: The Case of China. OrganizationScience 10(3):237-252. http://dx.doi.org/10.1287/orsc.10.3.237

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ORGANIZATION SCIENCE/Vol. 10, No. 3, May–June 1999pp. 237–252

Organizations as Adaptive Systems in ComplexEnvironments: The Case of China

Max Boisot • John ChildDepartment of Strategic Management, ESADE, P.O. Box 144, 08870,

Sitges, Barcelona, SpainThe Judge Institute of Management Studies, Cambridge University, Trumpington Street, Cambridge CB2 1AG,

United Kingdom

AbstractThis paper treats organizations as adaptive systems that have tomatch the complexity of their environments. The nature of thiscomplexity 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. Codificationinvolves the assignment of data to categories, thus giving themform. Abstraction involves a reduction in the number of cate-gories to which data needs to be assigned for a phenomenon tobe apprehended. Information is diffused through populations ofdata-processing agents, thus constituting the diffusion dimen-sion. Complexity theorists have identified the stability andstructure of algorithmic information complexity in a way thatcorresponds to levels of codification and abstraction. Theiridentification of system parts and the richness of cross-couplingdraws 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 understand the complexity and actingon 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. Historicalfactors have shaped the nature of complexity in China, givingit very different characteristics than those typical of Westernindustrial countries. Its organizations and other social units havecorrespondingly handled this complexity through a strategy ofabsorption rather than the reduction strategy characteristic ofWestern societies. Western firms operating in China thereforeface a choice between maintaining their norms of complexityreduction or adopting a strategy of complexity absorption thatis more consistent with Chinese culture. The specifics of thesepolicy alternatives are explored, together with their advantagesand disadvantages.

The paper concludes with the outlines of a possible agendafor future research, focusing on the investigation of complexity-

handling modes and the contingencies which may bear uponthe choice between them.(Adaptation; China; Complexity; Organizations)

IntroductionAs a theme for organizational scholars, complexity hasundergone some important transformations in recentyears. It figures in conference headings and, increasingly,in the popular literature as a managerial topic in its ownright (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, Etzioni1961, Perrow 1970, Simon 1969, Burns and Stalker1961). 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 inbiology and in physics, have transformed the subject.Much of the work coming out of research centres such asthe Santa Fe Institute in New Mexico, for example, withits emphasis on emergence and far-from-equilibrium phe-nomena, has radically different implications for how weapproach complex organizational processes than the re-search of three decades ago, concerned as it was then withabberations from stability and predictability.

From the new perspective, organizations are treated asinstances ofadaptive systems (Holland 1975), that is, sys-tems that have to match in a nontrivial way the complex-ity of their environment (Ross Ashby 1954, Wiener1961), either to achieve an appropriate measure of fit withit or to secure for themselves a degree of autonomy with

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MAX BOISOT AND JOHN CHILD Organizations as Adaptive Systems

238 ORGANIZATION SCIENCE/Vol. 10, No. 3, May–June 1999

respect to whatever constraints it might impose (Varelaet al. 1991).

Does the fact that human organizations are also inter-pretative systems (Weick 1995), that they function partlyon 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, theyadapt, if at all, to the complexity as their decision makersperceive and interpret it rather than to any objectivelygiven complexity in their environment. And, given anappropriate set of representational schemata, perceivedcomplexity can often be significantly reduced. Further-more, they also have the capacity to enact some of therepresentations that they construct for themselves, thusmodifying their environment proactively as well as adapt-ing to it (Child 1972, Giddens 1984, Weick 1995). Thejoint effects of interpretation and enactment have in thepast served to distinguish the social from the natural sci-ences (Dilthey 1883/1988, Weber 1964).

The new approach to complexity is tending to blur thatdistinction (Morin 1977). Both types of science viewcomplexity as arising out of the number of elements thatgo 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 looselycoupled than natural systems and thus inherently morecomplex. What do we mean by this? Simply that in theformer case, the interaction between the elements is pri-marily informational rather thanenergetic. The trade-offbetween energy and information is also visible within nat-ural systems themselves. The binding energy between nu-clear particles, for example, is of the order of 140 millionelectronvolts, that between the atoms that make up a mol-ecule is of the order of five million electronvolts, and thatbetween molecules is half an electronvolt. Clearly, thecombinatorial 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 isthus partly a reflection of its combinatorial power and sois its degree of complexity.

Finally, the complexity of the environment that orga-nizations are required to enact or adapt to reflects humancultural activity and level of development. These shapeboth the forces that an organization must respond to aswell as the representations and behavioural dispositionsthrough which the response is channelled.

Much evolutionary theorizing points to systems evolv-ing phylogenetically to handle ever more complexity overtime (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 acquirea more complex internal structure—i.e., eukaryotic cellsemerge from prokaryotic ones. In this way and over time,organisms grow and differentiate internally, acquiring so-phisticated data-processing capabilities as they do so.With growth and specialization comes an ability to handlean ever wider and varied range of internal representationsof 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 agood proxy measure of complexity—so do their survivalchances and reproductive fitness improve (Ross Ashby1954).

Interpretative systems, however, have two quite dis-tinct ways of handling the complexity that underlies thevariety:

(a) They can eitherreduce it through getting to under-stand it and acting on it directly. That is, they elicit themost appropriate single representation of that variety andsummon 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 canabsorb it through the creation of op-tions and risk-hedging strategies. That is, they can holdmultiple and sometimes conflicting representations of en-vironmental variety, retaining in their behavioural rep-ertoire a range of responses, each of which operates at alower level of specialization. This approach develops be-havioural plasticity. There may be less goodness of fitbetween any given response and the state of nature towhich it needs to be matched, but the range of environ-mental contingencies that an organism can deal with inthis way is greater than in a regime of specialization. Itmay endeavour to enhance its capability to deal with awider range of environmental contingencies by cooper-ating closely with a number of other organisms, whichcan assist with information and interpretation and sharerisk.

These strategies only partially overlap with those ofuncertainty reduction and absorption (Weick 1995). Theycorrespond to two distinct approaches to learning firstidentified by Holland (1975) in his work on complexadaptive systems and subsequently elaborated by March(1991) and March and Levinthal (1993) in an organiza-tion context: exploitative and exploratory learning. Eachof these two approaches to learning distinctively shapesthe way that data is processed and shared among the data-processing agents that make up an organization’s socialsystem. Since the processing and sharing of data are theconstitutive activities that make up a cultural process

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ORGANIZATION SCIENCE/Vol. 10, No. 3, May–June 1999 239

Figure 1 Structuring Information

(Boisot 1995, Schein 1992), we would expect to see or-ganizations, and societies, with different cultures vary inthe extent to which they choose to reduce or absorb thecomplexity that confronts them.

In what follows, we develop the argument that com-plexity reduction and complexity absorption representdistinct 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 complexitytheorists. We then move on to illustrate the argument withreference to China. China is the world’s largest socialsystem, and one whose form of complexity, and custom-ary modes of handling it, were not familiar to the Westernfirms now operating there. We analyze the choice theseorganizations have faced between maintaining Westernnorms of complexity reduction or adopting a strategy ofcomplexity absorption that is more consistent with Chi-nese culture. The paper concludes with the outlines of apossible agenda for future research, focusing on the in-vestigation of complexity-handling modes and the con-tingencies which may bear upon the choice betweenthem. Its contribution is therefore by way of an explora-tory exercise in theory-building.

The FrameworkThe I-Space is an augmented version of the frameworkthat we have used to analyse different aspects of China’smodernization (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 couldbe shared in a given population to be a function of howfar it could be codified, that is, compressed into codes(Boisot 1986). Financial information that is codified intoprices and quantities, for example, can be shared morereadily in a population of market players than informationthat is replete with qualitative nuance.

Codification, however, can be greatly facilitated by anappreciation of structure. Structure abstracts from phe-nomena those regularities that underpin the form theyadopt, very much in keeping with Weber’s (1964) use ofthe “ideal type.” The I-Space, therefore, takes the artic-ulation and sharing of experience to be a joint product ofcodification and abstraction, the twin poles of a structur-ation process through which a world is first created andthen objectified (Giddens 1984).

Codification involves the assignment of data to cate-gories—i.e., the giving ofform or formalization. A phe-nomenon is well codified when the basis of assignmentis clear and it can be performed speedily and unproble-matically—i.e., when black is black and white is whiteand no shades of grey emerge to cloud the judgment.

Abstraction, by contrast, involves a reduction in thenumber of categories to which data needs to be assignedfor a phenomenon to be apprehended—i.e., it involves adiscernment of the structures that underpin phenomena.These structures are multiple and often contradictory, oneof the reasons why the process of structuration has anirreducibly hypothetical character.

Codification and abstraction are distinct strategies foreconomizing 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 beprocessed in order to assign a given phenomenon to ap-propriate categories, abstraction saves on data processingby 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 havethe effect of reducing the complexity of data-processingtasks. 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 betweenPerrow’s dimensions of task complexity and our own asfollows:

The Codification DimensionFew Exceptions� Codified—i.e., a speedy assign-

ment of phenomena to categories implies that the task isroutinizeable and has few exceptions.

Many Exceptions� Uncodified—i.e., a slow assign-ment of phenomena to categories implies that the task hastoo many exceptions to be easily routinizable.

The Abstraction DimensionUnderstood� Abstract—i.e., one apprehends the

structure that underlies a given phenomenon.

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Figure 2 Locating Perrow’s Typology in the Framework

Figure 3 The Diffusion Curve in the I-SpaceNot understood� Concrete—i.e., one does not appre-hend the structure that underlies a given phenomenon.

In line with the propositions that we earlier derivedfrom the C-Space, the I-Space takes the codification andabstraction of data to facilitate its sharing among a popu-lation of data-processing agents. Populations of data-processing agents, suitably defined, make up the diffusiondimension of Figure 3. Through what transactional struc-tures these interact with each other will be partly deter-mined by the way that data flows along the diffusion di-mension.

Transactional structures are in fact implicit in Perrow’stypology, structures that affect the nature of connectionspossible among the coupled agents that make up the dif-fusion dimension of the I-Space. The Diffusion dimen-sion allows us to specify the percentage of agents sharinga given item of data. The question that might then beasked is how does such sharing of data affect the inter-action among agents? Although we may wish to interpretthe question at the level of social systems, the issue ofhow interactions among data-processing agents gives riseto stable organized patterns turns out to be a general oneand can be addressed independently of a given level orarea of application. Stable interaction patterns in neuralnetworks, for example, may be the result of “Hebbian”learning (Hebb 1949), a process in which the strength of

connections between data processing nodes—at the sociallevel we may call them agents—is a function of (a) cou-pling frequency and (b) coupling time.

In sum, in the I-Space, codification and abstraction aremutually reinforcing activities and both, working to-gether, facilitate the process of diffusion. The curve ofFigure 3 thus establishes in a schematic form the foundingproposition for our analysis, namely, that codification andabstraction increase the number of data-processing agents

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Figure 4 Institutions in the I-Spacethat can be reached, per unit of time, with a given mes-sage. The reason is intuitively obvious. Codification andabstraction reduce an agent’s data-processing load by ex-tracting information—about form and structure—fromdata. Messages that are codified and abstract are thus in-herently faster to encode and transmit than those whichare not. Whether such messages are effectively dealt withsubsequently by recipients depends on how far they re-quire a shared context for their interpretation (Shannonand Weaver 1949, Weick 1995).

The I-Space thus relates the flow of knowledge andinformation within a social system to the structure of thedata that act as their substrate. Clearly, the characteristicsof such flows will condition the interactions that are pos-sible between agents. Both the speed and frequency ofinteraction will reflect the time and effort required fortransactionally relevant knowledge to flow. Figure 4 lo-cates four institutionalized transactional structures in theI-Space as a function of the knowledge flows that char-acterizes them. The cultural characteristics of these trans-actional structures are summarized in Table 1.

Our earlier hypotheses (Boisot and Child 1996) sug-gested that there had to be a goodness of fit between aculture’s preferred approach to knowledge flows and thetransactional structures that it made use of. We examinedChina’s attempt at modernizing from this perspective,noting that the country could plausibly be interpreted asmodernizing in the lower regions of the C-Space. Thisentailed a decentralization from fiefs to clans in the con-text of modernization. We called the resulting culturalorder “Network Capitalism.” We suggested that Networkand Market Capitalism reflect two distinct ways in whichChinese and Western cultures respectively deal with thechallenge of complexity. Our belief is that market capi-talism reflects a cultural preference for complexity reduc-tion and that network capitalism is more strongly attunedto complexity absorption.

To progress the discussion, however, we first need toexplore how complexity might best be interpreted in theI-Space. We turn to this next with reference to the workof complexity theorists.

Complexity in the I-SpaceWe can identify two quite different yet complementaryapproaches to complexity. The first, associated with thework of Kolgomorov (1965) and Chaitin (1974), origi-nates in the theory of computation and goes by the nameof Algorithmic Information Complexity or AIC. It mea-sures complexity as a function of the shortest programmethat will describe a task or a phenomenon. Given that in

the absence of compressible regularities, the shortest pro-gramme is coterminous with the phenomena itself, Gell-Man, among others, has observed that AIC equates com-plexity with randomness. He suggests instead a measurewhich he labelseffective complexity (Gell-Mann 1995)and that equates complexity with the size of the shortestprogramme that describes the regularities in a given phe-nomenon. The second approach to complexity drawsfrom biology and studies of artificial life (Holland 1975,Kauffman 1993, Langton 1992, Ray 1992). It definescomplexity in terms of the density and variability of in-teractions that take place among coupled agents (Varelaet al. 1991). The two approaches complement each otherin the sense that the first focuses on the content of infor-mation flows among agents and the second on the struc-ture of the interactions that such flows allow amongagents. The first, in effect, measurescognitive complex-ity, whereas the second measures what we might callre-lational complexity.

If we now try to map these two measures of complexityon to the I-Space, it becomes clear that the codificationand abstraction dimensions of the space offer a measureof cognitive complexity, whereas the diffusion dimen-sion, through the transactional structures that it engen-ders, allows us to capturerelational complexity. Rela-tional complexity is best understood through a briefoverview of the work of Stuart Kauffman.

Kauffman, building on the work of Wright (1931), con-structs fitness landscapes—i.e., any well-defined propertyin its distribution across an ensemble—using what heterms NK Boolean networks, that is, nodes interlinkedwith varying degrees of density. Boolean networks arenonequilibrium open thermodynamic systems. In suchnetworks,N refers to the number of parts in the systemunder consideration—genes in a genotype, amino acids

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Table 1 Institutions in the I-Space

Undiffused Information Diffused Information

Codified Information

Bureaucracies Markets• Information diffusion limited and under central control• Relationships impersonal and hierarchical• Submission to superordinate goals• Hierarchical coordination• No necessity to share values and beliefs

• Information widely diffused, no control• Relationships impersonal and competitive• No superordinate goals—each one for himself• Horizontal coordination through self-regulation• No necessity to share values and beliefs

Uncodified Information

Fiefs Clans• Information diffusion limited by lack of codification to

face-to-face relationship• Relationships personal and hierarchical (feudal/charismatic)• Submission to superordinate goals• Hierarchical coordination• Necessity to share values and beliefs

• Information is diffused but still limited by lack of codification toface-to-face relationships

• Relationships personal but nonhierarchical• Goals are shared through a process of negotiation• Horizontal coordination through negotiation• Necessity to share values and beliefs

in a protein, etc. Each part makes a fitness contributionwhich depends upon that part and onK other parts amongthe N. In effect,K reflects how richly cross-coupled thesystem is. A geneticist would say that it measures therichness of epistatic interactions among system compo-nents (Kauffman 1993). WithK � 0 for example, thereare no epistatic interactions. WithK � N � 1, on theother hand, each node in the network is epistatically af-fected by every other node and we obtain the largest valuefor K.

The behaviour of the links between nodes can be tunedby employing a control parameter,P. In this way theycan be made to exhibit order, chaos, or a phase transitionbetween those two states that is labelled “the edge ofchaos.” It is in this phase transition that complex behav-iour emerges. If, for example, we letP be the fraction ofthe 2K positions in the Boolean function with either a 1response or a 0 response, whichever is the larger fraction,P will range from 0.5 to 1.0. The deviation ofP above0.5 then measures the internal homogeneity of theBoolean function. The critical value,Pc, identifies the lo-cus of a phase transition in the behaviour of a dynamicalsystem. In our scheme, a high value forP—i.e., close to1.0—reflects a high degree of stability and structure anda low level of AIC. It thus corresponds to an informationenvironment high in codification and abstraction. LowP,by contrast, that is,P close to 0.5, is low in stability andstructure 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 ofP, the lower the level of cognitivecomplexity.

In discussing his Boolean networks, Kauffman ob-serves:

As systems with many parts increase both the number of theseparts and the richness of interactions among the parts, it is typ-ical that the number of conflicting design constraints among theparts increases rapidly. These conflicting constraints imply thatoptimization can attain only ever poorer compromises. Further,it is clear that conflicting constraints are a very general limit inadaptive 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 costswill exceed total fitness, and increasing eitherN or K willno longer be profitable. The limits of complexity havebeen attained. Beyond the point the system undergoes aphase transition into the chaotic regime.

A high value for our control parameter,P, however,allows higher values to be achieved forK or N before aphase transition occurs than do lower values ofP. An-other way of saying this is that there is a trade-off betweencognitive and relational complexity. A low degree of cog-nitive complexity allows one to handle a higher degreeof relational complexity and vice versa without under-going a phase transition into chaos. In other words, cod-ification and abstraction facilitate the orderly processingof information among larger numbers of interacting per-sons.

Table 2 presents the complexity characteristics of our

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Table 2 The Complexity of Transactional Structures

RelationalComplexity

CognitiveComplexity

OverallTransactionalComplexity

Markets High (High K) Low (High P) MediumBureaucracies Low (Low K) Low (High P) LowFiefs Low (Low K) High (Low P) MediumClans Medium (Medium K) High (Low P) High

Figure 5 Phase Transitions in the I-Space

four transactional structures, relating these toK andP inKauffman’s scheme.N specifies the number of agents tobe located in a given I-Space and hence establishes thesize of its diffusion dimension. It defines the size of theagent population on whichK andP will operate and it isset by identifying those agents who might be candidatesfor involvement in transactional arrangements. Once anI-Space has been created, however,N becomes fixed.

In Table 2, we take markets to be characterized by highK, bureaucracies and fiefs by lowK, and clans by mediumK. It might at first sight seem surprising to impute a lowK to bureaucracies. After all, rational-legal bureaucraciesare 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, bureaucraciesseverely restrict the number of agents that one is requiredto 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 nowbuild on his analysis to tentively partition the I-Space intothe three phases that he identifies namely, the Ordered,the Complex, and the Chaotic. Since, in contrast toKauffman, our partitioning exercise is not derived froma series of simulations or from the use of Boolean net-works, it must of necessity remain schematic. It is shownin Figure 5.

Although it is not possible to establish more than anapproximate correspondence between the location of thethree phases and those of the transactional structures ofFigure 4, it is at least intuitively plausible to argue thatbureaucracies seek out the stability of the ordered regimeand that the other three transactional forms represent threedistinct responses to different mixes of cognitive and re-lational complexity.Markets, for example, have banishedcognitive complexity by codifying everything into an ab-stract set of prices but have to deal with the relationalcomplexity of large numbers bargaining (Williamson1975, Hayek 1945). Interactions between players may besimple (high P) but codified and abstract information

flows favours epistatic interactions on a large scale (highK). The assumption of self-regulation gives this transac-tional form homeostatic stability.

Fiefs, in contrast to markets, deal with small numbers(low K), and usually on the basis of loyalty and a complexset of reciprocal obligations. They do so, however, in anenvironment in which cognitive complexity is high (lowP).

Finally, clans appear to exhibit the highest level ofcomplexity of all our transactional structures. Althoughthe numbers involved are smaller than those required forefficient markets they are higher than in fiefs (mediumK). Cognitive complexity, however, is high (lowP). Here,overall transactional complexity is not the product oflarge numbers bargaining but of a complex set of inter-actions among a sizeable number of players. When thenumbers that participate in clan transactions go up, orcognitive and relational complexity are increased, clansare prone to slip into chaotic behaviour. For that reasonthey must be considered an “edge of chaos” phenomenon(Langton 1992).

Cultures, like individuals, vary in the extent to whichthey need order and stability in their commerce with re-ality (Hofstede 1980, Boisot 1995). The seeking of orderand stability can be interpreted in the I-Space as a movefrom whatever region one finds oneself in towards thepoint 0 of Figure 5 (top left-hand corner). Point 0 thusacts as an attractor in the I-Space and offers an escapefrom chaos. But how far do individuals or cultures actu-ally want to escape? For instance, do they want to movewholesale into the ordered regime? Or might they settlefor the excitements of the complex regime? Much willdepend on how they feel about complexity and the un-certainty that it creates. Attractors other than point 0might be on offer.

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Point 0 in the ordered regime is a world in which eventsare 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” (Hicks1935, p. 8). The complex regime is more difficult to man-age, with the degree of difficulty rising in line with thelevel of complexity. Here, the world is perceived as adiscernible 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 bediscerned and hence nothing can be managed. It can onlybe allowed for in the hope that organized complexity willemerge from chaotic processes themselves.

Our discussion of Kauffman suggests two ways ofmoving towards point 0 in the I-Space, whether from thechaotic towards the complex regime, or from the complextowards the ordered regime:

(1) Reduce cognitive complexity through acts of cod-ification and abstraction—i.e., aim for a highP.

(2) Reduce relational complexity by keeping the num-bers of transacting agents down—i.e., aim for a lowK.

Of course, it has to be recognized that to the extent thatrelational complexity is a product of 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 andabstract rules of interaction among agents—as well as bylimiting the number of agents that can interact.

Both strategies, however, involve complexity reduc-tion. The first strategy moves one up the I-space towardsgreater codification and abstraction. It allows one to dealwith large numbers but only by keeping transactions cog-nitively simple. Where the numbers are limited we findourselves in the ordered regimes characteristic of bureau-cracies; where numbers are not limited we find ourselvesin the medium complex regimes characteristic of marketprocesses.

The second strategy moves one towards the left in theI-Space by reducing the number of agents that one has todeal with. Where interactions among agents are cogni-tively simple we find ourselves once more in the orderedregime 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 isonly one of the ways available to us for dealing with it.For it can also be absorbed. This is the transactional strat-egy we associate with a clan order. It can only functionunder conditions of trust and shared values where therisks associated with uncertainty and ambiguity can be

pooled among agents and where mutual adjustments arepossible.

Clans are higher in entropy production than either theordered regime of bureaucracies or the complex regimesof markets or fiefs—that is, they consume more time andsocial resources in order to maintain themselves in a stateof dynamic equilibrium—but in compensation, they offera greater potential for adaptation and renewal.

Our general proposition is that cultures vary in how farthey 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 whosedevelopment trajectories have allowed them to build upan institutional capacity in the upper regions of the I-Space, for example, are more likely to aim for a reductionin cognitive complexity and to transact in large numberseither through bureaucracies or markets. By contrast, cul-tures whose institutional investments are mainly confinedto the lower regions of the I-Space may have little choicebut to hold cognitive complexity constant and to reducerelational complexity by keeping the numbers down towhat can be managed in face-to-face situations. Clearly,relational complexity will be lower in fiefs than in clansso that in the latter case more complexity will need to beabsorbed.

Handling Complexity—the Caseof ChinaApplying Kauffman’s parameters, China is characterizedby a lowP, a highN, and a level ofK that is high withinthe society’s constituent units, but low (albeit now rising)between those units.

Low PIn China, social order in the past has been precarious andunpredictable, due in large measure to the problem ofestablishing an adequate system of governance within acountry highly differentiated by geography, language,and local identities. The periodic breakdown and frequentarbitrariness of central authority, and the lack of clearrights generated considerable uncertainty. While the im-perial bureaucracy did not normally extend down beyonddistrict capitals, the state could nevertheless arbitrarilyintervene 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 theobligations 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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farmers, who were free to set the level of taxation at whateverthe local population could endure. Peasants could also be draftedarbitrarily for military duty 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 natural and officialcapriciousness. For example, Seagrave, in his study of theOverseas Chinese, notes how mass emigrations fromSouth China were caused by invasion from the North,imperial repression and taxation, and natural calamitiesboth local and in the North. The latter led to further pres-sures from a movement of population southwards. Theresult, 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 systemthat was independent of the state and supreme in its ownright. In the absence of a codified commercial law, mer-chants and producers were at the mercy of a system inwhich imperial officials and their acolytes could exercisearbitrary power through taxes, licensing fees, and restric-tions on trade and travel. Even today, despite continuedlegal 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 ChineseCommunist Party” (Lubman 1995, p. 2). Thus little pro-gress has been made in the effective ability of China’slaws to provide a means of controlling official arbitrari-ness (ibid., p. 11). Nor has China, even today, developeda strong “civil society” to constrain, and hence modulate,the power of the state (Nevitt, 1996).

High NChina as a socioeconomic system displays a high level ofKaufmann’sN. It consists of many and differentiated ele-ments. These are today manifest in the presence of mul-tiple business systems (state-controlled, collective, andprivate, each with different governance systems and lev-els of marketization), many regions which contrast inwealth, education, and culture, different provincial andother local authorities to which much power has now de-volved, and significant generational differences (Child1999a). Under the new wave of economic reform, state-owned enterprises are further differentiating the nature oftheir governance systems (Child 1999b). Its internal dif-ferentiation lends China the character of a complex cel-lular society.

Levels of KThe 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 highN but low levels ofK between itsconstituent units, a configuration which would of itselfbe conducive to a hierarchical mode of coordination fromthe centre. Indeed, Confucian philosophy legitimized theexpectation 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 thecentre. In the past fifty years, attempts to do so haveshifted dramatically, indeed sometimes violently, frommechanical coordination via central planning to the useof personal charisma by the Party Chairman. The variableand uncertain nature of central authority has encouragedlocal powers to make up the deficiency, and in turn stronglocal loyalties have added to the problems of securingeffective central governance.

Thus, levels ofK are highwithin the system’s constit-uent units, especially within local communities whichhave close-knit networks embracing administrative, po-litical, and business groups. This combination creates ten-sions between the central and local levels in the gover-nance system, and consequent ambiguities about theirrespective jurisdictions. While laws and regulations areformulated centrally, coordination between national gov-ernment bodies is often ineffective and, in addition, thelaws and regulations are administered locally. This cangive rise to considerable ambiguity as to who is “the gov-ernment” and behavioural inconsistencies between dif-ferent agencies and localities.

Ambiguity about governmental jurisdictions and pow-ers contributes to a low level of stability within the Chi-nese system and hence the low level ofP already noted.The form of complexity in China (low overallK com-bined with high localK and lowP) poses far greater dif-ficulties for those engaged in economic relationships, thandoes a highN per se. For it describes a situation in whicheconomic governance tends to be organized through in-tensive relations coordinated according to implicitrules—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 thehands of local government and Party officials. This is notto say, of course, that any kind of national plan is beingimposed—indeed, the contrary tends to be true becauseof the local variation that this system creates. The abilityof local authorities to exercise significant power stems inlarge part from the high levels ofK 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 remainconsiderable. Despite the objectives of the economic re-form, many state and collective enterprises are beholdento 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 arefears that the current corporate governance reforms willleave governmental agencies largely in control even ofsmaller 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 formwith multinational companies.

The cognitive complexity (lowP) which is caused byambiguities as to the locus of power and initiative in theChinese system, is added to by the lack of transparencyof many Chinese laws and/or their uncertain enforcement,as is the case with intellectual property rights. Local gov-ernmental agencies have powers to interpret regulations,issue licences, and impose taxes, which furnish amplescope for negotiation and corruption. Even some nationalregulations and taxes have been imposed retrospectively.

There also continues to be a shortage of two key busi-ness resources, namely domestic working capital (muchof 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 betaken for granted, further elements of uncertainty are in-jected into the business environment. Infrastructural lim-itations, especially in the transportation of goods, add an-other source of uncertainty. Each of these uncertaintiesincreases the temptation for local agents to act opportun-istically—for example, to renege on an employment orsupply contract in order to take advantage of availableeconomic 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 problem is recognizedat the highest level. Former premier Li Peng, addressingthe National People’s Congress in March 1994 stated thatthe struggle against corruption “is a matter of life anddeath for the nation” (quoted by McDonald 1995, p. 175).There are several specific practices which are quite com-mon, and which are particularly inimical to the establish-ment of trust. One is product piracy, including the illegaluse of their foreign partners’ brand names by Chineseenterprises. 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 manyforeign 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 that of bribery. Bribery, of course, implies the threat ofnon-cooperation or even reneging on agreements if side-payments are not made.

The low level ofP in the Chinese context generateshigh levels of cognitive complexity and uncertainty. Thisposes considerable problems for local Chinese people, notjust foreign investors. Historically, the Chinese havesought to adapt to these contingencies by forming rela-tional networks with lower numbers but denser interper-sonal links than those typical of Western countries. Thisrepresents a cultural preference for absorption, rather thanreduction, as the means for dealing with the nature ofcomplexity in China. The reliance on dense interpersonallinks, in which friendship, identity, and trust overlay 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. Thefirst comprises the extended family, and to a lesser degreerelationships stemming from a common formative expe-rience in hometown and school, all of which provide forgroup loyalty and shared identity. This trust is based uponblood and upbringing, and it often takes on fieflike qual-ities. The foundations of trust within these close socialunits are those of identification and affect. It is found inthe Chinese family business, in both mainland and over-seas Chinese communities. It has also provided the basison which the directors of state enterprises agreed to formhorizontal groups, and on which many joint ventures be-tween PRC enterprises and overseas Chinese investorshave 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 systemof social governance has been the appropriate institu-tional structure to adopt for economic transactions inChina. Trust within the clanlike networks is based onwhat the Chinese know asguanxi. Guanxi refers to thecredit which a person or a group has with others, basedon the giving of assistance or favours, or deriving frompersonal recommendations. It is significant within workunits, and even more so for the development of interor-ganizational relations in which the actors have no otherfoundation on which to establish trust in a society whereinstitutional guarantees and protection are weak. There isa risk involved in offering the favours through which itis hoped to build up guanxi, and the main guarantee

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against lack of reciprocity lies in the strong social normsby which the acceptance of favours places an obligationupon the recipient.

Personal networks are therefore particularly significantmodes of economic transacting in China because of theweak institutional sanctions against reneging on commit-ments. Both shared social identity and guanxi can providethe foundations for long-standing relationships whichgovern business transactions and upon which transac-tional networks are built. To an important extent, trans-actions within the Chinese business system are governedby the relatively tacit norms and expectations which ac-company these trust-based relationships, rather than bythe more codified rules characteristic of transactions reg-ulated either by hierarchical rules or by laws of contractapplied to market dealings (Boisot and Child 1996). Thisis the case even within the ostensibly bureaucratic PRCstate-owned enterprise, where typically key norms of con-duct remain implicit and where strong fieflike loyaltiesexist 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 contextdisplays a high degree of cognitive complexity and mod-erate levels of clan-based relational complexity. Thesedifferences in organizational context, we would hypoth-esize, will be reflected in a cultural preference by Westernorganizations on the one hand for deploying cognitivestrategies 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 ComplexityManagement: Western Firms in ChinaIt 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 senseof the cognitively complex implicit understandingswithin 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. Itmay, however, be possible though still difficult, for themto gain acceptance as trusted partners of somewhat looserclanlike networks.

This presents the foreign firm with two alternative ap-proaches towards handling the high complexity and weakinstitutional context in China. The two approaches reflectthe 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 maintaintheir familiar mode of handling complexity and enact theenvironment to permit this, or to adapt their mode of com-plexity handling to the local situation with the assistanceof local partners. The first approach is thus familiar to thefirm, but not to the context. The second approach is un-familiar to the firm, but culturally more attuned to thecontext. These contrasting approaches reflect, accordingto our argument, fundamental differences in the nature ofthe complexity that respectively confronts China andWestern countries. It will become evident that there issome parallel between the two approaches and, respec-tively, the “K” and “r” strategies identified in biogeo-graphical and evolutionary models. Put simply, theK-strategy involves a focused efficient investment in a givenreproductive attempt and is suited to a slowly-changing,predictable environment, while ther-strategy involvesmany reproductive attempts spread over a range ofpossible environmental situations. The latter are less ef-ficient in themselves, but offer a greater chance of speciessurvival in complex, unpredictable environments(MacArthur and Wilson 1967, Hannan and Freeman1989).

The first alternative is an attempt toreduce cognitivecomplexity through imposing familiar routines and stan-dards upon business in China. It approximates to whatcross-cultural theorists term a “domination” strategy(Tung 1993). This imposition attempts to replicate thestructured articulation of information that in Westerncountries is assisted by supporting institutions. It is pur-sued through a combination of complementary externaland internal actions. The external approach is to enact theenvironment to reduce its complexity through measuressuch as lobbying foreign governments to pressure Chinainto creating a more codified environment, especially vialegislation and its effective enforcement, deploying bigcorporate guns to negotiate Chinese institutional toler-ance of the foreign investor’s intentions, and using theChinese need for technology and finance as bargaininglevers for the introduction of Western norms. Coca-Cola’s highly publicized policy of contributing to localeconomic development has, for example, generated con-siderable goodwill and tolerance for its application of itspreferred global policies to China (cf., Nolan 1995). Byenacting rather than negotiating the environment, this ap-proach endeavours to restrict involvement in the system’srelational complexity and hence favours 100% foreignownership 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 intoa multinational corporation’s global network. MNCshave, for example, preferred to apply their own environ-mental protection standards in 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 controlover personnel selection so as to recruit employees, pref-erably young people, who are “untainted” by Chinesework and institutional norms, and a reliance upon a com-bination of training and attractive rewards to mould Chi-nese workplace behaviour (Lu and Bjo¨rkman 1997).

This approach has 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 structures and systems, and those adopt-ing it are prepared to incur short-term costs in the process.One cost is that the control has to be secured through acapital investment sufficient to secure a large majority ofjoint venture equity or sole ownership. Such control nor-mally requires a heavy presence of expatriates in the earlylife of the Chinese affiliate, which imposes a heavy fi-nancial burden, and there can be considerable conflictwith local personnel as the foreign parent company’sstructures and practices are applied. The intention is toreplace expatriates with “homegrown” Chinese managerswho can run and accept foreign systems as soon as theycan be found and trained.

There is some doubt, however, whether the early re-placement of expatriates is going to be feasible with thisapproach. One reason is that it bases cooperative rela-tionships between the Chinese and foreign parties almostentirely upon calculation, and not on any firmer bases ofmutual commitment or trust. As such, it is likely to en-gender only the most basic level cooperation between thepartners. The primary basis of the relationship lies in thepromise of favourable rewards to the Chinese partner, interms of dividends, employment, and technology transfer,and to individual Chinese employees in terms of highlevels of personal income. There is no doubt that this buyscooperation, but only up to a point and not on a basis ofa commitment to the joint enterprise. It is not surprising,therefore, that many foreign managers complain abouttheir partners’ instrumental, even underhand, attitude to-wards the protection of resources such as technologytransfer and brand equity, as well as about the difficultyof retaining good Chinese managers. There is a danger,then, with this approach that order is purchased withinthe China venture or subsidiary but at the expense of theexternal certainty that can be secured. Its advocates argue

that, given time, learning about external complexity canbe 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 (Johnstone1998), 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 unequivocallysupport the argument (Andersen Consulting 1995, Pan etal. 1999)

The alternative approach to dealing with the complex-ity of the Chinese system is one of using local Chinesecapabilities toabsorb it. This requires an attempt to en-gage with relevant clans and to enter into more intensiverelationships (i.e., high relational complexity) with Chi-nese partners and other significant groups. This is noteasy, and may take years rather than months. Clans arepredicated on outcomes from an iterated prisoner’s di-lemma relationship that are in favour of cooperationrather than defection. Resources are secured from outsid-ers through opportunistic behaviour and are used to cross-subsidize transactions between insiders. For transactionsbetween clan members, the “shadow of the future” istherefore very positive and real (Axelrod 1984). How-ever, the favourable conditions for benefiting from co-operation are extended only to those who have becomeaccepted as members of the clan. An outsider, such as aforeign firm in China, has to find ways of demonstratingbenefit 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 willtend to confront “defection” as the preferred Chinese op-tion. This implies that they have to offer substantial bene-fits to their prospective Chinese partners so that the costsof defection to the latter are high, and that once acceptedit is important to maintain the trust of the Chinese party.

Again, there are both external and internal routes todoing this. The external one includes the co-opting, onthe basis of mutual benefit, of Chinese partners who haveinstitutional influence, and allowing them to handle theexternal complexity which derives mainly from the bu-reaucracy and its manifestations of arbitrary behaviour.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 theventure’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 whichare 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, aplanned programme of visits between foreign and Chi-nese executives, relatively lengthy assignments of foreignexecutives to China joint ventures, and emphasizing theneed for cultural sensitivity. All these positiverelationship-building moves have, nevertheless, to buildon the perception of clear economic advantage by theChinese as well as the foreign partner.

This second approach attempts to absorb complexity inthe Chinese context by giving primacy to establishing aset of enduring relationships both within and outside thebusiness venture. These relationships are expected to of-fer relevant information, advice, and support within thecomplex external environment. There is a recognition thatthe knowledge and support functional to handling com-plexity is unique to the Chinese system and dispersedwithin it. While partnership requires mutual benefit, theaim is to develop relationships with Chinese counterpartsthat go further and incorporate an increasing level of trustbased on mutual understanding and even personal friend-ship. This approach, which implies a degree of cross-cultural integration (Tung 1993), is much more consistentwith the relationship-based approach of the Chinesethemselves towards complexity. Judged by the historicalexperience of the Chinese, as well as by criteria of cul-tural acceptability, the attempt to absorb complexity ap-pears to lay a sounder basis for Sino-foreign joint venturedevelopment. This conclusion is consistent with that ofresearch into joint ventures in other developing countrieswith a low institutional support for trust (Beamish 1988).

The choice between the two complexity managementstrategies would also need to be informed by a numberof contingent factors. The size of firms seems to be oneissue here. Typically, large firms are better able to enacttheir environment through acts of codification and ab-straction, and hence to reduce the complexity that theyconfront, than are small ones (Aldrich 1979). Small firmshave less scope for enactment. Their best strategy, there-fore, is to absorb the complexity they encounter throughthe building up of mutually supportive relationships. InChina, large state-owned firms continue to play the en-actment card and are increasingly doing so through merg-ers and the formation of horizontal “enterprise groups.”This is despite a degree of turbulence that has up to nowseriously impeded their effort. They have so far lackedthe rational-legal institutional environment that wouldgive stability to such an endeavour and hence make itworthwhile. By contrast, many small firms in China—thecollectives, township and village enterprises (TVEs), andprivate firms—have so far done well out of their strategies

of absorbing complexity via local networks. However, thefact that many firms in Western industrial societies haverecently been led to seek out clan or network forms ofgovernance, suggests that in times of rapid change or tur-bulence there are limits to what can be usefully enactedeven by large firms.

The ability of clans to handle greater cognitive com-plexity may therefore depend on a second contingent fac-tor, namely the severity of the selection environment thatthey face. A munificent environment will allow playersto absorb a greater degree of both cognitive and relationalcomplexity than one which is resource poor. Thus thedecentralization of Chinese enterprises into clans waspredicated on the period of sustained economic growthsince 1979. The two phenomena were mutually enabling.Arguably, the point can be generalized beyond the Chi-nese case. It may be no accident that in Western industrialsocieties, clans and networks have become the preferredforms of organizing within high growth industries. As isimplied by their location in the I-Space, networks arehigh-entropy producing forms of governance whose re-source consumption requirements need to be “covered”by high levels of innovation and growth. Innovation, inturn, thrives upon effective networking (Nohria andEccles 1992). The atomized competition of efficiency-seeking market processes is less favourable to the emer-gence of innovation than option-generating environmentof well-functioning clans. Nevertheless, clans consumemore resources per transaction than do markets. The face-to-face relations they require increase transaction costsand run into the limits of what one may term “boundedsociality”—the time and energy required to sustain face-to-face relations, given physical and time-zone distancesand the existence of many competing demands.

The experience of foreign firms in China also points totheir resource dependence as a further contingency thathas a bearing on the choice between complexity-reducingand complexity-absorbing strategies, for a firm’s abilityto enact its environment to the extent required by theformer strategy will be constrained if it depends on thatenvironment for key resources. Thus, the complexity ab-sorption approach appears to be more appropriate whenthe foreign partner does not possess overwhelming tech-nological, brand advantages, or financial advantages (i.e.,when its ability to purchase dominance through offeringaccess to these benefits is limited), and/or when the Chi-nese partner holds the key to market growth. In sectorssuch as petrochemicals and telecommunications, accessto the market depends on working with a Chinese partnerand, to a large extent, in accord with the norms of theChinese system.

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ConclusionWe have pursued a cultural and institutional analysis,drawing on concepts from the emerging field of com-plexity theory. We have applied the analysis to the chal-lenging, but most appropriate, case of China. This con-clusion reflects on how the complexity perspective addsto our understanding of societies as organizational con-texts, and of the ways in which organizations can handlethe different forms of complexity these contexts present.

The I-Space analysis indicates that cultures, societialand organizational, can either reduce or absorb complex-ity. Cognitive complexity is reduced by moves up the I-Space. If these moves are based on understanding andinsight, cognitive complexity will effectively be reduced.If, however, the move is forced and arbitrary, then cog-nitive complexity may well be increased rather than re-duced. Relational complexity, by contrast, is reduced bylimiting the number of agents that one may have to trans-act with. Thus, while a network or clanlike transactionalorder confronts greater cognitive complexity than mar-kets—i.e., it is located lower in the I-Space—its relationalcomplexity is lower. Being located to the right of fiefs inthe I-Space, however, its scope for relationship buildingis higher than the latter’s.

What we see therefore is a trade-off between the com-plexity of the relations that can be handled, and the com-plexity of what can be transacted through such relations.A market order can handle relational complexity of a highorder by codifying and abstracting the content of trans-actions into prices and quantities. Clans, on the otherhand, can handle greater cognitive complexity, but onlyby keeping the numbers down. We have suggested thatWestern and Chinese societies reflect this contrast.

Societies located in different parts of the I-Space varyin the capacity they require of their constituent organi-zations to handle cognitive complexity. Western marketcapitalism contrasts in this respect with East Asian net-work capitalism, as the case of China illustrates. The twoapproaches to handling complexity, reduction and ab-sorption, have developed as cultural responses to the spe-cific conditions of different societies over long periods oftime. It is not surprising, then, that Western, especiallyAmerican, firms show a strong preference for the reduc-tion approach towards coping with the complexity of theChinese situation. This reflects their formative experienceas corporations developing in a nation where the institu-tional pressures for mimetic isomorphism (Scott 1995)have resulted in internal corporate procedures and rulesthat reflect the advanced abstract principles and high lev-els of codification within American society at large. Jap-anese firms in China provide an instructive contrast. Theytend to take a minority or shared equity position in joint

ventures. This signals their willingness to discuss and ne-gotiate rather than play a purely independent role. It ap-pears to reflect the way that larger Japanese firms are usedin their home environment to a situation of high trans-actional complexity in which they relate closely, butfairly informally, with other companies and with govern-ment bodies (Whitley 1992).

Chandler (1962, 1977) has traced in detail how largeU.S. firms developed strategies of complexity reductionthrough formal structures and standard procedures. Thishas become the orthodox approach of large Westernfirms, and it is consistent with operating within legal-rational societies which have endeavoured to reduce lev-els of cognitive complexity as they developed. This con-trasts with the ways that China’s social tradition andpolitical economy have generated high levels of cognitivecomplexity, and pushed that country’s economic organi-zations in the direction of complexity absorption throughmore intense systems of relationships. Both Chinese andWestern strategies are adaptations to complexity, butgiven the path-dependent nature of social and economicdevelopment, each has given rise to distinctive institu-tional contexts for firms (North 1990).

This contrast implies that, when bringing their back-ground into a markedly different institutional context likeChina, Western multinationals have a strategic choice.The first option is to apply their standard policies andpractices in China, which are well understood and com-patible with their worldwide activities, by endeavouringto secure sufficient control to enact critical aspects of theChinese environment. This is the strategy of complexityreduction, aimed at preserving the firms’ low cognitivecomplexity and high international relational reach. Thesecond option is to endeavour to absorb the complexityof the Chinese situation through enlisting the support oflocal allies. This entails a greater degree of participationin local relational systems. It engages the Western firmin a greater level of cognitive complexity than it is fa-miliar with, and it may limit its ability to relate its policiesand practices in China to its worldwide system. This mayincrease its ability to learn, but introduce difficulties inapplying that learning outside the China context.

It is the officially expressed intention for large Chinesestate-owned enterprises to globalize in the future, whichopens up the issue of whether to favour partnership withforeign companies outside China. In terms of our analy-sis, it also suggests that Chinese enterprises will be en-tering economies in which the levels of cognitive com-plexity are lower than in China but which, at the sametime, take those Chinese firms beyond the reach of thedense, but contained, relational networks with which theyare familiar and can claim membership. In other words,

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they will be confronted with the prospect of operatingwithin business systems that are less complex cognitivelybut more complex relationally. If our analysis is correct,this implies the need for a considerable cultural adjust-ment on their part and, just like foreign firms in China,they have the choice of addressing the issue through areduction or an absorption strategy.

We may speculate that certain conditions bearing onthe ability of organizations to enact their environmentsand adopt a complexity reducing approach successfully,or alternatively to handle greater cognitive complexity viaa clan approach, are capable of generalization beyond thecase of China which we have considered in this paper. Inparticular, several contingencies may prove to be rele-vant, namely, the size of the organization, the selectionseverity of its environment, and its resource-based abilityto enact that environment.

We can now discern the outlines of a possible agendafor future research. In the first phase, the qualitative de-scriptive work that has characterized our study of Chinaneeds to be further enriched with case study material froma wider number of cultural and institutional settings, onesin which the contingencies just mentioned can be betterexplored. In this study we have identified some of thecultural and institutional circumstances under which firmswill reduce or absorb complexity in a given host countryenvironment—China’s. The same exercise could be at-tempted, perhaps with more formal measures in other hostcountry environments—in Europe, America, and otherparts of Asia. There is much to be learnt from such com-parative studies. Furthermore, the generality of the com-plexity reduction/absorption thesis could be investigatedat the industry as well as the country level. Do industriescharacterized by rapid technical change—and hence byimplication, by high levels of complexity—lend them-selves to reduction or to absorption strategies? Is thechoice of strategy sensitive either to the size of the firmor to the munificence of the industrial environment?

Only when the first phase of research has yielded abetter understanding of how I-Space and complexity con-cepts—codification, abstraction, diffusion, and transac-tional structures on the one hand; AIC,N, P, K, cognitive,and relational complexity on the other—map on to eachother, will we be able to move into a second phase andformalize a number of testable hypotheses that treat bothsets of concepts as powerful manifestations of a singleunderlying information process at work. For this secondphase, there will be a need to develop measures of com-plexity, of complexity reduction, and of complexity ab-sorption appropriate to organizational research both at thelevel of the firm and at the industry level. The growingfield of complexity studies is slowly defining its terms.

Organization theory will benefit from aligning some ofits own definitions with these.

AcknowledgmentsThe authors are grateful for comments made on a previous version ofthis paper by Nicole Biggart, Andrew Pettigrew, and two anonymousreviewers.

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organizations as adaptive systems in complex environments: the case of china

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