[17:08 25/8/2007 5019-modelski-ch05.tex] Job No: 5019 MODELSKI: Globalization as Evolutionary Process Page: 88 88–108
5 Is globalization self-organizing?1
Joachim Karl Rennstich
Globalization as a complex system?
Although in recent years the importance of world-historical trajectories
for the development of modern-day “globalization” has been increasingly
acknowledged, a number of important theoretical questions remain. The
scholarship on globalization often sharply diverges over the issue of its
developmental logic, in the sense of what “drives” the long-term development
of world-systems, a world system, or even a global (meta) system2 (that goes
beyond the social world).
Different explanations for this logic, ranging from random chance to the
dialectical nature of capitalism, have been offered. Yet, the observance of a
relatively stable pattern of global system development has been criticized either
for its linear nature or for the lack of theoretical underpinnings for its pulsating
behavior. Its critics argue that either such models are based on a technological
or economic determinism that has proven to be a poor predictor of global
system development, or they are missing the central element creating the
observed rhythm of a dynamic world-system development, and thus provide
a poor theoretical tool for analysis.
This “central element” is the object of this chapter. The arguments developed
here rest on the assumption that thinking of the global system as a complex,
self-organizing (mostly) social system allows us to step outside the constraints
of the study of the institutions and processes that “produce” globalization3
and instead enables us to analyze the underlying logic that drives, curtails, and
reinforces these processes. Here we offer a framework that combines complex
system analysis with an evolutionary theory of global system development.
Complex systems analysis offers us insights into the way that systems
establish “order” without a singular or initial ordering entity. Yet an order – or
developmental logic – does emerge in such systems, based on systems of trial
and error, adaptation, and system-wide learning, resulting in a system that
features “self-organization” (for a good summary of the relevant literature, see
Devezas and Corredine 2001; Devezas and Corredine 2002).4
Here we argue that globalization understood as a long-term social system
(involving economic, political, and cultural processes) forming a global social
world resembles such an emerging ordered system without a single orderer.
No single power, whether an empire, state, or any other unit, has transformed
the human social world over the last 500 or 1,000 years (or any other period)

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Is globalization self-organizing? 89
into the state we experience it today. Rather, globalization thus understood has
been the result of a number of recurring processes of trial and error, adaptation,
system-wide learning, and thus a complex system based on the principle of
self-organization.
Employing the general lessons derived from the study of complex systems,
it is possible to identify the general (or meta) developmental logic of the
long-term globalization process, while at the same time leaving room for
divergent schools of explanations on the factors that influence important order-
structuring factors such as learning or adaptation in the system.
One critical component in this process of order-structuring is the introduc-
tion of generational cohorts as a key sub-system of collective learning, which
includes not only the capacity for adaptation, but also for innovation. Based
on innovations originating in new forms of socio-technological behavior of
the first generation of innovators, the following second generation, groomed
in this new environment, transforms these innovations into a coherent
socio-technological paradigm. The third generation, while still enjoying the
spoils of the high returns on the leadership in this increasingly adapted
socio-technological paradigm, remains “stuck” in it, unable to adapt to
emerging new alternative socio-technological innovations, and allowing
new socio-economic innovations to arise in alternative and geographically
separate clusters. This leaves the fourth generation witnessing the rise
of challengers to this established order, and eventually the emergence
of a new socio-technological paradigm – often outside of its domain of
control.
While the argument developed here is not necessarily tied to a specific
school of long-term globalization, we use a long-wave model to demonstrate
the application of the generational argument developed here. The pattern
of roughly 100-year-long waves (or long cycles) of alternating leadership
clusters – characterized by their innovative development of a coherent socio-
technological paradigm – can be empirically traced and analyzed through the
observance of a four-step generational cohort pattern, and referred to here as
the “Buddenbrook cycle”.
Global system development: An evolutionary approach
Evolutionary models are characterized by a focus on change, dynamics, and
selection. Change in this view is constant, but never linear in its unfolding – it
changes pace, intensity, and impact, depending on the environment in which
this change unfolds. In doing so, changes are affecting the development of
environments that in turn affect them (feedback effects). The global system
constitutes such an environment of dynamic change. In its development,
it follows an “evolutionary logic” that explains the creation of “possibility
space”, or, in other words, the potential options for change open to the systems
and its parts (Clark et al. 1995). This evolutionary logic driving the global-
system process is based on the following set of epistemological assumptions

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90 Rennstich
of evolutionary economics (Andersen 1994), that also build the basis of the
model presented here:
• agents (e.g. individuals, groups, organizations, etc.) can never be “perfectly
informed” and thus have to optimize (at best) locally, rather than globally;
• an agent’s decision-making is (normally) bound to rules, norms, and
institutions;
• agents are to some extent able to imitate the rules of other agents
(imitation), to learn for themselves, and are able to create novelty
(innovation);
• the processes of imitation and innovation are characterized by significant
degrees of cumulativeness and path-dependency (but may interrupted by
occasional discontinuities);
• the interactions between the agents take place in situations of disequilibria,
and result in either successes or failures of commodity variants and method
variants as well as of agents; and
• these processes of change are non-deterministic, open-ended, and irre-
versible (creating a path of choices).
Thus, socio-political and ultimately global system change seen in this
light is always a historical, dynamic process involving the use as well
as the creation of resources (as diverse as simple objects, techniques, and
knowledge; or even entire social organizations). The evolutionary logic
is the result of social interaction, and thus human agency. This agency,
however, takes place and is embedded in an institutional and technological
context. In other words, whereas the driving logic (human agency) of this
process remains the same, its context changes, constituting a “social learning
algorithm” of evolutionary change that is at work at all levels of the global-
system process (from the individual to the change of the global system
as a whole). Within the framework presented here, the four mechanisms
driving the evolutionary globalization process and constituting a “social
learning algorithm” are: (1) variety creation (very broadly: cultural process);
(2) cooperation or segregation (social process); (3) selection (political process);
and (4) preservation and transmission (economic process).
Since such a synthesis has to be an ordered one, all world-system processes
have a time structure that allows for successive optimizations of these
mechanisms in a formal–logical “learning sequence” (following the numbered
sequence above). Global-system processes in this view, then, are seen as nested
and synchronized (i.e. coevolving) four-phase temporal learning experiments
driven by common “evolutionary logic” inherent in all these processes.
Evolutionary logic, system complexity, and world-system evolution
From an evolutionary perspective, the development of the global system
as we experience it today has been characterized by what McNeill and

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Is globalization self-organizing? 91
McNeill (2003) describe as a process of intensifying connections of human
“webs.” These webs are rather diverse in their form, strength of connections,
and the areas and peoples that they cover. Through the gradual amalgamation
of many smaller webs into a single world web, the global system emerges in
the form of the “Old World Web”, spanning most of Eurasia and North Africa
and forming about 2,000 years ago. With the expansion of oceanic navigation,
a more complex and extended (both in depth and width) single “cosmopolitan
web” emerged out of existing metropolitan (and the few remaining local) webs,
creating a truly global, single human web.
Descriptions of the development of a global system abound (as discussed
above). The analysis of McNeill and McNeill has been used here in order to
highlight two of the most important aspects of the global-system formation,
often only implicitly acknowledged in the respective analyses: the evolutionary
character of its development and the complexity of its connection. The long-
wave approach employed in this work is based on and extends the analysis of
the development of the modern era system (i.e. the current global organization
phase in the global or world-system process) as put forward by Modelski
and Thompson (1996) and Rennstich (2003a). The model developed there
takes into account the dynamic processes of the evolutionary drive of the
global world-system process and the resulting change in the overall network
structure of the nested, coevolving cultural, social, political, and economic
processes.
To readers familiar with existing long-wave narratives of world-system
development, it is important to note the inclusion of the element of system
complexity in the model presented here. In this view, a crucial aspect in terms
of its evolution from a set of previously loosely related webs or sub-systems
into the far more interconnected global system of today – the “weaving of the
global web” as a developmental or system-ordering process – is the recognition
of the relationship between these systems as a complex meta-system. The
advantage of employing such a meta-evolutionary model (a model that assumes
that the global-system formation follows the features of a complex system)
to the analysis of long-term global-system formation, is that it allows us
to draw on the important insights of other research traditions, employing
findings from seemingly unrelated subject matters, that nonetheless contribute
significant theoretical and empirical findings for our study of global-system
evolution. The meta-narrative (of innovation, adaption, and system-wide
learning) remains the same, whereas we can employ alternative explanations
for the social factors that structure the relationship of the social agents (and
thus have a direct impact on the capacity for innovation, adaptation, and
learning).
Change in complex systems, whether in the direction of greater or lesser
complexity, produces a trajectory or “historical path”, limiting future options
and thus becoming path-dependent in this way.5 The logic of the development
of these systems is based on trial-and-error. Configuration (adaptation), and
reconfiguration (i.e. learning) become an part of the entire system as well as

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92 Rennstich
the various sub-systems (or “web” in the terminology of McNeill). The path
as such is therefore not determined towards a specific goal. With each step,
a new structure (or environment) is created that encompasses previous self-
organization, learning and the current limitations, and to which the units have
to correspond, shaping yet another new structure in the process. Therefore,
complex systems such as the nested global economic, political, social, and
cultural processes under study here exhibit a tendency to “self-organization”,
that is, the endogenous ordering into hierarchies gives them a system-wide
form.6
The way the interrelationships between parts of the systems are established –
i.e. the weaving of the webs or, put differently, the structure of the networks
making up the global system – thus becomes crucial for our understanding of
the dynamics of these coevolving structures.
Network structures
The middle of the eighteenth century in this view, to use the image employed
by McNeill and McNeill, marks a change in the “spinning” of the global
system web, or, in complex systems terms, the punctuation of the complex
global system. Up to this point, webs had been extended and newly formed,
mostly in the form of the establishment of linkages between pre-existing
(metropolitan) webs, and, in turn, creating a larger, single web – a process
that we could describe as “external network” or web extension. What changes
during this time is the increasing tendency of “internal web weaving”, i.e. the
attempt to extend pre-existing large webs internally to create rival alternative
rather than complementing webs or networks.7
Table 5.1 lists the development of the network structure, in addition to the
coevolution of the economic and political process of globalization, describing
the leading sectors of each economic Kondratiev- or K-wave and the lead
economy of each political long wave of global world-system leadership.8 The
roots of the three main network systems in existence so far can be found in
the evolutionary “trials” (as part of the evolutionary development of variety
creation) during the two Chinese-dominated periods emerging in c.900 ce.9 In
particular, the Southern Sung period during the eleventh and twelfth centuries
provides many elements that are similar to those present in the following
maritime network system. Given their lineage and the larger evolutionary
pattern of development, however, it is analytically more sensible to regard
them as evolutionary trials, rather than part of the first external network
system.
Observing this process, we are able to mark three distinct network phases
during the evolution of the modern world system: a maritime commercial phase
(Genoa, Venice, Portugal, Dutch, England I), an industrial phase (England II,
US I), and the emerging digital commercial phase (US II). All three phases can
be divided into two meta-systems of internal and external network phases (as a
result of leading sectors and the different technological styles, see Table 5.1).10

[17:08 25/8/2007 5019-modelski-ch05.tex] Job No: 5019 MODELSKI: Globalization as Evolutionary Process Page: 93 88–108
T
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[17:08 25/8/2007 5019-modelski-ch05.tex] Job No: 5019 MODELSKI: Globalization as Evolutionary Process Page: 94 88–108
1
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p
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ce
ss

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Is globalization self-organizing? 95
In sum, the global-system process during the time of the punctuation (from
roughly the 1740s to the 1970s, see Figure 5.1) changes from a process
marked by external structure connections to one marked by internalizing
webs, manifesting the selected organizational and institutional structures,
until a new phase of evolutionary dynamics sets in during the late twentieth
century.11
One of the main characteristics of systemic leadership transitions in
most treatments of the subject seems to be the inability of the existing
leader to establish a similar leadership position in a newly emerging and
structurally different commercial and organizational arrangement. This shift
in the geographic and political location of power has been explained as
the outcome of the leader’s experience of success in the current setting,
creating an entrenched institutional setting (in a broader sense) that proves
adaptive in defending its turf but less so in fostering the rise of new leading
sectors. However, the case of Britain’s continued leadership over an extended
period of time (and separate long waves) has shown that this is not always
the case.
In the previous occurrence of a switch from one network system to another –
as a result of the change in the type of capitalist mode of “global web weaving”
(commercial maritime, industrial, and digital commercial) dominating the
global system to a new one – we have witnessed a phenomenon here referred
to as the “phoenix cycle”.12 In instances where the systemic chaos is not
only driven by the “normal” process of hegemonic crisis and breakdown (see
Figure 5.1), but also coincides with a systemic crisis (emerging out of the rising
complexity of the system), the existing leader can defend its leadership position
in the transforming world system. This shift is triggered by a change in the
major socio-economic interaction mode of the system, leading to a shift in the
system meta-structure (the “web-weaving”). Only if the parallel development
of a new cluster of innovations and the rise of new leading sectors can occur
within its domain, is the existing leader able to extend its leadership position
(see Figure 5.1).
As shown by a number of authors13 from various research traditions,
past success often contains the very ingredients for future demise. Whereas
continued endogenous innovation still takes place within the space of the
existing leader, adaptation to a newly emerging, changed environment (as
a result of the rise of new leading sectors elsewhere) proves very hard for a
society that can (and usually does) become locked into economic practices and
institutions that in the past proved so successful. Powerful vested interests
resist change, especially in circumstances when a nation is so powerful as to
institutionalize its commercial and organizational arrangement on a global
level, a change sorely needed, however, to maintain its leadership. Gilpin
(1996) thus concludes that “a national system of political economy most ‘fit’
and efficient in one era of technology and market demand is very likely to
be ‘unfit’ in a succeeding age of new technologies and new demands.” The
creation of these national systems and their respective fitness is the direct result

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96 Rennstich
of the social contextualization of inventions, technologies, and their resulting
innovations, developing into leading sectors in the case of the emerging new
systemic leader.
Transitions of systemic leadership usually involve the shift from one leader
to another, due to what Boswell (1999) calls the “advantage of backwardness”.
If we view the emergence of new commercial and organizational arrangements
as a largely endogenous process, its emergence also causes an environmental
shift that can be understood as an exogenous factor as well. However, the
response of the existing leader to this change is largely driven by endogenous
factors again – a process that results in a unique social contextualization of
technologies.
Figure 5.1 illustrates graphically the relationship between the rate of change,
rising system complexity, and prevalent system network structure or “mode of
web-weaving” earlier discussed on the basis of the development in Table 5.1.14
The bold black wave-like arrow in Figure 5.1 represents the rate of
complexity that rises over time. This graphical representation does not aim
to portray any “exact” representation from which the global system formation
has emerged. The illustration marks instead the first emergence of a specific
system-weaving mode (or modus operandus) that characterizes global-system
development as it seems to continue into the present day. “A” indicates the
point at which growth in complexity will begin to slow, as hypercoherence
takes effect and the possibilities for change (i.e. possibility space) begin
to decrease rapidly. Since complex socio-political systems (like all complex
systems) will inhibit an internal dynamic which leads them to increase in
complexity, the rate of decision-making must, necessarily, keep pace with this
increased complexity (see Devezas and Corredine 2002; Devezas and Corredine
2001; Devezas and Modelski 2003).
This system increases in reach and overall complexity until (during the
nineteenth century) it reaches a state in which the path-dependent system
eventually runs out of future possible choices – a state also referred to as
“hypercoherence”15 that regularly occurs in any complex system.16 In other
words, the global system experiences a systemic punctuation (also referred to as
“catastrophic change”) around 1850, resulting in the end of the experimental
phase in the global community process and starting with the democratic
phase as the set-up that seems the most fit and efficient in the global social
system.17
Decision-making (and thus the process of agency) does not take place in an
isolated environment, but rather a strongly contextual one, marked by high
levels of feedback effects: agency affects the environment in which it unfolds,
but also is formed by it. Thus, it is important not only to focus on the agents
(in the context of this work, defined as states aiming for systemic leadership
or hegemony), but also to identify the contextual environment in which this
agency takes place.
This structure is mainly the result of the need to cope with a rise in complex
decision-making through externalization of the decision-making process.18

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Is globalization self-organizing? 97
However, the more complex the system becomes – that is, the wider the
possibility space extends – the more liable it is to collapse. This collapse takes
place in the form of a selection of best-adapted organizational and institutional
variance, as the possibility space for change begins to close and the system
becomes hypercoherent.
Surrounding the time of this “punctuation” (starting around the middle of
the eighteenth century), the global-system process is marked by an important
change in the form of its “web-weaving” or network formation. Rather
than seeking to manage the extension between webs, large metropolitan
webs aim to turn into single, large “mono-structures” with control over
the entire web rather than mainly the external connections to other webs,
manifesting the selected organizational and institutional structures. This
network-system mode remains largely in place, until a new phase of evolu-
tionary dynamics begins in the late twentieth century (in the second half
of the twentieth century, see Figure 5.1), bringing back the main focus
on the organizational control of the connections between existing webs or
networks.
Point B in Figure 5.1 represents the point at which catastrophic change into
a decline mode occurs. The network structure of the global system during its
initial unfolding remains external in nature, bringing with it ever-higher levels
of complexity as the webs deepen in both depth and width. During point A, the
point of hypercoherence, the network structure becomes internally oriented,
leading to a point, B, of “catastrophic change” or punctuation (i.e. the selection
of a macro-organizational and institutional model in the global community
process).19
New innovations and technologies and their accompanying institutional
arrangements or paradigms20 made it possible to extend the management of
entire webs rather than just the external network of relationships between
existing webs. As a result, the major units of the global web – large,
metropolitan webs with their respective hinterlands – could now viably
seek to extend those hinterlands and incorporate large chunks of previously
connected but largely independent webs into their own domain. As a result,
the major mode of network structure creation and control switched from
an external network-oriented one, to a mode focused on the control of
internal networks that remained connected with other webs (forming a large
global web) but shifted their focus on to the internal networks rather than the
external ones.
Ultimately, however, the control of these systems proved too complex,
resulting in a state of hypercoherence of the global web (as described above).
Since the middle of the twentieth century, the global system – again as a result
of new technologies shifting the focus again on control of external network
connections rather than control over entire webs – has begun a new stage of
global-system formation that now incorporates not only the physical domain
of human interaction but also the “virtual” one that can be captured in a binary
(or “digital”) code.

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98 Rennstich
Social contextualization of technology
As pointed out at the beginning of this chapter, the crucial question of what
drives the pulsation or rhythm of these processes remains an important matter
for debate. The connection between the agents involved; their interactions
with each other; and also the institutional arrangements that these interactions
foster, are all in need for closer scrutiny. It is useful here to return back to the
parameters affecting the rate of learning and adaptation in complex social
systems such as the global-system one. While social systems include more
than individual agents, the duration of long waves are largely determined
by two biological control parameters (Devezas and Corredine 2002) as a
result of human agency. Those two parameters include (1) cognitive factors
(driving the rate of exchanging and processing information at the microlevel),
as well as (2) generational cohorts (constraining the rate of transfer of
knowledge).
A criticism that is often leveled at evolutionary models such as the
one described here, involves the alleged technological determinism that
supposedly drives the socio-economic processes that make up the global-
system development. Such criticism needs to be taken seriously. If indeed,
technological development alone would be the key driver of these processes,
then the theory would serve us poorly. As we know from many accounts,
technology in itself is very social (Basalla 1988). China had the technological
skills, the necessary infrastructure, and the resources in place to develop a
steel industry at the level of production that hundreds of years later would
enable the rise of industrialism in England. Yet this “preconditioning” did
not automatically lead toward the path of industrialization.
This points to an embedding of technology into a larger context, that is part
social, part economic, part political, and in its combination institutional – a
point that is highlighted in another example of the need to view technology
and innovation as an element embedded in a larger social21 context, as
described by Brews and Tucci (2003). Their study of the need to embed
information and communication technologies (ICTs) into a larger social context
to create the desired outcomes, demonstrates that the social contextualization
of technology exists independently of the complexity of the technologies and
innovations involved, but rather is a general attribute of the role of technology
in the processes that shape the formation of the global system as described
here.
This formation is striking in its (relative) regularity, at least since the
emergence of the trajectories emanating in Sung China in the ce 900s –
a regularity that is even more perplexing, given the significant differences in
their social contextuality, if one compares the Sung systems with those of the
Venetian city states, Portugal, the Netherlands, Britain, and the current US
systems (see Table 5.1). If the pattern does not necessarily derive from a direct,
determinant connection between technologies and the socio-technological
systems that they enable, then what else can explain this pattern?

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Is globalization self-organizing? 99
Cognitive factors
Cognitive factors which directly impact the capacity to process information
are important to the argument developed here. For millennia, humans have
employed technologies to aid them in this task: some of the earliest uses
of records were directly related to the storage of economic data and later
to contractual arrangements. As pointed out earlier, one feature of complex
systems is their initial relative simplicity. A global system process, even though
unfolding over millennia, can therefore only be made possible through the
increasing ability of technology to aid human agents and their collective
units in processing information, as the biological human capacity to process
information has developed much more slowly.
The complexity, as explained earlier, of a given complex system does not
develop in a linear fashion, but tends to grow in a non-linear and exponential
manner. Therefore, the very fact that technology and its socialization in terms
of information-capacity widening has increased in an exponential manner,
made the regular pattern of long waves possible in the first place. Otherwise
the increasing complexity of a broadening global system would have over-
burdened the human cognitive capacity process and forced the development
of the system to slow-down (as it did in pre-modern times).
This interrelationship between human-biological and technologically aided
cognitive processing capacity also explains the moment of “catastrophic
change” and the punctuation of the system process (see the earlier discussion
of Figure 5.1). The technologies of the pre-industrial age were simply not
sufficient to add the cognitive capacity necessary for a further weaving of a
now global web. It is during this phase that critical technologies for the shift
from analog to digital information processing occurs (these are long-term
transformations, after all).22
The cognitive challenges posed are daunting, as not only social, but
increasingly biological information gets coded in the same basic binary code
of 0 and 1 (as reflected in the rise of sectors such as biotechnology and
bio-informatics). Yet it seems that the necessary technological tools have
been developed to aid social agents in the cognitive processing capacity
needed to continue the evolutionary developmental path of global-system
formation.
Figure 5.2 uses the Buddenbrook cycle to trace the regular pattern of trial
and error, adaptation and learning (see also Table 5.1), and places it right at
the heart of the development of long cycles and long waves, and ultimately
the development of the center of global system development. It is the “human
element” at the heart of this entire process that explains the relative regularity
of its development independently of increasing technological capabilities
(which might point to an increase in the speed of this process); the extension
of the system; and the broadening of its demographic, geographic, and
institutional breadth (which might point to a slow-down or alternatively again
an increase in speed, as more variety-creation could take place and faster rates

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100 Rennstich
Buddenbrook Cycle
Leader
G1 G2 G3
leading
sector(s)
K-wave 1
Pre/Post K-wave
Generation
Founder and tail
generation
25–30 yrs
K-wave
Generation
Leading sector
generation
25–30 yrs
Generational
Buddenbrook cycle
Four consecutive
generations
100–120 yrs
K-waves
leading-
sector
based
25–30 yrs
Long cycles
of systemic
leadership
100–120 yrs
X X 1 2 3 4
LeaderLeading
sector(s)
leading
sector(s)
K-wave 2
G4
Figure 5.2 The Buddenbrook cycle as part of a leadership-long cycle
of learning and adaptation) or the increase in the destructive capabilities of the
actors during the decision-making and selection phases. Rather than a change
in the dynamics of the learning and/or adaptation process, we do see a relative
constancy.
We argue here that it is the social embedding of leading-sector technologies
that provides the crucial key to a better understanding of the regularity of
this process. This embedding is captured in what we summarize here as the
Buddenbrook cycle.
The buddenbrook cycle
This cycle (graphically depicted as part of a leadership long-cycle in Figure 5.2)
derives its name from the novel by Thomas Mann, in which he describes the rise
and decline of four generations of a trading family-firm in Lübeck, Germany
(and the parallel rise of a new alternative generational family-firm-set). Mann’s
description captures the very essence of the theory developed here:
The first generation (X1 of Unit X) establishes the foundation of a new set
of innovations (or “innovational frame”) through a new, alternative “way
of doing things”. We term this the “founder generation”.

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Is globalization self-organizing? 101
It is during this phase that certain key inventions, that often occurred
many years earlier, are formed into major innovations and their resulting
technologies. This transformation is the result of a unique combination of
the social context in which these technologies are embedded and the feedback
that these technologies evoke in turn in this social context. However, the
impact of these new ways of doing things is not yet large enough to allow the
unit to take a leadership role in the system.
The second generation (X2), brought up in an emerging new socio-
economic environment (i.e. the innovational frame), and thus socialized
in a certain use of the involved innovations and technologies, adds to the
first set of innovations and brings it to a second new height. We term this
the first “K-wave generation”.
This phase is critical in terms of the socialization of technology and
broadening of the innovational frame. The second generation takes up
the cues from the first “choice-maker” generational cohort, following the
paths taken up (for better or worse) by their previous generational peers.
They are taking the emerging new socio-technological paradigm for granted
and, through the application of chosen technologies, fully socialize these
technologies beyond the level of the choice-maker generation. It is during
this generation that the leading sectors fully develop as a result of their
completed embedding in the social context of a given unit (a family in
the case of the Buddenbrooks; a state in the case of the global-system
formation). These leading sectors in turn become the basis of the Kondratiev
waves that are the basis of the leadership long-cycles discussed earlier (see
Figure 5.1).
The third generation (X3), immersed in this “winning set” and aiming
to continue its way of doing things, is unable to adapt to a changing
environment, which itself is created and fostered by a new set of alternative
clusters and thus is forced to witness the decline of its own innovational
frame. We also term this generation a “K-wave generation” as it also marks
the development of a second set of leading sectors that provide the basis
for a second unit-based K-wave.
This third generation is mainly reaping the benefits of the earlier success
of the first two generational cohorts. During this phase, former innovations
(and the associated benefits of systemic control and rent-extraction) become
more widely adopted in the wider social context, and form a new norm. This
increasingly leaves room for new inventions to transform into innovations
outside this specific social context (the way that “things are being done”
in family A) and eventually leads to the rise of alternative sets of innovations
(in family Y1, Z1, etc.).

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102 Rennstich
The fourth generation (A4) finds itself in the middle of a process of
transition and transformation. The very innovations that once proved
critical in the development of systemic control and leadership have by now
become the norm. At the same time, a new generation cohort (the first
generation of Family B) outside of the generational lineage of Family A
establishes the foundation of a new set of innovations (or innovational
frame) through a new, alternative way of doing things. The center of
innovation (and the associated transformations) shifts from Family A to
Family B. We thus call this generation a “tail generation”.
Whereas the completion of the social embedding of technology has been
crucial for the success of the previous generation, leading to the successful
development of leading sectors within its domain, and enabling it to obtain a
position of systemic leadership, this embedding has now been manifested in
the institutionalization of this “wining set” – most beautifully illustrated in
the novel Buddenbrooks, when the newly crowned Consul Buddenbrook (taking
over the post from his father), decides against his own better judgment (as he
senses the threat emanating from the outside) to display the status of the family
and the family business through the purchase of a very grand house in the town
of Lübeck. Although the decline is already discernible, the family (and their
key decision-makers) seems unable to adapt to the changes in the environment
that they sense, but rather aim to manifest its still strong standing in the
established system through a focus on symbols demonstrating its institutional
control. In the end, however, just as Tom Buddenbrook in the novel, the system
leader is relegated to the sidelines, respected in the system, but clearly not in
control of it.
The non-determinate nature of self-organization is largely the result of the
constant need to adapt to new environments that are in turn affected by those
adaptations and the biological constraints (discussed earlier) that frame the
learning (and thus adaptive process), namely cognitive ability and generational
constraints. Even though some actors (depicted in the leadership long-cycles)
are able to obtain some limited systemic leadership position within the global-
system development, no actor is able to maintain this position beyond the
four-generation Buddenbrook cycle.
This model of a four-generational human (generational) cycle of social trial-
and-error, learning and adaptation is tested against the empirically measured
unfolding of long cycles and long waves as part of our earlier-discussed
global-system development model. Figure 5.323 plots (with a bold line) the
distribution of the actual length of the leadership long-cycles and long-
waves as identified in the modern era globalization model discussed above
and graphically represented in Figure 5.1, against a random distribution of
generation-based long waves. (The length of a generation is assumed to be
between 25 and 30 years, and the composition of a Buddenbrook cycle is
assumed to be four generations making up one long wave, as discussed below,
taking into account the mean length of the assumed length of generational

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Is globalization self-organizing? 103
D
en
si
ty
0.030
0.000
80 90 100 110 120 130 140
0.010
0.020
Figure 5.3 Distribution of length of generational waves, kernel density estimation
distribution of actual long wavelengths (thin line) v. random wavelengths
(mean = 110 years, SD = 12 years, bold line)
long-waves in the model (110 years) and a standard deviation of 12 years in
length.24)
The graph indicates a normal distribution in terms of the length of both
the generational Buddenbrook model (thin line) and the actual long-waves
of the past 1,000 years. A Shapiro–Wilk normality test results in W = 0.91
(p-value = 0.3), indicating25 that we cannot dismiss the normal distribution
of the generational wavelengths. In other words, if we expect either an
increase or decrease in the speed of global-system formation, then we need
to identify a trend in the distribution of the length of the waves (in the
respective direction, depending on an increase or decrease in speed expectation).
The results instead indicate that the modeled Buddenbrook cycle (which
argues for a consistent length for the trial-and-error, learning, and adaptation
process) is mirrored in the empirically measured length of the actual long
waves that mark the global-system process. The increased need of human
generations for cognitive processing capacity is satisfied by the increase in
technological capacity to aid humans in this task – up until the point of
punctuation of the global system (during the time of industrialization). The
end of this phase, marked by a shift from production-oriented leading sectors
and internal network domination to external network-focused, information-
based leading sectors, also marks the “restart” of the self-organizing principle
that guides global-system development. This time, however, it is based
on a new information principle: digital, binary code, versus the analog,
word/paper-based principle that was the information principle since the rise
of revolutionary information-processing technologies in northern Sung China
in the ce 900s).

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104 Rennstich
New technologies, old agent: The continuation of
self-organizational logic
This chapter has demonstrated in theoretical terms that the observed
regular pulse of global-system development is not necessarily the result of
a technological determinant. Rather, it is the outcome of a crucial element in
the transformation of inventions and innovations as an enabler of choices (or
“possibility space” in the language of evolutionary models) and technologies
that, once fully embedded in their social context, turn into technologies,
resulting in the development of leading sectors, which in turn enable some
units to emerge as powerful leaders in a transforming global system. It is
important to notice that the social context covers both the domestic and
national (endogenous in evolutionary terms) systems, as well as the larger
world systemic one. This “double socialization” is mirroring the feedback
that takes place in the socialization process during the transition from the
first (choice-maker) to the second generation, and the feedback effects that
the new leading sectors (that resulted from the domestic socialization) have
on the development of the global system as a whole. As in many social
transformations, these processes are rarely a one-way, cause-and-effect affair.
The interactions that take place in these processes shape the environments into
new forms, but, at the same time, those environments have an impact on the
form of socialization that emerges. Also, we hope to provide some common
ground for various long-term approaches of the study of the globalization. The
meta-framework presented here in the form of an evolutionary model, in our
view allows seemingly divergent narratives of global web-weaving to add to
our understanding of the globalization process as it unfolds over millennia,
bridging not only analytical approaches within political science, but also across
the social – and even biological – sciences.
Notes
1 The author would like to especially thank George Modelski, Tessalino Devezas,
and William R. Thompson, as well as the group of participants at the conference
in Vienna, for their support and helpful suggestions. The contribution of Michael
Colaresi in sharing his skills and invaluable insights regarding earlier drafts of this
paper is also greatly appreciated.
2 One of the aims of this chapter is to provide a common analytical ground for the
divergent schools of long-term globalization. Therefore, while acknowledging the
respective importance and distinctive meanings of world(-)system(s) and the term
global, we will use the term “global system” as a description of the meta-process
of globalization.
3 For an interesting discussion of this “endogeneity trap”, see Sassen (2006).
4 For examples of the application of a similar approach, see also Allen et al. (1992);
Scott and Lane (2000); Shaw (2000); and Ziman (2000).
5 This is the result of the structure of complex systems. Whereas in systems theory
all sub-systems relate to each other, complex systems consist of networks of links
of various types between all parts of the system, but each part is not necessarily
linked with all the others in the same way.

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Is globalization self-organizing? 105
6 As a result, these complex systems exhibit “morphogenesis” (i.e. the development
of an organism or of some part of one, as it changes as a species), based on processes
that are partly independent of agency, although they require agents to both initiate
them and enact them (Dark 1998).
7 By no means do we intend to deny a continuing connection between these webs –
a prerequisite for the argument of a continued development of a single, extending
global system. What is important in this context is the shift of emphasis from
control of web connections to one of control over larger sub-webs as a whole. This
process has often included the usurpation of smaller, existing webs into a larger
“imperial” web, with the aim of extending the sphere of control of a web, rather
than extending the web through external connections only through the focus on
the control of the connections rather than the other webs themselves.
8 Kondratiev or K-waves describe the emergence and subsequent decline of long-
term economic cycles (roughly 50 years in length) that are superimposed on
shorter – and better-known – business cycles, describing the “capitalist pulse”
of the economic global-system process. For a discussion of the concept of K-waves
in the context of the model employed here, see Rennstich (2003a). For a more
general discussion on K-waves, see, for example, Duijn (1983); Goldstein (1988);
Berry (1991); and Freeman and Louçã (2001).
9 This work follows the increasing use of ce (Common Era) and bce (before the
Common Era), which replaces the traditional dating system employing ad and bc
respectively for the same periods.
10 For a full discussion of these phases, see Rennstich (2003b).
11 The change in the dominant mode of the weaving of the global web is crucial for
a full understanding of the meaning of “domination” and “control” of the global
system, but is beyond the scope of the discussion here. As pointed out earlier, one of
the major advantages of the evolutionary approach as presented above is the ability
to separate the selection criteria (or systemic fitness) from the identification of the
general developmental logic of the system (self-organization). For this discussion,
see, for example, Rennstich (2005).
12 For a discussion on the effect of these types of rivalries between great powers, see
Rennstich (2003b, 2004). For a similar account, see Cantwell (1989); Levathes
(1996); and Pomeranz (2000). For an alternative account, see Frank (1998), who
distinguishes between “merchant capitalism” (pre-1770s), “industrial capitalism”
(1770s to 1940s), and “global capitalism” (post-1940s).
13 See for, example, Nelson and Winter (1982); Freeman and Soete (1990); Porter
(1990); Christensen (1997); Freeman and Louçã (1997); Gilpin (2001); and Perez
(2002).
14 See Rennstich (2003a) for a more thorough discussion of this argument.
15 The terms “hypercoherence” or “catastrophic change” refer not to the overall
breakdown of the global system process, but rather to the terminology used in
chaos- and catastrophe-theory. They represent an “option-narrowing” as the result
of the selection of a new organizational and institutional setting in the global
community process. After a relatively short period of internal network structure
dominance, the system reverts to an external system structure, setting in motion
a new rise in complexity, bringing with it a new phase of externally open systems,
and, consequently, in the end leading to a new stage of hypercoherence.
16 For a discussion of complex-systems theories, see Auyang (1998).
17 For a more detailed account, see Rennstich (2003a).
18 A good example might be the difference in organization of the decision-making
process in a small four-person firm, in contrast to the hierarchical structure found in
much larger enterprises. The sheer complexity of the need for individual decisions
renders it impossible for a single person to make all the necessary decisions.

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106 Rennstich
Rather, these organizations develop mechanisms of delegating decision-making –
connecting several agents over a number of hierarchies in a joint decision-making
network. The world as whole also resembles such a joint decision-making network.
It permeates from the global-system process to the nested social and political
processes and the inner core of the economic process. During this “search phase” of
expanding possibility space, the dynamics of the system develop best in a relatively
(externally) open environment.
19 It is important to note that “catastrophic change” here refers not to a breakdown
of the global-system process, but rather refers to the terminology used in chaos-
and catastrophe-theory and represents an “option-narrowing” as the result of the
selection of a new organizational and institutional setting in the global community
process. After a relatively short period of internal network structure dominance,
the system reverts to an external system structure, setting in motion a new rise
in complexity, bringing with it a new phase of externally open systems and
consequently in the end leading to a new stage of hypercoherence.
20 See Perez (2002) for an excellent discussion on the relationship between technology,
capital, and socio-economic and techno-economic paradigms that determine what
in evolutionary models is referred to as “possibility space”.
21 The use of the word “social”, especially in a work such as this that crosses
disciplinary boundaries, is laden with dangers. If not specified otherwise, it
is meant to capture inter-agent process, whether they can be characterized as
economic, political, or otherwise.
22 For a more detailed account, see, for example, Hobart and Schiffman (1998) and
Robertson (1998).
23 The author is indebted to and would like to extend his gratitude to Michael
Colaresi for bringing this approach to our attention.
24 The assumption of a range of 25–30 years as the length of a generation tries to
reflect the uncertainty and general disagreement about the “common” or “general”
length of a generation in the literature. Most observations that we are aware of are
reflective of this range (see, for example, from a wide range of approaches: Berger
1960; Jaeger 1985; Strauss and Howe 1991; Griffin 2004; Fenner 2005). The
mean of this range is taken to be 27.5 years, together with a standard deviation in
length of 12 years (of a long-wave consisting of four consecutive generations).
25 W is a measure of the straightness of the normal probability plot, and small
values indicate departures from normality (Shapiro and Wilk 1965). Rather than
“proving” a normal distribution, the test merely shows whether it is possible to
dismiss the normality of a given distribution, which in this case we cannot.
References
Allen, P. M., N. Clark, and F. Perez-Trejo (1992) “Strategic Planning of Complex
Economic Systems.” Review of Political Economy 4: 275–290.
Andersen, E. S. (1994) Evolutionary economics: post-Schumpeterian contributions. London
and New York: Pinter Publishers and St Martin’s Press.
Auyang, S. Y. (1998) Foundations of complex-system theories: in economics, evolutionary
biology, and statistical physics. Cambridge, UK: Cambridge University Press.
Basalla, G. (1988) The evolution of technology. Cambridge, UK, and New York:
Cambridge University Press.
Berger, B. M. (1960) “How long is a generation?” British Journal of Sociology 11: 10–23.
Berry, B. J. L. (1991) Long-wave rhythms in economic development and political behavior.
Baltimore: Johns Hopkins University Press.

[17:08 25/8/2007 5019-modelski-ch05.tex] Job No: 5019 MODELSKI: Globalization as Evolutionary Process Page: 107 88–108
Is globalization self-organizing? 107
Boswell, T. (1999) “Hegemony and Bifurcation Points in World History.”
In: Bornschier, V. and C. Chase-Dunn (eds.) The future of global conflict. London:
Sage Publications, pp. 262–284.
Brews, P. J., and C. L. Tucci (2003) “Internetworking: Building Internet-generation
Companies.” The Academy of Management Executive 17: 8–22.
Cantwell, J. (1989) Technological innovation and multinational corporations. Oxford, UK,
and Cambridge, MA: Basil Blackwell.
Christensen, C. M. (1997) The innovator’s dilemma: when new technologies cause great firms
to fail. Boston, MA: Harvard Business School Press.
Clark, N., F. Perez-Trejo, and P. M. Allen (1995) Evolutionary dynamics and sustainable
development: a systems approach. Aldershot, UK, and Brookfield, USA: Edward Elgar.
Dark, K. R. (1998) The waves of time: long-term change and international relations. London
and New York: Pinter.
Devezas, T. C., and J. T. Corredine (2001) “The Biological Determinants of Long-wave
Behavior in Socioeconomic Growth and Development.” Technological Forecasting and
Social Change 68: 1–57.
Devezas, T. C., and J. T. Corredine (2002) “The Nonlinear Dynamics of Technoeco-
nomic Systems: An Informational Interpretation.” Technological Forecasting and Social
Change 69: 317–335.
Devezas, T. C., and G. Modelski (2003) “Power Law Behavior and World System
Evolution: A Millennial Learning Process.” Technological Forecasting and Social Change
70: 798–838.
Duijn, J. J. V. (1983) The long wave in economic life. London and Boston, MA: George
Allen & Unwin.
Fenner, J. N. (2005) “Cross-cultural Estimation of the Human Generation Interval for
Use in Genetics-based Population Divergence Studies.” American Journal of Physical
Anthropology 128: 415–423.
Frank, A. G. (1998) ReOrient: global economy in the Asian age. Berkeley, CA: University
of California Press.
Freeman, C., and F. Louçã (2001) As time goes by: from the industrial revolutions to the
information revolution. Oxford, UK, and New York: Oxford University Press.
Freeman, C., and L. Soete (1997) The economics of industrial innovation. Cambridge, MA:
MIT Press.
Gilpin, R. (1996) “Economic Evolution of National Systems.” International Studies
Quarterly 40: 411–431.
Gilpin, R. (2001) Global political economy: understanding the international economic order.
Princeton, NJ: Princeton University Press.
Goldstein, J. S. (1988) Long cycles: prosperity and war in the modern age. New Haven, CT:
Yale University Press.
Griffin, L. J. (2004) “‘Generations and Collective Memory’ Revisited: Race, Region,
and Memory of Civil Rights.” American Sociological Review 69: 544–557.
Hobart, M. E., and Z. S. Schiffman (1998) Information ages: literacy, numeracy, and
the computer revolution. Baltimore, PA: Johns Hopkins University Press.
Jaeger, H. (1985) “Generations in History: Reflections on a Controversial Concept.”
History and Theory 24: 273–292.
Levathes, L. (1996) When China ruled the seas: the treasure fleet of the dragon throne,
1405-1433. New York: Oxford University Press.
McNeill, J. R., and W. H. McNeill. (2003) The human web: a bird’s-eye view of world
history. New York: W.W. Norton.

[17:08 25/8/2007 5019-modelski-ch05.tex] Job No: 5019 MODELSKI: Globalization as Evolutionary Process Page: 108 88–108
108 Rennstich
Modelski, G. (2000) “World System Evolution.” In: R. Denemark et al. (eds.) World
system history: the social science of long-term change. New York: Routledge.
Modelski, G., and W. R. Thompson (1996) Leading sectors andworld powers: the coevolution
of global politics and economics. Columbia, SC: University of South Carolina Press.
Nelson, R. R., and S. G. Winter (1982) An evolutionary theory of economic change.
Cambridge, MA: Belknap Press of Harvard University Press.
Perez, C. (2002) Technological revolutions and financial capital: the dynamics of bubbles and
golden ages. Cheltenham, UK: Edward Elgar Publishing.
Pomeranz, K. (2000) The great divergence: China, Europe, and the making of the modern
world economy. Princeton, NJ: Princeton University Press.
Porter, M. E. (1990) The competitive advantage of nations. New York: Free Press.
Rennstich, J. K. (2002) “The Phoenix-cycle: Global Leadership Transition in a Long-
wave Perspective”, paper presented at the annual meeting of the Political Economy
of World-Systems, University of California at Riverside, Riverside, CA.
Rennstich, J. K. (2003a) “Globalization and the Evolution of the Informational
Network Economy: Past, Present, and Future Technological Change.” Doctoral
Thesis, Indiana University, Bloomington, IN.
Rennstich, J. K. (2003b) “The Future of Great Power Rivalries.” In: Dunaway, W. A.
and I. M. Wallerstein (eds.), Emerging issues in the 21st century world-system: new
theoretical directions for the 21st Century world-system (2), Westport, CT: Praeger,
pp. 143–161.
Rennstich, J. K. (2004), “The Phoenix-cycle: Global Leadership Transition in a Long-
Wave Perspective.” In: Reifer, T. E. (ed.) Hegemony, globalization and antisystemic
movements. Boulder, CO: Paradigm Publishers, pp. 35–53.
Rennstich, J. K. (2005) “Three Steps in the Globalization of the International
System: Global Networks from 1000 B.C.E. to 2053 C.E.” In: Gills, B. K. and
W. R Thompson (eds.), Globalization and global history. London: Routledge.
Robertson, D. S. (1998) The new renaissance: computers and the next level of civilization.
New York: Oxford University Press.
Sassen, S. (2006) Territory, authority, rights: from medieval to global assemblages. Princeton,
NJ: Princeton University Press.
Scott, S. G., and V. R. Lane (2000) “A Stakeholder Approach to Organizational
Identity.” Academy of Management Review 25: 43–63.
Shapiro, S. S., and M. B. Wilk (1965) “An Analysis of Variance Test for Normality
(Complete Samples).” Biometrika 52: 591–611.
Shaw, M. (2000) Theory of the global state: globality as an unfinished revolution. New York:
Cambridge University Press.
Strauss, W., and N. Howe (1991) Generations: the history of America’s future, 1584 to
2069. New York: Quill.
Ziman, J. M. (2000) Technological innovation as an evolutionary process. Cambridge, UK,
and New York: Cambridge University Press.