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agent-based modeling, which is a computational technique used for simulating systems composed of huge numbers of components.
The hope is that such an integrated simulation of the whole economy could provide a realistic test bed for evaluating different strategies for economic stimulus, such as whether to reduce taxes or increase public spending; and perhaps most important, to be able to predict tipping points or forecast imminent crises so as to avoid potential recessions or even eventual collapse.
Clearly, both approaches are needed: the generality and parsimony of “universal” laws and systematic behavior reflecting the big picture and dominant forces shaping general behavior, coupled with and informed by detailed modeling reflecting the individuality and uniqueness of each company.
companies do indeed scale following simple power laws and as anticipated they do so with a much greater spread around their average behavior than for either cities or organisms.
crucial aspect of the scaling of companies is that many of their key metrics scale sublinearly like organisms rather than superlinearly like cities. This suggests that companies are more like organisms than cities and are dominated by a version of economies of scale rather than by increasing returns and innovation.
growth in both organisms and cities is fueled by the difference between metabolism and maintenance.
the total income (or sales) of a company can be thought of as its “metabolism” while expenses can be thought of as its “maintenance” costs.
companies manifest yet another variation on this general theme by following a path that sits at the cusp between organisms and cities. Their effective metabolic rate is neither sub- nor superlinear but falls right in the middle by being linear.
Expenses, on the other hand, scale in a more complicated fashion: they start out sublinearly but, as companies become larger, eventually transition to becoming approximately linear. Consequently, the difference between sales and expenses, which is the driver of growth, also eventually scales approximately linearly.
linear scaling leads to exponential growth and this is what all companies strive for.
the economy continues to expand at an exponential rate because the overall performance of the market is effectively an average over the growth performances of...
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the idealized growth curve of companies has characteristics in common with classic sigmoidal growth in biology in that it starts out relatively rapidly but slows down as companies become larger and maintenance expenses transition to becoming linear. However, unlike biology, whose maintenance costs do not transition to linearity, companies do not cease growing but continue to grow exponentially, though at a more modest rate.
After growing rapidly in their youth, almost all companies with sales over about $10 million end up floating on top of the ripples of the stock market.
companies become vulnerable if they are unable to keep up with the growth of the market. This is greatly exacerbated if a company is not sufficiently robust to withstand the continual ups and downs inherent in the market as well as in its own finances.
We, too, are finely balanced between metabolism and maintenance costs, a condition biologists refer to as homeostasis.
Ultimately, we reach a stage where even a small perturbation such as a minor cold or heart flutter can lead to death.
the general dynamics and overall life history of companies are effectively independent of the business sector in which they operate.
What is the special property of exponentials that they describe the decay of so many disparate systems? It’s simply that they arise whenever the death rate at any given time is directly proportional to the number that are still alive. This is equivalent to saying that the percentage of survivors that die within equal slices of time at any age remains the same.
the risk of a company’s dying does not depend on its age or size.
Just as all organisms must die in order that the new and novel may blossom, so it is that all companies disappear or morph to allow new innovative variations to flourish:
In 2000 Foster wrote an influential best-seller on business, aptly titled Creative Destruction.
the probability of a company’s lasting for one hundred years is only about forty-five in a million,
However, it is well known that there are lots of companies, especially in Japan and Europe, that have lived for hundreds of years.
these outliers have survived not by diversifying or innovating but by continuing to produce a perceived high-quality product for a small, dedicated clientele.
Standard company organizational charts are typically top-down, having a treelike structure superficially suggestive of a classic self-similar fractal.
it is not at all clear that the “official” organizational charts of companies represents the actuality of what the real operational network structures are.
The fact that companies scale sublinearly, rather than superlinearly like cities, suggests that they epitomize the triumph of economies of scale over innovation and idea creation.
To achieve greater efficiency in the pursuit of greater market share and increased profits, companies stereotypically add more rules, regulations, protocols, and procedures at increasingly finer levels of organization, resulting in the increased bureaucratic control that is typically needed to administer, manage, and oversee their execution.
the relative amount allocated to R&D systematically decreases as company size increases, suggesting that support for innovation does not keep up with bureaucratic and administrative expenses as companies expand.
While the dimensionality of cities is continually expanding, the dimensionality of companies typically contracts from birth through adolescence, eventually stagnating or even further contracting as they mature and move into old age.
The great challenge for companies is how to balance the positive feedback from market forces, which strongly encourage staying with “tried and true” products versus the long-term strategic need to develop new areas and commodities that may be risky and won’t give immediate return.
an essential feature of the long-term sustainability challenge embodied in the paradigm of complex adaptive systems; namely, the pervasive interconnectedness and interdependency of energy, resources, and environmental, ecological, economic, social, and political systems.
We need a broad and more integrated scientific framework that encompasses a quantitative, predictive, mechanistic theory for understanding the relationship between human-engineered systems, both social and physical, and the “natural” environment—a framework I call a grand unified theory of sustainability.
In biology, the network principles underlying economies of scale and sublinear scaling have two profound consequences. They constrain the pace of life—big animals live longer, evolve more slowly, and have slower heart rates, all to the same degree—and limit growth. In contrast, cities and economies are driven by social interactions whose feedback mechanisms lead to the opposite behavior.
Moreover, the social network dynamic underlying superlinear scaling leads to open-ended growth, which is the primary assumption upon which modern cities and economies are based. Continuous adaptation, not equilibrium, is the rule.
However, there is a big catch with potentially huge consequences.
in the superlinear case, the general solution exhibits an unexpectedly curious property technically known as a finite time singularity, which is a signal of inevitable change, and possibly of potential trouble ahead.
A finite time singularity simply means that the mathematical solution to the growth equation governing whatever is being considered—the population, the GDP, the number of patents, et cetera—becomes infinitely large at some finite time
This is obviously impossible, and that’s why somethi...
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Simple power laws and exponentials are continuously increasing functions that also eventually become infinitely large, but they take an infinite time to do so.
This kind of growth behavior is clearly unsustainable because it requires an unlimited, ever-increasing, and eventually infinite supply of energy and resources at some finite time in the future in order to maintain it. Left unchecked, the theory predicts that it triggers a transition to a phase that leads to stagnation and eventual collapse,
data on population growth and the growth of financial and economic indicators strongly support the theoretical predictions that we have been growing superexponentially and are indeed headed toward such a singularity.
this situation is qualitatively quite different from classic Malthusian dynamics, where this is no such singularity.
there has to be a transition from one phase of the system to another having very different characteristics, analogous to the way the condensation of steam to water which subsequently freezes to ice epitomizes transitions between different phases of the same system, each having quite different physical properties.
to avoid collapse a new innovation must be initiated that resets the clock, allowing growth to continue and the impending singularity to be avoided.
Having made the transition and “reset the clock” to avoid stagnation and collapse, the process begins all over again with the continuation of superexponential growth,
to sustain open-ended growth in light of resource limitation requires continuous cycles of paradigm-shifting innovations
There’s yet another major catch, and it’s a big one. The theory dictates that to sustain continuous growth the time between successive innovations has to get shorter and shorter.
This leaves open the intriguing question as to whether an analogous singularity dynamic has played a similar role in driving biological innovation
A singularity is a point at which a mathematical function is no longer “well behaved” in some specific way,
