2.2 Recessions—Traffic Jams in the World Economy?
19
2.2 Recessions—Traffic Jams in the World Economy?
Economic supply chains may exhibit a similar kind of behavior, as illustrated by John
Sterman’s “beer distribution game”.
4 The game simulates some of the challenges of
supply chain management. When playing it, even experienced managers will end up
ordering too much stock, or will run out of it.
5 This situation is as difficult to avoid as
stop-and-go traffic. In fact, our scientific research suggests that economic recessions
can be regarded as a kind of traffic jam in the global flow of goods, i.e. the world
economy. This insight is actually somewhat heartening, since it implies that we may
be able to engineer solutions to mitigate economic recessions in a similar way as one
can reduce traffic jams by driver assistant systems. The underlying principle will be
discussed later, in the chapter on Digitally Assisted Self-Organization. In order to
do this, however, one would need have real-time data detailing the global flow and
supply of materials.
2.3 Systemic Instability
Crowd disasters are another, tragic example of systemic instability. Even when every
individual within a crowd is peacefully minded and tries to avoid harming others,
many people may die nevertheless. Appendix 2.1 outlines why such extreme systemic
outcomes can result from normal, non-aggressive behavior.
What do all these examples tell us? They illustrate that the natural (re)actions of
individuals will often be counterproductive.
6 Our experience and intuition often fail
to account for the complexity of highly interactive systems, which tend to behave
in unexpected ways. Such complex dynamical systems typically consist of many
interacting components which respond to each other’s behaviors. As a consequence
of these interactions, complex dynamical systems tend to self-organize. That is, some
collective dynamics may develop (such as stop-and-go traffic), which is different from
the natural behavior of the system components when they are separated from each
other (such as drivers who don’t like to stop). In other words, the overall system may
show new characteristics that are distinct from those of its components. This can
result, for example, in “chaotic” or “turbulent” dynamics.
Group dynamics and mass psychology may be viewed as typical examples of
spontaneously emerging collective dynamics occurring in crowds. What is it that
makes a crowd turn “mad”, violent, or cruel? For example, after the London riots
of 2011, people have asked how it was possible that teachers and the daughters of
millionaires—people you would not expect to be criminals—were participating in
the looting? Did they suddenly develop criminal minds when the demonstrations
against police violence turned into riots? Possibly, but not necessarily so.
4 Sterman and Sterman [2], Helbing and Lämmer [3].
5 Nienhaus et al. [4].
6 Dorner [5].
19
2.2 Recessions—Traffic Jams in the World Economy?
Economic supply chains may exhibit a similar kind of behavior, as illustrated by John
Sterman’s “beer distribution game”.
4 The game simulates some of the challenges of
supply chain management. When playing it, even experienced managers will end up
ordering too much stock, or will run out of it.
5 This situation is as difficult to avoid as
stop-and-go traffic. In fact, our scientific research suggests that economic recessions
can be regarded as a kind of traffic jam in the global flow of goods, i.e. the world
economy. This insight is actually somewhat heartening, since it implies that we may
be able to engineer solutions to mitigate economic recessions in a similar way as one
can reduce traffic jams by driver assistant systems. The underlying principle will be
discussed later, in the chapter on Digitally Assisted Self-Organization. In order to
do this, however, one would need have real-time data detailing the global flow and
supply of materials.
2.3 Systemic Instability
Crowd disasters are another, tragic example of systemic instability. Even when every
individual within a crowd is peacefully minded and tries to avoid harming others,
many people may die nevertheless. Appendix 2.1 outlines why such extreme systemic
outcomes can result from normal, non-aggressive behavior.
What do all these examples tell us? They illustrate that the natural (re)actions of
individuals will often be counterproductive.
6 Our experience and intuition often fail
to account for the complexity of highly interactive systems, which tend to behave
in unexpected ways. Such complex dynamical systems typically consist of many
interacting components which respond to each other’s behaviors. As a consequence
of these interactions, complex dynamical systems tend to self-organize. That is, some
collective dynamics may develop (such as stop-and-go traffic), which is different from
the natural behavior of the system components when they are separated from each
other (such as drivers who don’t like to stop). In other words, the overall system may
show new characteristics that are distinct from those of its components. This can
result, for example, in “chaotic” or “turbulent” dynamics.
Group dynamics and mass psychology may be viewed as typical examples of
spontaneously emerging collective dynamics occurring in crowds. What is it that
makes a crowd turn “mad”, violent, or cruel? For example, after the London riots
of 2011, people have asked how it was possible that teachers and the daughters of
millionaires—people you would not expect to be criminals—were participating in
the looting? Did they suddenly develop criminal minds when the demonstrations
against police violence turned into riots? Possibly, but not necessarily so.
4 Sterman and Sterman [2], Helbing and Lämmer [3].
5 Nienhaus et al. [4].
6 Dorner [5].