20
F. Maggino et al.
multi-indicators system) allows a full and correct understanding of complexity (see
e.g., Bruggemann and Patil 2011).
Meadows (2009) defines a system as “an interconnected set of elements that
is coherently organized in a way that achieves something” (Meadows 2009,
11). This definition identifies the three main components of a system: elements,
interconnections and functions. A system is not just a collection of things; they
must be interconnected and have a purpose, i.e. they must be aimed at achieving
an objective. The purpose of a system is often difficult to understand. “The best
way to deduce the system’s purpose is to watch for a while to see how the system
behaves” (Meadows 2009, 14). From this Meadows’ statement, it can be deduced
that a system has its own behaviour, different from its parts and that, like any
behaviour, it can change over time. Each system is based on a stock, i.e. the elements
that constitute it in a given time. These stocks change over time due to the effect
of flows. “Flows are filling and draining, births and deaths, purchases and sales,
growth and decay, deposits and withdrawals, successes and failures” (Meadows
2009, 18). Meadows highlights the dynamism of the systems, their adaptation over
time. One cannot understand them without understanding their dynamics of stocks
and flows. Obviously, the change can concern both the system as such and one or
even all of its essential components. Change can also be traumatic and unexpected.
Most of systems are able to withstand the impact of drastic changes thanks to one
of their fundamental characteristics, resilience. “It is both the ability to adapt to
change by evolving and the ability to resist it by restoring its initial state. Resilience
presupposes change: it is not static being, but becoming” (Alaimo 2020, 21). A
system is, therefore, an organic, global and organized entity, made up of many
different parts, aimed at performing a certain function. If one removes a part of
it, its nature and function are modified; the parts must have a specific architecture
and their interaction makes the system behave differently from its parts. Systems
evolve over time and most of them are resilient to change.
Simple systems are characterized by few elements and few relationships between
them; they can be analyzed analytically. Complex systems, on the contrary, are made
up of many elements and many relations of different types; they can be analyzed
only in a synthetic way. In a complex system, elements and connections, besides
being numerous, are various and different.
A particular type of complex system is the Complex Adaptive System (CAS).
They add to the other characteristics typical of complex systems the ability to
adapt. CASs are able to adapt to the world around them by processing information
and building models capable of assessing whether or not adaptation is useful. The
elements of the system have the main purpose of adapting and, in order to achieve
this purpose, they constantly look for new ways of doing things and learning,
thus giving rise to real dynamic systems. These systems challenge our ability to
understand and predict. “It is evident that the main characteristics of complex
adaptive systems are typical of social organizations and phenomena. Each of them is
made up of a network of elements, which interact both with one another and with the
environment. They are multidimensional and their different elements or dimensions
are linked together in a non-linear way. They evolve over time, modifying both
F. Maggino et al.
multi-indicators system) allows a full and correct understanding of complexity (see
e.g., Bruggemann and Patil 2011).
Meadows (2009) defines a system as “an interconnected set of elements that
is coherently organized in a way that achieves something” (Meadows 2009,
11). This definition identifies the three main components of a system: elements,
interconnections and functions. A system is not just a collection of things; they
must be interconnected and have a purpose, i.e. they must be aimed at achieving
an objective. The purpose of a system is often difficult to understand. “The best
way to deduce the system’s purpose is to watch for a while to see how the system
behaves” (Meadows 2009, 14). From this Meadows’ statement, it can be deduced
that a system has its own behaviour, different from its parts and that, like any
behaviour, it can change over time. Each system is based on a stock, i.e. the elements
that constitute it in a given time. These stocks change over time due to the effect
of flows. “Flows are filling and draining, births and deaths, purchases and sales,
growth and decay, deposits and withdrawals, successes and failures” (Meadows
2009, 18). Meadows highlights the dynamism of the systems, their adaptation over
time. One cannot understand them without understanding their dynamics of stocks
and flows. Obviously, the change can concern both the system as such and one or
even all of its essential components. Change can also be traumatic and unexpected.
Most of systems are able to withstand the impact of drastic changes thanks to one
of their fundamental characteristics, resilience. “It is both the ability to adapt to
change by evolving and the ability to resist it by restoring its initial state. Resilience
presupposes change: it is not static being, but becoming” (Alaimo 2020, 21). A
system is, therefore, an organic, global and organized entity, made up of many
different parts, aimed at performing a certain function. If one removes a part of
it, its nature and function are modified; the parts must have a specific architecture
and their interaction makes the system behave differently from its parts. Systems
evolve over time and most of them are resilient to change.
Simple systems are characterized by few elements and few relationships between
them; they can be analyzed analytically. Complex systems, on the contrary, are made
up of many elements and many relations of different types; they can be analyzed
only in a synthetic way. In a complex system, elements and connections, besides
being numerous, are various and different.
A particular type of complex system is the Complex Adaptive System (CAS).
They add to the other characteristics typical of complex systems the ability to
adapt. CASs are able to adapt to the world around them by processing information
and building models capable of assessing whether or not adaptation is useful. The
elements of the system have the main purpose of adapting and, in order to achieve
this purpose, they constantly look for new ways of doing things and learning,
thus giving rise to real dynamic systems. These systems challenge our ability to
understand and predict. “It is evident that the main characteristics of complex
adaptive systems are typical of social organizations and phenomena. Each of them is
made up of a network of elements, which interact both with one another and with the
environment. They are multidimensional and their different elements or dimensions
are linked together in a non-linear way. They evolve over time, modifying both