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Introduction to System Dynamics

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Luis Jesús Pérez Rivera

on 20 January 2016

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Transcript of Introduction to System Dynamics

Introduction to System Dynamics
Models
In the human mind there are just relations, images and abstractions.

Models are an abstract representation of a certain reality's aspect.


Paradigms
Paradigm is a filter trough we appreciate reality. It's rarely noticed or questioned.

It is the set of concepts, beliefs and thesis that are accepted by the scientific community in a certain time in history. Based upon it, all research activity is developed.

MODELS are
simplified
versions of the reality.

By designing models, non relevant variables from the analyst perspective will be excluded.


Paradigm in Social Sciences
Set of experiences, believes and values that affect the way in which an person perceives reality and the way the individual responds to that perception.
Mental models
Formal models
Commonly used.
Affected by psychological aspects.
It's the vision of the world from each person (paradigms).
They lack clarity.
Not effective for taking decisions.
Mathematically sustained.
Can show the dynamic consequences of the interactions.
The model can be shared without ambiguity.
They are compared to reality to make sure they are appropriate..
Why to model?
1. Human mind is not capable of foreseeing the dynamic consequences of the interactions between the elements of the system.

2. Intuition is not reliable when complex problems are being dealt with.

3. Analytic resolution methods are not feasible when non-lineal relations exist.
Why to model?
4. Reality comprehension is improved. Existent complex relations are made explicit.

5. Experimentation is possible. (at a low cost and risk)
The value of a model arises when it improves our comprehension of the characteristics of the behavior in a more effective way than if the system was observed in reality.
M Sc. Luis Jesús Pérez Rivera
System Dynamics Origins
- Cybernetics: Wiener (40's) / Ashby (50's)

- Servomecanism's theory:

Characteristics:

-
Feedback
- Dynamic behavior
- They regulate their own activity
System Dynamics Origins
He observed the feedback phenomena within the organizations.
Jay Forrester:
Creator of System Dynamics
MIT Sloan School of Management
1961: "Industrial Dynamics" (Industrial business cycles)

1968: "Principles of Systems " (Generalization of his previous work)

1969: "Urban Dynamics" (broader social problems)

1971: "World Dynamics" Derivation of his world at the Club of Rome (World population, evolution of natural resources, pollution).
Models: World1/World2
Jay Forrester's main publications
From the models of the Club of Rome emerges "The limits to Growth" by Donella Meadows presenting the model
World3
(5th order model)
System Dynamics Origins
System Dynamics. Fundamental Aspects.
Definition:
Discipline that studies the relations between the structure and the behavior of a system with the help of computer simulation models.
It's the study of how the feedback structure of a system defines its dynamic behavior.
Feedback
Process where information of the results of previously taken actions is constantly obtained.
Feedback loop
Close chain of actions.
It's the basic concept for the comprehension of the dynamic behavior.
Analyze the components of the cycle separately is not useful to understand the global behavior.
Causal Loop Diagrams (CLDs)
Are an important tool to represent the feedback structure of systems.

Excellent for:

Quickly capturing hypotheses about the causes of dynamics.
Building and capturing the mental models of individuals and teams.
Communicating the important feedback loops believed to be responsible for a problem.
In CLDs the variables are related by
causal links
, shown by arrows.

Each causal link has a polarity (positive or negative) to indicate how the dependent variable (cause) changes when the independent variable (effect) changes.

Important feedback loops are also identified on the diagram.
Positive Polarity
X Y
+
If X
increases
(
decreases
), then Y
increases
(
decreases
)
above
(
below
) what it would have been if the change hadn't occurred. In the case of accumulations X adds to Y.

X Y
X Y
Seen in another way:
Negative Polarity
X Y
-
If X
increases
(
decreases
), then Y
decreases
(
increases
)
below
(
above
) what it would have been if the change hadn't occurred. In the case of accumulations, X subtracts from Y.

X Y
X Y
Seen in another way:
Causal links and their polarities describe the structure of the system, not the system behavior.

They describe what would happen IF there was a change.

While determining the polarity of a causal link, it's assumed that the rest of the variables remain constant.
Reinforcing loop (Positive loop)
Self-
R
einforcing
They are responsible for growth processes.
The variation in an element spreads along the loop, reinforcing the original variation.
Often called virtuous or vicious cycles.
- It's a methodology for the study of complex systems, such as the ones found in business and other social systems.

- Modeling the structure helps considering details that are ignored on a mental model.

- It's a methodology to model and study the
behavior trough time
of any kind of system, analyzing how a structure change in a part of the system affect the behavior of the system as a whole.

- It's a tool to analyze policies and identify sources of resistance.


System Dynamics. Fundamental Aspects.
Self reinforcing loops examples
Balancing loop (Negative Loop)
- Self
B
alancig
- They are responsible for stabilization processes.
- A variation in an element is counteracted when it spreads along the loop.
- They tend to create equilibrium
System Dynamics Origins
Solve practical issues.

It arises in a time of changes, scientific and technological movements:

Computer and Informatics.
Cybernetics and feedback processes.
General Systems Theory
Interdisciplinary studies become important
Causal loop diagram notation
Dynamics of Multiple-Loop Systems
Guidelines for causal loop diagrams
Causal diagrams must include only (what you believe to be) genuine causal relationships.

Correlations among variables will emerge from the behaivor of the model when you simulate it.
1. Causality vs. Correlation
2. Label link and loop polarities
Determining loop polarity
There are two ways: The fast way and the right way
The Right way

Count the number of
negative links
on the loop:
If EVEN (eg. 2,4,6), then the loop is positive (
R
).

If

ODD (eg. 1,3,5), then the loop is negative (
B
)
A single negative link reverses the signal, - eg. an increase becomes a decrease - but another negative link reverses the signal again.
The Fast way
Trace the effect of a small change in one of the variables as it propagates around the loop.

If the feedback effect reinforces the original change, it's a positive loop (
R
).

If the feedback effect oposses the original change it's a negative loop (
B
).
Identify and label the polarity of the links and loops in the examples shown.
Challenge
3. Name your loops
4. Indicate important delays in cusal links
Different time delays in the response of gasoline demand and expenditures to price
Your causal diagrams should include delays that are important to the dynamic hypothesis or significant relative to your time horizon.
5. Variable names
Choose variables whose normal sense of direction is positive.
Avoid the use of variable names containing prefixes indicating negation (eg. non, un)
Should be nouns or noun phrases
. Remember that a CLD captures the structure of the system, not its behavior.
Must have a clear sense of direction.
The meaning of an increase or decrease must be clear.
6. Choose the right level of aggregation
Too much detail makes it hard to see the overall feedback structure and interaction between loops.

Too little detail may result in difficulties arising when someone else is trying to understand the logic of the model.
7. Make Goals of Negative Loops Explicit
All negative feedback loops have goals.
11. Distinguish between Actual and Perceived Conditions
There may be delays caused by reporting and measurement processes, along with bias and distortions.
Tips for causal loop diagrams layout
1. Use curved lines for information feedback, (easier feedback loop visualization).

2. Make important loops follow circular or oval paths.

3. Organize your diagrams to minimize crossed lines.

4. Avoid junk chart (e.g. symbols without meaning).

5. Iterate to find the best layout.
System Dynamics. Fundamental Aspects
System have characteristics that are product of their behavior and structure.

The feedback loop is the basic element for the comprehension of the dynamic behavior of a system.

A system dynamic behavior is determined by its structure.

The presence of delays cause oscillations.

Relations between variables can be linear or not.
assuming the initial chicken population is fairly small, but includes at least one rooster, What the behavior of the system would be when both loops are active?
More tips and guidelines...
Don't use time as a causal factor.
Think in quantitative variables.
Validate the units of variables.
Use short names with a clear meaning for your variables.
Don't use verbs. Actions are contained within the causal relationships.
Don't use causal links to express "and then..."
Don't try to always create feedback loops.
Avoid redundant / unreal loops.
youtube.com/watch?v=y-PvBo75PDo
youtube.com/watch?v=O-OqgFE9SD4
youtube.com/watch?v=m_ex_ejxzic&list=UU8A9L4UYgk_tTvkZhaDOLVQ
youtube.com/watch?v=9y46hJCaHVQ&list=UU8A9L4UYgk_tTvkZhaDOLVQ
Self reinforcing loops examples
Connection to the 5th discipline
"Systems thinking is a discipline for seeing the structures that underlie complex situations and for discerning high from low leverage change."

- Detail complexity: many variables
- Dynamic complexity: cause and effect are subtle and the effects over time of intervention are not obvious. (the leverage is here)
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