The major characteristics of dynamic complexity include: Non-linearity: Dynamic complexity is characterized by non-linear relationships, meaning that small changes in one variable can lead to disproportionate or unexpected effects on other variables within the system. This non-linearity can result in amplification or dampening of effects, making predictions and outcomes challenging to anticipate. Feedback Loops: Feedback loops are an essential component of dynamic complexity. They occur when the output of a system feeds back into the system as an input, influencing its behavior. Feedback loops can be positive (reinforcing) or negative (balancing). Positive feedback loops amplify changes, leading to exponential growth or instability, while negative feedback loops regulate or stabilize the system. Delays: Delays refer to the time it takes for a change in one variable to produce a noticeable effect on another variable within the system. Delays can introduce time lags, making it difficult to anticipate and respond to changes effectively. Delays can lead to oscillations, oscillating patterns, or unintended consequences in complex systems. Emergent Behavior: Dynamic complexity often gives rise to emergent behavior, which is the collective behavior of the system that cannot be attributed solely to the behavior of its individual components. Emergent behavior results from the interactions and interdependencies among system elements and is often not directly observable from studying the components in isolation.

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Explain the major characteristics of dynamic complexity (updated 2023)
Purpose This assignment is intended to help you: Summarize the key concepts of organizational
systems thinking.
Explain the major characteristics of dynamic complexity. Action Items
(This assignment is modified from the Dynamic Complexity Exercise on p. 289 of your
textbook.) In one to two sentences
each, summarize the following system characteristics that contribute to dynamic complexity:
Change Trade-offs History dependency Tight coupling Nonlinearity Read the case study on page
289. (ATTACHED) Write a 300- to 500-word explanation of how the system characteristics
listed above are expressed in the case study.
Dynamic complexity
refers to the intricate and interconnected nature of systems where cause-and-effect relationships
are not linear or predictable. It involves the presence of feedback loops, delays, non-linear
relationships, and interactions among multiple variables.
The major characteristics of dynamic complexity include:
1. Non-linearity: Dynamic complexity is characterized by non-linear relationships, meaning
that small changes in one variable can lead to disproportionate or unexpected effects on
other variables within the system. This non-linearity can result in amplification or
dampening of effects, making predictions and outcomes challenging to anticipate.
2. Feedback Loops: Feedback loops are an essential component of dynamic complexity.
They occur when the output of a system feeds back into the system as an input,

2. influencing its behavior. Feedback loops can be positive (reinforcing) or negative
(balancing). Positive feedback loops amplify changes, leading to exponential growth or
instability, while negative feedback loops regulate or stabilize the system.
3. Delays: Delays refer to the time it takes for a change in one variable to produce a
noticeable effect on another variable within the system. Delays can introduce time lags,
making it difficult to anticipate and respond to changes effectively. Delays can lead to
oscillations, oscillating patterns, or unintended consequences in complex systems.
4. Emergent Behavior: Dynamic complexity often gives rise to emergent behavior, which is
the collective behavior of the system that cannot be attributed solely to the behavior of its
individual components. Emergent behavior results from the interactions and
interdependencies among system elements and is often not directly observable from
studying the components in isolation.
5. Sensitivity to Initial Conditions: Dynamic complex systems can be highly sensitive to
initial conditions, meaning that small variations or perturbations in the starting state can
lead to significant differences in the system’s behavior over time. This sensitivity can
result in a wide range of possible outcomes and make long-term predictions challenging.
6. Unpredictability: Due to the non-linear nature and interdependencies of variables,
dynamic complexity often leads to unpredictability. Even minor changes or disturbances
can propagate and produce large-scale, unexpected effects. This unpredictability makes it
difficult to accurately forecast or control complex systems.
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