System Dynamics: Energy, Information, and Feedback Loops

Posted on Nov 27, 2024 in Social sciences

System Element

A system requires energy and information inputs from its environment (e.g., sun, earth, water) to function and sustain its internal components, including living organisms (fauna).

The term “energy” encompasses all these necessary inputs. A system’s input current represents the energy required for its operation and maintenance.

Generally, the energy within an environmental care system follows the law of conservation: the energy remaining in a system equals the imported energy minus the exported energy.

Systems utilize various resources:

• Material Resources
• Financial Resources
• Human Resources
• Information

However, information is a unique form of energy that doesn’t adhere to the law of conservation. Instead, it follows the law of increments.

The Law of Increments states that the information remaining in a system isn’t the difference between input and output. Rather, it’s the sum of existing information plus new incoming information. The system accumulates information; output doesn’t deplete it.

VarID R. Sabih’s Law of Requisite Variety states that for one control system to effectively manage another, its capacity to absorb variety must match the variety it receives. Two key observations arise:

• A system’s potential states (variety of means) are practically infinite, while its capacity to capture environmental variety is limited.
• According to the Law of Requisite Variety, a system must be able to absorb the variety produced by its environment. This is impossible unless the system has mechanisms to reduce environmental variety.

Conversion Process: Systems capture energy and information from the environment, process it, and potentially release it back as a product. There are two types of processes:

• Processes directly contributing to the final product.
• Supporting or ancillary processes.

Graphics are taken from the book “Introduction to General Systems Theory”

Output Current: This represents the system’s export to the environment—the product it delivers. There are two types:

• Positive Output Current: Beneficial to the community.
• Negative Output Current: Detrimental to the community.

A viable system prioritizes positive output currents to ensure its own survival and adaptation to environmental demands. This allows it to continuously acquire necessary input currents.

Stafford Beer defines a viable system as one capable of adapting to a changing environment. Three key characteristics are:

• Self-organization: Maintaining a stable structure while adapting to changing requirements.
• Self-control: Keeping key variables within acceptable limits (area of normality).
• Autonomy: Possessing sufficient resources and freedom to maintain variables within their normal range.

Some output currents (e.g., hobbies, aesthetics, values) may not be directly beneficial but don’t necessarily imply negative impacts.

The activity cycle describes the relationship between input and output currents. A functioning system captures inputs and generates outputs.

Feedback Stream: This communication loop assesses system performance and facilitates optimization. It involves:

• Capturing information from the output current.
• Comparing results against a standard output stream.
• Improving material and energy intake.
• Improving system conversion processes.
• Encouraging positive feedback loops.

Feedback provides information on the system’s progress toward its objective. This information is reintroduced to make necessary adjustments. It acts as a control mechanism, ensuring goal achievement.

Two types of feedback exist:

• Corrective Feedback Current (Negative Feedback)
• Positive Feedback Current (Amplifying Feedback)

Sensors (cybernetic systems) determine whether the output current is positive or negative.

Objectives of General Systems Theory (GST)

GST has two main objectives, based on levels of ambition and confidence (reliability and coverage of the event):

• Low ambition, high confidence: Identifying isomorphisms and similarities across disciplines to develop theoretical models applicable to specific fields.
• High ambition, high confidence: Developing a comprehensive “system of systems” framework, functioning within a gestaltic theoretical structure.

K. Boulding emphasizes that abstract knowledge requires nurturing to flourish and be shared effectively. He also highlights the importance of transparency in scientific endeavors.

W. Churchill stressed the importance of individual contributions to the overall system’s success.

H. Simon observed a phenomenon of selective perception in industry, where individuals only process information that aligns with their preconceptions.

Approaches to Developing GST

Two main approaches exist:

• Observing empirical phenomena across disciplines and building theoretical models to explain them. This approach aims to reduce the set of all conceivable systems to a more manageable size.
• Classifying empirical fields hierarchically based on the complexity of their basic organizational units and developing appropriate levels of abstraction. This systematic approach leads to a “system of systems” concept.

Boulding proposes a hierarchical order of system levels:

1. Static structures (e.g., atomic model)
2. Simple dynamic systems (e.g., solar system)
3. Cybernetic systems (e.g., thermostat)
4. Open systems (e.g., cells)
5. Genetic-social systems (e.g., plants)
6. Animal systems
7. Human systems
8. Social structures (e.g., companies)
9. Transcendental systems (e.g., the universe)

Some scholars add a tenth level: Ecological systems.

Practical Applications of GST

• Cybernetics (Norbert Wiener): Uses mechanisms to automate processes and predict future events.
• Information Theory: Quantifies and organizes information, transforming chaos into order (information = negative entropy).
• Game Theory (Von Neumann): Creates scenarios to analyze strategic decision-making in competitive situations.
• Decision Theory: Generates possible solutions to problems (optimal and suboptimal) and selects the best option, considering perfect and imperfect competition.
• Relational Topology/Mathematics: Analyzes phenomena within a given context.
• Factor Analysis: Breaks down complex phenomena into individual factors for independent study.
• Systems Engineering: Analyzes, designs, and implements systems.
• Operations Engineering: Focuses on the scientific control of existing systems.

Principle of Bodies in Balanced Systems

Systems within a larger system strive for equilibrium, even without direct interaction.

Physical Laws (Newtonian Perspective)

• A body remains at rest or in uniform motion unless acted upon by an external force. A system in its optimal state experiences no external influence (inertia of rest).
• When a system is disturbed, it responds in a way that seeks to restore equilibrium (inertia of motion).
• For every action, there is an equal and opposite reaction. A disruptive force acting on a system elicits a balancing response.

Principle of Organicity

Evolutionary processes demonstrate an increase in the degree of organization, particularly in open systems like living organisms.

Definitions of organicity:

• Systems strive for greater stability or increased entropy (disorganization).
• Greater organization implies greater complexity.
• All living matter structures itself in a fundamental way (law of organization).

Bodies (Living or Open Systems)

Organisms possess balancing mechanisms (homeostatic mechanisms) that regulate inputs and outputs within acceptable limits. These mechanisms influence the system’s progression or regression.

Systems evolve towards greater complexity; regression is not inherent. Evolution is an increase in complexity, while involution is a decrease.

Entropy and Negentropy

Entropy represents chaos. System entropy tends to increase. Maximum entropy occurs when a system is on the verge of transitioning to a new state.

Negentropy represents order. It’s the process of organizing data into information, controlling uncertainty.

Objectives, Priorities, and Exchange

Organizational Objectives

The traditional objective of any organization is profit maximization (revenue exceeding costs). However, a holistic perspective considers the entire system, including factors like pollution, worker well-being, and ethical considerations.

Profit maximization isn’t always the primary focus. Other considerations include:

• Closed Model: Understanding inputs, given known processes and outputs, to optimize the input-output relationship.
• Constrained Maximization: Organizational or governmental policies may restrict profit levels.
• Economic Man vs. Organized Man: The economic man focuses on monetary returns, while the organized man prioritizes system benefit.

Simon argues that the economic man maximizes economic gain, while the organized man maximizes satisfaction.

Hierarchy of Objectives (Downs)

1. Final Objective: The ultimate goal, representing the organization’s overall purpose.
2. Social Behavior Objectives: Shared goals within a social group, influencing behavioral patterns.
3. Personal Objectives: Individual or company objectives related to survival and purpose.
4. Office Objectives: Specific organizational objectives.

Hierarchy of Objectives (Perrow)

• Social Objectives: Goals of an organized group.
• Consumer Objectives: Product-focused objectives, evaluating output based on consumer satisfaction.
• System Objectives: The overall rationale and purpose of the system.
• Product Objectives: Meeting product standards and achieving the desired end goal.
• Derivative Objectives: The impact of the product on a specific area.

Objectives can be categorized as:

• General Objectives: The system’s rationale.
• Specific Objectives: Activities to be accomplished.
• Operational Objectives: Tasks to be performed.