CLD model

Causal Loop Diagram (CLD) is a graphical tool used to visually represent the causal relationships among variables within a system. It is a visual representation that illustrates how various factors in a system are interrelated in terms of positive and negative causal links, often forming loops.

Introduction

We may encounter questions about the organization’s strategic decisions, the complexity of social issues, or the impact of environmental changes on the enterprise. In this situation, we need a tool, a method that can reveal the core of the problem and capture the internal relationships of the system. The CLD model is just such a tool

Elements

Variables:Represent the primary states or accumulative variables in the system.

Flows:Represent the movement or interaction between variables.

Arrows:Indicate causal relationships between variables. The direction of the arrow signifies the direction of influence, whether positive or negative. Loops:Closed pathways formed by variables, which can be reinforcing (positive) or balancing (negative).

Relationships

1. Positive Relationship: A positive relationship means that the direction of change between two variables is consistent. When one variable increases, the other variable associated with it also increases, and vice versa. This relationship is usually represented by an arrow, with the direction of the arrow indicating the direction of change.

   Example: In a sales scenario, there may be a positive relationship between advertising investment and sales, that is, increasing advertising investment may lead to an increase in sales.

2. Negative Relationship: A negative relationship indicates that the direction of change between two variables is opposite. When one variable increases, the other variable decreases and vice versa. Also represented by arrows, the direction of the arrow indicates the trend of change.

   Example: In environmental science, there may be an inverse relationship between the number of trees and the amount of carbon dioxide in the air, where increasing the number of trees may lead to a decrease in carbon dioxide in the air.

3. Positive Feedback Loop: Positive feedback is a cyclic system in which changes in one variable cause changes in another variable, which in turn reinforces changes in the first variable. This cycle can cause the system to rapidly evolve in one direction until it reaches a certain limit.

   Example: In financial markets, positive feedback may cause prices to rise, attracting more investors, leading to more price increases.

4. Negative Feedback Loop: Negative feedback is a cyclic system in which changes in one variable cause changes in another variable, which in turn attenuates changes in the first variable. This cycle helps maintain the balance of the system.

   Example: In a temperature regulating system, negative feedback can cause the system to tend to maintain a constant temperature. When the temperature rises, the system takes steps to bring it down, and vice versa.

Adjustment of feedback

Positive feedback: The superposition of multiple positive relationships or multiple negative relationships appears as enhancement Negative feedback: A negative relationship with an odd number is expressed as negative feedback

Boundary

Defining boundaries helps focus attention on a specific problem or system. System scope that is too broad can lead to information overload and obscure problem analysis. By clearly defining boundaries, you can more clearly identify the focus of the problem, helping to build a more targeted and simpler CLD model.

CLD in research

Step by step

The establishment of CLD relationship is a step-by-step logical and sequential superposition.

Also have boundaries

Limit the relationship to three areas: traffic conditions, urban conditions, and land conditions.

Advantages, Disadvantages and Limitations

Advantages

1.Help to understand the relationship, find the inherent relationship

2.Using Causal relationships can predict the future

Disadvantages

1.Difficult to obtain data, especially when large-scale, complex systems are involved.

2.Complex system is not easy to manage and understand

Limitations

1.Simplify reality

2. subjective judgment

3. Easily lead to misleading conclusions –>Combine with other quantitative analysis methods and field surveys to obtain more comprehensive and accurate analysis results.

Reuse

Text and figures are licensed under Creative Commons Attribution CC BY 4.0. Source code is available at https://github.com/chadchae, unless otherwise noted. The figures that have been reused from other sources do not fall under this license and are recognized by footnoted text: “Figure from …”.

Comments/Corrections

To make comments about this posting or to suggest changes or corrections, send email to Chungil Chae (Chad), send a direct message on Twitter at @chadchae.