Components are individual parts of a system that combine to make a larger whole. Components are not limited to physical objects; they may also include reservoirs where matter or energy is held, societal entities, system attributes, or a subsystem within the larger system.
The components of a system depend on how the boundaries of that system are defined. Narrow system boundaries exclude more components, while broader boundaries include more. As additional components are considered, the number of interactions between components increase, creating systems with higher complexity and more emergent properties.
To provide an example of potential system components, we must first define the system. If your system is a person riding a bicycle excluding the environment, system components can include the bike frame, pedals, tires, chain, rider, and rider actions. If your system is a person riding a bike including the environment, system components can include the bike frame, pedals, tires, chain, rider actions, road conditions, traffic, weather, and even hills.
Interconnections are the relationships between the components of a system that allow the system to function. Interconnections hold the system together and reveal how the manipulation of one component can affect another or even the entire system.
Interconnections between components are the relationships that allow for the expression of emergent properties. These relationships create interactions among the components, which allows the entire system to express characteristics that are greater than the sum of their parts.
In the context of riding a bicycle, a sequence outlining the interconnections of potential system components is as follows: Pedalling → Chain Movement → Wheel Rotation → Bicycle motion
An emergent property is a function of a system that arises from components working together. This function cannot be replicated by any one isolated component, as new behaviors and traits only “emerge” when the components interact through interconnections.1
1. Carmichael, S. T. Emergent Properties of Neural Repair: Elemental Biology to Therapeutic Concepts. Ann Neurol 2016, 79 (6), 895–906. https://doi.org/10.1002/ana.24653
In many cases, emergent properties of complex systems can be negative or undesirable in effect. The implementation of systems thinking, which allows you to examine these emergent properties, allows these unintended consequences to be examined and mitigate undesirable effects.2
2. Emergence: The Key to Understanding Complex Systems. https://systemsthinkingalliance.org/the-crucial-role-of-emergence-in-systems-thinking/ (accessed 2026-07-09).
In the context of the system of an individual riding a bike, the successful transportation of the individual from point A to B can be considered an emergent property. A wheel cannot transport the rider on its own, pedals cannot create movement independently, and a rider standing beside a bicycle is not cycling.
Feedback loops are self-perpetuating mechanisms of change and their subsequent response(s) to that change. They involve a cyclical process where the output of the system is circled back and used as input to either amplify the effect of the disturbance, an amplifying feedback loop, or diminish the effects of the disturbance, a balancing feedback loop.3
3. Feedback Loops – Complex Systems Frameworks Collection. https://www.complexsystemsframeworks.ca/framework/feedback-loops/ (accessed 2026-07-09).
The behavior of a feedback loop, whether it has a balancing or amplifying effect, is a direct result of the type of loop it is. Neither type of loop has inherently beneficial or detrimental effects, the outcome of its behavior is dependent on the system the feedback loop is embedded within.
In the context of an individual riding a bicycle, balancing feedback and reinforcing feedback loops can be outlined as follows:
Balancing = Bicycle leans left → rider notices imbalance → rider steer slightly right → balance restored
Reinforcing = Pedalling faster → bicycle gains speed → great momentum → easier to maintain balance → rider pedals faster
A leverage point is a component of a system that can be targeted by a disturbance to achieve a desired or predicted outcome. These are points where small changes can have a disproportionately strong influence on the system by triggering a larger system change.4
4. Steele, R. Identifying Leverage Points – a Systems Thinking Perspective and Approach. https://www.unescap.org/sites/default/files/Session%202.%20Identifying%20leverage%20points_0.pdf (accessed 2026-09-07).
Leverage points are places where small actions can cause great change with significantly less effort. They are easily triggered by disturbances and are inherently positive in nature as they are used to achieve a desired outcome and improve performance.
If an individual was riding a bicycle and struggling to cycle uphill, shifting to a lower gear to make pedalling easier could be considered a leverage point.
A boundary shows the limit or edge of a system by separating it from its surrounding environment. When boundaries are widened, new influences become visible.
Since boundaries divide a system from its environment, the way in which the boundaries are defined directly influences the properties of the system. As boundaries get larger and more components are included in the system, the number of interconnections and potential for emergent properties increases. As boundaries are narrowed and components are excluded, interconnections break and emergent properties fail to be expressed.
A narrow boundary in the context of an individual riding a bicycle: system only includes the individual and the bicycle.
An expanded boundary in the context of an individual riding a bicycle: system includes the individual, the bicycle, and the surrounding environment like the weather, traffic, hills and bike lanes.
The dynamics of a system can be understood as the behavior that describes how a system, or component of a system, act over time based on circular, interconnected cause/effect relationships.
Feedback loops are the hidden structures that drive system dynamics. The system is continuously responding to change through circular cause and effect relationships or feedback loops. Adjustments, whether reinforcing or balancing, are not one-time actions.5
5. Parkinson, J. A.; Gould, A.; Knowles, N.; West, J.; Goodman, A. M. Integrating Systems Thinking and Behavioural Science. Behav Sci (Basel) 2025, 15 (4), 403. https://doi.org/10.3390/bs15040403.
As the terrain under the bicycle is not consistent, the rider must continuously adjust the handlebars to maintain balance. Steering once to turn left at the beginning of a ride does not eliminate the need to turn left again later.
Putting all the elements together:
In the bicycle and person system, the components (bike parts and rider) are connected through interconnections that create the emergent property of the successful transportation of the individual from point A to B. Feedback loops help maintain balance or amplify instability, leverage points improve performance like easier pedaling, boundaries determine whether environmental components are included or excluded, and dynamics explains how the system behaves over time.
To model how to apply the elements of systems thinking to chemistry concepts, we will use a glass of water as the system of interest.
Putting all the elements together:
Components (atoms and molecules) interact through interconnections (bonding and intermolecular forces), creating emergent properties like surface tension and solvent behavior. Feedback loops influence system stability, either amplifying temperature change or balancing it. Leverage points such as temperature can shift system behavior through phase changes, boundaries determine what interactions are considered, and dynamics explain how water changes across time.