Terms like green transition, sustainability transition, and the circular economy are frequently used in the media to draw attention to the urgent need to mitigate climate change and halt biodiversity loss. Despite nuanced differences, the concepts share a common focus: driving changes that must occur simultaneously across multiple levels of action. However, achieving that is far more challenging than it appears. 

The sustainability transition is often described as a super wicked problem because it meets four distinct criteria: i) solutions are time-sensitive, as the window for action is closing rapidly; ii) no single entity has the authority or capacity to address the issue independently; iii) the very actors expected to implement solutions are often contributors to the problem, and iv) short-term, narrow interests frequently undermine sustainable solutions, despite their long-term rationality. 

While promoting sustainability transitions is as complex as squaring the circle, inaction is not ethically, morally, or economically viable. Success depends on identifying and amplifying enablers of positive change while mitigating unintended consequences. In essence, achieving sustainability requires the simultaneous application of both acceleration and braking mechanisms. 

Can complexity theory provide a meaningful framework for advancing a sustainability transition?

It certainly has the potential to do so. Complexity theory has been depicted as a powerful approach to understanding emergent phenomena arising from the interdependence of actors, systems, and events. 

At its core, complexity theory emphasizes the importance of relationships over individual components of a system. It cautions against oversimplification occasioned by breaking systems into parts, which often leads to overestimating or underestimating the role of specific actors. Complexity theory proposes self-organizing and spontaneous processes where actors respond dynamically to emerging threats and opportunities without top-down coordination. These processes rely on cyclical feedback loops: positive feedback reinforces change, while negative feedback balances and stabilizes the system. Such dynamics often result in nonlinear development, where even small interventions can trigger significant shifts—or, conversely, large-scale interventions fail to produce noticeable results. Development is path-dependent, shaped by past events and constrained by the available choices moving forward. 

Although complexity theory does not discount the value of planning, it places greater emphasis on the adaptive capacity of actors. Doing so involves adapting to the environment and actively shaping it through decisions and behaviors. A sustainability transition involves both systems and their environments co-evolving, advancing—or regressing—together. 

What could this mean in the context of a sustainability transition? 

For example, the International Energy Agency’s net-zero scenario predicts that clean energy technologies will unlock new business opportunities, create jobs, and foster innovation. However, such outcomes are far from guaranteed. Technological progress does not occur in isolation but is deeply intertwined with economic, legal, political, and social structures. Success in sustainability transitions depends on the pace of technological advancements, the adaptability of businesses, the active engagement of citizens and communities, and a solid institutional foundation. This foundation must be built on fruitful dialogue between decision-makers who use scientific knowledge and the researchers who generate it. 

Sustainability transitions require mutually reinforcing actions at different levels. For instance, progress will stall if a government sets ambitious emission reduction targets, but local authorities lack the resources or expertise to implement them. In such cases, rather than fostering self-organization, the result is inertia. Beyond developing technical capabilities, effective regulation and economic incentives are needed to encourage sustainable investments. 

Growth in renewable energy adoption, for instance, can create positive feedback loops: costs decrease as technologies advance and investments grow, making sustainability increasingly attractive for a broader range of actors. At the same time, addressing resistance to change is essential, especially in sectors dependent on fossil fuels. Electric vehicle use works well in urban areas with dense charging networks but it is a less attractive option in remote regions. 

Sustainability transitions, in essence, involve reshaping the attractor landscape. This term refers to a collection of principles that maintain system logic within specific boundaries. The landscape emerges from the interplay of deliberate, goal-oriented actions (such as regulations) and autonomous behaviors (such as innovation). An attractor landscape provides predictability, steering actors toward sustainable solutions while discouraging choices that exacerbate climate change. For instance, economic measures like congestion charges reduce car use and generate funds to develop low-emission public transport. Concurrently, investments in infrastructure, such as pedestrian and cycling pathways, offer appealing alternatives that promote sustainable mobility. Communicating the health benefits of walking and cycling reinforces those options’ attractiveness. Together, such measures can create an attractor landscape where sustainable mobility becomes the dominant norm rather than just one choice among many. 

Although complexity theory is not a silver bullet, it offers a valuable framework for simultaneously analyzing factors that enable and hinder sustainability transitions, providing insights at both societal and individual levels.