4.2.3.2 Reinforcing feedbacks

As in natural systems, tipping points in human systems are driven by self-reinforcing (mathematically ‘positive’) feedbacks: an increase in a variable leads to a closed loop of causal consequences that further increase the same variable. For example, one person or organisation’s decision to take the train rather than fly, or install solar panels, or pedestrianise a road, can increase the determination of others to do likewise. Such feedbacks are instrumental both in the enabling phase before a tipping point is reached and in the acceleration phase once a tipping point has passed (Figure 4.2.4). They can exist in any domain of human systems (social, economic, political and technological) and in their interactions with natural systems. For example, the self-reinforcing feedbacks of economies of scale and learning by doing have reduced the cost of solar PV and wind for energy generation to below that of coal power, with the result that most new power generation installed globally in 2022 was renewable (IEA, 2022). 

Synergies between self-reinforcing feedbacks across multiple domains can help policymakers further enable the conditions for positive tipping (Fesenfeld et al., 2022, Pahle, 2018). Fesenfeld et al., (2022) highlight that synergies between policy-induced technological and behavioural changes can create self-reinforcing feedbacks and political conditions for positive tipping. For example, the German Renewable Energy Sources Act (EEG) triggered synergistic feedback effects in financial investment, technological innovation and cost reductions of renewable energy (Schmidt and Sewerin, 2018). Other self-reinforcing feedbacks associated with such policy interventions include shifts in public opinion, social norms and practices in favour of renewable energy, which in turn can reduce political opposition and create windows of opportunity for more stringent policy options, such as carbon taxation (Figure 4.2.4) (Fesenfeld et al., 2022; Lockwood, 2013; Schmid et al., 2019). Building on this logic in socio-technical transitions research, Geels and Ayoub (2023) distinguished seven feedback loops between behaviours of different social actors and technological changes in tipping dynamics.

Moreover, feedback and spillover effects between regions can play an important role in catalysing global change. For example, the German feed-in tariff created a first marketplace for solar PV panels that in turn has led to economies of scale in the production process of such panels in China. This has led to substantial cost reductions of solar panels so that PV became an attractive clean technology option at the global level. In turn, this has created a political momentum for change in other regions, such as China, the EU and US. In the transport sector, macro-economic modelling shows that mandates for switching to electric vehicles in major automobile markets such as China, the US or Europe can help to accelerate tipping points in other markets (Lam and Mercure, 2022).