Electric vehicle (EV) adoption is not determined by technology alone. It also depends on how governments, industries, infrastructure, and public support develop together, while overcoming resistance from established fossil-fuel and automotive interests. Comparing California, Texas, and Michigan, we show why some states have progressed much faster than others. As responsibility for transport decarbonization increasingly shifts to state governments in the United States, our findings highlight the need for policies tailored to local economic, political, and industrial conditions rather than a one-size-fits-all approach.

Although socio-technical feedback studies have recently raised increasing interest in understanding the acceleration of sustainability transitions, limited studies can explain why these feedback loops differ across places. Thus, they provide limited explanations for why different places manifest different paces of low-carbon transitions. To address this gap, we develop a framework that links feedback loops with contextual moderators to reflect place-specific feedback dynamics. We identify five reinforcing loops: industrial transformation, technological change, infrastructure investment, behavior change, and environmental legitimacy, with two balancing loops rooted in fossil-fuel resistance and legacy automotive lock-ins. Additionally, we argue that state-level governance capacity and policy orientation perform as contextual moderators shaping the strength and interactions of these feedback loops. We apply our framework to a comparative case study of EV transitions in California, Texas, and Michigan to demonstrate how these feedback dynamics, together with their divergent contextual moderators, impact their different paces of EV transitions. Studying state-level EV transitions in the United States is particularly timely and policy-relevant, considering recent federal rollbacks.

Why do some U.S. states lead in EV transitions? Place-specific governance shapes the pace of change.

A key process suggested to foster fast, nonlinear change and accelerate the energy transition is social tipping. Social tipping dynamics in low-carbon transitions occur when a small change or intervention in the socioeconomic system has a large effect on emission reductions. When tipping in one system or sector spills over to another system or sector, this may lead to tipping cascades, accelerating the overall transition, further weakening the old system, and reinforcing the new, ultimately reaching the regime tipping point. Leveraging such tipping cascades requires a model of how social processes and interventions scale up (upward scaling cascades) through socioeconomic systems. In this paper, we therefore present a stylized agent-based model to explore the emergence of cascades from the existing evidence about interactions within and between sectors. The model provides insights into the interactions between positive and balancing feedback loops, the potential for lock-ins (or reverting to the old system), and potential leverage points. Specifically, we focus on interactions between energy, mobility, and housing.

The challenge of climate change mitigation is unprecedented. Staying within a maximum global warming of 1.5 requires accelerating the transition to a low-carbon society. We model how interactions between heat pumps (HPs), electric vehicles (EV), solar panels, and home batteries (HBs) can accelerate the transformation to decentralized and sustainable household energy provision.

Modeling how interactions between HPs, EV, solar panels, and HBs can accelerate the energy transition.

Achieving sustainability and climate goals requires accelerating the transition from fossil fuels to renewable energy. This study explores how and why Australia’s electricity transition has accelerated in recent years. By examining developments in solar and wind technologies, policies, and public attitudes, the research uncovers the feedback mechanisms and ‘tipping points’ that have driven progress and those that now risk slowing it. The findings provide new insights for policymakers and investors seeking to sustain momentum in clean energy transitions while managing emerging social, technical, and policy challenges.

Understanding the mechanisms that accelerate sustainability transitions is critical for achieving climate targets. This study provides new empirical insights through a socio-technical analysis of Australia’s electricity transition, focusing on wind and solar photovoltaic. Integrating theories of multi-level transitions, acceleration dynamics, and positive tipping points, we develop a taxonomy of feedback mechanisms relating to niche acceleration, regime decline, and niche deceleration. Using longitudinal analysis, process tracing, and qualitative system dynamics, we identify, categorise, and map 25 reinforcing and balancing feedbacks influencing the pace and direction of change. The analysis shows that Australia’s transition has unfolded through alternating periods of acceleration and deceleration in technology diffusion, shaped by interacting techno-economic, policy, and social actor feedbacks. Early public support and targeted policies triggered acceleration in the 2000s, while major cost reductions and industry advocacy reinforced momentum after 2016. Reinforcing feedbacks driving fossil-fuel regime decline emerged only once renewables reached a critical market share, whereas new balancing feedbacks, such as grid constraints, supply chain pressures, and policy misalignment, now present deceleration risks. The study advances understanding of acceleration dynamics by explicitly mapping causal feedback structures and revealing their sequencing, comparative strength, and cumulative effects. These insights inform adaptive policy strategies to sustain transition momentum.

Unpacking the feedbacks that are accelerating and slowing Australia’s clean energy transition.

Our time seems to be trapped in a paradox. On the one hand, the capacity to master information has tremendously increased, but on the other hand the capacity to use the knowledge humanity produces seems at stake. There is a gap between our capacity to know and our capacity to act. We attempt to better understand that situation by considering the evolution of knowledge processing along human history, in particular the relation between the development of information technologies and the complexity of societies, the balance between the known and the unknown, and the current emergence of autonomous machines allowing intelligent processes.

Information-processing capacities developed historically in conjunction with the complexity of human societies. Positive feedback loops contributed to the co-evolution of knowledge, social organization, environmental transformation, and information technologies. Very powerful loops now drive the rapid emergence of global digital platforms, disrupting legacy organizations and economic equilibria. The simultaneous emergence of the awareness of the sustainability conundrum and the digital revolution is striking. Both are extremely disruptive and contribute to a surge in complexity, but how do they relate to each other? Paradoxically, as the capacity to master information increases, the capacity to use the knowledge humanity produces seems to lag. The objective of this paper is to analyze the current divergence between knowledge and action, from the angle of the co-evolution of information processing and societal transformation. We show how the interplay between perception and action, between the known and the unknown, between information processing and ontological uncertainty, has evolved toward a sense of control, a hubris, which abolishes the unknown and hinders action. A possible outcome of this interplay might lead to a society controlled to stay in its safe operating space, involving a strong delegation of information processing to autonomous machines, as well as extensive forms of biopolitics.

The sustainability conundrum and the digital revolution are entangled phenomena leading to complexity and disruption.