8.2.1 Insights from Energy Transition Studies

Energy transition studies provide insights into how sequential events lead to shifts in energy generation and consumption patterns. Energy transitions involve changes in fuels and their associated technologies and systems (Hirsh & Jones, Reference Hirsh and Jones2014), including economic systems (Fouquet & Pearson, Reference Fouquet and Pearson2012) and their rise to claim substantial market shares (Smil, Reference Smil2010a,Reference Smilb). On average, energy transitions have been observed to progress from an initial share of 1%–10% of the energy consumption for a particular service in a specific sector, eventually reaching 50%, 90% and even 99% (Grubler et al., Reference Grubler, Wilson and Nemet2016). The duration from the invention of a critical technology to an 80% share of energy consumption averages around 95 years (Fouquet, Reference Fouquet2016), indicating a relatively slow pace. However, it is important to note that such state changes proceed non-linearly compared to typical technological diffusion and substitution (Grubler, Reference Grubler1996).

Historical energy transitions further illustrate the concepts of speed, duration and acceleration. The Netherlands’ transition to fossil gas, Ontario’s coal retirements and Denmark’s shift to heat and power systems occurred relatively quickly, demonstrating that rapid transitions are possible (Sovacool, Reference Sovacool, Hess, Amir, Geels, Hirsh, Medina and Yearley2020). Similarly, Indonesia’s shift from kerosene to gas for cooking was achieved in just 10 years (Thoday et al., Reference Thoday, Benjamin, Gan and Puzzolo2018). Additionally, the rapid transition from incandescent bulbs to LED lighting exemplifies swift changes in consumption patterns (International Energy Agency, 2020; Zissis et al., Reference Zissis, Bertoldi and Serrenho2021). The transportation sector also showcases accelerated sustainability transitions. The shift from horse-drawn transportation to railways in the 1850s occurred within a few decades (Geels, Reference Geels2005). More recently, the transition from internal combustion engines to electric vehicles is gaining momentum (Bloomberg NEF, 2021; Muratori et al., Reference Muratori, Alexander, Arent, Bazilian, Cazzola, Dede and Ward2021), driven by advances in battery technology, declining costs and increasing consumer demand for sustainable transportation (Muratori et al., Reference Muratori, Alexander, Arent, Bazilian, Cazzola, Dede and Ward2021).

8.2.2 Critiques and Considerations

Despite these examples of rapid transitions, some scholars argue that complex technological and economic factors can slow down rapid changes. For instance, Smil (Reference Smil2016) notes that historical global energy transitions have often taken considerable time, citing that coal took 60 years to provide half of the world’s energy supply. The global energy system remains heavily reliant on fossil fuels, with little evidence that the transition away from coal is accelerating. In response to scepticism about rapid transitions, Grubler et al. (Reference Grubler, Wilson and Nemet2016) offer a nuanced critique, suggesting that the speed of past transitions should be understood in light of factors such as the complexity of the technology, the length of the formative phases in technology development, spatial diffusion and market size. They argue that future sustainability transitions will differ significantly from historical ones. Rapid transitions are often characterised by substituting older technologies with established alternatives without significant disruption or the need for integration with existing infrastructures. Successful transitions also benefit from knowledge spillovers, smaller markets (e.g. Ontario’s transition to hydropower (Sovacool, Reference Sovacool2016; Rosenbloom et al., Reference Rosenbloom, Haley and Meadowcroft2018)) and tangible advantages for end-users, such as improved health outcomes (e.g. Indonesia’s switch to LPG cooking (Sovacool, Reference Sovacool2016; Thoday et al., Reference Thoday, Benjamin, Gan and Puzzolo2018)), convenience and well-coordinated public policies (e.g. France’s adoption of nuclear energy (Jasper, Reference Jasper2014)).

8.2.3 The Concept of Timescapes

While speed, duration and acceleration are key aspects of temporalities in sustainability transitions, another important dimension is timescapes, a concept that integrates various temporal dynamics. Derived from Appadurai’s (Reference Appadurai1996) notion of scapes, timescapes reflect the complex interplay of temporal rhythms and structures (Bornemann & Strassheim, Reference Bornemann and Strassheim2019). Scapes are dynamic constructs that encompass various dimensions of global cultural flows, interactions and imaginaries (Appadurai, Reference Appadurai1996). A timescape, therefore, refers to the intricate interplay of temporal dimensions within sustainability transitions, including the rhythms, sequencing and temporal structures that influence speed, duration and acceleration. Timescapes are not static; they are interconnected and constantly evolving networks shaped by global cultural processes, such as the Paris Agreement and visions of sustainable futures (cf. Bornemann & Strassheim, Reference Bornemann and Strassheim2019). This concept suggests the complexities and interconnections inherent in contemporary global dynamics, emphasising the role of culture, communication and power – akin to ‘landscape pressures’ in the Multilevel Perspective (see Chapter 2) – in shaping the trajectories of sustainability transitions in the modern world.

8.3.1 Temporality, Technological Choices and Innovation

The field of sustainability transition research emphasises the importance of considering the timeline of socio-technical developments, which can range from long-term social and cultural shifts to short-term changes in practices and project implementations (Geels & Schot, Reference Geels and Schot2007). For example, Grubler et al. (Reference Grubler, Wilson and Nemet2016) highlight the relationship between the speed of transitions and the complexity of technological systems. They argue that complex transitions are slower because new, intricate socio-technical combinations require significant time to emerge (cf. Loorbach et al., Reference Loorbach, Rotmans, Kemp, de Roo and Hillier2016). The longevity of large-scale energy infrastructures and industries (Smil, Reference Smil2016) has resulted in significant carbon lock-ins and path-dependent futures within established socio-technical systems (Unruh, Reference Unruh2000).

Within the timescapes of sustainability transitions, it is crucial to distinguish between a ‘grand’ transition – characterised by pervasive changes in a socio-technical system that affect resources, carriers and end-use applications – and the concepts of substitution and diffusion (Grubler et al., Reference Grubler, Wilson and Nemet2016). Substitution involves replacing one technology with another without disrupting or needing to integrate existing institutions and infrastructures. In contrast, diffusion refers to the gradual adoption of technology over time. While substitution can occur rapidly, Grubler et al. (Reference Grubler, Wilson and Nemet2016) suggest that both diffusion and a ‘grand’ transition are inherently lengthy processes involving interrelated technologies, infrastructures and institutions. Consequently, these lengthy processes may contribute to a slower transition.

8.3.2 Temporality, Income and Consumption

Historical evidence indicates a strong correlation between the speed of sustainability transitions and shifts in resource consumption from one energy source to another. For example, the transition from biomass to coal in the late nineteenth century, followed by the shift from coal to oil after World War II (Fouquet, Reference Fouquet2016; Pearson, Reference Pearson, Webb, Wade and Tingey2021), highlights the close relationship between resource consumption patterns and sustainability transitions. As more individuals transition from fossil fuel-powered cars to electric vehicles (Sioshansi & Webb, Reference Sioshansi and Webb2019), a projected increase in energy demand is anticipated (Bogdanov et al., Reference Bogdanov, Ram, Aghahosseini, Gulagi, Oyewo, Child and Breyer2021). This rise in the adoption of new technologies, particularly as their costs decrease, can stimulate demand for sustainable alternatives and further accelerate the sustainability transition. Additionally, the growing utilisation of AI computing power and servers, expected to contribute to an uptick in electricity consumption, may also impact overall energy demand (Koot & Wijnhoven, Reference Koot and Wijnhoven2021).

Historically, rising incomes have led to increased energy demand, as seen in the UK (Fouquet, Reference Fouquet2016). This trend suggests that sustainability transitions can accelerate as energy consumption increases in industrialising economies, particularly in developing countries now and in the future (Delina, Reference Delina2017; Kober et al., Reference Kober, Schiffer, Densing and Panos2020). While heightened energy demand may incentivise continued reliance on fossil infrastructure, it also signals a growing market for sustainable energy alternatives. As energy demand rises, a critical opportunity exists to redirect investments and innovations towards sustainable energy solutions, thereby driving the acceleration and scaling up of energy transitions.

8.3.3 Temporality and Markets

Time and cost reductions are other critical factors for accelerating sustainability transitions. Prices are crucial in these rapid shifts, particularly regarding the willingness to invest in niche technologies (Geels et al., Reference Geels, Kern and Clark2023). A historical example is the transition from gas to electric lighting in the late nineteenth century, where theatres and restaurants adopted electric lighting despite the higher costs (Fouquet, Reference Fouquet2016). Although renewable technologies have proven their affordability and market readiness (IRENA, 2019; Timilsina, Reference Timilsina2021; Luderer et al., Reference Luderer, Madeddu, Merfort, Ueckerdt, Pehl, Pietzcker and Kriegler2022), many developing countries still need prices to decrease further to compete with fossil fuels (Delina, Reference Delina2017). Lowering these costs could facilitate a faster transition (Fouquet, Reference Fouquet2016). An illustrative example of a tipping point is the significant drop in solar and wind power costs over the past decade, making them increasingly competitive with conventional fossil fuels (IRENA, 2019; Luderer et al., Reference Luderer, Madeddu, Merfort, Ueckerdt, Pehl, Pietzcker and Kriegler2022). Furthermore, projections from the International Renewable Energy Agency (2020) indicate that these cost declines are expected to continue, further expediting the transition to renewable energy sources.

In addition to cost reductions, the time required to construct renewable energy infrastructure has also decreased (Luderer et al., Reference Luderer, Madeddu, Merfort, Ueckerdt, Pehl, Pietzcker and Kriegler2022). This reduction in both temporal and financial investments for establishing renewable energy systems enhances the feasibility of transitioning to sustainable energy sources, thereby fostering a swifter adoption of renewables (Bloomberg NEF, 2021; Luderer et al., Reference Luderer, Madeddu, Merfort, Ueckerdt, Pehl, Pietzcker and Kriegler2022). However, factors such as the stage of diffusion, the sequence of spatial diffusion and market size influence changes in market shares (Grubler et al., Reference Grubler, Wilson and Nemet2016). To accelerate sustainability transitions, sustainable technologies and systems must be implemented simultaneously, supported by appropriate policies and deployed across multiple market sizes (Way et al., Reference Way, Ives, Mealy and Farmer2022).

Policymakers must collaborate with influential actors, such as investors, to drive this change. However, partnering with established players can create tensions, especially when they control the technologies and intellectual property essential for rapid transitions (Ciplet and Harrison, Reference Ciplet and Harrison2020). This dynamic may result in large-scale transition pathways that neglect local and small-scale initiatives, which are crucial for ensuring just transitions (Newell et al., Reference Newell, Geels and Sovacool2022; van Bommel & Höffken, Reference van Bommel and Höffken2023). As a result, financial actors with the capital needed to accelerate transitions often prioritise large-scale investments, further sidelining smaller efforts.

8.3.4 Temporality, Politics, Institutions and Policy

Sustainability transitions involve various actors and institutions, including policymakers, government and the market (Sanderink & Nasiritousi, Reference Sanderink and Nasiritousi2020; Delina, Reference Delina2017; also see Chapters 3 and 14 in this book). Understanding the pace of these transitions requires considering factors like temporality, politics, institutions and policies. Supportive measures, such as subsidies, equitable market conditions and effective institutional arrangements, are crucial in facilitating sustainability transitions (Delina, Reference Delina2017).

Subsidies and other supportive policies can help bridge the cost gap between sustainable and traditional technologies, especially in developing countries where sustainable options remain expensive (Rentschler & Bazilian, Reference Rentschler and Bazilian2017; BNEF, 2020). Additionally, fostering a fair market landscape through policies that promote competition and prevent market distortions is integral to successful sustainability transitions (Rentschler & Bazilian, Reference Rentschler and Bazilian2017). Supportive institutional arrangements, including regulatory frameworks and development support, also create an enabling environment for accelerating sustainability transitions (IEA, 2020; Delina, Reference Delina2017; also see Chapters 5 and 14). However, political and institutional factors can significantly influence sustainability transitions. For instance, a concentrated nuclear industry with substantial political influence in France has likely slowed the country’s shift to renewables (Jasper, Reference Jasper2014). Similarly, in the United States, heavy lobbying by fossil fuel companies has likely obstructed climate policy and energy transition efforts (Downie, Reference Downie2019). Thus, the pace and timescapes of sustainability transitions are contingent upon evolving political dynamics and interests.

8.3.5 Temporality, End-Users and the Public

Sustainability transitions are socially complex, making it essential to understand the public’s role and the passage of time (Skjølsvold & Coenen, Reference Skjølsvold and Coenen2021; Küpers & Batel, Reference Küpers and Batel2023). The public significantly influences processes that ensure a just transition. Social movements, such as the climate action movement, have raised awareness and pressured governments to shift towards renewable energy sources (IPCC, 2018; Komendantova, Reference Komendantova2021). Community energy projects empower local communities to develop and own renewable energy sources, fostering public support for the transition (Bauwens, Reference Bauwens2019). Germany’s Energiewende, supported by public backing, has successfully increased the share of renewable energy in its energy mix (Heinrich, Reference Heinrich2018). Additionally, in-my-backyard movements focus on developing renewable energy sources locally while addressing community concerns (Sovacool, Reference Sovacool2019).

Understanding the diverse interests of the public (Skjølsvold & Coenen, Reference Skjølsvold and Coenen2021) is crucial for policymakers and researchers aiming to accelerate sustainability transitions. Policymakers must consider this diversity (see Chapter 12) when designing effective and just policies, while researchers should incorporate these factors in their analyses. The ability of end-users to adapt to their changing needs and desires (Grubler et al., Reference Grubler, Wilson and Nemet2016; Süsser et al., Reference Süsser, Gaschnig, Ceglarz, Stavrakas, Flamos and Lilliestam2022) also influences the speed of sustainability transitions. These varied end-user experiences inform technology development and promote broader sustainability innovations, including knowledge spillovers, entrepreneurialism and niche applications for pilots and demonstrations (Blanco et al., Reference Blanco, de Coninck, Agbemabiese, Anadon, Lim, Pengue and Winkler2022). However, addressing the tension between inclusive participation and the pace of sustainability transitions is vital, broadening the debate on transition speed. This is especially crucial for including often-excluded actors, groups and regions, recognising and analysing polycentric governance (Newell et al., Reference Newell, Geels and Sovacool2022; Skjølsvold & Coenen, Reference Skjølsvold and Coenen2021; see Chapters 9, 15 and 21 in this book), and considering justice issues, particularly human rights and environmental impacts, in sustainability transition policies (van Bommel & Höffken, Reference van Bommel and Höffken2023).

8.3.6 Temporality and Just Transitions

Accelerated sustainability transitions can negatively impact vulnerable populations facing resource access challenges and marginalisation. For instance, studies indicate that rural communities may be left behind in the energy transition if policymakers do not prioritise energy access (Clausen & Rudolph, Reference Clausen and Rudolph2020; Chan & Delina, Reference Chan and Delina2023). A historical example is the introduction of steam engines during the Industrial Revolution, which led to rapid urbanisation and increased urban consumption (Allen, Reference Allen2009), leaving rural areas underdeveloped and exacerbating poverty in remote areas (Acheampong et al., Reference Acheampong, Nghiem, Dzator and Rajaguru2023; see Chapter 23; cf. Chapter 22). Today, the most energy-poor members of society, often living in remote areas without electricity grid access, are also the poorest (Hanke et al., Reference Hanke, Grossmann and Sandmann2023; see Chapter 23). Although renewable energy projects in rural areas have the potential to provide electricity and create employment opportunities for those living in poverty, challenges such as lack of financing, technical expertise and supportive policies hinder these benefits (Sergi et al., Reference Sergi, Babcock, Williams, Thornburg, Loew and Ciez2018; Fathoni et al., Reference Fathoni, Setyowati and Prest2021; see Chapter 15). Furthermore, large-scale renewable energy projects in countries like Ghana and Mexico seem to have only minimally benefited rural communities (Bukhari et al., Reference Bukari, Kemausuor, Quansah and Adaramola2021; de Jesus Fernandez & Watson, Reference de Jesus Fernandez and Watson2022).

To prevent the marginalisation of rural populations in sustainability transitions, policymakers are well advised to prioritise resource access and design projects that consider the needs of local communities (Clausen & Rudolph, Reference Clausen and Rudolph2020). Successful community-led sustainability initiatives, such as the First Nations-led renewable energy projects in Canada (Stefanelli et al., Reference Stefanelli, Walker, Kornelsen, Lewis, Martin, Masuda and Castleden2019), highlight the importance of prioritising resource access for marginalised communities, potentially through subsidies for off-grid renewable energy systems (Gebreslassie et al., Reference Gebreslassie, Cuvilas, Zalengera, To, Baptista, Robin and Castán Broto2022). However, it is crucial to recognise that enhanced stakeholder engagement, such as through ‘energy democracy’, which aims to empower local communities in energy decision-making, may lead to uneven opportunities for participation when certain groups dominate the dialogue or when resources for engagement are inequitably distributed, perpetuating inequalities in access and representation (Newell et al., Reference Newell, Geels and Sovacool2022). This may result in place-related injustices, such as the exclusion of rural voices in decision-making processes, the prioritisation of urban over rural needs and the unequal distribution of environmental benefits and burdens (Skjølsvold & Coenen, Reference Skjølsvold and Coenen2021) (also see Chapter 16 in this book).

8.4.1 Inter, Multi- and Trans-Disciplinary Research

Examining the temporal dimensions within sustainability transitions represents a significant area of research that warrants greater attention. Diverse temporal understandings and their connections to various aspects of sustainability transitions exist across different societies and contexts. Therefore, it is key for future research to explore the heterogeneous and global interpretations of competing timeframes (Delina & Janetos, Reference Delina2017). Furthermore, recognising that these temporalities are intertwined with power dynamics and politics is vital, similar to the role of technologies in transitions (Jasanoff, Reference Jasanoff, Jasanoff and Kim2015; Delina & Janetos, Reference Delina2017).

To investigate the political underpinnings of temporalities in sustainability transition research, future studies could examine broader conceptions of political and social structures encapsulated within temporal frameworks. It is also vital to consider whose voices are amplified and who is marginalised, as well as how temporal structures in sustainability transitions may exacerbate vulnerability or enhance resilience. By probing these issues, researchers can critically assess the political dimensions of pressing sustainability transition targets, such as deadlines for achieving net-zero economies (Marquardt & Delina, Reference Marquardt and Delina2021).

Interdisciplinary, multidisciplinary and transdisciplinary research approaches offer valuable avenues for comprehensively exploring temporalities within sustainability transition research (Kleinman, Reference Kleinman2018; Sovacool et al., Reference Sovacool, Hess, Amir, Geels, Hirsh, Medina and Yearley2020). By collaborating with scholars from diverse fields, researchers can better understand the intricate and evolving processes involved in sustainability transitions. Interdisciplinary research integrates insights and methodologies from various disciplines to address temporal research inquiries (Thompson Klein et al., Reference Thompson Klein2001). In contrast, multidisciplinary research employs different perspectives to tackle a shared research question. For instance, interdisciplinary studies on the temporal aspects of sustainability transitions may involve partnerships between economists, sociologists and environmental scientists to comprehend the economic, social and ecological ramifications of various sustainability transition scenarios. Transdisciplinary research combines knowledge and methodologies from multiple disciplines while actively engaging non-academic actors to address temporal issues in sustainability transition studies (Thompson Klein et al., Reference Thompson Klein2001).

8.4.2 Multi- and Mixed-Methods Research Approaches

Multi-method research approaches provide a valuable means to examine and study the temporalities of sustainability transitions (Shove & Walker, Reference Shove and Walker2014; Geels, Reference Geels2018; Sovacool et al., Reference Sovacool, Hess, Amir, Geels, Hirsh, Medina and Yearley2020). By combining qualitative and quantitative methods, researchers can better understand the complex and dynamic processes involved. Relying on a single method may fail to capture the full range of factors influencing sustainability transitions, as it can overlook critical perspectives and nuances that a multi-faceted approach can reveal.

Qualitative methods, such as interviews and focus groups, offer insights into the experiences, perspectives (see Chapter 19) and values of sustainability transition actors (see Chapters 12 and 17). Conversely, quantitative methods, including statistical analysis and modelling, help identify patterns and trends in resource use, technology acceptance and sustainability transitions over time. Moreover, multi- and mixed-methods research can help overcome the limitations of individual approaches (Sovacool et al., Reference Sovacool, Hess, Amir, Geels, Hirsh, Medina and Yearley2020). For instance, while small sample sizes may restrict qualitative methods, quantitative methods may only partially capture the nuances of social and cultural factors influencing sustainability transitions. By integrating different research methods, researchers can provide a more holistic view of the intricate processes involved in energy transitions, ultimately informing policy and practice (Strengers, Reference Strengers2018).

9.2.1 Interaction 1: Differentiation

Niches protect, nurture and empower experimentation in sustainability in ways that regimes either ignore or address only superficially. In other words, a founding interaction between niche and regime is one of opposition and differentiation. Niches try to do things in profoundly different ways and there is a clear aspiration to stretch and transform regimes in fundamental ways. Niches reject the regime ways of innovating and seek alternatives. Niche spaces contain antagonistic features in relation to regimes.

9.2.2 Interaction 2: Appropriation

Whilst niches are defined through differentiation, it is often the case that specific elements of their socio-technical configuring activities offer readily appropriable innovations for regimes. Those elements can be specific technological or organisational innovations that can be inserted into regimes without too much disruption. This involves processes for diffusing that innovation out of the supportive context of the niche and adapting and embedding it within the regime. A fit-and-conform dynamic dominates this interaction (Smith & Raven, Reference Smith and Raven2012). The regime is more eco-efficient as a result, but is not fundamentally changed.

9.2.3 Interaction 3: Hybridisation

Hybridisation involves interactions that generate stretch-and-transform reconfiguration processes in the regime. Elements of the novel technologies, organisational forms and norms experimented with in niches are not simply appropriated into regimes but retain the capacity to alter some broader dimension of the regime in a quite fundamental way. A new technology design becomes dominant, for example, or the organisation of actors in the regime becomes more decentralised, say, or some regime rules are rewritten. Policy advocacy and intermediary support are important enablers of hybridisation (Chapter 20). Both serve as bridges between, on the one hand, adaptations to niche practices so that these can influence the regime which, and on the other hand, supports accommodating changes in the regime that makes it receptive to the niche innovation.

9.2.4 Interaction 4: Criticism

Even when hybridisation leads to regime transformation, the results can be disappointing when compared to niche aspirations. More radical experiments remain stuck in the niche space. However, this does not necessarily equate to a lack of interaction. Niche experiments can embody radical ideas, values and practices that are vital to the deeper politics of sustainability transitions (Smith, Hargreaves, Hielscher, Martiskainen, & Seyfang, Reference Smith, Hargreaves, Hielscher, Martiskainen and Seyfang2016). Radical alternatives in niche spaces confront the compromises of hybridisation by maintaining radical difference and resisting co-option. Experiments are seen as demonstrative of the political and economic power relations that need changing (e.g. the way capital is invested, the ideology of the state, the quality of democracy), and thus experiments are emblematic anticipations of deeper sustainability transformations. Critical niches are important for keeping political and economic transformations in view and in debate.

Even this simple list of four interactions makes it difficult to talk about reconfiguration as a single process originating in niches and transforming regimes. Interactions take different forms, work in both directions simultaneously, and they are likely to have varying consequences.

9.3.1 Automating Sustainability

The automation regime is an important enabler of sustainability in the Fourth Industrial Revolution. As Klaus Schwab, Executive Chairman of the World Economic Forum puts it:

Management consultants, research institutes, governments, investors, industrialists and politicians argue that advanced deployments of cloud computing, the Internet of Things, robotics, 3D printing, big data, machine learning, synthetic biology, and smart materials will enable the automated control over sustainable systems of production and consumption. This activity constitutes the automation regime and its sustainability. A proponent of an earlier wave of automation provided a useful definition that is still relevant:

The automation regime today encompasses vastly more complex systems. The kinds of feedback and interactions are more sophisticated, and the scope of application is more ambitious. Automation spreads beyond established workplace and household settings and is applied to the control of urban systems, farming and food, health services, energy grids, policing and warfare, mobility and logistics, social welfare and public affairs.

Sustainability will be achieved through the automated engineering insertion of the environment into cyber-physical systems of production and consumption. The integration of computation into physical processes in real time is being developed through the widespread use of embedded sensors and control exerted over digital platforms and data centres. Environmental sustainability is seen in terms of an automation regime that uses natural resources, controls waste sinks and manages ecosystem services efficiently and productively within these systems (Dauvergne, Reference Dauvergne2020).

Political leadership, institutional power and economic investment is committed to the automation regime. Everyone and everything are expected to integrate and conform to the new cyber-physical systems. The way the technologies of automation are deployed and actors organised is framed by the promise and drivers of the Fourth Industrial Revolution, which is capitalism’s fundamental need for renewed capital accumulation, increased labour productivity and enhanced managerial control for green growth. And yet, empirical analysis of the automation regime questions the wisdom of this pathway to sustainability.

9.3.2 Automated Unsustainability

There are deep uncertainties and widely debated concerns about the social impact of automation – notably its consequences for employment, equality and inclusion. Automation has already taken jobs, stoked divisions and undermined communities. However, the precise picture is much more complicated. Empirical analysis finds firms can, for example, find it easier and more profitable to deploy the 3Cs for micro-managing workers and intensifying human tasks. Labour becomes controlled like robots rather than being replaced by robots. Even within automated systems, their smooth operation requires human operatives undertaking ‘ghost work’ (usually exploitative), such as cleaning data, training algorithms, overseeing platforms, and tending to uncertain interfaces with society. In contrast to the workerless factories, fields, infrastructures and even cities promoted by management consultants, automation has historically led to the emergence of new classes of human tasks and occupations. However, even the higher-skilled jobs can be alienating, undignified and increasingly precarious (cf. Sustainable Development Goal Eight).

In terms of environmental sustainability, it is questionable whether and how the improved efficiency and controls afforded by cyber-physical systems will offset the resources and contamination required to build the automation regime and its seemingly limitless expansion of production. Observations of the rebound effect in cleaner technologies beg questions about whether and how aggregate increases in production and consumption risks outstripping the relative eco-efficiencies of individual system components. Moreover, escalating upgrades typical in digital systems can draw into ever faster cycles of obsolescence the material components of cyber-physical systems. Green growth, upon which the automation regime is founded, shows few signs globally of decoupling economic growth from ecological collapse (Hickel & Kallis, Reference Hickel and Kallis2020).

Faced with sustainability questions, advocates and investors of the Fourth Industrial Revolution redouble their automation strategies by extending controls further and deeper into ecological and social systems. Environments continue to be perceived instrumentally, as mixtures of raw materials, waste sinks, and ecosystem services. Complex and uncertain environments appear as objects within cyber-physical systems and over which managers have synoptic control. Similarly, people and societies are presumed to comply with the system behaviours envisaged by designers. Empirical research problematises these assumptions. Feminist research reminds us how automation’s objectification of natures and people must eventually confront realities in which systems are only ever partially comprehensive of the situations in which they are entangled. The automation regime tries to objectify into its operations a diversity of sometimes troublesome and lively subjects. The automated race into the Fourth Industrial Revolution overwhelms reasonable questions about repair, care and sufficiency of systems towards these subjects. Why do sustainability transitions have to follow this path? Just how essential is automation for our futures?

9.3.3 A Post-Automation Niche Space

The post-automation niche is constituted globally by very different protagonists compared to the research organisations, venture capitalists, management consultancies, governments and businesses promoting the Fourth Industrial Revolution. Post-automation experiments are cultivated by hackers, citizen scientists, coders, free culture activists and artists, grassroots innovators, social entrepreneurs, and informal petty-producers occupying what sociologist Adam Arvidsson calls an industrious (cf. industrial) space (Allen & Potts, Reference Allen and Potts2016; Arvidsson, Reference Arvidsson2019; Benkler, Reference Benkler2016; Smith, Fressoli, Abrol, Arond, & Ely, Reference Smith, Fressoli, Abrol, Arond and Ely2017). This space provides our example for niche–regime interactions. The niche uses ostensibly automating technologies in radically different organisational arrangements, and based on very different norms, compared to the regime.

9.3.4 Niche–Regime Interactions

How can a marginal post-automation niche space, radically different to automation in conception and practice, interact with such a powerful regime? What kinds of transformations might emerge, and with what implications for sustainability transitions?

10.2.1 Technological Innovation System Perspective

The technological innovation system (TIS) perspective places a selected technology center stage with the idea to analyse its prospects, often including drivers and barriers (Bergek et al., Reference Bergek, Jacobsson, Carlsson, Lindmark and Rickne2008; Hekkert et al., Reference Hekkert, Suurs, Negro, Kuhlmann and Smits2007). The focus is typically not only on early stages of innovation but also diffusion of innovations from small to mass markets as well as mature technologies and those in decline have been studied (Andersen & Gulbrandsen, Reference Andersen and Gulbrandsen2020; Carlsson & Jacobsson, Reference Carlsson and Jacobsson1994; Markard et al., Reference Markard2020).

Types of systems: From the outset, it was acknowledged that TIS necessarily interact with other systems in its context (Carlsson & Stankiewicz, Reference Carlsson and Stankiewicz1991; Edquist, Reference Edquist and Edquist1997; Markard & Truffer, Reference Markard and Truffer2008). These systems include other technological innovation systems (Bergek, Hekkert, Jacobsson, Markard, Sanden, & Truffer, Reference Bergek, Hekkert, Jacobsson, Markard, Sandén and Truffer2015), established socio-technical systems (Markard et al., Reference Markard, Wirth and Truffer2016) different systems in a technology value chain (Andersen & Markard, Reference Andersen and Markard2020; Mäkitie et al., Reference Mäkitie, Hanson, Steen, Hansen and Andersen2022; Stephan et al., Reference Stephan, Schmidt, Bening and Hoffmann2017) and systems at other spatial scales (Binz & Truffer, Reference Binz and Truffer2017). This shows that there is a broad range of systems whose interactions we can study. We will get back to this in Section 10.3.

Types of interactions: Bergek et al. (Reference Bergek, Hekkert, Jacobsson, Markard, Sandén and Truffer2015) distinguished two types of interactions between a focal TIS with systems in its context: links and structural couplings (Bergek, Hekkert, Jacobsson, Markard, Sanden, & Truffer, Reference Bergek, Hekkert, Jacobsson, Markard, Sandén and Truffer2015). The former capture uni-lateral influences (i.e. context systems affecting the TIS but not vice versa), whereas the latter capture bi-lateral interdependencies. Structural couplings are understood as elements (e.g. actors, networks, institutions, technologies) shared by the focal TIS and context systems. The same actors, for instance, may operate in multiple systems, technologies may be used in multiple systems and systems may also have similar institutions (e.g. mass production logic) (Bergek, Hekkert, Jacobsson, Markard, Sandén, & Truffer, Reference Bergek, Hekkert, Jacobsson, Markard, Sandén and Truffer2015). For example, some oil companies diversified into offshore wind creating new structural couplings between the oil and gas system and the offshore wind TIS (Mäkitie et al., Reference Mäkitie, Andersen, Hanson, Normann and Thune2018). Scholars have also referred to functional couplings (see below) between the systems involved in a TIS value chain to describe the flows of material resources between them (Gong & Andersen, Reference Gong and Andersen2024). A TIS may also have linkages to context systems as finance, education or science (Fontes et al., Reference Fontes, Bento and Andersen2021; Malhotra et al., Reference Malhotra, Schmidt and Huenteler2019).

Main insights: In our reading, TIS studies have made at least three contributions to multi-system dynamics. First, novel technologies need to be embedded into a wider context of existing systems and structures: to obtain resources, to benefit from complementary innovations, to attract firms, to receive policy support or to create legitimacy (Binz et al., Reference Binz, Harris-Lovett, Kiparsky, Sedlak and Truffer2016; Binz & Truffer, Reference Binz and Truffer2017; Karltorp et al., Reference Karltorp, Guo and Sandén2017; Wirth & Markard, Reference Wirth and Markard2011). For this embedding, an emerging TIS must adapt (to a certain extent) to the structures of existing systems in its context, e.g. by addressing context problems. For our review, it is important to note that there can be a wide range of different systems to interact with, plus a wide range of interactions.

Second, the interactions between systems change over time. As a technology matures and the associated TIS grows, it starts to increasingly influence context systems, potentially also creating conflicts (Markard, Reference Markard2020; Markard et al., Reference Markard, Wirth and Truffer2016). The result is a shift from dependence to interdependence (or integration) between focal TIS and context systems. Also, resource flows change. While knowledge flows across systems might dominate in early stages of TIS development (Malhotra et al., Reference Malhotra, Schmidt and Huenteler2019), later stages increasingly demand additional flows of resources such as materials (e.g. minerals for batteries), skilled labor and capital for upscaling (Jacobsson & Karltorp, Reference Jacobsson and Karltorp2013). The new demand for resources might be a source of competition and conflict with other systems (Wirth & Markard, Reference Wirth and Markard2011). For our review, we note that system interactions and interdependencies may change as systems transform.

Third, TIS studies have highlighted the relevance of a technology value chain perspective, which widens the focus from a selected part of an innovation to broader up- and down-stream developments (Andersen & Markard, Reference Andersen and Markard2020; Sandén & Hillman, Reference Sandén and Hillman2011; Stephan et al., Reference Stephan, Schmidt, Bening and Hoffmann2017). The value chain approach therefore divides a TIS into various subsystems corresponding to different parts of the value chain including upstream (produce important materials and components of the technology), midstream (integration of components and manufacturing of technology units) and downstream (where technology is used). Each subsystem is embedded in different institutional environments and actor-networks. For example, for electric vehicles, the subsystem related to raw materials (e.g. lithium or graphite) is embedded in the mining system, the subsystem related to integration and manufacturing is embedded in the automotive industrial system, the utilisation subsystem is embedded in the wider transportation system and subsystem related to recycling is embedded in the waste management system (Gong & Andersen, Reference Gong and Andersen2024). A key issue for TIS value chain performance is to achieve sufficient institutional alignment and actor coordination across the heterogeneous systems involved to avoid bottlenecks (Malhotra et al., Reference Malhotra, Schmidt and Huenteler2019; Stephan et al., Reference Stephan, Schmidt, Bening and Hoffmann2017). This perspective is particularly helpful for grasping widespread diffusion of a focal technology where establishing and upscaling a value chain is important (Markard, Reference Markard2020). For multi-system dynamics, we note that heterogeneity of sectoral systems in the value chain can complicate actor collaborations and lead to bottlenecks in resource flows in the TIS.

10.2.2 Multi-level Perspective

The multi-level perspective (MLP) was developed to study transitions of socio-technical systems, juxtaposing the emergence of novelty in niches and the persistence of existing structures in regimes, both affected by exogenous developments at the so-called landscape level (Geels, Reference Geels2002, Reference Geels2006, Reference Geels and Hendriks2024).

Multi-system interactions in the MLP have played some role early on. Examples include niche innovations such as combined heat and power plants or biorefineries: they affect, interact with and potentially bridge different socio-technical systems (Raven & Verbong, Reference Raven and Verbong2007; Sutherland et al., Reference Sutherland, Peter and Zagata2015). Similarly, landscape developments such as market liberalisation affect multiple socio-technical systems, creating similarities across systems (Konrad et al., Reference Konrad, Truffer and Voß2008).

Types of systems: The MLP literature focuses on socio-technical systems. Recent MLP split up socio-technical systems into production, distribution and consumption subsystems, which means that also the relationships between these subsystems can be studied as multi-system interactions (Bauknecht et al., Reference Bauknecht, Andersen and Dunne2020; McMeekin et al., Reference McMeekin, Geels and Hodson2019). Others differentiate subsystems according to technologies (e.g. car, train and airplane regimes and car-sharing, mobility as a service and electric vehicle niches within the whole system of transportation) and study interactions between these (Geels, Reference Geels2018; van Welie et al., Reference van Welie, Cherunya, Truffer and Murphy2018). The most common approach is to study regime–regime interaction (e.g. oil and gas with internal combustion engine vehicles), regime–niche interactions (e.g. hydropower regime and electric vehicle niche) and niche–niche interactions (e.g. electric vehicles and roof-top solar), for niches and regimes located in different socio-technical systems (Haley, Reference Haley2015; Papachristos et al., Reference Papachristos, Sofianos and Adamides2013; Raven & Verbong, Reference Raven and Verbong2007).

Types of interactions: Konrad et al. (Reference Konrad, Truffer and Voß2008) distinguishes between functional and structural couplings as main types of multi-system interactions. Functional couplings refer to flows of resources across systems (e.g. materials, energy, financial resources) that create functional interdependencies. Structural couplings refer to overlaps in the elements of two or more socio-technical systems, i.e. actors, technology or institutions (Konrad et al., Reference Konrad, Truffer and Voß2008; Sutherland et al., Reference Sutherland, Peter and Zagata2015; van der Vleuten, Reference van der Vleuten2019). Another distinction is about modes of system interactions where scholars have suggested various types: (1) competition, (2) symbiosis, where systems develop functional relationships (Nykamp et al., Reference Nykamp, Andersen and Geels2023), (3) integration, where separate systems become integrated via a new innovation (Bakhuis et al., Reference Bakhuis, Kamp, Barbour and Chappin2024), (4) spillover, where elements from one systems are taken up within another (Konrad et al., Reference Konrad, Truffer and Voß2008; Mäkitie et al., Reference Mäkitie, Hanson, Steen, Hansen and Andersen2022) and (5) niche interference, in which niche-innovations in different systems interact and co-evolve (Papachristos et al., Reference Papachristos, Sofianos and Adamides2013; Verbong et al., Reference Verbong, Geels and Raven2007).

Main insights: The MLP holds three main insights for understanding multi-system dynamics. First, transitions in one system can be constrained by inertia in other systems, thereby making transition processes more complex (Bakhuis et al., Reference Bakhuis, Kamp, Barbour and Chappin2024). Required changes in other systems may be a mix of minor (e.g. expanding biomass production in agriculture) or major changes (e.g. shifting to renewables in electricity supply for low-carbon electric vehicles) that can result in coupled transitions across multiple systems (Nykamp et al., Reference Nykamp, Andersen and Geels2023).

A second insight is that inherent differences between socio-technical systems (e.g. system architecture, regulations, culture, business models, user practices) may complicate creating new interactions and halt unfolding multi-system dynamics. Even when new interactions could benefit both systems, we might see disagreements, misunderstanding and conflicts between central actors (Andersen, Geels, Steen, & Bugge, Reference Andersen, Geels, Steen and Bugge2023; Ertelt & Kask, Reference Ertelt and Kask2024; Raven & Verbong, Reference Raven and Verbong2007; Sutherland et al., Reference Sutherland, Peter and Zagata2015).

Third, multi-system interactions may be uneven or asymmetric. For example, systems may differ in terms of resources and power, or exposure to external pressure to change. Such asymmetries can result in one-sided solutions, or disruptions (e.g. new electrifying sectoral systems critical depend on grid access but grid actors are not dependent on new users reflecting markedly different incentive structures) (Nykamp et al., Reference Nykamp, Andersen and Geels2023; Rosenbloom, Reference Rosenbloom2019). The challenges from system differences often surface once a focal innovation starts to diffuse widely and incumbent actors rather than pioneers need to change (Andersen, Geels, Steen, & Bugge, Reference Andersen, Geels, Steen and Bugge2023; Geels, Reference Geels2021). Multi-system interactions are thus also about power and politics.

10.2.3 Deep Transitions Perspective

The DT perspective looks at large-scale, fundamental and long-term socio-economic transformations (Schot & Kanger, Reference Schot and Kanger2018). A central concept is surges of development which refers to major transformations such as the age of Steel, Electricity and Heavy Engineering (Perez, Reference Perez2009). Each surge involves transitions in individual socio-technical systems and the emergence of a new ‘multi-system complex’ (i.e. a novel configuration of multiple systems that interact in a coordinated manner). DT suggests that surges typically share common directionality because they are guided by a macro-level selection environment creating between-surges continuity (Davies & Schot, Reference Davies, Schot, Wesche and Hendriks2024).

A deep transition is viewed as a series of connected and fundamental transitions in multiple socio-technical systems in a similar direction that involves discontinuity in the macro-level selection environment (Schot & Kanger, Reference Schot and Kanger2018). The DT framework builds on the multi-level perspective and on the techno-economic paradigm framework (Davies & Schot, Reference Davies, Schot, Wesche and Hendriks2024; Perez, Reference Perez2009). The idea is to better understand the larger context (or landscape), in which contemporary transitions unfold, and how this context changes. The perspective is particularly interested in the emergence of overarching structures (e.g. production and consumption practices) that guide and affect multiple socio-technical systems (Kanger & Schot, Reference Kanger and Schot2019). Key concepts include meta-rules (norms and institutions that span multiple systems) and meta-regimes (sets of rules that span multiple systems) (Kanger, Reference Kanger2022).

The process of DT involves several steps. New rules emerge in niches in individual socio-technical systems in response to (meta-)regime problems. The new rules compete with incumbent rules, and eventually, they replace existing rules and create a new regime. New rules increasingly cross system boundaries, thereby turning into meta-rules. They might lead to cross-system alignments although variety and contestations may still occur. Subsequently, new meta-rules combine in a new meta-regime which spreads across different socio-technical systems. Finally, the new meta-regime acts as a selection environment for new niches and diffuses to more and more systems, ultimately changing the landscape (Kanger & Schot, Reference Kanger and Schot2019; Schot & Kanger, Reference Schot and Kanger2018). Industrial mass-production, digitalisation or servitisation can serve as examples here.

Types of systems: The DT perspective looks at socio-technical systems. Its primary interest is in the diffusion of meta-rules and meta-regimes across different socio-technical systems and how these systems become aligned and connected in a complex of systems as a consequence.

Types of interactions: A key form of interaction in the DT perspective is that socio-technical systems develop common features over time through the presence and workings of meta-rules and meta-regimes – similar to the idea of isomorphism in institutional theory (DiMaggio & Powell, Reference DiMaggio and Powell1983). As underlying mechanisms, DT also mentions functional and structural couplings. They are regarded both as transmission channels of and as means for consolidating meta-rules. DT also discusses the role of organisations (e.g. consultancies, international organisations) in creating and shaping couplings between meta-regimes (Schot & Kanger, Reference Schot and Kanger2018; van der Vleuten, Reference van der Vleuten2019). To emphasise flows of ideas or legitimacy, the notion of rhetorical couplings is used. It refers to cross-system discourses, i.e. referring to an activity/rule in one system to legitimise an activity in another system (Kanger & Sillak, Reference Kanger and Sillak2020).

Main Insights: First, the DT perspective broadens the scope of analysis to a broad range of interconnected socio-technical systems. In fact, the framework theorises the interplay of transition processes at the level of individual socio-technical systems and larger complexes of systems (Kanger & Schot, Reference Kanger and Schot2019; Schot & Kanger, Reference Schot and Kanger2018). In MLP terms, it can be viewed as a theory of landscape changes, which is mindful about the directionality of multi-system dynamics.

Second, DT is concerned with similarities across systems and how they emerge. It shows how transformations of individual systems may generate new meta-rules (or change existing ones) and how these may combine into meta-regimes and diffuse across multiple systems (Kanger, Reference Kanger2022).

Third, the framework points to agency and the role different kinds of actors play in the creation and diffusion of meta-rules (Kanger et al., Reference Kanger, Schot, Sovacool, van der Vleuten, Ghosh, Keller, Kivimaa, Pahker and Steinmueller2021; van der Vleuten, Reference van der Vleuten2019). However, this aspect has not been elaborated systematically yet and empirical studies are required here.

Finally, the DT perspective highlights the importance of directionality (and potential lock-ins) created by meta-rules. As such the perspective enables transition scholars to examine issues around deep-rooted societal values, conventions and practices associated with capitalism, equality, our relationship with nature or the exploitation of resources (Kanger et al., Reference Kanger2022).

10.3.1 Systems

Our review revealed that scholars have analysed interactions between a broad range of different systems. So, a key task for future studies will be to be explicit about the type of systems studied, about which analytical boundaries were set and why, and what multi-system phenomena are in the focus. On this basis, we can start to analyse why, how, when and where interactions take place or change.

In the review, we observed four ways of delineating a socio-technical system: (a) complexes of systems comprised of various socio-technical systems that are functionally interdependent, exchange resources and may be coordinated by shared (meta) rules such as the complex made up by oil and gas, oil-based transport, fossil-based energy and petrochemical systems emerging in the early twentieth century, (b) socio-technical systems in the traditional sense, providing societal services such as energy, water or transport and covering production, distribution and consumption domains. (c) sub-systems of socio-technical systems or sectors (e.g. power supply, distribution systems, chemicals or mining) and (d) systems associated with specific technologies e.g. windmills or electric vehicles which are applied in yet other systems/sectors to generate their key service.Footnote ² Reminiscent of this, we note a tendency to narrow system boundaries for analysing multi-system dynamics, e.g. focusing on production, distribution or consumption sub-systems rather than the larger socio-technical system as one. Splitting up ‘whole systems’ to better characterise subsystems and technologies as well as how they differ and interact is one way of handling the growing complexity of multi-system dynamics and real-world transitions. Regardless of these different system delineations, it is worthwhile to remember that some flexibility in boundary setting remains and that different research questions require different system boundaries.

We also observe that multi-system dynamics may unfold ‘horizontally’ or ‘vertically’ (also see Bergek et al., Reference Bergek, Hekkert, Jacobsson, Markard, Sandén and Truffer2015 for similar observation). Horizontal multi-system dynamics may refer to relationships between production, distribution and consumption domains in the provision of a societal service or between distinct systems of provision (e.g. water, energy, transport) (McMeekin et al., Reference McMeekin, Geels and Hodson2019). Vertical multi-system dynamics may refer to the systems connected via value chains covering mining, materials, manufacturing and use of a particular technology or product (Andersen et al., Reference Andersen, Steen, Mäkitie, Hanson, Thune and Soppe2020; Stephan et al., Reference Stephan, Schmidt, Bening and Hoffmann2017). These types of multi-system dynamics are rarely considered in an integrated way which arguably obscures some aspects of transitions. Think of how limited critical minerals and underwhelming manufacturing capacity in Europe influence further developments in production (renewable energy diffusion), distribution (power cables, transformers and battery systems) and consumption (batteries and electric vehicles) (Andersen et al., Reference Andersen, Mäkitie, Steen and Wanzenböck2024; Edler et al., Reference Edler, Blind, Kroll and Schubert2023).

In addition, there is so far limited attention to describing and analysing system differences (e.g. structures or business cultures) and how these influence system interactions (Miörner et al., Reference Miörner, Binz and Fuenfschilling2021; Nykamp et al., Reference Nykamp, Andersen and Geels2023). Indeed, understanding the combination of cross-system (inter)dependencies and system differences is a basic rationale for multi-system analysis.

We also observe that although interacting systems can be spatially delineated (e.g. local vs. global) and multi-system interactions unfold across different places (e.g. electricity systems in Germany and Denmark), that area of multi-system analysis merits more attention to connect the geography of transitions (Binz et al., Reference Binz, Coenen, Murphy and Truffer2020).

10.3.2 Interactions

In terms of types of interactions, we noted a significant variety in the literature (modes and types), but also that the concept of structural couplings has received attention in all three perspectives, and it might be promising to study and develop further.

As also noted by Rosenbloom (Reference Rosenbloom2020), interaction concepts are, across the three frameworks, mostly applied descriptively and in an abstract and macroscopic manner which leads to a limited understanding of local, micro-level accounts of how system interactions are created and changed in practice (Andersen & Geels, Reference Andersen and Geels2023; Breitschopf et al., Reference Breitschopf, Grimm, Billerbeck, Wydra and Köhler2023; Rosenbloom, Reference Rosenbloom2020). This is important because the emergence and scaling of new low-carbon value chains, sustainable transitions of systems and of complexes of systems all involve the creation of many new interactions.

We acknowledged that transition scholars have recently made efforts to address this issue by identifying structural coupling mechanisms related to the dimensions of technology (technological complementarities such as the need for particular inputs or complementary innovations), actors (e.g. company diversification across systems creates organisational couplings and capability or value changes in multi-system consumers can transmit these across systems) and institutions (e.g. actors can build cross-system institutional couplings to overcome system differences, and similar changes in cultural conventions in distinct systems can lead to new institutional couplings) (Andersen & Geels, Reference Andersen and Geels2023; Andersen, Geels, Steen, & Bugge, Reference Andersen, Geels, Steen and Bugge2023; Ertelt & Kask, Reference Ertelt and Kask2024; Käsbohrer et al., Reference Käsbohrer, Hansen and Zademach2024; Löhr & Chlebna, Reference Löhr and Chlebna2023; van der Vleuten, Reference van der Vleuten2019).Footnote ³ A related proposal is to shift analytical focus from individual couplings to multi-system sites or interfaces that encompass multiple different couplings and their interrelations (Andersen, Geels, Steen, & Bugge, Reference Andersen, Geels, Steen and Bugge2023; Löhr & Chlebna, Reference Löhr and Chlebna2023; Rosenbloom, Reference Rosenbloom2020). An interface approach draws attention to how inter-system domains are created and associated tensions and conflicts. Despite these suggestions, the analysis of multi-system interactions and multi-system dynamics more broadly would benefit from more attention to the role of actor strategies and of politics, i.e. how actors and coalitions work to influence the pace and directionality of multi-system dynamics (see Löhr et al., Reference Löhr, Markard and Ohlendorf2024; Ohlendorf et al., Reference Ohlendorf, Löhr and Markard2023).

In terms of the content of interactions, we note that for TIS and MLP, multi-system interactions are often about flows of (tangible and intangible) resources across system boundaries (e.g. electricity, fuels, data, materials, finances). DT, however, focus on diffusion of rules, ideas and principles which often is a precursor to tangible resource flows that, in turn, require new structural couplings to consolidate. While resource flows are facilitated by specific structural couplings (Andersen & Geels, Reference Andersen and Geels2023), our understanding of how meta-rules travel across systems is less clear. DT suggests rhetorical couplings as transmission mechanism, but this concept remains rather unexplored, e.g. how are they created and how do they relate to structural couplings.

Lastly, we note that multi-system interactions are almost exclusively studied in relation to the emergence or diffusion of new technologies or practices. However, as highlighted by DT, existing, unsustainable systems are already connected via bundles of functional and structural couplings. Such couplings may imply greater resilience to external pressures for change and suggest that incumbency is inherently a multi-system phenomenon (Andersen & Gulbrandsen, Reference Andersen and Gulbrandsen2020; Johnstone et al., Reference Johnstone, Stirling and Sovacool2017). It is therefore important for future studies to explore the role of multi-system interactions in destabilisation and decline of systems or complexes of systems.

10.3.3 New Multi-system Dynamics Phenomena

From our review, we note that TIS and MLP studies largely focus on ‘bilateral’ multi-system dynamics, i.e. between a focal technology or system, and context systems (Figure 10.1(b) or (c)). DT, however, considers deep transitions across most if not all socio-technical systems in the economy (Figure 10.1(d)). DT does apply the notion of a complex of systems which is used to describe clusters of co-evolving systems (or surges) around particular impactful technologies or energy carriers which is seen as a mechanism for bringing about DT. However, from a sustainability transitions perspective, the emergence of complexes is an important phenomenon in its own right. While DT does provide an abstract account of how such complexes emerge and transform, it remains quite ’broad-brushed’ and insufficient with respect to e.g. diffusion and coupling mechanisms, actor strategies, system properties, tensions and conflicts as well as governance issues (Kemp et al., Reference Kemp, Pel, Scholl and Boons2022).

Many currently unfolding multi-system transition processes such as net-zero, circular economy or digitalisation resemble multi-system complexes ‘in the making’. To better grasp such multi-system dynamics, we need more conceptual exploration of the emergence and transformation of system complexes as this currently escapes existing frameworks.

Contemplating the example of low-carbon electrification reveals some of the limitation of existing frameworks. While there are several studies of low-carbon electrification, these tend to focus on a focal innovation and/or bi-lateral multi-system dynamics (see e.g. Andersen, Geels, Steen, & Bugge, Reference Andersen, Geels, Steen and Bugge2023; Käsbohrer et al., Reference Käsbohrer, Hansen and Zademach2024; Löhr & Chlebna, Reference Löhr and Chlebna2023). However, low-carbon electrification as phenomenon exhibits dynamics that merit a multi-system complex approach (see e.g. Markard & Rosenbloom, Reference Markard, Rosenbloom, Rogge, Kern and Meadowcroft2022; Nykamp et al., Reference Nykamp, Andersen and Geels2023; Ryghaug & Skjølsvold, Reference Ryghaug and Skjølsvold2023), see Text Box 10.1.

Our general understanding of the processual aspects of how multi-system complexes change (emerge, contract/expand or decline) is still limited. More knowledge is needed e.g. about how new systems become included, whether and how complexes can build momentum (e.g. successful electrification in one system creates resources and support for electrification in other systems), the relation between horizontal and vertical multi-system dynamics within complexes, to what extent new meta-rules and -regimes are critical to complex development (in the electrification example it was not immediate clear) or which strategies actors pursue to navigate or expand complexes.

The questions raised above, will also be relevant for related phenomena. One example is about transitions from linear technology value chains to a circular economy, which depends on institutional alignments across interdependent actors and systems that often lead to tensions and conflicts (Kuhlmann et al., Reference Kuhlmann, Meuer and Bening2023), as well as changes in functional and structural couplings (Gong & Andersen, Reference Gong and Andersen2024; Magnusson et al., Reference Magnusson, Zanatta, Larsson, Kanda and Hjelm2022). The complex of systems perspective can also be useful for thinking about the challenges of multi-purpose technologies such as mobile phones, carbon capture or batteries. Such technologies take part in the transitions of multiple systems at the same time and connect them in a complex (see e.g. Decourt, Reference Decourt2019; Finstad & Andersen, Reference Finstad and Andersen2023). Next to these, phenomena as digitalisation (Andersen et al., Reference Andersen, Frenken, Galaz, Kern, Klerkx, Mouthaan, Piscicelli, Schor and Vaskelainen2021; John et al., Reference John, Wesseling, Worrell and Hekkert2022) or the bio-economy (Wirth & Markard, Reference Wirth and Markard2011) also seem to exhibit multi-system complex dynamics. Surely each of these evolving complexes have their own particularities that are waiting to be explored.

11.3.1 Actors and Disruption

Several of the new articles strengthen the understanding of niche actors in altering and disrupting existing practices and cultural models. For example, analysing institutional work related to plant-based protein innovations, Bulah et al. (Reference Bulah, Negro, Beumer and Hekkert2023) show that niche actors actively work to disrupt cultural norms and values upholding the meat regime. Disruptive actors also work to undermine the institutions upholding the regime and work to disrupt, for example, policy or monetary support to dominant regime technologies and practices. Also, Bobbins et al. (Reference Bobbins, Caprotti, de Groot, Pailman, Moorlach, Schloemann and Siwali2023) highlight the role of practices, community dynamics and lived experience of actors in enabling the disruptiveness of innovations, underlining that disrupting innovations never exist beyond and ‘apart from’ existing socio-technical systems and cultural dynamics but as integral parts of them.

Looking at the role of prosumers in the energy transition, Weigelt et al. (Reference Weigelt, Lu and Verhaal2021) show the active role of disruptive actors by illustrating that disruption emerges not only from disruptive technologies but also their application by actors. They found that prosumers applied niche innovations in a novel and disruptive manner, especially in relation to incumbent actors’ business models, showcasing an example of a ‘stretch-and-transform’ process (see Smith & Raven Reference Smith and Raven2012). Thus, recent research using the concept of disruption strengthens the understanding of disruptions as forces undermining regime institutions and their practices, and potentially accelerating transition to more sustainable practices. This is in accordance with the understanding of transition strategies by Smith and Raven (Reference Smith and Raven2012) and shows that niche actors can deploy innovations in disruptive or conforming ways in relation to the existing socio-technical regime.

In contrast to our earlier review of disruption (Kivimaa et al. Reference Kivimaa, Laakso, Lonkila and Kaljonen2021), recent work has paid more attention to the increasingly complex role of incumbents as agents in both promoting and resisting transition. While the traditional take on disruption regarding incumbent actors has been the reduced value of (i.e. a disruption to) existing skills and resources held by the incumbents (e.g. Abernathy & Clark Reference Abernathy and Clark1985; Turnheim & Geels Reference Turnheim and Geels2013), new research has revealed the opportunities for incumbents to repurpose their skills and resources in response to disruptions (Mäkitie Reference Mäkitie2020; Nemes et al. Reference Nemes, Chiffoleau, Zollet, Collison, Benedek, Colantuono and Dulsrud2021). Kivimaa and Sivonen (Reference Kivimaa and Sivonen2023) have interpreted this as a process of ‘disruption to and repurposing skills and assets’ in the context of regime decline (see chapter 11.4 on decline). While facing disruption of skills and assets, incumbents are in a rather passive position, repurposing them shows a more active reaction to the ongoing transition.

There are other possible actions too. In this vein, two papers highlight the multifaceted role of disruptive incumbent actors. Interestingly, Galvan et al. (Reference Galvan, Cuppen and Taanman2020) show, by analysing grid operators, that incumbent regime actors can engage in both disruptive and maintaining practices simultaneously. Incumbents’ work in disrupting institutions that create barriers for their interests may also open space for the growth of niches. In turn, Loehr et al. (Reference Loehr, Chlebna and Mattes2022) foreground that along disruptive actions of incumbents, it is also crucial to analyse defensive institutional work that aims to resist and prevent transition. Defensive work resists disruptions and is geared at maintaining existing practices of the regime. It can take the shape of delegitimising novel practices, rules and technologies (Lehmann et al. Reference Lehmann, Graf-Vlachy and Koenig2019; Loehr et al. Reference Loehr, Chlebna and Mattes2022). Defensive work may in its turn have a disruptive effect towards the transition process (Loehr et al. Reference Loehr, Chlebna and Mattes2022), in other words a disruption of disruption. This understanding of disruption as impeding ongoing developments towards sustainability offers a novel perspective on the dimensions of disruptive actors and disruptive behaviour and practices. We suggest that a more nuanced understanding of disruptive incumbency can open avenues for harnessing the role of incumbency in accelerating transition, while also offering conceptual tools for navigating the various forms of regime resistance as well as disruption.

11.3.2 The COVID-19 Pandemic and Disruption

Recent articles on disruptive landscape events, especially on the COVID-19 pandemic, highlight the usefulness of categorising different dimensions of disruption and a detailed analysis of what is being disrupted and by whom. While landscape-level shocks open an opportunity for rapid change on a large scale, recent research underlines the complexities and resistances faced by such disruptive processes. Nemes et al. (Reference Nemes, Chiffoleau, Zollet, Collison, Benedek, Colantuono and Dulsrud2021) emphasise how the COVID-19 pandemic is exceptional in its large-scale influence on all-encompassing disruption on supply chains, so essentially a substantial landscape shock (see Kanda & Kivimaa Reference Kanda and Kivimaa2020). They note that the pandemic revealed the need to develop more resilient socio-technical systems against future disruptions.

Markard and Rosenbloom (Reference Markard and Rosenbloom2020) argue that the disruptive power of landscape-level shocks, such as the COVID-19 pandemic, must be actively harnessed to accelerate the decline of carbon-intensive technologies, industries and practices. Disruptive landscape events have potential to break ‘carbon lock-ins’ and open and accelerate low-carbon pathways, but this must be coupled with long-term processes of destabilisation and phase-out, to prevent a return to the preceding status quo once the initial landscape disruption has passed. This indicates that disruption on the level of institutions and regulations is needed to realise the disruptive potential of landscape shocks, again pointing out the interrelatedness of different spheres of disruption and the limits of one dimension alone. Indeed, Hirth et al. (Reference Hirth, Oncini, Boons and Doherty2022) have criticised the expectation that disruptive events kick-start systemic change towards sustainability. They showed that the COVID-19 pandemic did not disrupt regime practices in the context of different food provision sectors, because routinised and non-deliberative practices hindered transformation. This underlines that, other disruptions, influencing practices and behaviour, are needed to realise the disruptive potential of landscape shocks. Landscape disruption alone seems insufficient to stimulate sustainability transitions.

11.3.3 Nature of Disruption: Outcome Versus Process

Novel work on disruption continues to address the debate on whether disruption should be understood as a transition process or its outcome. For instance, Lazarevic et al. (Reference Lazarevic, Salo and Kautto2022: p.5) present dealignment and destabilisation as processes within the sustainability transition that facilitate “the development of disruptive policy frameworks and governance arrangements that challenge existing systems”. Hence, they indicate, too, that destabilisation is the process and disruption the outcome and the means to achieve transitions. This matches the definition presented above (and in Kivimaa et al. Reference Kivimaa, Laakso, Lonkila and Kaljonen2021) that portrays disruption as transition-related change. Also, Simoens et al. (Reference Simoens, Fuenfschilling and Leipold2022) associate disruption as an outcome, describing disruptive discursive change that can unlock previously unchallenged values and beliefs, creating openings for alternative discourse.

Contrary to this understanding, Blomsma et al. (Reference Blomsma, Bauwens, Weissbrod and Kirchherr2023) regard disruption as a process with three phases: release, reorganisation and eruption. They associate ‘circular disruption’ to a formation of a new paradigm which differs from the linear model of innovation and economy and which refers to systemic, widespread and fast change. This understanding is in partial contradiction to our previous proposal (Table 11.2), where certain types of disruptions are also associated with gradual transformative change and reconfiguration. Blomsma et al. (Reference Blomsma, Bauwens, Weissbrod and Kirchherr2023) also call for increased reflexivity among the transition studies community, to move from describing historic disruptions to outlining the conditions necessary for accelerating systemic change in close collaboration with other actors. On the other hand, Heiges and O’Neill (Reference Heiges and O’Neill2022) highlight the value of descriptive policy analysis when evaluating the impacts of past and existing disruptive or destabilising policies. They show that in the case of plastics recycling in the US, existing niches were not mature enough to become dominant regime actors when a major policy event took place. This opened space for the emergence of multiple co-existing regimes as a novel transition pathway, which can create further understanding for transition dynamics and governance. In other words, examining past and ongoing policy developments can reveal unexpected transition dynamics and add to existing understanding of potential transition pathways (Heiges & O’Neill Reference Heiges and O’Neill2022).