PurposeThe aim of this paper is to understand how systemic change agents influence the twin digital and green transitions. The authors build on agency-based theories to argue that transition pathways are influenced by a combination of place-based characteristics, the mobilisation and preferences of systemic change agents (such as local clusters), and the institutional and economic context. The conceptual framework defines the different steps of the twin transition, and it identifies how systemic change agents and geographic characteristics determine the direction and speed of the transition pathway.Design/methodology/approachThis paper starts with a literature review to identify the different schools of thoughts on transition pathways and the twin transition, before developing a conceptual framework and deriving policy implications.FindingsFirst, this paper argues that each transition involves three steps: framing, piloting and scaling. Each of these steps is driven by systemic change agents who engage local actors in trust-based collaboration, pool resources, create network effects and exchange information to source solutions for industry-level challenges. Second, the combination of place-based characteristics and the actions of local systemic change agents define the path of the transition and the new (post-transition) equilibrium. Finally, this paper sets out implications for policymakers who are interested in using systemic change agents to shape transition pathways in their local area.Research limitations/implicationsFurther research is needed to provide robust empirical evidence from a range of territorial realities for the hypotheses in this paper. Specifically, the role of systemic change agents, such as trade associations, regional organisations, clusters or research groupings, needs to be investigated more closely. These agents can play a key role in progressing the transition because they already focus on sourcing solutions to joint challenges and opportunities by exchanging information, engaging local actors in trust-based collaboration, pooling resources and fostering network effects and critical mass. Future research should investigate how policymakers can best leverage on these crucial actors to progress or steer transitions and how this varies depending on place-based characteristics. This could include, for instance, training activities, networking and collaboration (e.g. through the European Cluster Collaboration Platform) or clearer sign-posting the key next steps required for the transition.Practical implicationsThis paper identifies specific ways in which local actors can influence the direction and speed of transitions at each stage of the transition: at the framing stage, political entrepreneurship can be fostered through collaboration and smooth information flows between different levels of governance, at the piloting stage, commercial and social entrepreneurship require effective knowledge sharing and a wide and open search for solutions which, in turn, may require capacity building at the local level and coordination across stakeholder groups and levels of governance and effective scaling up can be fostered through network effects, joint commitment from a broad range of stakeholders and pooling of resources to achieve economies of scale.Social implicationsAn important implication of the framework is that, if several places are undergoing a parallel or joint transition, the result may not be convergence between these places. Instead, different places may choose different end points and they may proceed at different speeds. For instance, in the context of the European Union’s green and digital transitions, it is unlikely that every region will transition to a similar level of digitisation or make steps in the same direction when it comes to sustainability.Originality/valueThis paper plugs a gap in understanding how systemic transitions unfold and how their speed and direction are influenced by different stakeholder groups. This paper develops a conceptual framework to define twin transition pathways and it analyses prominent place-based factors affecting these pathways.
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