The accelerating urgency of climate change necessitates innovative strategies to integrate sustainability into supply chain management (SCM). This article bridges network theory and sustainable supply chain management (SSCM) to examine how network structures and firm-level sustainability performance interact to shape sustainable practices across complex supply chain networks. Employing a multi-scalar approach, the research spans macro-level analysis of an entire network and meso-level insights from industry-specific sectors.

The study utilizes Social Network Analysis (SNA) and Exponential Random Graph Models (ERGMs) to explore how sustainability metrics influence network connectivity, firm centrality, and tie formation. Key findings highlight the role of central firms as sustainability hubs and the significance of relational dynamics, such as homophily, in shaping collaborative behaviors.

This research contributes theoretically by integrating network theory into SSCM, offering new insights into the structural and relational dynamics critical to advancing sustainable supply chains. Practically, it provides actionable guidance for managers and policymakers, advocating for interventions such as digital traceability systems, targeted support for central firms, and collaborative platforms to foster resilience and sustainability. The findings underscore the importance of leveraging network configurations and central actors to drive systemic change, paving the way for resilient, adaptive, and sustainable supply chains aligned with global climate goals.

Transformations are prevalently difficult to grasp in their process and dynamics. In the literature they are therefore predominantly described ex-post. To better understand this social phenomenon, it is important to examine transformations, such as the energy transition, as they unfold. Particularly in complex infrastructures like electricity supply, it becomes evident how microstructural decisions generate macrostructural effects and vice versa. In this, Network analysis presents itself as a suitable methodological approach, as it allows for scale-free analysis and the dynamic representation of interdependent levels.

The goal is to make transformation processes as such more tangible. Therefore, the study addresses the research question: What needs to be mobilized in a transformation process to change the distribution of capital within the field in the desired way? By combining Bourdieu’s concept of capital with network-theoretical approaches, the study investigates how small-scale changes can lead to large-scale transformations. A case study of an energy transition living lab serves as an empirical approach to examine theoretical assumptions and explore possibilities for analysing transformations in their processualism.

The theoretical framework is defined by a targeted reduction of field structure and an expanded interpretation of Bourdieu’s concept of capital. Particular attention is given to the forms of relationships between entities within the transformation process. The study adopts a temporal perspective, analysing capital mobilization and the expansion of influence within the network over time. The results aim to provide deeper insights into the dynamics of transformation processes and enhance the understanding of their internal logics.