Industrial symbiosis (IS) is a collaborative strategy where an innovation ecosystem promotes the shift towards circular and sustainable models by enabling the exchange of resources, energy, and by-products among businesses. The existing literature has paid limited attention to analysing the different network configurations that these ecosystems can adopt and their effects on long-term resilience and sustainability. Building on the complex adaptive systems (CAS) theory, this paper proposes a taxonomy to underpin the evolution of IS networks, aiming to identify and characterise several potential network structures of increasing complexity, from internal reuse and bilateral exchange to distributed and hybrid configurations. This research examines how network configurations affect the system's capacity to respond to external shocks, evolve, and produce collective benefits. Finally, this paper provides a valuable theoretical framework for understanding self-organisation mechanisms in IS and offers valuable insights for designing more robust and adaptive networks and circular economy policies.
Exploring the configurations and evolutionary dynamics of industrial symbiosis networks: A complex adaptive systems-based perspective / Abbate, S.; Centobelli, P.; Di, Gregorio; Mogrovejo, G. P.. - In: JOURNAL OF INNOVATION & KNOWLEDGE. - ISSN 2444-569X. - 14:(2026). [10.1016/j.jik.2026.100974]
Exploring the configurations and evolutionary dynamics of industrial symbiosis networks: A complex adaptive systems-based perspective
Centobelli P.
;
2026
Abstract
Industrial symbiosis (IS) is a collaborative strategy where an innovation ecosystem promotes the shift towards circular and sustainable models by enabling the exchange of resources, energy, and by-products among businesses. The existing literature has paid limited attention to analysing the different network configurations that these ecosystems can adopt and their effects on long-term resilience and sustainability. Building on the complex adaptive systems (CAS) theory, this paper proposes a taxonomy to underpin the evolution of IS networks, aiming to identify and characterise several potential network structures of increasing complexity, from internal reuse and bilateral exchange to distributed and hybrid configurations. This research examines how network configurations affect the system's capacity to respond to external shocks, evolve, and produce collective benefits. Finally, this paper provides a valuable theoretical framework for understanding self-organisation mechanisms in IS and offers valuable insights for designing more robust and adaptive networks and circular economy policies.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.


