Simulating industrial symbiosis

understanding and shaping circular business models for viable and robust industrial symbiosis networks through collaborative modelling and simulation

Anders

The European Commission aims for a full circular economy (CE), an economy that aims to reuse all resources in 2050. CE is a promising way to increase welfare and wellbeing while decreasing environmental footprints. Industrial symbiosis, in which companies exchange residuals for resource efficiency, is essential to the circular transition. However, many companies are hesitant to implement business models for industrial symbiosis because of the various roles, stakes, opinions, and resulting uncertainties for business continuity.

This dissertation supports researchers, professionals, and students in understanding and shaping circular business models for industrial symbiosis networks through collaborative modelling and simulation methods. Three theoretical perspectives, design science research, complex adaptive socio-technical systems, and circular business model innovation, shed light on designing business models for industrial symbiosis. A serious game and agent-based models were developed in multiple case studies with researchers, practitioners, and students. These were then used to design circular business models and explore their efficacy under uncertain conditions, such as various behavioural intentions of potential partners in diverse natural and societal contexts. This thesis advances business model design and experimentation by integrated simulation of social and technical aspects of industrial symbiosis. Furthermore, the research shows how simulations facilitate learning processes in designing circular business models. Ultimately, the thesis equips researchers, practitioners, and students with knowledge, tools, and methods to shape a circular economy.

Reference Lange, K. P. H. (2022). Simulating industrial symbiosis: understanding and shaping circular business models for viable and robust industrial symbiosis networks through collaborative modelling and simulation. [Research HvA, graduation external, TU Delft]. Technische Universiteit Delft. https://doi.org/10.4233/uuid:9f4f569c-1dd5-4ef1-9e5e-85fb479f069d
15 June 2022

Publication date

Jun 2022

Author(s)

Paulien Herder
Gijsbert Korevaar
Inge Oskam

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