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.
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This is a repository containing an agent-based model (code, data, documents and results) of Industrial Symbiosis Network implementation. The repository is related to the publication:Lange, K.P., Korevaar, G., Nikolic, I., Herder, P.M., 2021. Actor Behaviour and Robustness of Industrial Symbiosis Networks: An Agent-Based Modelling Approach, 2020:64:4. JASSS. https://doi.org/10.18564/JASSS.4635The purpose of the model is to explore the influence of actor behaviour, combined with environment and business model design, on the survival rates of Industrial Symbiosis Networks (ISN), and the cash flows of the agents. We define an ISN to be robust, when it is able to run for 10 years, without falling apart due to leaving agents.The model simulates the implementation of local waste exchange collaborations for compost production, through the ISN implementation stages of awareness, planning, negotiation, implementation, and evaluation.One central firm plays the role of waste processor in a local composting initiative. This firm negotiates with other firms to become a supplier of their organic residual streams. The waste suppliers in the model can decide to join the initiative, or to have the waste brought to the external waste incinerator. The focal point of the model are the company-level interactions during the implementation or ending of synergies.The model consists of three types of actors, waste suppliers, processor, and incinerators. The modeled waste supplier and processor are part of the ISN. In the model these agent types negotiate and evaluate the outcomes by means of the Theory of Planned Behavior. The modeled incinerator is part of the external environment. This agent acts as the infinite sink of all waste flows, taking up op the waste that is not used in the local composting initiative.
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The demand for mobile agents in industrial environments to perform various tasks is growing tremendously in recent years. However, changing environments, security considerations and robustness against failure are major persistent challenges autonomous agents have to face when operating alongside other mobile agents. Currently, such problems remain largely unsolved. Collaborative multi-platform Cyber- Physical-Systems (CPSs) in which different agents flexibly contribute with their relative equipment and capabilities forming a symbiotic network solving multiple objectives simultaneously are highly desirable. Our proposed SMART-AGENTS platform will enable flexibility and modularity providing multi-objective solutions, demonstrated in two industrial domains: logistics (cycle-counting in warehouses) and agriculture (pest and disease identification in greenhouses). Aerial vehicles are limited in their computational power due to weight limitations but offer large mobility to provide access to otherwise unreachable places and an “eagle eye” to inform about terrain, obstacles by taking pictures and videos. Specialized autonomous agents carrying optical sensors will enable disease classification and product recognition improving green- and warehouse productivity. Newly developed micro-electromechanical systems (MEMS) sensor arrays will create 3D flow-based images of surroundings even in dark and hazy conditions contributing to the multi-sensor system, including cameras, wireless signatures and magnetic field information shared among the symbiotic fleet. Integration of mobile systems, such as smart phones, which are not explicitly controlled, will provide valuable information about human as well as equipment movement in the environment by generating data from relative positioning sensors, such as wireless and magnetic signatures. Newly developed algorithms will enable robust autonomous navigation and control of the fleet in dynamic environments incorporating the multi-sensor data generated by the variety of mobile actors. The proposed SMART-AGENTS platform will use real-time 5G communication and edge computing providing new organizational structures to cope with scalability and integration of multiple devices/agents. It will enable a symbiosis of the complementary CPSs using a combination of equipment yielding efficiency and versatility of operation.