Modelling investment decision making of organic waste treatment companies in new technology contributing to the circular economy

An essential part of the circular economy is energy recovery and recycling of waste. Anaerobic digestion serves as a method for renewable energy extraction out of the organic fraction of municipal solid waste. Also basic resources can be created from waste: the H2020-project VOLATILE aims to develop a technology to extract volatile fatty acids through a platform that can be integrated into anaerobic digestion. From a technology development perspective as well as in light of the EU goals for circular economy implementation, it is useful to gain insight in whether companies are willing or reluctant to adopt this type of technology that contributes to the circular economy.
Therefore, we interviewed different types of waste treatment companies about their daily operations and extracted concepts that matter in their decision making behaviour. These concepts will be integrated in an agent-based model that explicitly takes into account behavioural aspects of these companies. The agent-based model must allow us to determine the main criteria that affect decision-making of waste treatment companies related to new technology contributing to the circular economy. It also enables us to analyse how different policy scenarios can guide companies towards these investments.
Results of the qualitative data analysis show that decision making strategies are not purely economic-based, but also depend on a broader set of values maintained by a company. These values relate to concepts such as “environmental friendliness”, “public vs. private company management” and “willingness to collaborate with others”. The agent-based model will incorporate these concepts, company-specific values regarding these concepts and how interaction between companies affects these values through learning. Together with economic feasibility, which will also be part of the agent-based model, this must lead to new insights on the willingness to adopt new technology.
Emergent decision making behaviour as a result of the agent-based model will be validated by going back to the interview data and through iteration, the importance of values for decision making will be refined. Subsequently, decision making will be com-pared under different policy scenarios and therefore, our model will be useful to identify policy recommendations.