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Agent-Based Modelling for the Transition to a Circular Economy: Addressing Market Dynamics and Policy Interventions

Description

In this agent-based model, I aim to model circular practices in businesses. I specifically focus on the area of non-renewable and finite resources. I use the idea of a material pool to represent the reuse, recycling, repairing, and refurbishing of raw materials within the business. I assume a profit-maximization strategy by the companies and look at how different regulatory policies and consumer preferences impact the choices the effects on the profit of the businesses. I also look at the spatial implications on such a model, when the businesses are located throughout space.

Table of Contents

Features

  • Feature 1: "Monopolistic" setup - each company has access to its own set of raw resources and there is no competition in the market.
  • Feature 2: "Competitive" setup - each company shares access to one set of raw resources and there is competition in the market.
  • Feature 3: "Spatial" influence - here I look at the effect of spatial dynamics in the competitive market. I consider both cases in which everyone in the space shares the same resources as well as when there are different resources in each zone.

Installation

Prerequisites

  • The requirements.txt file contains all libraries required.

Steps

  1. Clone the repository: 
    git clone https://github.com/ethz-coss/circular-businesses-model.git
cd circular-businesses-model
  2. Install dependencies: 
    pip install -r requirements.txt

Usage

  1. Update the parameters.txt file with your desired parameters.
  2. Run the main.py file.

Contributing

Contributions are welcome! Please fork the repository, make your changes, and submit a pull request.

License

This project is licensed under the MIT License. See the LICENSE file for details.

Acknowledgements

  1. This framework was developed as part of a study on transitioning to a circular economy.
  2. More details are available in the report Agent-Based Modelling for the Transition to a Circular Economy: Addressing Market Dynamics and Policy Interventions.pf
  3. Generative artificial intelligence technologies were used in this project for code generation and report editing.