Artificial Intelligence-Powered Decisions Support System for Circular Economy Business Models

Julius Mboli, Dhavalkumar Thakker, Jyoti Mishra

2023

Abstract

The circular economy (CE) is preferred to linear economy (LE) as it aims to keep resources in use for as long as possible, extracting maximum value before recovering and regenerating them. This reduces the need to extract new raw materials and reduces waste, leading to more sustainable economic growth. Contrarily, LE also known as a ”take, make, use, dispose” model, is based on resources extraction, products creation, and waste disposal, which can lead to depletion of resources, environmental degradation and several other hazards. Several barriers are delaying the switching to CE. Artificial Intelligence (AI) and emerging technologies can play significant roles in the implementation of CE. In this work, A novel AI-powered model that can serve as a Decisions Support System (DSS) for CE models is proposed and demonstrated. Product life extension is created via reuse, repair, remanufacture, recycle and cascade loop. The result of the model outperformed the LE model. The study demonstrates that technologies can enable smart monitoring, tracking, and analysis of products to support decision-making (DM). AI-powered sensors and devices can monitor the use of resources in real-time, allowing for more accurate tracking and reporting of resource use.

Paper Citation

in Harvard Style

Mboli J., Thakker D. and Mishra J. (2023). Artificial Intelligence-Powered Decisions Support System for Circular Economy Business Models. In Proceedings of the 25th International Conference on Enterprise Information Systems - Volume 1: ICEIS, ISBN 978-989-758-648-4, SciTePress, pages 656-666. DOI: 10.5220/0011997100003467

in Bibtex Style

@conference{iceis23,
author={Julius Mboli and Dhavalkumar Thakker and Jyoti Mishra},
title={Artificial Intelligence-Powered Decisions Support System for Circular Economy Business Models},
booktitle={Proceedings of the 25th International Conference on Enterprise Information Systems - Volume 1: ICEIS,},
year={2023},
pages={656-666},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011997100003467},
isbn={978-989-758-648-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 25th International Conference on Enterprise Information Systems - Volume 1: ICEIS,
TI - Artificial Intelligence-Powered Decisions Support System for Circular Economy Business Models
SN - 978-989-758-648-4
AU - Mboli J.
AU - Thakker D.
AU - Mishra J.
PY - 2023
SP - 656
EP - 666
DO - 10.5220/0011997100003467
PB - SciTePress