To read this content please select one of the options below:

The application of artificial intelligence in waste management: understanding the potential of data-driven approaches for the circular economy paradigm

Federico Lanzalonga (Department of Management, University of Turin, Turin, Italy) (Społeczna Akademia Nauk, University of Social Science, Lodz, Poland)
Roberto Marseglia (Department of Civil Engineering and Architecture, Universita degli Studi di Pavia, Pavia, Italy) (Alia Servizi Ambientali S.p.a., Firenze, Italy)
Alberto Irace (Alia Servizi Ambientali S.p.a., Firenze, Italy)
Paolo Pietro Biancone (Department of Management, University of Turin, Turin, Italy)

Management Decision

ISSN: 0025-1747

Article publication date: 13 February 2024

150

Abstract

Purpose

Our study examines how artificial intelligence (AI) can enhance decision-making processes to promote circular economy practices within the utility sector.

Design/methodology/approach

A unique case study of Alia Servizi Ambientali Spa, an Italian multi-utility company using AI for waste management, is analyzed using the Gioia method and semi-structured interviews.

Findings

Our study discovers the proactive role of the user in waste management processes, the importance of economic incentives to increase the usefulness of the technology and the role of AI in waste management transformation processes (e.g. glass waste).

Originality/value

The present study enhances the circular economy model (transformation, distribution and recovery), uncovering AI’s role in waste management. Finally, we inspire managers with algorithms used for data-driven decisions.

Keywords

Acknowledgements

The authors are grateful to Alia Servizi Ambientali Spa for their interviews and enthusiasm toward the research project.

Citation

Lanzalonga, F., Marseglia, R., Irace, A. and Biancone, P.P. (2024), "The application of artificial intelligence in waste management: understanding the potential of data-driven approaches for the circular economy paradigm", Management Decision, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/MD-10-2023-1733

Publisher

:

Emerald Publishing Limited

Copyright © 2024, Emerald Publishing Limited

Related articles