A Systematic Review of Sustainable Supplier Selection Using Advanced Artificial Intelligence Methods

Hanen Neji, Mouna Rekik, Lotfi Souifi, Ismail Bouassida Rodriguez

2025

Abstract

Artificial intelligence (AI) algorithms have significantly advanced various fields, driving innovation in domains such as healthcare, finance, and sustainability. In the realm of sustainable development, selecting suppliers is crucial for promoting environmental responsibility and safeguarding the well-being of future generations. This complex decision-making process requires evaluating suppliers across numerous criteria. Multi-Criteria Decision-Making (MCDM) and AI techniques, including Natural Language Processing (NLP), Deep Learning (DL), and Machine Learning (ML), have emerged as powerful tools to address these challenges. However, these methods often face transparency issues and the risk of greenwashing, which can erode trust in sustainability assessments. To address this, we conducted a systematic literature review (SLR) of 44 papers published between 2019 and 2024, sourced from databases such as Springer (12 papers), IEEE Xplore Digital Library (11 papers), and Science Direct (21 papers). This review offers an equitable analysis of MCDM and AI models (NLP, DL, ML) for evaluating both supplier sustainability and the risk of greenwashing. Additionally, sentiment analysis techniques are integrated to enhance transparency and provide insights into stakeholder perceptions.

Paper Citation

in Harvard Style

Neji H., Rekik M., Souifi L. and Rodriguez I. (2025). A Systematic Review of Sustainable Supplier Selection Using Advanced Artificial Intelligence Methods. In Proceedings of the 17th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART; ISBN 978-989-758-737-5, SciTePress, pages 451-460. DOI: 10.5220/0013149900003890

in Bibtex Style

@conference{icaart25,
author={Hanen Neji and Mouna Rekik and Lotfi Souifi and Ismail Rodriguez},
title={A Systematic Review of Sustainable Supplier Selection Using Advanced Artificial Intelligence Methods},
booktitle={Proceedings of the 17th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART},
year={2025},
pages={451-460},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013149900003890},
isbn={978-989-758-737-5},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 17th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART
TI - A Systematic Review of Sustainable Supplier Selection Using Advanced Artificial Intelligence Methods
SN - 978-989-758-737-5
AU - Neji H.
AU - Rekik M.
AU - Souifi L.
AU - Rodriguez I.
PY - 2025
SP - 451
EP - 460
DO - 10.5220/0013149900003890
PB - SciTePress