Strategic Returns Prevention in E-Commerce: Simulating Financial and Environmental Outcomes Through Agent-Based Modeling

Marie Niederlaender, Urs Liebau, Yajing Chen, Emil Breustedt, Saad Driouech, Dirk Werth

2025

Abstract

Product returns pose an environmental and financial burden on manufacturers and online retailers worldwide, especially in the fashion sector. Over 50% of all ordered garments end up being returned, which gives rise to an ongoing search for approaches to successfully manage returns or to avoid returns in the first place. For both approaches, an accurate prediction of returns can be useful, since it allows for an improved inventory risk assessment and strategic reselling of garments, while also providing crucial information on common drivers of return rates. This study focuses on preventive strategies in the context of customers placing selection orders in online shops. An Agent based approach provides insight into the outcomes of three different return prevention strategies, which are compared with the original outcome of real world data from a German clothing manufacturer selling garments for special occasions. The four outcomes are analysed in terms of their financial and environmental impact, utilising common life cycle assessment strategies.

Paper Citation

in Harvard Style

Niederlaender M., Liebau U., Chen Y., Breustedt E., Driouech S. and Werth D. (2025). Strategic Returns Prevention in E-Commerce: Simulating Financial and Environmental Outcomes Through Agent-Based Modeling. In Proceedings of the 17th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART; ISBN 978-989-758-737-5, SciTePress, pages 453-462. DOI: 10.5220/0013180600003890

in Bibtex Style

@conference{icaart25,
author={Marie Niederlaender and Urs Liebau and Yajing Chen and Emil Breustedt and Saad Driouech and Dirk Werth},
title={Strategic Returns Prevention in E-Commerce: Simulating Financial and Environmental Outcomes Through Agent-Based Modeling},
booktitle={Proceedings of the 17th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART},
year={2025},
pages={453-462},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013180600003890},
isbn={978-989-758-737-5},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 17th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART
TI - Strategic Returns Prevention in E-Commerce: Simulating Financial and Environmental Outcomes Through Agent-Based Modeling
SN - 978-989-758-737-5
AU - Niederlaender M.
AU - Liebau U.
AU - Chen Y.
AU - Breustedt E.
AU - Driouech S.
AU - Werth D.
PY - 2025
SP - 453
EP - 462
DO - 10.5220/0013180600003890
PB - SciTePress