Authors:
Marie Niederlaender
1
;
Urs Liebau
2
;
Yajing Chen
2
;
Emil Breustedt
2
;
Saad Driouech
1
and
Dirk Werth
1
Affiliations:
1
August-Wilhelm Scheer Institut, Uni Campus D 5 1, Saarbrücken, Germany
;
2
August-Wilhelm Scheer Institut, Center for Digital Greentech, Clausthal-Zellerfeld, Germany
Keyword(s):
Agent-Based Simulation, Customer Returns Behavior, Return Prevention, Sustainable Supply Chain.
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 environmen
tal impact, utilising common life cycle assessment strategies.
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