University of Twente Student Theses
Finding the optimal return policy leniency and adopting rising technologies : A simulation study on Zalando
Tran, Ha Minh Nguyet (2022) Finding the optimal return policy leniency and adopting rising technologies : A simulation study on Zalando.
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| Abstract: | This research seeks to reduce e-commerce fashion returns by finding the optimal monetary policy leniency and adoption of Augmented Reality (A.R.) and Customer Profiling Technology (CPT). While A.R. provides virtual try-on, such as clothing filters, on consumers to reduce legitimate returns due to fit issues, CPT tracks personal I.D.s by every return to prevent wardrobing behaviours. A prescriptive model is developed, and a simulation study on Zalando is conducted to investigate these technologies' impact and the conditions that foster the adoption. The results show that (1) a partial refund is more optimal than a full refund, (2) CPT offers significant benefits when e-tailers offer a lenient policy, (3) under high opportunism, A.R. should only be adopted if it is highly effective, and (4) CPT and A.R. together hold significant value under a lenient return policy but offer little value under a restrictive policy. Notably, in some cases, CPT can reverse the impact of A.R. on profits. |
| Item Type: | Essay (Bachelor) |
| Faculty: | BMS: Behavioural, Management and Social Sciences |
| Subject: | 85 business administration, organizational science |
| Programme: | International Business Administration BSc (50952) |
| Link to this item: | https://purl.utwente.nl/essays/91339 |
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