Abstract

E-commerce returns, particularly in the fashion sector, have become a growing sustainability concern. Existing studies of reverse logistics often rely on assumptions or proprietary datasets, resulting in limited transparency and potentially distorted theorisation. This research-in-progress explores the use of tracking devices to generate data on the reverse logistics of consumer returns. Trackers were placed in twenty returns across European fashion e-tailers, producing 563 geolocation data points. Data analysis reveals substantial inconsistencies between declared and actual logistics flows, with large e-tailers’ returns travelling significantly longer distances than previously reported. Benchmarking further suggests that the Google Maps API provides reliable distance measures. The study contributes to Green IS research by positioning independent data generation as a means to reduce information asymmetries and by advancing a performative view of data as an enabler of sustainability outcomes. Expected contributions include more accurate emissions estimation, comparative analyses, and new directions for governance and accountability research.

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