Returns within Fashion E-Tailing

Abstract: The purpose of this master’s thesis is to provide a contribution to the research body regarding consumer returns, particularly within the online fashion retail industry. A quantitative data analysis approach is chosen and two main methods are used: data study that aims to identify patterns and interesting relationships in the data, and a simulation study that uses real input data to attempt to identify how different fashion product categories are affected in various future scenarios regarding consumer return behavior. The five research questions posed are presented below. 1. How are different product categories affected in terms of profitability by increasing return rates? 2. How are different product categories affected in terms of profitability by increasing or decreasing return delay? 3. a) How are return rate, discount rate and time in sales period (TISP) connected? b) How is return rate affected by sales price? 4. Is it possible to find data to indicate the occurrence of “retail borrowing”? 5. To what extent does the data indicate the occurrence of multiple size ordering and return behavior? The study provides the following abbreviated answers to each research question: 1. The study finds that the products that suffer the worst effects are those with an already high return rate, and low to medium base sales price. Sales period length does not seem to differentiate products in terms of profits between different return scenarios. 2. The results regarding return delay were inconclusive. The study provides suggestions for further investigation of the effects of return delay. 3. Discount rate correlates negatively with return rate and positively with TISP, while return rate correlates negatively with TISP. There is also a positive correlation between return rate and sales price. 4. This study could not find conclusive evidence indicating the occurrence of retail borrowing behavior. 5. The study found that multiple size ordering and return behavior is prevalent in the data. 2.26% of all orders and 12.9% of orders containing returns are associated with at least one instance of multiple size ordering and returning.