Evaluation of the allocation performance in a fashion retail chain using data envelopment analysis

Efficiency is one of the most important criteria of performance evaluation in any supply chain management, especially in the fashion retail industry. In the fashion industry, products are characterized by short life cycles and demand uncertainty. Most fast-fashion companies have employed the allocation practice that includes initial allocation and multireplenishment to capture the latest market information. Previous studies focus more on optimizing allocation policies, but overlook the efficiency issue, and the models always tend to be complex and are difficult to understand or apply. In this study, we model the allocation process as a multi-stage system with multiple inputs and outputs. A time-based dynamic network Data Envelopment Analysis (DEA) model, called multi-stage efficiency model (MEM), is developed to evaluate the allocation performance. The MEM considers undesirable outputs, dual-role factors (inventory as an output at the end of previous stage and the input at the beginning of the next stage) and the inconsistent attributes of the dual-role factors among the multi-stages. Meanwhile, the traditional DEA model is introduced to demonstrate the MEM is essential to capture the allocation performance. Based on the MEM results, the more appropriate initial allocation strategy is identified and the factors affecting allocation performance are discussed. The model is applied to a major Canadian fast-fashion company to validate the effectiveness. This article not only provides valuable managerial insights of supply chain management for fashion companies, but also makes contributions to the industrial application of theoretical OR (operation research) models.