Analysis of Risk Mitigation Strategies in the Retail Sector. Application of AHP and TOPSIS Methods.

Abstract

The retail sector faces a complex landscape marked by operational risks that directly impact its sustainability and profitability. Problems such as inventory errors, checkout fraud, and distribution failures generate significant economic losses and jeopardize consumer confidence. In an increasingly competitive market characterized by demanding customers and constant pressure for efficiency, it is essential to identify and select effective and adaptable risk mitigation strategies. Previous literature offers partial approaches, as most studies do not integrate a structured, objective prioritization of alternatives under multiple criteria, which limits informed decision-making. This work addresses this gap through the combined application of the Analytic Hierarchy Process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) methods, multi-criteria tools that allow for weighing factors such as cost, impact, time, and residual risk. The results reveal that technological solutions, specifically advanced inventory control and report automation, outperform intensive training in terms of loss reduction and operational efficiency. Consequently, the research not only provides a replicable model for other sectors, but also practical guidelines for strengthening retail resilience.