Artificial Intelligence (AI) automates human decision-making. Algorithmic pricing---an AI application for scalable price determination---is now prevalent in ride-hailing, travel, drugs, gasoline, and online retail. A common thread across all these implementations is heightened price variability due to frequent price adjustments made by the algorithms. We study the impact of this algorithmic pricing-induced price variability on consumer behavior. Using granular clickstream data from a U.S. online grocery retailer that adopted algorithmic pricing, we show that increased price variability raises consumer price sensitivity and therefore partially offsets the gains typically attributed to algorithmic pricing. We corroborate these findings from the field through controlled lab experiments. We also identify factors that amplify or attenuate the effects of price variability.
Diego Aparicio is Assistant Professor in the Marketing Department. He teaches the MBA elective on Pricing as well as the core Marketing Management course across the MBA, Master in Management and Executive Education programs.
His research explores pricing and assortment strategies, monetization models, digital platforms, and retail analytics. Prior to joining IESE Business School, he worked in the finance and technology sectors—experience that continues to shape his data-driven approach to research and teaching. He brings a practical perspective to topics such as market dynamics, algorithmic pricing and the evolving role of artificial intelligence in commerce.
Assistant Professor Aparicios’s work has been featured by the National Bureau of Economic Research (NBER), the European Central Bank and the Federal Trade Commission, and has been covered in leading outlets such as The Economist, Bloomberg and the U.S. Bureau of Labor Statistics—reflecting its influence on both public policy and business practice.