Optimal Pricing of Product Considering Consumer Regret Psychology

This paper investigates the application of skimming pricing in sales strategies for businesses, considering the influence of regret psychology on consumer decision-making. It introduces two types of regret psychology-high-price regret and out-of-stock regret-into the consumer utility function, developing a two-stage consumer decision-making model. The paper then addresses optimal pricing and profit strategies for dynamic pricing and commitment pricing approaches. Additionally, it compares and analyzes the advantages and disadvantages of these models. Finally, it examines how high-price regret and out-of-stock regret affect optimal profits. The study suggests that dynamic pricing is optimal when consumers are more sensitive to high-price regret, while commitment pricing is preferable for maximizing profits when consumers are more sensitive to out-of-stock regret. Moreover, it finds that the lower the consumer high-price regret coefficient, the higher the optimal profit for enterprises. For businesses selling “continuous demand” commodities, optimal profit increases with consumer out-of-stock regret coefficient, whereas for businesses selling “fault-line demand” commodities, optimal profit decreases with this coefficient. This research can provide a theoretical model for AI to analyze consumer behavior while considering consumer regret psychology, and then help enterprises to provide decision support for product pricing and revenue management.