Abstract: This article presents the results of the development of a hybrid mathematical dynamic pricing model, the "Cascade Degradation Coefficient," for the cut flower market. The research methodology is based on the synthesis of dynamic and stochastic modeling frameworks, utilizing piecewise-defined functions to describe cascade degradation, monotonic cosine-based functions to model the visual factor, a modified hyperbolic tangent to account for psychological perception, and multiplicative seasonal modulators. As a result, a multiplicative model integrating four independent factors has been created: temporal, visual, psychological, and seasonal. The conducted verification confirmed the model's physical realizability. The practical significance of the research lies in the creation of a tool for transitioning from intuitive pricing to data-driven optimization, enabling the maximization of profit and minimization of losses from write-offs in flower retail and e-commerce.

Keywords: Pricing Model, Cascade Degradation Coefficient, Perishable Goods, Cut Flower Market, Hybrid Mathematical Model, Stochastic Modeling, Data-Driven Optimization, Flower Retail, Perishable Product Pricing, Multiplicative Model

Pages: 607-614