Pricing strategy based on a stochastic problem with barter exchange under variable promotional effort for a retail channel

Barter exchange platform gains popularity as an effective trade exchange strategy to minimize the vast use of paper money. In retail management, the application of the barter platform is growing because of cashless trade. It allows a retail enterprise to trade unused products in exchange for other assets purchased by reducing the actual purchase of assets. In this context, the study analyzes a stochastic model of a barter exchange problem under a retail channel. It investigates the barter exchange policy in three different models: conventional newsvendor model without barter exchange, with barter exchange, and with barter exchange with promotional effort and emissions level. The market demand for products is considered random and random with deterministic variables for three types of models. Stochastic models are solved in two different ways: with and without probability distribution functions of the random market demand. For maximization of the retailer's profit, the proposed framework obtains optimal decisions on ordered quantity, retail price, promotional effort, and emissions level. Five examples are tested and numerical results show that the barter exchange policy is more profitable than a traditional newsvendor model. A combination of stochastic and deterministic variable demand provides 34.31% more profit than a stochastic demand. Sensitivity analysis, discussions, and managerial insights are provided in detail on optimal decisions.