Dynamic pricing and inventory control for fresh agricultural products under dual channel

This study investigates a joint pricing and inventory control problem for fresh agricultural products within dual channels. Considering factors such as service level, holding/lost costs, and consumer demand, this study presents a single-period model, followed by two stochastic dynamic programming models that extend across multiple periods. These models represent traditional dual channels and buy online, pick up in store (BOPS) dual channels, with each period containing selling stages of both discounted and regular pricing. At the start of each period, the retailer determines the order quantity for fresh agricultural products, sets discount prices for unsold inventories from the prior period (which would otherwise be disposed of), and establishes regular prices for fresh products in the subsequent stage. By leveraging the concave nature of the model and Karush-Kuhn-Tucker (KKT) condition analysis, an optimal pricing and inventory control policy is proposed, demonstrating superior performance compared to static strategies. The key findings include: (1) Discount pricing is effective in attracting consumers to non-fresh products, leading to lower inventory levels and higher profits, regardless of the inventory management strategy. Notably, in markets where low price sensitivity and discount prices are maintained below a certain threshold, setting higher regular prices with lower order quantities can maximize profits. (2) Centralized inventory management in a dual-channel setup can reduce inventory levels and increase profits compared to independent control policies. (3) In a BOPS dual-channel strategy, enhanced service levels, such as varied purchasing options, can boost revenue, offering advantages not present in traditional dual channels. Finally, numerical studies are conducted to further analyze the optimal policy and assess efficiency losses relative to static policies.