Stochastic Optimal Control for Dynamic Pricing and Production in Fashion Retailing: An Economic Sustainability Approach

This study develops a stochastic optimal control model to optimize dynamic pricing and production strategies for fashion retailers facing uncertain demand and rapid product devaluation. Applying the Hamilton–Jacobi–Bellman equation approach, we derive profit-maximizing joint pricing and production policies. Key findings include the following: (1) Dynamic pricing and responsive production strategies outperform static pricing in terms of expected discounted profit under various market conditions. (2) Optimal dynamic prices exhibit a declining trend over the product lifecycle, aligning with observed practices in fast fashion. (3) The optimal production rate adapts to current inventory levels and market conditions, balancing the trade-off between stockouts and holding costs. (4) The model demonstrates robustness to variations in price elasticity, providing a flexible decision framework for diverse fashion market segments. (5) Extreme demand volatility reduces the economic benefits of dynamic policies, highlighting the need for additional risk management strategies. This research contributes to sustainable operations’ literature by integrating pricing and production decisions under uncertainty, offering theoretically grounded and practical insights for fashion retailers to enhance profitability and reduce waste.