A multi-stage stochastic programming model for dynamic pricing and lead time decisions in multi-class make-to-order firm

Make-to-order firms use different strategies, such as dynamic pricing and due date management, to influence their performance. In these strategies, orders are segmented into classes based on their sensitivity to lead time and price. Quoting different prices and lead times to different classes of customer can increase a firm’s profit and its capacity utilization. Most research in this area does not consider the effects of production constraints on price and lead time decisions. In this paper, we consider the role of flexibility in dynamically choosing the price, lead time and segmentation of customers in make-to-order environments with limited production capacity and multi-period horizon under a stochastic demand function. To reflect the dynamic variations of a system’s conditions, we propose a Multi-stage Stochastic Programming (MSP) method to jointly determine prices, lead time and production. Furthermore, we assume that demand is a linear function of price, lead time and time. Through numerical analyses, we indicate the benefits of dynamic pricing and lead time decisions, based on different customer classes in various environments.