Setting Due Dates and Scheduling Jobs to Maximize Customer Satisfaction and Profits

Dynamic job shop scheduling research has previously assumed that the probability of the customer placing an order is always one, implying that customers will place orders regardless of lead times quoted from the producer and customer lead time expectations. As firms increasingly compete on the basis of the delivery speed and reputation, the relative performance of quoted versus actual realized lead times will have a strong effect on whether the customer will place future orders or not. Previous research has not considered differing customer requirements or the impact on the customer’s subjective assessment of the overall purchase performance and subsequently on customer satisfaction and repurchases intentions. This paper formally integrates concepts from operations management, marketing, and consumer decision theory into a single due date scheduling framework in order to model the antecedents and consequences of customer satisfaction. We use the results on dynamic priority queues to propose the new way of quoting due dates by explicitly considering the customers lead time requirements. Simulation experiments reveal that job shop policies and machine capacities have significant impact on customer satisfaction and subsequently, on net profit. Finally, we show that dynamic due date quotation policy performs significantly better than several other policies previously tested in the literature.