Dynamic quotation of leadtime and price for a Make-To-Order system with multiple customer classes and perfect information on customer preferences

We study the optimal dynamic quotation of leadtime and price for a Make-To-Order manufacturer to improve its expected profit. The manufacturer knows the probability distribution of customers' sensitivity on quoted leadtime and price according to history data. They can also obtain information on individual sensitivity of each customer through negotiations with customers. Our analysis shows that the information of individual sensitivity leads to additional expected profit. Moreover, our numerical experiments demonstrate that the additional expected profit can be significant.