A MLE+MNLBased Dynamic Leadtime Pricing Method

We study leadtime pricing in a B2B context where a firm provides guaranteed due-date delivery service to customers that are heterogeneous in their valuation of the products and preference in delivery time. We consider two types of customers based on their delivery preference: one that prefers just-in-time (JIT) delivery and another that prefers responsive delivery. Each type of customer has varying flexibility in delivery dates. The firm has constrained production capacity, and to manage that capacity offers multiple leadtime options – some with due-date guarantees. We develop a maximum-likelihood estimation and multinomial-logit function (MLE+MNL) based pricing method to find the optimal price quote so that the firm maximizes its expected profit while ensuring the due-date guarantee. We form stochastic-nonlinear-programming (SNLP) models to solve the price quote to maximize the firm’s expected profit in a stochastic context based on the improved MLE+MNL based pricing method. The problem specific techniques are developed for solving the proposed SNLP models and the simulation results show that near optimal solutions can be found.