A dynamic pricing strategy for a 3PL provider with heterogeneous customers

We study the pricing problem for a third-party-logistics (3PL) provider that provides warehousing and transportation services. When customers arrive at the 3PL provider, they specify the delivery dates for their freight, and before the specified delivery dates, their freight is stocked in the 3PL provider’s warehouse. We propose a dynamic pricing strategy (DPS) and develop a stochastic-nonlinear-programming (SNLP) model which computes the optimal freight rates for different delivery dates incorporating the 3PL provider’s current holding cost and available transportation capacity for each route. As customers are heterogeneous in their valuations and price sensitivities for delivery dates, and the distributions of the customers’ delivery date preferences are unknown to the 3PL provider, we modify the standard multinomial logit (MNL) function to predict customer choices. Through a simulation experiment, we show that the proposed MNL function can be a good replacement for the mixed MNL function when the mixed MNL function is not applicable. Through simulation we also compare the proposed DPS with a static pricing strategy. We show that with our DPS both the 3PL provider and its customers are better off, and the 3PL provider has different investment incentives for increasing transportation capacity. Our results can be also applied in similar settings that feature holding costs, limited production capacity and delivery-date-sensitive customers.