Capacity and price setting for dispersed, time-sensitive customer segments

We consider joint pricing and capacity decisions for a facility serving heterogeneous consumers that span a continuous range of locations, and are sensitive to time delays. Within this context, we analyze two contrasting service strategies: segmentation and pooling. Consumer segments differ with respect to their reservation prices and time sensitivities, and are dispersed over a single distance dimension. The firm serves these consumers using a process that we initially model as an M/M/1 queuing system. We analyze profit-maximizing price and capacity levels for a monopolist, and contrast the optimal segmentation and pooling policies. We find that when consumers are time sensitive, and can expect queuing delays at the firm’s facility (due to random arrival and service times), then scale economies from pooling can outweigh segmentation benefits. Yet, segmentation outperforms pooling when consumer segments differ substantively, in which case the firm can use capacity as a lever to price discriminate between the segments. Moreover, by contrasting a dedicated-services strategy, which directly targets specific segments and serves them separately, with the alternative of allowing consumers to self-select, we find that self-selection has a moderate negative influence on profits. We also examine the profit impact of employing alternative queuing systems, and find that a hybrid strategy based on a prioritized queuing discipline, that combines elements of segmentation (by offering different waiting times) and pooling (by sharing capacity across consumer segments), can outperform both the pure segmentation and pooling strategies.