Abstract

This paper studied the optimal pricing strategy based on a highly realistic pricing scheme in order to maximize the revenue of a service modeled as an M/G/m/m loss system. The blocking probability is considered together to prevent compromising the quality of service. Customers’ willingness-to-pay is regarded to be randomly distributed, indicating price-dependent arrival. Considering the severe complexity of the proposed model, the optimal pricing strategy is numerically investigated through computational experiments based on case studies of two actual services currently operated at Incheon International Airport (Seoul, South Korea). The two services represent a congested and quiet situation, allowing for the analysis of opposite cases. The results of the computational experiments clearly demonstrate distinct optimal strategies for the two contrasting situations. The performance of the two services with their current pricing strategies is evaluated, providing managerial insights for the service providers.