Service firms have increasingly been competing for market share on the basis of delivery time. Many firms now choose to set customer expectation by announcing their maximal delivery time. Customers will be satisfied if their perceived delivery times are shorter than their expectations. This gap model of service quality is used in this paper to study how a firm might choose a delivery-time commitment to influence its customer expectation, and delivery quality in order to maximize its market share. A market share model is developed to capture (1) the impact of delivery-time commitment and delivery quality on the firm's market share and (2) the impact of the firm's market share and process variability on delivery quality when there is a congestion effect. We show that the choice of the delivery-time commitment requires a proper balance between the level of service capacity and customer sensitivities to delivery-time expectation and delivery quality. We prove the existence of Nash equilibria in a duopolistic competition, and show that this delivery-time commitment game is analogous to a Prisoners' Dilemma.

This special issue, by addressing problems surrounding marketing and operations management, depicts state-of-the-art approaches, methodologies, and insights to improve a firm's or supply chain's overall performance. Top scholars in the field address many of the ways in which companies can synchronize their marketing and operations departments or their supply chain partners to improve competitiveness and profit. The information in this issue should be of interest both to academics and managers, and represents the current thoughts in an emerging area of marketing and operations interfaces.

We consider the order-fulfillment process of a supplier producing a customized capital good, such as production equipment, commercial aircraft, medical devices, or defense systems. As is common in these industries, prior to receiving a firm purchase order from the customer, the supplier receives a series of shared forecasts, which are called “soft orders.” Facing a stochastic internal manufacturing lead time, the supplier must decide at what time to begin the fulfillment of the order. This decision requires a trade-off between starting too early, leading to potential holding or cancellation costs, and starting too late, leading to potential delay costs. We collect detailed data of shared forecasts, actual purchase orders, production lead times, and delivery dates for a supplier-buyer dyad in the semiconductor equipment supply chain. Under the assumption that the supplier acts rationally, optimally balancing the cancellation, holding, and delay costs, we are able to estimate the corresponding imputed cost parameters based on the observed data. Our estimation results reveal that the supplier perceives the cost of cancellation to be about two times higher and the holding costs to be about three times higher than the delay cost. In other words, the supplier is very conservative when commencing the order fulfillment, which undermines the effectiveness of the overall forecast-sharing mechanism.