Revenue Management (RM) continually receives a lot of attention from many industries. An on-demand IT service becomes an obvious alternative for firms to outsource their IT work. We present a nonlinear programming model for applying RM to the on-demand IT service industry to determine the optimal price or service level for each class. The multinomial logit demand model is used to describe customer choice over multiple classes with different service-level agreements (SLAs). By numerical analysis, we study the impacts of system capacity, customer waiting incentives, and competitor's strategies on the service provider's (SP) performance. We show that RM is beneficial to this industry. It alleviates the impacts of insufficient capacity and achieves optimal resource allocation and profit. Our numerical study suggests that to be more profitable, SP has to either have more capacity, offer multiple service classes or provide waiting incentives to satisfy more demand.
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