Pricing computer services: queueing effects
Communications of the ACM
Cost allocation revisited: an optimality result
Management Science
Optimal incentive-compatible priority pricing for the M/M/1 queue
Operations Research
User delay costs and internal pricing for a service facility
Management Science
Optimal internal pricing and backup capacity of computer systems subject to breakdowns
Decision Support Systems - Special issue: economics of information systems
Computing services supply management: incentives, information, and communication
Decision Support Systems - Special issue: economics of information systems
Pricing and capacity decisions of clustered twin-computer systems subject to breakdowns
Decision Support Systems
Experimental Evidence for Agency Models of Salesforce Compensation
Marketing Science
Competition in Service Industries
Operations Research
Managing Patient Service in a Diagnostic Medical Facility
Operations Research
On the staffing policy and technology investment in a specialty hospital offering telemedicine
Decision Support Systems
Capacity planning and performance contracting for service facilities
Decision Support Systems
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Capacity investment and capacity allocation have always been critical management decisions, especially in the presence of agency issue for capital-intensive and congestion-prone service organizations. Prior research has often modeled only one aspect of the issue, such as proposing internal pricing scheme for capacity allocation ignoring demand uncertainty and the influence of the manager, optimizing capacity alone ignoring the agency issue, or incentive contract design ignoring capacity limit and service delay. We show that simply employing a traditional incentive contract (which often ignores service delays) for the manager responsible for promoting a center's services will provide incorrect incentives and lead to a more congested and less profitable system. When firms focus on optimizing operational capacity alone, ignoring the impact of managers on service demand, they are able to maintain the optimal utilization and service quality by balancing capacity and delay costs. However, they forgo profit-increasing opportunities, as they ignore the impact of the optimal incentive contract and do not motivate the managers enough to boost demand. To tackle the management challenges faced by modern service centers, we take an integrated capacity-contracting approach by incorporating operational delays and capacity decisions within the incentive contract design. Embedding a queuing model in a general incentive contracting framework, we present a novel approach to deriving the optimal compensation contract and operational capacity for a service center. We illustrate in numerical examples that a Pareto improvement can be achieved with our integrated contracting approach because every party, from the firm to the manager, to customers, to equipment and software vendors, benefits.