Optimal incentive-compatible priority pricing for the M/M/1 queue
Operations Research
The role of inventory in delivery-time competition
Management Science
Optimal service speeds in a competitive environment
Management Science
Pricing and delivery-time performance in a competitive environment
Management Science
Congestion and Complexity Costs in a Plant with Fixed Resources that Strives to Make Schedule
Manufacturing & Service Operations Management
Competition and Outsourcing with Scale Economies
Management Science
Customer Loyalty and Supplier Quality Competition
Management Science
Introduction to Probability Models, Ninth Edition
Introduction to Probability Models, Ninth Edition
Operations Systems with Discretionary Task Completion
Management Science
Competition in Service Industries
Operations Research
Managing Response Time in a Call-Routing Problem with Service Failure
Operations Research
Management Science
Reducing Delays for Medical Appointments: A Queueing Approach
Operations Research
Incentives for Quality Through Endogenous Routing
Manufacturing & Service Operations Management
Joining Longer Queues: Information Externalities in Queue Choice
Manufacturing & Service Operations Management
Manufacturing & Service Operations Management
Constraint-based methods for scheduling discretionary services
AI Communications
The Labor Illusion: How Operational Transparency Increases Perceived Value
Management Science
Diagnostic Accuracy Under Congestion
Management Science
Hi-index | 0.01 |
In many services, the quality or value provided by the service increases with the time the service provider spends with the customer. However, longer service times also result in longer waits for customers. We term such services, in which the interaction between quality and speed is critical, as customer-intensive services. In a queueing framework, we parameterize the degree of customer intensity of the service. The service speed chosen by the service provider affects the quality of the service through its customer intensity. Customers queue for the service based on service quality, delay costs, and price. We study how a service provider facing such customers makes the optimal “quality--speed trade-off.” Our results demonstrate that the customer intensity of the service is a critical driver of equilibrium price, service speed, demand, congestion in queues, and service provider revenues. Customer intensity leads to outcomes very different from those of traditional models of service rate competition. For instance, as the number of competing servers increases, the price increases, and the servers become slower. This paper was accepted by Sampath Rajagopalan, operations and supply chain management.