The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Quality–Speed Conundrum: Trade-offs in Customer-Intensive Services
Abstract
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.
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Cites
Hospital Nurse Staffing and Patient Mortality, Nurse Burnout, and Job Dissatisfaction
Aiken, L. H. (2002) · JAMA · doi:10.1001/jama.288.16.1987 · Cited by 5,226
Primary Care: Is There Enough Time for Prevention?
Yarnall, K. S. H., Pollak, K. I., Østbye, T., Krause, K. M., & Michener, J. L. (2003) · American Journal of Public Health · doi:10.2105/ajph.93.4.635 · Cited by 1,641 · cited 2×
“Because of high levels of demand, doctors need to rush between patients,3 spending most of their time treating acute illnesses—a process that is also dissatisfying to patients (Yarnall et al. 2003).”
BackgroundOn the time relations of mental processes: An examination of systems of processes in cascade.
McClelland, J. L. (1979) · Psychological Review · doi:10.1037/0033-295x.86.4.287 · Cited by 1,298
Cited by
When Does the Devil Make Work? An Empirical Study of the Impact of Workload on Worker Productivity
Tan, T. F., & Netessine, S. (2014) · Management Science · doi:10.1287/mnsc.2014.1950 · Cited by 297
Incorporating Artificial Intelligence into Healthcare Workflows: Models and Insights
Dai, T., & Abràmoff, M. D. (2023) · Tutorials in Operations Research: Advancing the Frontiers of OR/MS: From Methodologies to Applications · doi:10.1287/educ.2023.0257 · Cited by 29
Metadata
- Authors
- Anand, K. S., Paç, M. F., & Veeraraghavan, S.
- Venue
- Management Science
- Published
- 2011-01
- Volume
- 57
- Issue
- 1
- Pages
- 40-56
- ISSN
- 0025-1909 (ISSN-L)
- 1526-5501
- OpenAlex
- W2108252519
- Cited by
- 255
- References
- 3
- FWCI
- 15.79
- Type
- journal article
- Language
- en
- Open access
- closed
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