The vast majority of interactions between customers and service providers are experiences that extend over time. Service systems that deliver excellent customer experience achieve greater customer satisfaction and therefore customer loyalty, and eventually raise revenue. The temporal aspects of service delivery have not yet been analyzed as carefully as its monetary aspects, while knowing how to control the timing of the service delivery and consequently enhancing the customers’ experience can give a competitive advantage to the service providers in many industries from call centers to hospitals. By developing analytical data-driven models and conducting empirical studies, we address the gap between operations management models and the-state-of-the-art in marketing and psychology literature, using quantitative methods such as Markov Decision Process (MDP), queueing theory, and predictive analytics as well as qualitative methods such as surveys and interviews. This line of research has led to the development of practical policies to control and optimize system’s throughput, customer’s wait-time and customer’s satisfaction in different service operations, which are presented in three chapters of this thesis.

Creator

• Ansari, Sina

DOI

• https://doi.org/10.21985/n2-31q5-8635

Subject

• Industrial engineering
• Operations research

Language

• en

Alternate Identifier

• etdadmin_upload_617413
• http://dissertations.umi.com/northwestern:14402

Keyword

• Predictive Analytics
• Service Operations
• Satisfaction
• Wait-time
• Markov Decision Process

Date created

• 2018-01-01

Resource type

• Dissertation

Rights statement

• In Copyright