Managing Service Systems with Unknown Quality and Customer Anecdotal Reasoning

Service Systems with Experience-Based Anecdotal Reasoning Customers

T he existing queueing literature typically assumes that customers either perfectly know the expected waiting time or are able to form rational expectations about it. In contrast, in this article, we study canonical service models where customers do not have such full information or capability. We assume that customers lack full capability or ample opportunities to perfectly infer the service r...

Managing Customer Arrivals in Service Systems with Multiple Identical Servers

We analyze a discrete multi-server model for scheduling customer arrivals under no-shows. The challenge is to assign customers to time slots so that the service system utilizes its resources efficiently and customers experience short waiting times. We provide theoretical and heuristic guidelines for an effective practice of appointment overbooking in order to offset no-shows. Recursive and expl...

Managing Customer Relationships through Price and Service Quality

Managing Service Systems with an Offline Waiting Option and Customer Abandonment

M service providers offer customers the choice of either waiting in a line or going offline and returning at a dynamically determined future time. The best-known example is the FASTPASS® system at Disneyland. To operate such a system, the service provider must make an upfront decision on how to allocate service capacity between the two lines. Then, during system operation, he must provide estim...

Managing Quality of Service with Soft Constraints

The term “quality” as it is commonly understood in the context of Quality of Service (QoS) is “something” by which a user of the service (in a very large meaning) will judge how good the service is. In this research project we mainly focus our attention to three areas related with QoS: i) Networks, ii) Web Services and iii) Trust Management (TM). As defined in (Crawley et al. 1998), QoS is “a s...