SENTHIL K. VEERARAGHAVAN, University of Pennsylvania - The Wharton School - Operations & Information Management Department
Email: senthilv@wharton.upenn.edu
LAURENS G. DEBO, University of Chicago
Email: ldebo@chicagogsb.edu

A classic example that illustrates how observed customer behavior impacts other customers' decisions is the selection of a restaurant whose quality is uncertain. Customers often choose the busier restaurant, inferring that other customers in that restaurant know something that they do not. In an environment with random arrival and service times, customer behavior is reflected in the lengths of the queues that form at the individual servers. Queue lengths could signal two factors - potentially higher arrivals to the server or potentially slower service at the server. We study the effect of both arrival and service rates on the inference made by an arriving customer.

In our model, based on both private information about the service quality and queue length information, customers decide which queue to join. When the service rates are the same, we confirm that in equilibrium it may be rational to ignore private information and purchase from the service provider with the longer queue when only one additional customer is present in the longer queue. We show that such congestion driven choice behavior causes alternating cycles of successful and unsuccessful periods for a service provider. Hence, we provide an explanation based on endogenous choice-making for often observed "in" and "out" behavior of restaurants. We show that the success of a service provider depends on the private information of the customer arriving at an empty system and hence, contains a significant factor of luck. When the service rates and unknown service values are negatively correlated our results are strengthened; customers strictly prefer to join longer queues. When the service rates are positively correlated with unknown service values, customers might join shorter queues.

ALEX GERSHKOV, University of Bonn
Email: alex.gershkov@uni-bonn.de
PAUL SCHWEINZER, University of Bonn, Economic Theory II
Email: Paul.Schweinzer@uni-bonn.de

We address the scheduling problem of reordering an existing queue into its efficient order through trade. To that end, we consider individually rational and balanced budget direct and indirect mechanisms. We show that this class of mechanisms allows us to form efficient queues provided that existing property rights for the service are small enough to enable trade between the agents. In particular, we show on the one hand that no queue under a fully deterministic service schedule such as first-come, first-serve can be dissolved efficiently and meet our requirements. If, on the other hand, the alternative is service anarchy (ie. a random queue), every existing queue can be transformed into its efficient order.

FRANCISCO SILVA, Universitat Pompeu Fabra - Faculty of Economic and Business Sciences
Email: francisco.silva@econ.upf.es
DANIEL SERRA, Universitat Pompeu Fabra - Faculty of Economic and Business Sciences
Email: DANIEL.SERRA@ECON.UPF.ES

Previous covering models for emergency service consider all the calls to be of the same importance and impose the same waiting time constraints independently of the service's priority. This type of constraint is clearly inappropriate in many contexts. For example, in urban medical emergency services, calls that involve danger to human life deserve higher priority over calls for more routine incidents. A realistic model in such a context should allow prioritizing the calls for service.

In this paper a covering model which considers different priority levels is formulated and solved. The model heritages its formulation from previous research on Maximum Coverage Models and incorporates results from Queuing Theory, in particular Priority Queuing. The additional complexity incorporated in the model justifies the use of a heuristic procedure.