000027284 001__ 27284
000027284 005__ 20131209145627.0
000027284 0247_ $$2urn$$aurn:nbn:ch:rero-006-110421
000027284 0248_ $$aoai:doc.rero.ch:20111107144229-PD$$punisi$$prero_explore$$pcdu33$$pthesis$$pinfonet_economy$$pthesis_urn$$zreport$$zbook$$zjournal$$zcdu16$$zpostprint$$zpreprint$$zcdu1$$zdissertation$$zcdu34
000027284 041__ $$aeng
000027284 080__ $$a33
000027284 100__ $$aSankaranarayanan, Karthik$$d1980-02-22
000027284 245__ $$9eng$$aStudy on behavioral patterns in queuing$$bAgent based modeling and experimental approach
000027284 300__ $$a117 p
000027284 502__ $$92011-10-27$$aThèse de doctorat : Università della Svizzera italiana, 2011 ; 2011ECO006
000027284 506__ $$ffree
000027284 508__ $$asumma cum laude
000027284 520__ $$9eng$$a“Time is money” if you are a service provider or a customer using the  service. In the current economic scenario where there is heavy  competition, customers have more alternatives at their  disposal; which means understanding customers is of paramount  importance. This dissertation delves into this terrain, and tries to provide  a conceptual and an experimental framework to  understand the complex dynamics we see every day in queuing. The  traditional approach to queuing has been towards designing an efficient  facility, with little focus towards the customers who  use these facilities. This approach has been helpful to understand the  capacity requirements, and the impact of different configurations of  production and service facilities, but has limited our ability  to explain the behavior observed in many real queues. This dissertation  continues the shift in focus from the service facility design to the  information structure, and the behavior of the customers in  a queuing system. Two extensions are proposed to the traditional  queuing framework: Customers are provided with 1) information  regarding the performance of the facility (feedback) and 2)  computational capability to process the information provided. In a  nutshell, the customers in this model choose which facility to use  depending on their expectations which are based on past  experiences. I present two agent based modeling frameworks to  characterize the customers using the facility. This approach helps us to  model homogenous customers, and it is useful because  every customer perceives differently the cost of waiting and also the  efficiency of the system. Agent based models help to understand how  the customers might co-evolve with the facility that  serves them, which is difficult to achieve within the traditional queuing  framework. Finally, an experiment is designed using the guidelines from  experimental economics to validate the agent based  modeling framework.
000027284 695__ $$9eng$$aBehavioral queuing ; Agent based modeling ; Experimental economics
000027284 700__ $$aLarsen, Erik$$eDir.
000027284 700__ $$aAckere, Ann van$$eCodir.
000027284 8564_ $$f2011ECO006.pdf$$qapplication/pdf$$s2279551$$uhttp://doc.rero.ch/record/27284/files/2011ECO006.pdf$$yorder:1$$zTexte intégral
000027284 918__ $$aFacoltà di scienze economiche$$bVia Giuseppe Buffi 13, CH-6904 Lugano
000027284 919__ $$aUniversità della Svizzera italiana$$bLugano$$ddoc.support@rero.ch
000027284 980__ $$aTHESIS$$bUNISI$$fTH_PHD
000027284 990__ $$a20111107144229-PD