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Call center simulations: call center simulation modeling: methods, challenges, and opportunities
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Source Winter Simulation Conference archive
Proceedings of the 35th conference on Winter simulation: driving innovation table of contents
New Orleans, Louisiana
SESSION: Advanced tutorials table of contents
Pages: 135 - 143  
Year of Publication: 2003
ISBN:0-7803-8132-7
Authors
Vijay Mehrotra  San Francisco State University, San Francisco, CA
Jason Fama  Blue Pumpkin Software Inc., Sunnyvale, CA
Sponsors
INFORMS/CS : Institute for Operations Research and the Management Sciences/College on Simulation
NIST : National Institute of Standards and Technology
IEEE/SMCS : Institute of Electrical and Electronics Engineers/Systems, Man, and Cybernetics Society
ACM: Association for Computing Machinery
(SCS) : The Society for Modeling and Simulation International
SIGSIM: ACM Special Interest Group on Simulation and Modeling
IIE : Institute of Industrial Engineers
IEEE/CS : Institute of Electrical and Electronics Engineers/Computer Society
ASA : American Statistical Association
Publisher
Winter Simulation Conference 
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ABSTRACT

Using stochastic models to plan call center operations, schedule call center staff efficiently, and analyze projected performance is not a new phenomenon, dating back to Erlang's work in the early twentieth century. However, several factors have recently conspired to increase demand for call center simulation analysis.

• Increasing complexity in call traffic, coupled with the almost ubiquitous use of Skill-Based Routing.

• Rapid change in operations due to increased merger and acquisition activity, business volatility, outsourcing options, and multiple customer channels (inbound phone, outbound phone, email, web, chat) to support.

• Cheaper, faster desktop computing, combined with specialized call center simulation applications that are now commercially available.

In this tutorial, we will provide an overview of call center simulation models, highlighting typical inputs and data sources, modeling challenges, and key model outputs. In the process, we will also present an interesting "real-world" example of effective use of call center simulation.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Andrews, B. H. and S. M. Cunningham. 1995. L. L. Bean Improves Call Center Forecasting. Interfaces 25:1--13.
 
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Andrews, B. H. and H. L. Parsons. 1989. L. L. Bean Chooses an Agent Scheduling System. Interfaces 19:1 - 9.
 
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Andrews, B. H. and H. L. Parsons. 1993. Establishing Telephone-Agent Staffing Levels Through Economic Optimization. Interfaces 23:14--20.
 
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Feinberg, R. A., I. Kim, B. Hokama, K. Ruyter, and C. Keen. Operational Determinants of Caller Satisfaction in the Call Center. International Journal of Service Industry Management 11:131--141.
 
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Grossman, T. A., D. A. Samuelson, S. L. Oh, and T. R. Rohleder. 2001. Call Centers. In Encyclopedia of Operations Research, ed. S. L. Gass and T. M. Harris, 73--76. Norwell: Kluwer Academic Publishers.
 
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Hoffman, K. L. and C. M. Harris. 1986. Estimation of a Caller Retrial Rate for a Telephone Information System. European Journal of Operational Research 27:207--214.
 
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Mabert, V. A. 1985. Short-Interval Forecasting of Emergency (911) Workloads. Journal of Operations Management 5:259--271.
 
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Mandelbaum, A. 2001. Call Center Research Bibliography with Abstracts, Technical Report, Technion, Israel Institute of Technology.
 
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Mehrotra, V. 1997. Ringing Up Big Business. OR/MS Today 24:18--24.
 
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Collaborative Colleagues:
Vijay Mehrotra: colleagues
Jason Fama: colleagues