Modeling latent sources in call center arrival data
In this paper, we discuss issues that arise in the analysis of call center arrivals that are mostly linked to individual ads. More specifically, we consider the case where there is no complete linkage between the calls and the advertisements that led to the calls. The ability to model and infer such latent call arrival sources is important from a marketing as well as an operations point of view since knowledge of the linkage improves forecasting performance of the model. We pose this as a missing data problem and develop a data augmentation algorithm for the Bayesian analysis. We implement the proposed algorithm to simulated and actual call center arrival data and discuss its performance.
Year of publication: |
2010
|
---|---|
Authors: | Landon, Joshua ; Ruggeri, Fabrizio ; Soyer, Refik ; Murat Tarimcilar, M. |
Published in: |
European Journal of Operational Research. - Elsevier, ISSN 0377-2217. - Vol. 204.2010, 3, p. 597-603
|
Publisher: |
Elsevier |
Keywords: | Call center modeling Nonhomogeneous Poisson process Data augmentation Markov chain Monte Carlo |
Saved in:
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