Modeling and Analysis of Call Center Arrival Data: A Bayesian Approach
提出一个带协变量和时间效应的调制泊松过程模型，用于分析呼叫中心到达数据，评估不同广告策略的效果并预测到达模式，采用贝叶斯方法进行估计。
In this paper, we present a modulated Poisson process model to describe and analyze arrival data to a call center. The attractive feature of this model is that it takes into account both covariate and time effects on the call volume intensity, and in so doing, enables us to assess the effectiveness of different advertising strategies along with predicting the arrival patterns. A Bayesian analysis of the model is developed and an extension of the model is presented to describe potential heterogeneity in arrival patterns. The proposed model and the methodology are implemented using real call center arrival data.