Abstract
Researchers apply Neural Networks widely in model prediction and data mining because of their remarkable approximation ability. This study uses a prediction model based on the Elman and NARX Neural Network and a back-propagation algorithm for forecasting call volumes in call centers. The results can help determine the optimal number of agents necessary to reduce waiting time for customers, enabling profit maximization and reduction of unnecessary costs. This study also compares the performance of the Elman-NARX Neural Network model with the time-lagged feed-forward Neural Network in addressing the same problem. The experimental results indicate that the proposed method is efficient in forecasting the call volumes of call centers.
Original language | English |
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Pages (from-to) | 4811-4814 |
Number of pages | 4 |
Journal | Journal of Business Research |
Volume | 69 |
Issue number | 11 |
DOIs | |
Publication status | Published - 2016 Nov |
Subject classification (UKÄ)
- Computer Systems
Free keywords
- Call center
- Forecasting
- Model prediction
- Neural Networks