The Korean Journal of Applied Statistics (응용통계연구)

The Korean Statistical Society (한국통계학회)
권호 표지
DOI QR코드

DOI QR Code

Spectral Analysis Accompanied with Seasonal Linear Model as Applied to Intra-Day Call Prediction

스펙트럼 분석과 계절성 선형 모델을 이용한 Intra-Day 콜센터 통화량예측

  • Received : 20101000
  • Accepted : 20110100
  • Published : 2011.04.30
Download PDF
⟨ Previous Next ⟩

Abstract

In this paper, a seasonal variable selection method using the spectral analysis accompanied with seasonal linear model is suggested. The suggested method is applied to the prediction of intra-day call arrivals at a large North American commercial bank call center and a signi cant intra-month seasonal variable I detected. This newly detected seasonal factor is included in the seasonal linear model and is compared with the seasonal linear models without this variable to see whether the new variable helps to improve the forecasting performance. The seasonal linear model with the new variable outperformed the models without it in one-day-ahead forecasting.

본 논문에서는 스펙트럼 분석과 계절성 선형 모델을 이용하여 intra,-day 콜센터 통화량 예측에 필요한 계절성 변수를 찾아내는 방법을 제시한다. 제시한 방법을 북미 지역의 어느 은행의 5분 단위 콜센터 통화량에 실증 적용하여 기존의 통계적 방법으로는 입증할 수 없었던 월 단위 계절성 변수가 유의함을 보인다. 새로이 찾아진 연수가 intra-day 콜센터 통화량 예측능력을 향상시키는지 확인하기 위해서 새로운 변수를 포함하는 계절성 선형 모델과 이 변수를 포함하지 않은 계절성 선형 모델의 익일 통화량 예측능력을 비교 평가한다. 평가결과 새로운 변수를 포함한 모델이 우수하다는 결과를 얻었다.

Keywords

References

  1. Andrews, B. H. and Cunningham, S. M. (1995). L.L. bean improves call center forecasting, Interfaces, 25, 1-13.
  2. Bartlett, M. S. (1966). An Introduction to Stochastic Process, Cambridge University Press, London.
  3. Bianchi, L., Jarrett, J. and Choudary Hanumara, R. (1993). Forecasting incoming calls to telemarketing centers, Journal of Business Forecasting Methods and Systems, 12, 3-12.
  4. Brown, L. D., Gans, N., Mandelbaum, A., Sakov, A., Shen, H., Zeltyn, S. and Zhao, L. H. (2005). Statistical analysis of a telephone call center: A queueing-science perspective, Journal of the American Statistical Association, 100, 36-50. https://doi.org/10.1198/016214504000001808
  5. Durbin, J. (1967). Tests of serial independence based on the cumulated periodogram, Bulletin of the International Statistics Institute, 42, 1039-1049.
  6. Fuller, W. A. (1976). Introduction to Statistical Time Series, John Wiley & Sons, New York.
  7. Gans, N., Koole, G. and Mandelbaum, A. (2003). Telephone call centers: Tutorial, review and research prospects, Manufacturing and Service Operations Management, 5, 79-141. https://doi.org/10.1287/msom.5.2.79.16071
  8. Shen, H. and Huang, J. Z. (2008). Interday forecasting and intra-day updating of call center arrivals, Manufacturing and Service Operations Management, 10, 391-410. https://doi.org/10.1287/msom.1070.0179
  9. Taylor, J. W. (2008). A comparison of univariate time series methods for forecasting intraday arrivals at a call center, Management Science, 54, 253-265. https://doi.org/10.1287/mnsc.1070.0786
  10. Tych, W., Pedregal, D. J., Young, P. C. and Davies, J. (2002). An unobserved component model for multirate forecasting of telephone call demand: The design of a forecasting support system, International Journal of Forecasting, 18, 673-695. https://doi.org/10.1016/S0169-2070(02)00071-7
  11. Weinberg, J., Brown, L. D. and Stroud, J. R. (2007). Bayesian forecasting of an inhomogeneous poisson process with applications to call center data, Journal of the American Statistical Association, 102, 1185-1198. https://doi.org/10.1198/016214506000001455