Journal of Korean Institute of Industrial Engineers (대한산업공학회지)

Korean Institute of Industrial Engineers (대한산업공학회)
권호 표지

Quantifying the Bullwhip Effect in a Supply Chain Considering Seasonal Demand

공급사슬에서 계절적 수요를 고려한 채찍효과 측도의 개발

  • Cho, Dong-Won (Department of Industrial and Management Engineering, Hanyang University) ;
  • Lee, Young-Hae (Department of Industrial and Management Engineering, Hanyang University)
  • 조동원 (한양대학교 산업경영공학과) ;
  • 이영해 (한양대학교 산업경영공학과)
  • Received : 2009.03.21
  • Accepted : 2009.08.07
  • Published : 2009.09.30
Download PDF
⟨ Previous Next ⟩

Abstract

The bullwhip effect refers to the phenomenon where demand variability is amplified when one moves upward a supply chain. In this paper, we exactly quantify the bullwhip effect for cases of seasonal demand processes in a two-echelon supply chain with a single retailer and a single supplier. In most of the previous research, some measures of performance for the bullwhip effect are developed for cases of non-seasonal demand processes. The retailer performs demand forecast with a multiplicative seasonal mixed model by using the minimum mean square error forecasting technique and employs a base stock policy. With the developed bullwhip effect measure, we investigate the impact of seasonal factor on the bullwhip effect. Then, we prove that seasonal factor plays an important role on the occurrence of the bullwhip effect.

Keywords

References

  1. Alwan, L. C., Liu, J. J., and Yao, D-Q. (2003), Stochastic Characterization of Upstream Demand Processes in a Supply Chain, IIE Transactions, 35(3), 207-219 https://doi.org/10.1080/07408170304368
  2. Box, G. E. P. and Jenkins, G. M. (1976), Time Series Analysis : Forecasting and Control, Revised Edition, Holden-Day, San Francisco, California
  3. Chen, F., Drezner, Z., Ryan, J. K., and Simchi-Levi, D. (2000a), Quantifying the Bullwhip Effect in a Simple Supply Chain : The Impact of Forecasting, Lead Times, and Information, Management Science, 46(3), 436-443 https://doi.org/10.1287/mnsc.46.3.436.12069
  4. Chen, F., Drezner, Z., Ryan, J. K., and Simchi-Levi, D. (2000b), The Impact of Exponential Smoothing Forecasts on the Bullwhip Effect, Naval Research Logistics, 47(4), 269-286 https://doi.org/10.1002/(SICI)1520-6750(200006)47:4<269::AID-NAV1>3.0.CO;2-Q
  5. Chopra, S. and Meindl, P. (2007), Supply Chain Management : Strategy, Planning and Operations, Pearson International Edition, Prentice Hall, Upper Saddle River, New Jersey
  6. Duc, T. T. H., Luong, H. T., and Kim, Y. D. (2008), A Measure of Bullwhip Effect in Supply Chains with a Mixed Autoregressive-moving Average Demand Process, European Journal of Operational Research, 187(1), 243-256 https://doi.org/10.1016/j.ejor.2007.03.008
  7. Forrester, J. W. (1969), Industrial Dynamics, MIT Press, Cambridge
  8. Gilbert, K. C. (2005), An ARIMA Supply Chain Model, Management Science, 51(2), 305-310 https://doi.org/10.1287/mnsc.1040.0308
  9. Gilbert, K. C. and Chatpattananan, V. (2006), An ARIMA Supply Chain Model with a Generalized Ordering Policy, Journal of Modeling in Management, 1(1), 33-51 https://doi.org/10.1108/17465660610667793
  10. Graves, S. C. (1999), A Single-Item Inventory Model for a Nonstationary Demand Process, Manufacturing and Service Operations Management, 1(1), 50-61 https://doi.org/10.1287/msom.1.1.50
  11. Heyman, D. and Sobel, M. (1984), Stochastic Models in Operations Research, McGraw-Hill, New York
  12. Kelle, P. and Milne, A. (1999), The Effect of (s, S) Ordering Policy on the Supply Chain, International Journal of Production Economics, 59(1-3), 113-122 https://doi.org/10.1016/S0925-5273(98)00232-1
  13. Lee, H. L., Padmanabhan, V., and Whang, S. G. (1997a), The Bullwhip Effect in Supply Chain, Sloan Management Review, 38(3), 93-102
  14. Lee, H. L., Padmanabhan, V., and Whang, S. G. (1997b), Information Distortion in a Supply Chain : The Bullwhip Effect, Management Science, 43(4), 546-558 https://doi.org/10.1287/mnsc.43.4.546
  15. Luong, H. T. (2007), Measure of Bullwhip Effect in Supply Chains with Autoregressive Demand Process, European Journal of Operational Research, 180(3), 1086-1097 https://doi.org/10.1016/j.ejor.2006.02.050
  16. Luong, H. T. and Phien, N. H. (2007), Measure of Bullwhip Effect in Supply Chains : The Case of High Order Autoregressive Demand Process, European Journal of Operational Research, 183(1), 197-209 https://doi.org/10.1016/j.ejor.2006.09.061
  17. McCullen, P. and Towill, D. (2002), Diagnosis and Reduction of Bullwhip in Supply Chains, Supply Chain Management : An International Journal, 7(3), 164-179 https://doi.org/10.1108/13598540210436612
  18. Nahamis, S. (1997), Production and Operations Analysis, 3rd ed., Irwin McGraw-Hill, New York
  19. Sterman, J. D. (1989), Modeling Managerial Behavior : Misperceptions of Feedback in a Dynamic Decision Making Experiment, Management Science, 35(3), 321-339 https://doi.org/10.1287/mnsc.35.3.321
  20. Wei, W. W. S. (1990), Time Series Analysis : Univariate and Multivariate Methods, Addison-Wesley, Redwood City, California
  21. Zhang, X. (2004), The Impact of Forecasting Methods on the Bullwhip Effect, International Journal of Production Economics, 88(1), 15-27 https://doi.org/10.1016/S0925-5273(03)00128-2