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The role of forecasting on bullwhip effect for E-SCM applications

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  • Bayraktar, Erkan
  • Lenny Koh, S.C.
  • Gunasekaran, A.
  • Sari, Kazim
  • Tatoglu, Ekrem

Abstract

The bullwhip effect represents the information distortion in customer demand between orders to supplier and sales to the buyer. Demand forecasting is one of the main causes of the bullwhip effect. The purpose of this study is to analyze the impact of exponential smoothing forecasts on the bullwhip effect for electronic supply chain management (E-SCM) applications. A simulation model is developed to experiment the different scenarios of selecting right parameters for the exponential smoothing forecasting technique. It is found that longer lead times and poor selection of forecasting model parameters lead to strong bullwhip effect in E-SCM. In contrast, increased seasonality helps to reduce the bullwhip effect. The most significant managerial implication of this study lies in the need to reduce lead times along the E-supply chain to mitigate the bullwhip effect. While high seasonality would reduce the forecast accuracy, it has a positive influence on the reduction of bullwhip effect. E-SCM managers are therefore strongly suggested to utilize exponential smoothing by selecting lower values for [alpha] and [beta] and a mid-value for [gamma] to keep the bullwhip ratio low, while at the same time to increase forecast accuracy.

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  • Bayraktar, Erkan & Lenny Koh, S.C. & Gunasekaran, A. & Sari, Kazim & Tatoglu, Ekrem, 2008. "The role of forecasting on bullwhip effect for E-SCM applications," International Journal of Production Economics, Elsevier, vol. 113(1), pages 193-204, May.
    • Handle: RePEc:eee:proeco:v:113:y:2008:i:1:p:193-204
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    Cited by:

    1. Chiang, Chung-Yean & Lin, Winston T. & Suresh, Nallan C., 2016. "An empirically-simulated investigation of the impact of demand forecasting on the bullwhip effect: Evidence from U.S. auto industry," International Journal of Production Economics, Elsevier, vol. 177(C), pages 53-65.
    2. Sari, Kazim, 2010. "Exploring the impacts of radio frequency identification (RFID) technology on supply chain performance," European Journal of Operational Research, Elsevier, vol. 207(1), pages 174-183, November.
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    6. Gaalman, Gerard & Disney, Stephen M. & Wang, Xun, 2022. "When bullwhip increases in the lead time: An eigenvalue analysis of ARMA demand," International Journal of Production Economics, Elsevier, vol. 250(C).
    7. Lau, H.C.W. & Ho, G.T.S. & Zhao, Y. & Chung, N.S.H., 2009. "Development of a process mining system for supporting knowledge discovery in a supply chain network," International Journal of Production Economics, Elsevier, vol. 122(1), pages 176-187, November.
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    9. Maria Isabel Pedro & Felipe Lopes Cabral, 2013. "A New Innovative Model Using RFID: A System Design and Its Implementation," International Journal of Finance, Insurance and Risk Management, International Journal of Finance, Insurance and Risk Management, vol. 3(2), pages 508-508.
    10. Ciancimino, Elena & Cannella, Salvatore & Canca Ortiz, José David & Framiñán Torres, José Manuel, 2009. "Análisis multinivel de cadenas de suministros: dos técnicas de resolución del efecto bullwhip // Supply Chain Multi-level Analysis: Two Bullwhip Dampening Approaches," Revista de Métodos Cuantitativos para la Economía y la Empresa = Journal of Quantitative Methods for Economics and Business Administration, Universidad Pablo de Olavide, Department of Quantitative Methods for Economics and Business Administration, vol. 8(1), pages 7-28, December.
    11. Xu, Henry & Koh, Lenny & Parker, David, 2009. "Business processes inter-operation for supply network co-ordination," International Journal of Production Economics, Elsevier, vol. 122(1), pages 188-199, November.
    12. de Lima, Daruichi Pereira & Fioriolli, José Carlos & Padula, Antonio Domingos & Pumi, Guilherme, 2018. "The impact of Chinese imports of soybean on port infrastructure in Brazil: A study based on the concept of the “Bullwhip Effect”," Journal of Commodity Markets, Elsevier, vol. 9(C), pages 55-76.
    13. Erkan Bayraktar & Kazim Sari & Ekrem Tatoglu & Selim Zaim & Dursun Delen, 2020. "Assessing the supply chain performance: a causal analysis," Annals of Operations Research, Springer, vol. 287(1), pages 37-60, April.
    14. Ton Hien Duc, Truong & Luong, Huynh Trung & Kim, Yeong-Dae, 2010. "Effect of the third-party warehouse on bullwhip effect and inventory cost in supply chains," International Journal of Production Economics, Elsevier, vol. 124(2), pages 395-407, April.
    15. K. Devika & A. Jafarian & A. Hassanzadeh & R. Khodaverdi, 2016. "Optimizing of bullwhip effect and net stock amplification in three-echelon supply chains using evolutionary multi-objective metaheuristics," Annals of Operations Research, Springer, vol. 242(2), pages 457-487, July.
    16. Reza Hadizadeh & Amir Abbas Shojaie, 2017. "A Measure of SCM Bullwhip Effect Under Mixed Autoregressive-Moving Average with Errors Heteroscedasticity (ARMA(1,1)–GARCH(1,1)) Model," Annals of Data Science, Springer, vol. 4(1), pages 83-104, March.
    17. Ciancimino, Elena & Cannella, Salvatore & Bruccoleri, Manfredi & Framinan, Jose M., 2012. "On the Bullwhip Avoidance Phase: The Synchronised Supply Chain," European Journal of Operational Research, Elsevier, vol. 221(1), pages 49-63.
    18. Udenio, Maximiliano & Vatamidou, Eleni & Fransoo, Jan C., 2023. "Exponential smoothing forecasts: Taming the Bullwhip Effect when demand is seasonal," Other publications TiSEM 8fca6329-83b9-4a49-a2aa-e, Tilburg University, School of Economics and Management.

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