Abstract
Bullwhip effect (BWE) in a supply chain, attributed as the amplification of variance of demand along its route of propagation, compels a manufacturer to bear additional costs in the form of non-optimal resource usage. An accurate forecasting approach for demand prediction can be instrumental in mitigating the BWE. Numerous researchers have attempted to assess the impact of several forecasting approaches such as Moving Average, Single, Double and Triple Exponential Smoothing models, ARIMA, AI-based methods on BWE. However, Multiplicative Holt-Winters approach in mitigating the BWE is not widely exploited particularly with respect to the influence of the initial values of the level and growth rate of this approach. Hence, in this research endeavour, an attempt is made to study the impact of these parameters of the Multiplicative Holt-Winters model on the bullwhip effect in a two-echelon supply chain. Accordingly a simulation is performed in MS Excel along with ANOVA to reveal the significance of the parametric values. The preliminary results demonstrate that the initial values of the level have a significant impact over the bullwhip effect whereas the initial values of the growth rate maintain a U-type relationship. Thus, a scope is revealed for further study to improve the widely adopted Multiplicative Holt-Winters forecasting approach for tackling the BWE through exploration of optimal conditions.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Adenso-DÃaz, B., Moreno, P., Gutiérrez, E., Lozano, S.: An analysis of the main factors affecting bullwhip in reverse supply chains. Int. J. Prod. Econ. 135(2), 917–928 (2012)
Barlas, Y., Gunduz, B.: Demand forecasting and sharing strategies to reduce fluctuations and the bullwhip effect in supply chains. J. Oper. Res. Soc. 62(3), 458–473 (2011)
Bayraktar, E., Koh, S.L., Gunasekaran, A., Sari, K., Tatoglu, E.: The role of forecasting on bullwhip effect for E-SCM applications. Int. J. Prod. Econ. 113(1), 193–204 (2008)
Bowerman, B.L.B., O’Connell, A.B., Koehler, B.L.: Forecasting, Time Series, and Regression, 4th edn. Curt Hinrichis, USA (2005)
Chatfield, D.C.: Underestimating the bullwhip effect: a simulation study of the decomposability assumption. Int. J. Prod. Res. 51(1), 230–244 (2013)
Chen, F., Drezner, Z., Ryan, J.K., Simchi-Levi, D.: Quantifying the bullwhip effect in a simple supply chain: The impact of forecasting, lead times, and information. Manage. Sci. 46(3), 436–443 (2000)
Chen, F., Ryan, J.K., Simchi-Levi, D.: The impact of exponential smoothing forecasts on the bullwhip effect. Nav. Res. Logist. (NRL) 47(4), 269–286 (2000)
Chiang, C.Y., Lin, W.T., Suresh, N.C.: An empirically-simulated investigation of the impact of demand forecasting on the bullwhip effect: Evidence from US auto industry. Int. J. Prod. Econ. 177, 53–65 (2016)
Das, D., Dutta, P.: A system dynamics framework for integrated reverse supply chain with three way recovery and product exchange policy. Comput. Ind. Eng. 66(4), 720–733 (2013)
Forrester, J.W.: Industrial dynamics—a major breakthrough for decision makers. Harv. Bus Rev. 36(4), 37–66 (1958)
Geary, S., Disney, S.M., Towill, D.R.: On bullwhip in supply chains—historical review, present practice and expected future impact. Int. J. Prod. Econ. 101(1), 2–18 (2006)
Jaipuria, S., Mahapatra, S.S.: An improved demand forecasting method to reduce bullwhip effect in supply chains. Expert Syst. Appl. 41(5), 2395–2408 (2014)
Koh, S.L., Gunasekaran, A.: A knowledge management approach for managing uncertainty in manufacturing. Ind. Manag. Data Syst 106(4), 439–459 (2006)
Lee, H.L., Padmanabhan, V., Whang, S.: The bullwhip effect in supply chains. MIT Sloan Manag. Rev. 38(3), 93 (1997)
Mao, J.: Customer brand loyalty. Int. J. Bus. Manag. 5(7), 213 (2010)
Metters, R.: Quantifying the bullwhip effect in supply chains. J. Oper. Manag. 15(2), 89–100 (1997)
Paik, S.K., Bagchi, P.K.: Understanding the causes of the bullwhip effect in a supply chain. Int. J. Retail Distrib. Manag. 35(4), 308–324 (2007)
Pati, R.K., Vrat, P., Kumar, P.: Quantifying bullwhip effect in a closed loop supply chain. Opsearch 47(4), 231–253 (2010)
Sterman, J.D.: Modeling managerial behavior: Misperceptions of feedback in a dynamic decision making experiment. Manage. Sci. 35(3), 321–339 (1989)
Sun, H.X., Ren, Y.T.: The impact of forecasting methods on bullwhip effect in supply chain management. In: Proceedings of the 2005 Engineering Management Conference, vol. 1, pp. 215–219 (2005)
Tratar, L.F.: Forecasting method for noisy demand. Int. J. Prod. Econ. 161(1), 64–73 (2015)
Wang, X., Disney, S.M.: The bullwhip effect: Progress, trends and directions. Eur. J. Oper. Res. 250(3), 691–701 (2016)
Wright, D., Yuan, X.: Mitigating the bullwhip effect by ordering policies and forecasting methods. Int. J. Prod. Econ. 113(2), 587–597 (2008)
Zhang, X.: The impact of forecasting methods on the bullwhip effect. Int. J. Prod. Econ. 88(1), 15–27 (2004)
Acknowledgements
This study was conducted under the FRGS project (FRGS14-102-0343) funded by Ministry of Higher Education (MOHE), Malaysia. The authors are grateful to MOHE and Research Management Centre (RMC), IIUM for their support.
Author information
Authors and Affiliations
Corresponding authors
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer International Publishing AG
About this paper
Cite this paper
Emrul Kays, H.M., Karim, A.N.M., Hasan, M., Sarker, R.A. (2018). Impact of Initial Level and Growth Rate in Multiplicative HW Model on Bullwhip Effect in a Supply Chain. In: Sarker, R., Abbass, H., Dunstall, S., Kilby, P., Davis, R., Young, L. (eds) Data and Decision Sciences in Action. Lecture Notes in Management and Industrial Engineering. Springer, Cham. https://doi.org/10.1007/978-3-319-55914-8_26
Download citation
DOI: https://doi.org/10.1007/978-3-319-55914-8_26
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-55913-1
Online ISBN: 978-3-319-55914-8
eBook Packages: EngineeringEngineering (R0)