Abstract
Based on the results obtained in game round 1, the theoretical foundations of supply chain management methods are developed and implemented with a corresponding optimization strategy. Supply chain management will be defined and the bullwhip effect will be discussed in detail, including the measures for its prevention. Demand forecasting and inventory management will be introduced as primary supply chain management methods. The detailed theories and learning content of the presented methods will be discussed in Part II, Chap. 11, mainly in parallel self-study. At a second review meeting, the teams present their results and interpret their behavior from round 1 from which they derive solutions for an optimal communicative supply chain. They must choose both a forecasting method and an inventory management process that will be implemented for the next game round.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Andler K (1929) Rationalisierung der Fabrikation und optimale Losgrösse. R. Oldenbourg, München
Beer A (2014) Der Bullwhip-Effekt in einem komplexen Produktionsnetzwerk. Springer Gabler, Wiesbaden
Chen F et al (2000) The impact of exponential smoothing forecasts on the bullwhip effect. Naval Res Logistics 47(4):269–286
Cronson R, Donohue K (2006) Behavioral causes of the bullwhip effect and the observed value of inventory information. Science 52(3):323–336
DecisionCraft (2010) Choosing the right forecasting technique. DecisionCraft Inc. http://www.decisioncraft.com/dmdirect/forecastingtechnique.htm. Accessed 16 Nov 2014
Dietl H (2012) Operations management. Universität Zürich. http://www.business.uzh.ch/professorships/som/stu/Teaching/F2012/BA/BWL/5_Lagerhaltungsmanagement.pdf. Accessed 16 Nov 2014
Harris F (1913) How many parts to make at once factory. Magazine Manag 10(2):135–136. 152
Holland W, Sodhi M (2004) Quantifying the effect of batch size and order errors on the bullwhip effect using simulation. Int J Logistics Res Appl 7(3):251–261
Juneau J, Coates E (2001) An economic order quantity model for time-varying demand. .Int J Mod Eng http://www.ijme.us/issues/spring2001/articles/economicorder.htm. Accessed 16 Nov 2014
Lee HL et al (1997) The bullwhip effect in supply chains. Sloan Manag Rev 38(3):93–102
Metters R (1997) Quantifying the bullwhip effect in supply chains. J Oper Manag 15(2):89–100
Sucky E (2009) The bullwhip effect in supply chains-an overestimated problem? Int J Prod Econ 118(1):311–322
Teng J, Yang H (2007) Deterministic inventory lot-size models with time-varying demand and cost under generalized holding costs. Inf Manag Sci 18(2):113–125. http://ijims.ms.tku.edu.tw/PDF/M18N22.pdf. Accessed 16 Nov 2014
Waser B (2010) Hochschule Luzern
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer-Verlag GmbH Germany
About this chapter
Cite this chapter
Gronwald, KD. (2017). Development and Implementation of a SCM Strategy. In: Integrated Business Information Systems. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-53291-1_5
Download citation
DOI: https://doi.org/10.1007/978-3-662-53291-1_5
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-662-53290-4
Online ISBN: 978-3-662-53291-1
eBook Packages: Computer ScienceComputer Science (R0)