Abstract
System Dynamics (SD) is a methodology that can be used for analysing and understanding complex feedback systems. Influencing factors, time delays as well as dynamic relations between factors and effects can be assumed and used for simulations and the development of strategies. Whereas the aim of SD models is the better understanding of the relationship between underlying structure and behaviour of the feedback system, it can also — at least in principal — be used for forecasting. This paper analyses this application field by using real and generated data on new product diffusions in a calibration — validation — setting.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Bass FM (2004) A New Product Growth Model for Consumer Durables. Management Science 50(12 Supplement): 1825–1832
Bass FM (2004) Comments on “A New Product Growth for Model Consumer Durables”. Management Science 50(12 Supplement): 1833–1840
Bass FM, Krishnan T, Jain D (1994) Why the Bass model fits without decision variables. Marketing Science 13(3): 203–223
Bähr-Seppelfricke U (1999) Diffusion neuer Produkte — Der Einfluss von Produkteigenschaften. Deutscher Universitäts-Verlag GmbH Wiesbaden
Barlas Y (1996) Formal aspects of model validity and validation in System Dynamics. System Dynamics Review 12(3): 183–210.
Forrester JW (1961) Industrial Dynamics. Cambridge MIT Press
Goldenberg J, Libai E, Muller E (2004) From density to destiny: Using spatial dimension of sales data for early prediction of new product success. Marketing Science 23(3): 419–428
Lilien G, Kotler P, Moorthy KS (1992) Marketing Models. Prentice-Hall International, INC.
Lyneis JM (2000) System Dynamics for market forecasting and structural analysis. System Dynamics Review 16(1): 3–25
Maier FH (1998) New product diffusion models in innovation management — a system dynamics perspective. System Dynamics Review 14(4): 285–308
Maier FH (1995) Die Integration wissens-und modellbasierter Konzepte zur Entscheidungsunterstützung im Innovationsmanagement. Duncker & Humblot Berlin
Mahajan V, Peterson RA (1985) Models for Innovation diffusion. SAGE Publications, Beverly Hills London New Delhi
Milling P, Maier F (1996) Invention, Innovation und Diffusion, Eine Simulationsanalyse des Managements neuer Produkte. Duncker & Humblot Berlin
Parker P (1994) Aggregate diffusion forecasting models in marketing: A critical review. International Journal of Forecasting 10(2): 353–380
Putsis JR W P, Srinivasan V (2000) Estimation Techniques for Macro Diffusion Models. In: Mahajan V, Muller E, Wind Y (eds) New Product Diffusion Models. Kluwer, Boston, pp 263–291
Schmalen H, (1989) Das Bass-Modell zur Diffusionsforschung. Zeitschrift für betriebswirtschaftliche Forschung 41(3): 210–226
Sterman JD (2000) Business Dynamics — Systems Thinking and Modeling for a Complex World. Irwin Mc Graw Hill
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Schmidt, S., Baier, D. (2006). System Dynamics Based Prediction of New Product Diffusion: An Evaluation. In: Haasis, HD., Kopfer, H., Schönberger, J. (eds) Operations Research Proceedings 2005. Operations Research Proceedings, vol 2005. Springer, Berlin, Heidelberg . https://doi.org/10.1007/3-540-32539-5_98
Download citation
DOI: https://doi.org/10.1007/3-540-32539-5_98
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-32537-6
Online ISBN: 978-3-540-32539-0
eBook Packages: Business and EconomicsBusiness and Management (R0)