Abstract
Consumer adoption of innovations is a key concern for strategic management in many companies as adoption ultimately drives the market success of new products. The respective adoption processes are inherently complex due to the social systems (i.e., the respective consumer markets) from which they arise. Markets characterized by the simultaneous presence of several multi-generation technologies, wherein products that rest upon successively introduced generations of technology compete against each other, constitute a particularly challenging case. Our agent-based model contributes to the field of technology diffusion research in that it accounts for novel and advanced product features in each technology generation, the reluctance of (some) users to switch to a new (as yet unfamiliar) technology, and various social influences between consumers. Calibrated with data from several sources, our results closely replicate the actual development of the German consumer computer market from 1994 to 2013.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Axtell, R.L.: Why agents? On the varied motivations for agent computing in the social sciences. In: Macal, C.M., Sallach, D. (eds.) Proceedings of the Workshop on Agent Simulation: Applications, Models, and Tools, pp. 3–24. Argonne National Laboratory, Argonne (2000)
Delre, S.A., Jager, W., Bijmolt, T.H.A., Janssen, M.A.: Will it spread or not? The effects of social influences and network topology on innovation diffusion. J. Prod. Innov. Manag. 27, 267–282 (2010)
Desmarchelier, B., Fang, E.S.: National culture and innovation diffusion: exloratory insights from agent-based modeling. Technol. Forecast. Soc. Change 105, 121–128 (2016)
Druehl, C.T., Schmidt, G.M., Souza, G.C.: The optimal pace of product updates. Eur. J. Oper. Res. 192, 621–633 (2009)
Günther, M.: Diffusion of multiple technology generations: an agent-based simulation approach. In: Kocaoglu, D.F., Anderson, T.R., Daim, T.U., Kozanoglu, D.C., Niwa, K., Perman, G. (eds.) Proceedings of the Portland International Conference for Management of Engineering and Technology (PICMET ’16), pp. 2931–2940. PICMET, Portland (2016)
Günther, M., Stummer, C., Wakolbinger, L.M., Wildpaner, M.: An agent-based simulation approach for the new product diffusion of a novel biomass fuel. J. Oper. Res. Soc. 62, 12–20 (2011)
Kiesling, E., Günther, M., Stummer, C., Wakolbinger, L.M.: Agent-based simulation of innovation diffusion: a review. Cent. Eur. J. Oper. Res. 20, 183–230 (2012)
Kilicay-Ergin, N., Lin, C., Okudan, G.E.: Analysis of dynamic pricing scenarios for multiple-generation product lines. J. Syst. Sci. Syst. Eng. 24, 107–129 (2015)
Palmer, J., Sorda, G., Madlener, R.: Modeling the diffusion of residential photovoltaic systems in Italy: an agent-based simulation. Technol. Forecast. Soc. Change 99, 106–131 (2015)
Rogers, E.M.: Diffusion of Innovations, 5th edn. Free Press, New York (2003)
Stummer, C., Kiesling, E., Günther, M., Vetschera, R.: Innovation diffusion of repeat purchase products in a competitive market: an agent-based simulation approach. Eur. J. Oper. Res. 245, 157–167 (2015)
Swinerd, C., McNaught, K.R.: Comparing a simulation model with various analytic models of the international diffusion of consumer technology. Technol. Forecast. Soc. Change 100, 330–343 (2015)
van Rijnsoever, F.J., Oppewal, H.: Predicting early adoption of successive video player generations. Technol. Forecast. Soc. Change 79, 558–569 (2012)
Xiao, Y., Han, J.: Forecasting new product diffusion with agent-based models. Technol. Forecast. Soc. Change 105, 167–178 (2016)
Zhang, T., Siebers, P.-O., Aickelin, U.: Simulating user learning in authoritative technology adoption: an agent based model for council-led smart meter deployment planning in the UK. Technol. Forecast. Soc. Change 106, 74–84 (2016)
Zsifkovits, M., Günther, M.: Simulating resistances in innovation diffusion over multiple generations: an agent-based approach for fuel-cell vehicles. Cent. Eur. J. Oper. Res. 23, 501–522 (2015)
Acknowledgements
We would like to thank Immanuel Block for his support in acquiring the empirical data.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer International Publishing AG
About this paper
Cite this paper
Günther, M., Stummer, C. (2018). Simulating the Diffusion of Competing Multi-generation Technologies: An Agent-Based Model and Its Application to the Consumer Computer Market in Germany. In: Fink, A., Fügenschuh, A., Geiger, M. (eds) Operations Research Proceedings 2016. Operations Research Proceedings. Springer, Cham. https://doi.org/10.1007/978-3-319-55702-1_75
Download citation
DOI: https://doi.org/10.1007/978-3-319-55702-1_75
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-55701-4
Online ISBN: 978-3-319-55702-1
eBook Packages: Business and ManagementBusiness and Management (R0)