Skip to main content

Simulating the Diffusion of Competing Multi-generation Technologies: An Agent-Based Model and Its Application to the Consumer Computer Market in Germany

  • Conference paper
  • First Online:
Operations Research Proceedings 2016

Part of the book series: Operations Research Proceedings ((ORP))

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.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. 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)

    Google Scholar 

  2. 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)

    Article  Google Scholar 

  3. Desmarchelier, B., Fang, E.S.: National culture and innovation diffusion: exloratory insights from agent-based modeling. Technol. Forecast. Soc. Change 105, 121–128 (2016)

    Article  Google Scholar 

  4. Druehl, C.T., Schmidt, G.M., Souza, G.C.: The optimal pace of product updates. Eur. J. Oper. Res. 192, 621–633 (2009)

    Article  Google Scholar 

  5. 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)

    Google Scholar 

  6. 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)

    Article  Google Scholar 

  7. 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)

    Article  Google Scholar 

  8. 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)

    Article  Google Scholar 

  9. 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)

    Article  Google Scholar 

  10. Rogers, E.M.: Diffusion of Innovations, 5th edn. Free Press, New York (2003)

    Google Scholar 

  11. 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)

    Article  Google Scholar 

  12. 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)

    Article  Google Scholar 

  13. van Rijnsoever, F.J., Oppewal, H.: Predicting early adoption of successive video player generations. Technol. Forecast. Soc. Change 79, 558–569 (2012)

    Article  Google Scholar 

  14. Xiao, Y., Han, J.: Forecasting new product diffusion with agent-based models. Technol. Forecast. Soc. Change 105, 167–178 (2016)

    Article  Google Scholar 

  15. 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)

    Article  Google Scholar 

  16. 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)

    Article  Google Scholar 

Download references

Acknowledgements

We would like to thank Immanuel Block for his support in acquiring the empirical data.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Christian Stummer .

Editor information

Editors and Affiliations

Rights and permissions

Reprints 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

Publish with us

Policies and ethics