Skip to main content

Dynamic Modeling of New Technology Succession: Projecting the Impact of Macro Events and Micro Behaviors On Software Market Cycles

  • Conference paper
Unifying Themes in Complex Systems

Abstract

The subject of technology succession and new technology adoption in a generalized sense has been addressed by numerous authors for over one hundred years. Models which accommodate macro-level events as well as micro-level actions are needed to gain insight to future market outcomes. In the ICT industry, macro-level factors affecting technology adoption include global events and shocks, economic factors, and global regulatory trends. Micro-level elements involve individual agent actions and interactions, such as the behaviors of buyers and suppliers in reaction to each other, and to macro events. Projecting technology adoption and software market composition and growth requires evaluating a special set of technology characteristics, buyer behaviors, and supplier issues and responses which make this effort particularly challenging.

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 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

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Bibliography

  1. Arthur, W. Brian, “Complexity and the Economy”. Science, 2 April 1999, 284, 107–109.

    Article  ADS  Google Scholar 

  2. Arthur, W. Brian, “Competing Technologies, Increasing Returns, and Lock-in by Historical Events”. The Economic Journal, 99, (March 1989), pp. 116–131.

    Article  Google Scholar 

  3. Arthur, W. Brian & Wolfgang Polak, “The Evolution of Technology within a Simple Computer Model”. Santa Fe: Santa Fe Institute, December 17, 2004.

    Google Scholar 

  4. Bonabeau, Eric, “Don’t Trust Your Gut”. Cambridge: Harvard Business Review, May, 2003.

    Google Scholar 

  5. Bonabeau, Eric, “Agent-based modeling: methods and techniques for simulating human systems”. Proceedings of the National Academy of Sciences, vol.99, suppl. 3, May 14, 2002.

    Google Scholar 

  6. Correia, Joanne, and Mertz, Sharon “CRM Market Trends”. Gartner. Inc.: Gartner Customer Relationship Management Summit, San Diego, October, 2005.

    Google Scholar 

  7. David, Paul A. “Clio and the Economics of QWERTY”. Economic History, Vol. 75 No.2, pp. 332–337, May, 1985

    Google Scholar 

  8. Farrell, Joseph, and Garth Saloner, “Standardization, Compatibility, and Innovation”. M.I.T. Working Paper #345, April, 1984.

    Google Scholar 

  9. Feiman, J., Kirwin, B., Morello, D. and Redman, P. “Enterprise Personality Profile: Dimensions and Descriptors”. Gartner, Inc., ID Number: COM-22-3417, March 16, 2004.

    Google Scholar 

  10. Haines, Michael, “The Enterprise Personality Profile Builds Sales Insight”. Gartner, Inc., ID Number: G00122510, September 2, 2004.

    Google Scholar 

  11. Katz, Michael L., and Carl Shapiro, “Technology Adoption in the Presence of Network Externalities”. The University of Chicago: Journal of Political Economy, 1986, vol. 94, no. 4, pp. 822–841

    Google Scholar 

  12. Kirwin, B., Feiman, J., Morello, D. and Redman, P. “Enterprise Personality Profile: How Did We Get There?”. Gartner, Inc., ID Number: COM-22-3093, March 16, 2004

    Google Scholar 

  13. Windrum, Paul, “Unlocking a lock-in: towards a model of technological succession”. Maastricht: Maastricht Economic Research Institute on Innovation and Technology

    Google Scholar 

  14. Windrum, Paul & Chris Birchenhall, “Technological diffusion, welfare and growth: technological succession in the presence of network externalities”. Maastricht: Maastricht Economic Research Institute on Innovation and Technology, MERIT Infonomics Research Memorandum Series, 2002.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2010 Springer

About this paper

Cite this paper

Mertz, S.A., Groothuis, A., Fellman, P.V. (2010). Dynamic Modeling of New Technology Succession: Projecting the Impact of Macro Events and Micro Behaviors On Software Market Cycles. In: Minai, A., Braha, D., Bar-Yam, Y. (eds) Unifying Themes in Complex Systems. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85081-6_52

Download citation

Publish with us

Policies and ethics