The innovation theory (briefly, 2T), which has been developed in the ISCOM project and which is presented in this book (Chapters 9 and 10), is based on the analysis of different case studies, spanning different time periods and different kinds of products, from the introduction of printing in the Renaissance, to key new technologies introduced in the 19th and 20th centuries, up to present-day ongoing innovation efforts.
Access provided by Autonomous University of Puebla. Download to read the full chapter text
Chapter PDF
Similar content being viewed by others
References
Axelrod, R., & Tesfatsion, L. (2006). A guide for newcomers to agent-based modeling in the social sciences. In L. Kenneth, K. L. Judd, & L. Tesfatsion (Eds.), Handbook of computational economics, volume.2: Agent-based computational economics (pp. 1647–1658). Amsterdam, The Netherlands: North-Holland.
Bak, P. (1996). How nature works. New York, NY: Springer.
Epstein, J. M., & Axtell, R. (1996). Growing artificial societies: Social science from the bottom up. Cambridge, MA: Massachusetts Institute of Technology Press.
Fontana, W., & Buss, L. W. (1994). What would be conserved if ‘the tape were played twice’? Proceedings of the National Academy of Sciences, 91, 757–761.
Gilbert, N., & Terna, P. (2000). How to build and use agent-based models in social science. Mind and Society, 1, 57–72.
Kauffman, S. A. (1993). The origins of order. Oxford, UK: Oxford University Press.
Lane, D., & Maxfield, R. (2005). Ontological uncertainty and innovation. Journal of Evolutionary Economics, 15, 3–50.
Lane, D.A., Serra, R., Villani, M., & Ansaloni, L. (2005). A theory-based dynamical model of innovation processes. ComPlexUs, 2, 177–194.
Palla, G., Derényi, I., Farkas, I., & Vicsek, T. (2005). Uncovering the overlapping community structure of complex networks in nature and society. Nature 435, 814.
Scott, J. P. (2000). Social network analysis: A handbook. (2nd ed.). London, UK: Sage Publications Ltd.
Serra, R., & Villani, M. (2006). Agents, equations and all that: on the role of agents in understanding complex systems. In M. Schaerf, & M. O. Stock (Eds.). Reasoning, action and interaction in AI systems and theories. Springer Lecture Notes in Computer Science 4155, 159–175.
Serra, R., Villani, M. Graudenzi, A., & Kauffman, S. A. (2007). Why a simple model of genetic regulatory networks describes the distribution of avalanches in gene expression data. Journal of Theoretical Biology, 249, 449–460.
Serra, R., Villani, M., & Semeria, A. (2004). Genetic network models and statistical properties of gene expression data in knock-out experiments. Journal of Theoretical Biology, 227, 149–157.
Serra, R., Zanarini, G., Andretta, M., & Compiani, M. (1986). Introduction to the physics of complex systems. Oxford, UK: Pergamon Press.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer Science+Business Media B.V.
About this chapter
Cite this chapter
Serra, R., Villani, M., Lane, D. (2009). Modeling Innovation. In: Lane, D., Pumain, D., van der Leeuw, S.E., West, G. (eds) Complexity Perspectives in Innovation and Social Change. Methodos Series, vol 7. Springer, Dordrecht. https://doi.org/10.1007/978-1-4020-9663-1_14
Download citation
DOI: https://doi.org/10.1007/978-1-4020-9663-1_14
Publisher Name: Springer, Dordrecht
Print ISBN: 978-1-4020-9662-4
Online ISBN: 978-1-4020-9663-1
eBook Packages: Humanities, Social Sciences and LawSocial Sciences (R0)