Modelling societal transitions with agent transformation

Open Access


Transition models explain long-term and large-scale processes fundamentally changing the structure of a societal system. Our concern is that most transition models are too static. Although they capture a move of focus from static equilibria to transitions between dynamic equilibria, they are still rooted in an “equilibriumist” approach. Improvement is possible with agent-based models that give attention to endogenous system processes called “transformation processes”. These models can render far more dynamic pictures of societal systems in transition, and are no longer remote from descriptions in the emerging transition literature.


Societal transitions Integrated sustainability assessment Agent-based modelling 


  1. Axelrod R (1997) The evolution of strategies in the iterated prisoner’s dilemma. In: Axelrod R (ed) The complexity of cooperation: agent-based models of competition and collaboration. Princeton University Press, Princeton Google Scholar
  2. Bergman N, Haxeltine A, Whitmarsh L et al. (2008) Modelling socio-technical transition patterns and pathways. J Artif Soc Soc Simul 11(3):7 Google Scholar
  3. de Haan J (2007) Pillars of change: a theoretical framework for transition models. Paper presented at the symposium ‘modelling transitions to sustainability’ at the ESEE 2007 conference ‘integrating natural and social sciences for sustainability’ Google Scholar
  4. Fowler JH, Laver M (2008) A tournament of party decision rules. J Confl Resolut 52(1):68–92 CrossRefGoogle Scholar
  5. Frenken K (2006) Innovation, evolution and complexity theory. Edward Elgar, Cheltenham and Northampton Google Scholar
  6. Geels FW (2002) Understanding the dynamics of technological transitions: a co-evolutionary and socio-technical analysis. Centre for studies of Science, Technology and Society, Twente University, Enschede, p 426 Google Scholar
  7. Geels FW, Schot JW (2007) Typology of socio-technical transition pathways. Res Policy 36(3):399–417 CrossRefGoogle Scholar
  8. Greene DL, Leiby P, Tworek E et al (2006) Systems analysis of hydrogen transition with HytTrans. In: Transportation research board annual meeting 2006, Paper #06-2538 Google Scholar
  9. Haxeltine A, Whitmarsh L, Bergman N et al. (2008) Conceptual framework for transition modelling. Int J Innov Sustain Dev 3(1–2):93–114 CrossRefGoogle Scholar
  10. Holling CS, Gunderson LH (2002) Resilience and adaptive cycles. In: Gunderson LH, Holling CS (eds) Panarchy: understanding transformations in human and ecological systems. Island Press, Washington, pp 25–62 Google Scholar
  11. Kauffman S (1989) Adaptation on rugged fitness landscapes. In: Stein E (ed) Lectures in the science of complexity. Addison-Wesley, Reading Google Scholar
  12. Kollman K, Miller J, Page S (1992) Adaptive parties in spatial elections. Am Polit Sci Rev 86:929–937 CrossRefGoogle Scholar
  13. Kollman K, Miller J, Page S (1998) Political parties and electoral landscapes. Br J Polit Sci 28:139–158 CrossRefGoogle Scholar
  14. Laver M (2005) Policy and the dynamics of political competition. Am Polit Sci Rev 99(2):263–281 CrossRefGoogle Scholar
  15. Laver M, Schilperoord M (2007) Spatial models of political competition with endogenous political parties. Philos Trans R Soc B 362(1485):1711–1721 CrossRefGoogle Scholar
  16. Nelson RR, Winter SG (1982) An evolutionary theory of economic change. Belknap—Harvard University Press, Cambridge Google Scholar
  17. Rip A, Kemp R (1998) Technological change. In: Rayner S, Malone EL (eds) Human choice and climate change, vol 2. Battelle Press, Columbus, pp 327–399 Google Scholar
  18. Rotmans J (2005) Societal innovation: between dream and reality lies complexity. ERIM, Erasmus Research Institute of Management, Rotterdam Google Scholar
  19. Rotmans J (2006) Tools for integrated sustainability assessment: a two-track approach. The Integr Assess J 6(4):35–57 Google Scholar
  20. Rotmans J, Loorbach D (2008) Transition management: reflexive governance of societal complexity through searching, learning and experimenting. In: Van den Bergh JCJM, Bruinsma FR (eds) The transition to renewable energy: theory and practice. Edward Elgar, Cheltenham Google Scholar
  21. Rotmans J, Kemp R, van Asselt MBA (2001) More evolution than revolution: transition management in public policy. Foresight 3(1):15–32 CrossRefGoogle Scholar
  22. Schelling T (1971) Dynamic models of segregation. J Math Sociol 1:143–186 Google Scholar
  23. Schwoon M, Alkemade F, Frenken K et al (2006) Flexible transition strategies towards future well-to-wheel chains: an evolutionary modelling approach. FNU working paper Google Scholar
  24. Struben JR (2006) Identifying challenges for sustained adoption of alternative fuel vehicles and infrastructure. MIT sloan research paper no. 4625-06. Available at SSRN:
  25. Struben JR, Sterman J (2006) Transition challenges for alternative fuel vehicle and transportation systems. MIT sloan research paper no. 4587-06. Available at SSRN:
  26. van Asselt MBA, Rotmans J (2002) Uncertainty in integrated assessment modellig: from positivism to pluralism. Clim Chang 54:75–105 CrossRefGoogle Scholar
  27. Watts DI, Strogatz SH (1998) Collective dynamics off ‘small-world’. Networks 393(6684):440–442 Google Scholar
  28. Weaver PM, Rotmans J, Turnpenny J et al. (2007) Methods and tools for integrated sustainability assessment (MATISSE): A new European project. In: George C, Kirkpatrick C (eds) Impact assessment and sustainable development: European practice and experience, chapter 9. Edward Elgar, Cheltenham Google Scholar

Copyright information

© The Author(s) 2008

Authors and Affiliations

  • Michel Schilperoord
    • 1
  • Jan Rotmans
    • 1
  • Noam Bergman
    • 2
  1. 1.Faculty of Social Sciences, Dutch Research Institute for TransitionsErasmus University RotterdamDR RotterdamThe Netherlands
  2. 2.Environmental Change Institute DysonUniversity of OxfordOxfordUK

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