Models and Communication in the Policy Process

  • Matteo Pedercini
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7041)


Policy-making is a complex process that involves a variety of actors. Several difficulties of various nature intervene in such process, making the identification and implementation of successful policies especially difficult. The usefulness of models in addressing technical obstacles related to the incorrect understanding of the issues and inferring of policy impacts have been broadly investigated [1,2]. Beyond facilitating technical aspects of the policy process, models can also facilitate communication among actors involved in such process.


Policy Process Successful Policy System Dynamics Approach Correct Communication Group Support System 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Sterman, J.D.: Business Dynamics: Systems Thinking and Modelling for a Complex World. McGraw-Hill Higher Education, New York (2000)Google Scholar
  2. 2.
    Tversky, A., Kahneman, D.: Judgment under uncertainty: Heuristics and biases. Science, New Series 185(4157), 1124–1131 (1982)Google Scholar
  3. 3.
    Lindblom, C.E.: The Science of “Muddling Through”. Public Administration Review 19(2), 79–88 (1959)CrossRefGoogle Scholar
  4. 4.
    Saeed, K.: A Re-evaluation of the Effort to Alleviate Poverty and Hunger. Socio Economic Planning Sciences 21(5), 291–304 (1987)CrossRefGoogle Scholar
  5. 5.
    Meadows, D., Robinson, J.: The electronic oracle: computer models and social decisions. System Dynamics Review 18(2), 271–308 (2002)CrossRefGoogle Scholar
  6. 6.
    Saeed, K.: Development planning and policy design, a System Dynamics approach. Ashgate, Londo (1994)Google Scholar
  7. 7.
    Senge, P., Sterman, J.D.: Systems thinking and organizational learning: Acting locally and thinking globally in the organization of the future. European Journal of Operational Research 59(1), 137–150 (1992)CrossRefGoogle Scholar
  8. 8.
    Sterman, J.D.: Learning in and about complex systems. System Dynamics Review 10(2-3), 291–330 (1994)CrossRefGoogle Scholar
  9. 9.
    Davidsen, P.I.: Educational Features of the System Dynamics Approach to Modelling and Learning. Journal of Structural Learning 12(4), 269–290 (1996)Google Scholar
  10. 10.
    Größler, A., Maier, F.H., et al.: Enhancing Learning Capabilities by Providing Transparency in Business Simulators. Simulation & Gaming 31(2), 257–278 (2000)CrossRefGoogle Scholar
  11. 11.
    Vennix, J.A.M.: Building consensus in strategic decision making: system dynamics as a group support system. Group Decision and Negotiation 4(4), 335–355 (1995)CrossRefGoogle Scholar
  12. 12.
    Andersen, D.F., Richardson, G.P., et al.: Group Model Building: Adding More Science to the Craft. System Dynamics Review 13(2), 187–201 (1997)CrossRefGoogle Scholar
  13. 13.
    Ford, D.N., Sterman, J.D.: Expert Knowledge Elicitation to Improve Formal and Mental Models. System Dynamics Review 14(4), 309–340 (1998)CrossRefGoogle Scholar
  14. 14.
    Fiddaman, D.: Dynamics of Climate Policy. Syst. Dyn. Rev. 23, 21–34 (2007)CrossRefGoogle Scholar
  15. 15.
    Kopainsky, B., Pedercini, M., Davidsen, P.I., Alessi, S.M.: Blending planning and learning for national development. Simulation & Gaming 41(5), 641–642Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Matteo Pedercini
    • 1
  1. 1.Millennium InstituteWashingtonU.S.A.

Personalised recommendations