Advertisement

Multi-Agent-Based Simulation: Why Bother?

  • Scott Moss
  • Emma Norling
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3891)

Abstract

This year’s MABS workshop was the sixth in a series which is intended to look at “using multi-agent models and technology in social simulation,” according to the the workshop series homepage [1]. We feel that this is an appropriate time to ask the participants and the wider community what it is that they hope to gain from this application of the technology, and more importantly, are the tools and techniques being used appropriate for achieving these aims? We are concerned that in many cases they are not, and consequently, false or misleading conclusions are being drawn from simulation results. In this paper, we focus on one particular example of this failing: the consequences of the inappropriate use of numbers. The translation of qualitative data into quantitative measures may enable the application of precise analysis, but unless the translation is done with extreme care, the analysis may simply be more precisely wrong. We conclude that as a community we need to pay careful attention to the tools and techniques that we are using, particularly when borrowing from other disciplines, to make sure that we avoid similar pitfalls in the future.

Keywords

Management Research Strategic Management Journal Social Simulation Workshop Series Establishment View 
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.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Sichman, J.S.: Multi-agent-based simulation (MABS) – the international workshop series (2005), website http://www.pcs.usp.br/~mabs/
  2. 2.
    Gilbert, N., Conte, R., Sichman, J.S.: ICMAS 1998 workshop on multi-agent systems and agent-based simulation (MABS) (1998), website http://cress.soc.surrey.ac.uk/mabs98.html
  3. 3.
    de Jong, A., de Ruyter, K., Wetzels, M.: Antecedents and consequences of group potency: A study of self-managing service teams. Management Science 51, 1610–1625 (2005)CrossRefGoogle Scholar
  4. 4.
    Hales, D.: Change your tags fast! a necessary condition for cooperation? In: Davidsson, P., Logan, B., Takadama, K. (eds.) MABS 2004. LNCS (LNAI), vol. 3415, pp. 89–98. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  5. 5.
    Laursen, K., Salter, A.: Open for innovation: the role of openness in explaining innovation performance among U.K. manufacturing firms. Strategic Management Journal 27, 131–150 (2006)CrossRefGoogle Scholar
  6. 6.
    Sosa, R., Gero, J.S.: Social change: Exploring design influence. In: Hales, D., Edmonds, B., Norling, E., Rouchier, J. (eds.) MABS 2003. LNCS, vol. 2927, pp. 106–119. Springer, Heidelberg (2003)CrossRefGoogle Scholar
  7. 7.
    Pfeffer, J., Fong, C.T.: The end of business schools? less success than meets the eye. Academy of Management Learning & Education 1 (2002)Google Scholar
  8. 8.
    Ghoshal, S.: Bad management theories are destroying good management practices. Academy of Management Learning & Education 4, 75–91 (2005)CrossRefGoogle Scholar
  9. 9.
    Bennis, W.G., O’Toole, J.: How business schools lost their way. Harvard Business Review (2005)Google Scholar
  10. 10.
    Antunes, L., Balsa, J., Urbano, P., Moniz, L., Palma, C.R.: Tax compliance in a simulated heterogeneous multi-agent society. In: Sichman, J.S., Antunes, L. (eds.) MABS 2005. LNCS (LNAI), vol. 3891, Springer, Heidelberg (2006)CrossRefGoogle Scholar
  11. 11.
    Melo, A., Belchior, M., Furtado, V.: Analyzing police patrol routes with the simulation of the physical reorganization of agents. In: Sichman, J.S., Antunes, L. (eds.) MABS 2005. LNCS (LNAI), vol. 3891, Springer, Heidelberg (2006)CrossRefGoogle Scholar
  12. 12.
    Rodrigues, M.R., Luck, M.: Analysing partner selection through exchange values. In: Sichman, J.S., Antunes, L. (eds.) MABS 2005. LNCS (LNAI), vol. 3891, Springer, Heidelberg (2006)CrossRefGoogle Scholar
  13. 13.
    Sultanik, E.A., Peysakhov, M.D., Regli, W.C.: Agent transport simulation for dynamic peer-to-peer networks. In: Sichman, J.S., Antunes, L. (eds.) MABS 2005. LNCS (LNAI), vol. 3891, Springer, Heidelberg (2006)CrossRefGoogle Scholar
  14. 14.
    Edmonds, B.: Against the inappropriate use of numerical representation in social simulation. Technical Report 04-131, Centre for Policy Modelling (2004), available at http://cfpm.org/cpmrep129.html
  15. 15.
    Edmonds, B.: Assessing the safety of (numerical) representation in social simulation. In: Proceedings of the 3rd European Social Simulation Association conference (ESSA 2005), Koblenz, Germany (2005)Google Scholar
  16. 16.
    Academy of Management Review: Information for contributors. Academy of Management Review 30, 230 (2005)Google Scholar
  17. 17.
    Academy of Management Journal: Information for contributors. Academy of Management Journal 48, 179 (2005)Google Scholar
  18. 18.
  19. 19.
    Administrative Science Quarterly website (2005), http://www.johnson.cornell.edu/publications/asq/contributors.html
  20. 20.
    Management Science website (2005), http://mansci.pubs.informs.org/amission.html
  21. 21.
    Hackman, J., Wageman, R.: A theory of team coaching. Academy of Management Review 30, 269–287 (2005)CrossRefGoogle Scholar
  22. 22.
    Wageman, R.: How leaders foster self-managing team effectiveness: Design choices versus hands-on coaching. Organization Science 12, 559–577 (2001)Google Scholar
  23. 23.
    Cronbach, L.: Coefficient alpha and the internal structure of tests. Psychometrika 16, 297–333 (1951)CrossRefMATHGoogle Scholar
  24. 24.
    Cohen, S.G., Ledford Jr., G.E., Spreitzer, G.M.: A predictive model of self-managing work team effectiveness. Human Relations 49, 643–676 (1996)CrossRefGoogle Scholar
  25. 25.
    Milton, L., Westphal, J.: Identity confirmation networks and cooperation in workgroups. Academy of Management Journal 48, 191–212 (2005)CrossRefGoogle Scholar
  26. 26.
    Edwards, J.R.: The study of congruence in organizational behavior research: Critique and a proposed alternative. Organizational Behavior and Human Decision Processes 58, 51–100 (1994)CrossRefGoogle Scholar
  27. 27.
    Edwards, J.R.: Alternative to difference scores: Polynomial regression analysis and response surface methodology. In: Drasgow, F., Schmitt, N. (eds.) Measuring and Analysing Behavior in Organizations: Advances in Measurement and Data Analysis, pp. 350–400. Jossey-Bass ( (2002)Google Scholar
  28. 28.
    Cohen, P.R.: Heuristic Reasoning about Uncertainty: An Artificial Intelligence Approach. Pitman, London (1985)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Scott Moss
    • 1
  • Emma Norling
    • 1
  1. 1.Centre for Policy ModellingManchester Metropolitan UniversityUK

Personalised recommendations