1. A Model of Opinion Dynamics Among Firms Volker Barth, GELENA research group, Oldenburg University Potentials of Complexity Science for Business, Governments, and the Media Collegium Budapest, 03-05.08.2006

2. Outline  Motivation/Background  Basic model:  Opinion update based on external attribute  Extended model:  Opinion update based on multiple attributes  Conclusions

3. Motivation  Empirical case studies on learning of organisations with respect to sustainability (GELENA project)  Imitation and copying (Consulting)  Existence of networks  Leader-follower dynamics within organisations “Change agents”, Time lags

4. Motivation  Existing studies  Binary opinions  Continuous opinions Opinion exchange often based on thresholds (“bounded confidence” model) Source: Weisbuch et al., 2002

5. Basic Model (1): Agents 0+1 Full OppositionFull AgreementUndecided  Personal attribute (authenticity, credibility): a i = 0.1, 0.2,…1.0, Poisson distributed  Individual opinion (o i ):  One meeting per time step  Update opinion during meeting: o B (t+1) = o B (t) + (o A (t) - o B (t)) a A , for a A > a B

6.  Agents localised on lattice (torus)  Social connections, no (direct) spatial meaning  Limited environments (vonNeumann, Moore)  Meet only agents within environment Basic Model (2): Social Networks s

7. Agent Interaction: Sample Result  49 agents, 5000 meetings, Von Neumann, range: 2 Opinion range Local opinion leader

8. Agent Interaction: Network effect  49 agents, 5000 meetings, average over 30 runs

9. Basic Model: Summary  Agent opinions fluctuate between visible opinion leaders  Greater visibility  smaller opinion range  Local opinion leaders  Eccentric, but unchanged opinions; little impact on mainstream  Extend opinion range

10. Extended Model: Firm Interaction  Companies  Firm opinion (follows CEO opinion)  Firm attribute: economic performance  Agents now company executives  Implicit: Firm opinion and performance connected  Executives update opinion upon: 1.meetings with other executives 2.average firm opinion of better-performing firms: o i ’ = o i (t) + ( - o i (t) ) 

11. Firm Interaction: Sample Results  49 executives, 5000 meetings, von Neumann (s=1)  = 510 -5  = 510 -4

12. Firm Influence Parameter   49 executives, 5000 meetings, avg. over 30 runs

13. Firm Interaction: Sample Results 2  49 executives, 5000 meetings, von Neumann (s=1)  = 10 -3 Local opinion leader

14. Extended Model: Summary  Average firm opinion is attractor  Convergence (“Consensus”) of mainstream depends on interaction speed  Local opinion leaders still exist  Small effects on mainstream in the short run (“fuzzy fringe”)  Long-term attractor in the (very) long run  “Global opinion leader”

15. Conclusions  External attributes reflect actual opinion formation of humans  Narrow consensus requires credible and widely known proponents  otherwise localised opinions, wider range  Orientation on uniform opinions leads to narrow consensus  rules, values  Fixed, unbalanced opinions can shift mainstreams in the long run  Extremism

16. Thank you!

17. Visibility of firms

18. Agent Interaction: Network effect 1  49 agents, 5000 meetings, average over 30 runs

19. Agent Interaction: Network effect 2  49 agents, 5000 meetings, average over 30 runs

20. Firm Influence Parameter   49 executives, 5000 meetings, avg. over 30 runs