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,

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

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

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

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

 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

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

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

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

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) ) 

Firm Interaction: Sample Results  49 executives, 5000 meetings, von Neumann (s=1)  =  =

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

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

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”

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

Thank you!

Visibility of firms

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

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

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