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Outline

2 min read

I. Introduction (1 min)

  • Hook:

    “What if groupthink, decision delays, or conflict in teams could be solved… by math?”

  • Define key terms:

    • Operations Research: mathematical modeling, optimization, decision science.

    • Group Dynamics: how people behave in groups—decision making, conformity, leadership, conflict.

  • Thesis statement:

    “This talk explores how operations research can be applied to model, predict, and optimize group behavior, turning social interactions into systems we can understand and improve.”

II. Foundations of Group Dynamics (2 min)

  • Briefly introduce foundational theories:

    • Tuckman’s stages: Forming → Storming → Norming → Performing

    • Lewin’s Field Theory: behavior = function(person, environment)

  • Real-world relevance:

    • Team projects, committees, management, social movement coordination

  • Transition:

    “Now let’s ask—how do we model this?”

III. Operations Research Models Relevant to Group Dynamics (4 min)

1. Linear Programming in Team Optimization

  • Assign roles/tasks optimally based on constraints (skills, time)

  • Example: maximizing team efficiency with limited resources

2. Game Theory

  • Group interactions as strategic decisions

  • Examples:

    • Prisoner’s Dilemma: cooperation vs. competition

    • Public Goods Game: free-riding in teams

3. Network Optimization and Graph Theory

  • Information/communication flow in a group

  • Centrality analysis (who is most influential)

  • Example: project management – critical path method (CPM)

4. Multi-Agent Simulation & Markov Models

  • Simulating how group decisions evolve over time

  • Opinion dynamics, social contagion models

Transition line:
“With these tools, let’s see how real-world problems in group behavior can be optimized.”

IV. Case Studies / Applications (3 min)

1. Workplace Collaboration

  • OR used to assign team tasks dynamically to reduce burnout

  • Resource allocation models for collaborative environments

2. Conflict Resolution

  • Modeling negotiation as a zero-sum or non-zero-sum game

  • Example: interest-based bargaining in labor disputes

3. Group Decision-Making

  • Voting rules & consensus optimization using integer programming

  • Jury decision modeling, boardroom voting

V. Challenges & Ethical Considerations (1.5 min)

  • Over-reductionism: can complex human emotions be “optimized”?

  • Data limitations: how to quantify interpersonal dynamics?

  • Ethical questions: manipulation of group behavior?

VI. Future Directions (1 min)

  • Human-AI Group Collaboration：OR helps AI adapt to human teams

  • Social Robotics：Using OR to manage swarm behavior

  • Disaster response teams：Optimal group deployment in time-critical missions

VII. Conclusion (0.5 min)

  • Summary:

    “Group dynamics may feel abstract, but operations research offers a structured, data-driven lens to understand and improve it.”

  • Final hook:

    “By bridging social behavior with mathematics, we don’t dehumanize it—we empower it.”

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