The document discusses individual decision making under uncertainty using decision trees. It provides an example of a decision facing Sarah Chang about whether to continue R&D on a new product or abandon the project. It frames the decision as a choice between two alternatives, maps it out as a decision tree showing probabilities and payoffs, and solves the tree to determine the optimal decision is to continue R&D. It also briefly discusses another example of Indiana Jones choosing which cup is the Holy Grail.

1. Individual Decision Making

5. Review of subject structure Subject Situation Description Tool Analysis Individual Decision-Making Single-agent decision One agent must make an optimal decision. The actions of others have no direct influence. Uncertainty and the time-value of money may be concerns. Decision tree Roll-back Strategic Decision-Making Simultaneous moves Both agents know everything about the game and each other. Decisions happen simultaneously. Matrix Game Nash Equilibrium Sequential moves Both agents know everything about the game and each other. Decisions happen sequentially. Sequential Game Roll-back Negotiations Bilateral Two agents who are active negotiations. Try to maximise value and appropriate their share Bargaining Theory Nash bargaining Monopoly One seller versus many buyers. All agents are active negotiators. Bargain over value split. VAUC (Value-Appropriation Under Competition) CDV & added value Many sellers Many sellers versus many buyers. All agents are active negotiators. Bargain over value split. VAUC CDV, added value, Market-clearing prices Mass-Market Pricing Monopoly One seller versus many buyers. Firm sets price. Supply (cost) & Demand (revenue) Functions MC = MR Oligopoly Many sellers vs. many buyers. Firms set prices. Bertrand, Cournot Nash, undercut-proofness

8. Individual decision making: “non-strategic” decisions Topic 1

11. Types of Decisions Degree of Uncertainty Low High Degree of Interdependence with others’ actions High Low Market entry Extreme sports What to wear What to have for lunch How hard to study Whether to do an MBA Which MBA What to bid

13. Example (non-strategic under certainty) = Decision Node: indicates a point at which an action must be taken (one path for each possible action) CBD $120,000 $150,000 Brunswick open a restaurant don’t $0 Entry decision Location decision

16. Step II Abandon Continue Not Proposal $0 Expend $50,000 and perhaps win

18. Step III Abandon Continue Not Proposal $0 Win Lose 0.05 0.95 $800,000 -$50,000

19. Step IV Abandon Continue Not Proposal $0 Win Lose 0.05 0.95 -$50,000 Succeed Fail 0.5 0.5 $800,000 Expend $50,000 and perhaps win Expend $50,000 and have a good chance of winning

20. Step V No Prop No Prop Abandon Continue $0 W L 0.05 0.95 -$50,000 Succeed Fail 0.5 0.5 $800,000 No Prop -$200,000 W L 0.9 0.1 -$250,000 $600,000 -$200,000 W L 0.05 0.95 -$250,000 $600,000

24. Solving the Tree Abandon Continue Not Proposal $0 Win Lose 0.05 0.95 $800,000 -$50,000 ? Expected value = 0.05 ($800,000) + 0.95 (-$50,000) = - $7,500

25. Solving the Tree Abandon Continue Not Proposal $0 -$7,500 ? Choose the branch with the best payoff

26. Solving the Tree Abandon Continue Succeed Fail 0.5 0.5 $0 Not Proposal -$200,000 Win Lose 0.9 0.1 -$250,000 $600,000 Not Proposal -$200,000 Win Lose 0.05 0.95 -$250,000 $600,000

27. Solving the Tree Abandon Continue Succeed Fail 0.5 0.5 $0 Not Proposal -$200,000 Win Lose 0.9 0.1 -$250,000 $600,000 Not Proposal -$200,000 -$207,500

28. Solving the Tree Abandon Continue Succeed Fail 0.5 0.5 $0 Not Proposal -$200,000 $515,000 -$200,000

29. Solving the Tree Abandon Continue Succeed Fail 0.5 0.5 $0 $515,000 -$200,000