BA 511 Politics & Games

1. BA 511 Politics & Games A Sampling of Managerial-Related Issues

2. Firms as Governance Structures • Coase-Williamson-Radner • Aside on transactions costs/nature of firm • Markets: • Strong incentives & contract dispute • Weak administrative control/planning • Firms: • Strong on administrative control • Weak on incentives & contract dispute • Optimal mix make-buy; optimal planning; market in firm; pre-contract & post-contract issues

3. Decision Mechanism Problems • Case: 1912 Election • Wilson 42%; Roosevelt 27%; Taft 23 %; Debs 6% • LA “David Duke”; 2008 GOP Primaries … • Arrow Theorem: No mechanism (voting; market) can satisfy basic conditions: • (i) no dictator; (iii) all relevant preferences/options matter; (iii ) consistency outcomes with order/arrangement; (iv) consistency from individual to aggregate preferences; • AT: violation inevitable; which is most acceptable? • Mechanisms subject to manipulation • Management Implications? • Proposal order; proposal voting rules; decision chain;

4. Costs of Decisions: No Magic in 50% Rule Benefits of additional Parties to agreement Costs of additional Parties to agreement 100% 0% M*

5. Policies (rules) v. Discretion Tradeoffs • Cases: • NWA Detroit Tarmac Debacle • Coach K: “people set rules to keep from making decisions” • End-of-year budget bait-switch • Econ Issues • How costly is discretion? • Influence on incentives/forward-looking behavior • How widespread/systematic is the event/problem • How costly is adherence to policy • Specifying contingencies; writing rules (TC) • Paradox: Rule for departing from rule?

6. Change Politics & Org Inertia • Cases: • Branch Rickey: Brooklyn Dodgers; • Jack Welch: GE; UTA President • Basic Principles • Optimal rate of change • Interest group dynamics • Who can you count on • Higher level management • “Lieutenants”

7. Examples of Settings and Behaviors Group/individual Cooperation Dynamics (inter/intra group, unit) Prisoner’s Dilemma; Hostage’s Dilemma Promises/Threats/Commitments Cooperation/Non-coop: Prisoner’s Dilemma; Hostage’s Dilemma Pricing games; Inter/Intra-unit or group dynamics; Location Games Geographic; Proposal Bidding-Bargaining; Employment Processes (hiring; monitoring) Signalling-Filtering Misc Pricing, Ads, Competition, Entry, Exit Parent-child; Spouses; Siblings Politics & “Games” Many governance (and market) settings involve strategizing of 2 (or more) players where their decisions are “actively interdependent” • Not just “playing against market” with fixed prices/behavior • Think chess, poker, or rock-paper-scissors, not roulette

8. Essential Features of Games • Case: Consider Poker or “Chicken” • Players • Information/beliefs of players • Actions/strategies available to players • Payoffs to moves/paths • Timing of moves/sequence or together • Manipulation of any of these elements by players • Solving: Putting self in other’s shoes

9. Solution Concepts & Game Basics:Thinking Ahead—Reasoning Back • Case: Apollo 1 Aftermath • Tom Hanks’ HBO series-- From the Earth to the Moon– U.S. space program from Mercury through moon landings. Strategic segment involves the aftermath of the Apollo 1 deaths of 3 astronauts during a launch pad tests: • A capsule fire during a routine test. • The fire resulted from a spark in wiring • The test under highly pressurized, pure oxygen capsule; contractor (North American) sent repeated warnings to NASA • Capsule reached temperatures over 1000 in 15 seconds • NASA planned to lay substantial blame on NA   • NA chief engineer argues for exposing NASA memos • NA executive, “no, we’re not and goes on to respond; we’re going to just take it” • Can you make sense of the boss’ decision?

10. Manipulating Elements of the Game and Countering Manipulation • Cases: Cortez ship burning; Poker betting • (Credible) Commitment & actions/beliefs • Cases: Retail Stores; My Daughter • Limiting available actions • Expanding available actions • Case: Proposal Consideration by Committees/Task Forces • Agenda Control • Amendments

11. First or Second Mover Advantage? • Case: Princess Bride • First Mover Advantage if manipulation of possible through changing game or beliefs of rival • Cases: Sailing; NCAA Football Overtime • Second Mover Advantage if information becomes available by rival’s move • Poker? • Tradeoff: info manipulation v. info gathering

12. Smart but Not Too Smart • Case: Email Phishing Schemes • Too good to be true, probably is • Case: Colts in 2010 Super Bowl • Dominant strategy but a lot of mixing • Don’t outsmart yourself

13. “Location” Games (with extensive information and single dimension) • Where to setup shop if consumer/voters positioned uniformly (or normally) along a road, given that competitor is trying to setup shop in best location also? • Simple Solution: Move to the middle (median), otherwise, competitor can locate just to the “busier” side and capture everyone on that side • Examples: Variety of retail stores; primary & general election races;

14. “Location” Games(with very limited information) • Where to setup shop if consumer/voters clustered in 10 large cities, you will locate in 5 and a rival firm will locate in 5 but agreements that divide cities are strictly prohibited and punishable by large punitive fines? • Solutions: use of “focal points” • Stanford-Harvard MBA “Divide the Cities” Game • Variants: T. Schelling (Strategy of Conflict) where to meet in NYC?

15. Median Location/Voter Model Breakdown(multiple dimensions) No single dominant position due to asymmetry of preferences Y: Income Customer /Voter Preferences - Metrics X: Traffic 0

16. Prisoner’s Dilemma • Criminals arrested; interrogated w/no cooperation • Choices: Confess/Don’t confess • 1 Confesses = low/high sentences • 2 Confess = moderate sentences • 0 Confess = low/acquittal • Outcomes: cooperative (positive sum) solution v. competitive solution • How to arrive at cooperative solution? • With no/limited info & explicit cooperation? • With cheating?

17. Prisoner’s Dilemma-like Games • Hostage’s Dilemma • Multi-person version of PD • Oligopoly Games • (pricing, ads, entry, …) • Cooperation (maybe implicit) leads to higher profits than competition

18. Game Basics: Bargaining Tactics • Case: Builder-Homeowner • Understanding Incentives/Tradeoffs & Info • Info asymmetry • Flex-price: flexibility of changes; no “hold-out problem”; wrong incentive for info problem • Fixed-price: Incentive to monitor & control expenses; “hold-out” problem on changes; incentive to cut corners • Case: Car-buying • Signaling • Patience is best signal of patience

19. Ultimatum Game (and related) theory and experimentation • Split of pot if 2 parties agree on split; 1 makes offer-1 accepts or declines offer; • Variations: size of pot; depreciation of pot; anonymity; repetition; wealth of participants; … • Money matters but not all that matters • Typical outcomes: bigger than 99:1, less than 50:50 • Patience is a virtue • Patience is the best signal of patience • Tradeoffs in most bargaining situations

20. Bargaining Tradeoffs(Home Building-Purchasing Case) • Builder-Homeowner • Builder info advantage • Buyer Choices: • Flex Price w/fixed percentage • Fixed-Price w/negotiated changes • Info/Incentive Tradeoffs

21. Insight on Solutions • “Nash Equilibrium”: outcome where opponent doing best possible • Sequential • “Rollback”: Look ahead to last period and work back • Simultaneous • Iterative: step-by-step analysis of best choice given a decision by other • Repeated Simultaneous • Rollback + Iterative

22. Iterative Solutions to Simultaneous Game(PD Example) • Payoffs = (Coke profits , Pepsi profits) • Decisions: Price Low or Price High

23. Solutions to Simultaneous • First Iteration: Coke considers best choice if Pepsi sets low price (column 1) Best choice for Coke, if Pepsi Sets Low Price

24. Solutions to Simultaneous • Second Iteration: Coke considers best choice if Pepsi sets high price; • Low is dominant strategy for Coke; Low better than high in both iterations Best outcome for Coke, If Pepsi Sets High Price

25. Solving Sequential Games “Life must be understood backward, but … it must be lived forward.” - Soren Kierkegaard (Consider Chess as Example) • Diagram a game tree – simplify if needed • Start with the last move in the game • Determine the best course(s) of action for the player with the last move • Trim the tree -- Eliminate the dominated strategies • Repeat the procedure at the prior decision node(s) with the trimmed tree

26. An Example: Market Entry • Game Essentials: • Players: Current firm (F) with large market share faces a potential entrant (E) • Timing: Potential entrant moves first • Moves: Potential entrant (enter-stay out) Current firm (accept passively-fight) • Information: full information • Payoffs: (see game tree) • Rules: Fixed (to simplify game for now)

27. out (0, 100) E in (-10,-20) fight F acc (20,75) Scenario in Game Tree Payoffs = (E, F) expressed as profits (mil $)

28. (-10,-20) fight F acc (20,75) Looking Forward… • Entrant makes the first move: • Must consider how F will respond • If enter: • Current Firm better off if accepts; so trim “fight” branch from tree

29. (0, 100) out E in F acc (20,75) … And Reasoning Back • Now consider entrant’s move with tree trimmed • Solution = (In, Accept Passively )