The competitive threat!

1. Residential Workshop*Strategy & Competition S&CA Part IGame Theory PerspectivePatrick McNutt FRSAVisiting Fellow, Manchester Business School, UKVisiting Professor, Smurfit Business School, Dublin, IrelandTwitter @tuncnuncwww.patrickmcnutt.com*some of these slides may be used at Masterclass from Patrick McNutt

2. strategy without tactics is the slowest route to victory, tactics without strategy is the noise before defeatSun Tzu The Art of War

3. ‘The most meaningful way to differentiate your company from your competitor (….) How you gather, manage, and use information will determine whether you win or lose’.Bill Gates**quoted by Reid Hoffman in ‘Learn from People, Not Classes’ HBR March/April 2019 pp50-52

4. The competitive threat! • Traditional Analysis is focused on answering this question for Company X: what market are we in and how can we do better? • Economics of strategy (T/3) asks: what market should we be in? Answer: I. Identity of near-rival II. Co-operate in order to compete III. Maximin strategy: second mover advantage (SMA)

5. Economics Foundations from Topics 1 & 2 Trade-offs Demand and e-Needs Algorithmic pricing BIN < END Technology & Capacity

6. Game Theory Foundations from Topics 3 & 4 Game Design Rational Behaviour The Bayesian persuasion problem

7. Failure of Law of One Price BIN Price < END price Discussion of first assignment Game Dimension Sufficiently Intelligent Algorithm v Rational ‘onsumer’

8. Strategy as game theory: so, what is game theory about?Winning strategy…Visit www.patrickmcnutt.com • Is there an unbeatable strategy? Game DesignPayoffs & PreferencesRational BehaviourPrisoners’ Dilemma

9. Traditional Trade-Off

10. Prisoners’ Dilemma

11. Decoding Strategy and T/3 Design • TYPE • Observed behaviour (inductive) in a game, G. • Players are ascribed a type and a belief system • Identify the players in the game and the player’s type. Finding the patterns in rival behaviour. • What is a player’s true payoff? Private information v observed behaviour • Independence v interdependence; one-shot v repeated play. • TECHNOLOGY • Consumers’ preferences as technology in a game. • Individuals ‘enveloped’ by a game evolve as players • Technology per se as the competitor • TIME • Time, no time and timeless: dT/dt = -1

12. Pre-Play Game DesignT/3: ‘furniture of the player mind’ • To become a player in the game: (i) observe patterns (ii) recognise mutual interdependence (iii) strategy as signalling. • Players have a type and a belief system. Examples: Leo the Liar and gPhone Case Study: Philip Morris & BAT • Evaluation of a player’s type in terms of executing strategy • Updating belief systems. • Credible threats. • Baumol type (don’t chase the low price?) • To decode type observe timing of moves, frequency of moves, magnitude of moves, matching moves (T4T) and repetition.

13. Signalling: Linguistic communication strategy(honey bees) • Rule-guided communication (later we look at Folk Theorem and tacit cartels) • PLT: positive learning transfer (between shareholders & activist (Bayesian) shareholders) • Noise: Think x, Do y • Moonshot or ’false flags’

14. Player type and signalling • Decisions (observed actions) are interpreted as signals • Observed patterns and Critical Time Line (CTLs).Go to Appendix in McNutt • Recognition of market interdependence (zero-sum and entropy) • Price as a signal - Baumol model of TR max • Scale and size: capacity & cost leadership • Dividends as signals in a Marris model • Algorithmic prices and ‘folk theorem’

15. PRE-PLAY INSIDE THE GAME ENVELOPE Altruism v Selfish Gene Co-operate (Trust) v Compete (Cheat)

16. How to play in the ‘envelope’ of a game? Decode information on opponent type: observed behaviour, historic behaviour, corporate intelligence. Players recognise interdependence: action-reaction sequence. Participation in G has reward/payoff that depends on what each player believes about the other. Solution concept: Updating belief systems at an equilibrium point when neither player can do better independently of the opponent.

17. Reason & Rationality: Equivalence & ‘enveloped by the game’

20. Convert Preferences into a Tucker Payoff Table 1. Payoffs are cardinal numbers 1,2 or -1 or ½ And 2 > 1 and -3 < -1 2. Payoffs reflect individual preferences 3. Cardinal ranking 1st preference = a 2nd preference = b 3rd preference…….4th preference…… Least preferred = L Cardinality a > b Transitivity a > b > L L << │a, b│

21. Template Payoff TablePayoffs reflect preference order. Use cardinal numbers (2 > 1 and (-2 < -1)Guaranteed a 2 but is there is an elusive b = 3?

22. Nash Equilibrium •Many common games (and therefore many common strategic situations) are not solvable. Is behaviour irrational? RED in trying to do better than a 2 (with a 3) ends up with a 1 • Search for a solution in Nash equilibrium • Nash Equilibrium, is now one of the most fundamental concepts in the economics of strategy • Later we examine Thief of Nature to arrive at a solution in terms of the number of moves in a game (SMA), self-enforcing mechanism and ESS.

23. Thief of Nature Cheating on 2nd move after signalling trust on 1st move delivers ❺ 2 moves❺ Short-term gain 2 moves❺ > 2 moves ❹ Indifference with thief of nature….Lake Wobegon effect Opponent likewise with ‘I-think-You think-I-think’ and punishes the cheater for breaking trust. If knowledge of N moves then Short-term gain < Long Term Benefit Apply Euler’s number 0.375 Corollary: 4th move in a 10th-11th move sequence S, type betrayed on 4th move. 4/S ≈ 0.375

24. GAME DESIGN for STRATEGYPayoffs reflect preference order. What if? 2 strategies.What if? 2 players.Then if Strategy I is the consensus……..?

26. Strategic Trade-Off Then if Strategy I is the consensus……(i) There is an incentive to cheat(ii) Both players have to commit(iii) Players have to build trust

27. Strategic Trade-Off in Pure StrategiesThen if Strategy I Left and Strategy II Right are the consensus……(i) There is no incentive to cheat(ii) Both players have to commit=> Self-enforcing mechanism: prob ρ = (0,1)

28. Economic FoundationsClassroom Discussion on Elasticity and on Capacityhttp://www.patrickmcnutt.com/elearning/kaelo-learning-interactions-2/

29. Describe (prices as signals) game dimension • Players and type of players • Prices interpreted as signals • Understand (price) elasticity of demand and cross-price elasticity • Patterns of observed behaviour • Leader-follower as ‘knowledge’ in the game • Accommodation v entry deterrence • Action as a Reaction, • Observed Behaviour as ‘signalling’ type • Pooling and separating equilibrium (on type) • Camouflage and ‘false flags’ • Nash equilibrium: ‘best you can do, given reaction of a competitor’

30. Non Co-operative Strategic Games

31. Topics 1 & 2 to Topics 3 & 4

34. CL Type : Capacity & Costs Equivalence

35. Discussion of Strategy Set • Nash premise: Action, Reaction and CV matrix • Non-cooperative sequential (dynamic) games • TR Test McNutt pp48..one-shot move • Limit price [to avoid entry] and predatory pricing to force exit. • Near rival plays Minimax, so I play Maximin [focus on my worst minimum payoff and try to maximise]. • Segmentation strategy to obtain FMA • Relevance of ‘chain-store’ tumbling price paradox • Dark Strategy and 3 Mistakes in McNutt pp117-118

36. Oligopoly Games (n < 5) & T/3 Framework Study of strategic interactions: how firms adopt alternative strategies by taking into account rival behaviour. Structured and logical method of considering strategic situations. It makes possible breaking down a competitive situation into its key elements and analysing the dynamics between the players. Key elements: Players. Company or manager. Strategies. Payoffs Nash Equilibrium. Every player plays her best strategy given the strategies of the other players.

37. Player Types I Baumol type: player in a Bertrand game who will reduce price if demand is elastic. CL type: in Cournot capacity game we have a cost-leader type, CL, with reserve capacity. Incumbent and entrant: In the geography the incumbent already exists in the geography and the entrant is intent on entering or presents a threat of entry (contestable market). Dominant incumbent is a player with at least 25-40% of the market share. Often linked with Stackelberg or ‘top-dog’ in Besanko.

38. Costs of not being a Player • No playbook • Bounded rationality and opportunity costs with trade-offs • Make or Buy dilemma • First Mover Advantage (FMA) v Second Mover Advantage (SMA) Play to win v Play not to lose! • Fail to anticipate competitor reactions • Follower status ‘behind the curve’ • Technology lag and failure to differentiate ‘fast enough’ to sustain a competitive advantage • Near rival will try to minimise your gains by playing a minimax strategy

39. Player Types II Extant incumbent: An incumbent that has survived a negative event such as a price war of a failed innovation or technology-lag. De novo entrant: An entrant intent on entering – the incumbents can observe plant building or product launch. Potential entrant: An entrant that presents a threat of entry into a game through signalling with noise or ‘moonshot’ or planned capacity building in another game [with economies of scope). Stackelberg type: A price leader in a Bertrand game moving first in the belief that others will follow or in the knowledge that other are disciplined (often linked to collusive behaviour).

40. Surprise and Noise (and Moon-shot/false flags) • Binaryreaction: • Will Player B react? Yes or No? • If Yes, decision may be parked as ‘do-nothing strategy’ • If NO, decision proceeds on error & mistakes • Firsgt mover disadvantage • Surprise: action ≠ type • Cognitive Bias • Noise • Non-binaryreaction: • Player B will react. probability = ρ% • Probability (1-ρ)% A.N.Other player will react? Who? • Moon-shot and false flags • Spherical competitors • Decision taking on conjecture of likely reaction • No Surprise if discounted with contingent risk profile

41. Masterclass Games of Strategic Interaction Pure Conflict The Prisoner’s Dilemma Self-enforcing mechanisms Bertrand price games (Sony v MS case) Cournot games with Pareto dominant strategies (EK and Qantas case) Evolutionary Stable Strategies (ESS) Coordination Game with Asymmetric Information: (Sony v Toshiba case)

42. Decoding Strategy & Pattern Sequencing Complete knowledge on the type and complete information of the identity of a near rival: Actionyou -> Reactionnear-rival ->… ..-> Reactions……NashReplyyou….. Strategy defined in terms of an equilibrium: how well either player does in a game depends on what each player believes the other player will do.

43. 2000: Bertrand G1: PS2 v xBox 26 Oct 2000 US$299 Sony move (opening move)do-nothing from MS, waiting time imposed on Sony15 Nov 2001 US$299 MS moveno price differential, Sony bounded rational14 May 2002 US$ 199.99 Sony moveretaliatory punishment move15 May 2002 US$199 MS moveBertrand price reaction13 May 2003 US$ 179.99 Sony moveengaging in price war14 May 2003 US$179 MS move29 Mar 2004 US$149‘point of balance’ game converging to Nash equilibrium US$149 or less11 May 2004 US$149.99 Sony move2005:Cournot G2: PS3 v xBox360 22 Nov 2005 Xbox launched MS move6 Feb 2006 MS move US$179 (Xbox one-shot move)20 Apr US$129.99 Sony move (PS2 one-shot move)27 Apr 2006 MS move ( production: capacity signal)8 May 2006 Sony move launch PS3 (end May: capacity signal)………..t -> ∞

44. PATTERN – 2000-2006 Announcement PS3 production schedule to ship 6 million units by 31 Mar 07 at $499 PS2 launched at $299 PS2 at $199.99 PS2 at $179.99 PS2 at $149.99 100 million PS2 shipped PS2 at $129.99 11 May 04 20 April 06 8 May 06 15Nov01 26 Oct 00 14 May 02 15 May 02 13 May 03 14 May 03 29 Mar 04 05 1 Nov 30 Oct 05 22Nov05 6 Feb 06 27 April 06 Xbox at $179 22 million Xbox shipped Microsoft Xbox launched at $299 Revised production schedule for Xbox 360 to 5- 5.5 million units by 30th June 2006 Xbox 360 launched at $399 Xbox at $199 Xbox at $179 Xbox at $149

45. Nash Equilibrium & Define a price war • Construct the Bertrand reaction functions • Compute a Critical Time Line (CTL)from observed signals.. • Find a price point of intersection • Case Analysis of Sony v Microsoft in McNutt pp 141-144 and also in Kaelo v2.0

46. Reasons to Play

47. Perfect market: perfect competition • Defining a perfect market as follows: If ΔPi increases, then the firm’s output = 0 or rivals follow the price increase. • In a perfect market price differences cannot persist across time • Perfect competition = perfect market + near rivals So perfect market ≠> perfect competition but perfect competition => perfect market Folk Theorem and price hierarchy developed in Masterclass Note: Given that the winner raises price over time, the loser has no incentive to lower price. Reason: although the loser has always lost so far, which should push the loser to lower prices further, the loser knows that the winner is raising price, so that by not lowering price, the loser will win at the margins inside the price hierarchy.

48. Player A’s Conjectural Variation [CV] Matrix In a what-if scenario, a player creates a CV matrix to allow (i) filtering of the competitors (ii) that are likely to react to each action.

49. Thinking Strategically… http://www.managementinnovation.net/wp-content/uploads/2011/08/Playing-War-Games-To-Win.pdf Principles of competition and cooperation. Chess and perfect information Backward induction and forward reasoning Timing in games Normal form and Extensive form • one-shot v repeated play. • FRPD

50. Two basic forms of model are used to analyse games: The Normal (Strategic) Form of a game •Summarises players, strategies and payoffs in a ‘payoff matrix’ •Particularly suitable for analysing static games (e.g. games with simultaneous moves). Making choices simultaneously The Extensive (Dynamic) Form of a game •Summarises players, strategies and payoffs in a ‘game tree’ •Useful where the timing of players actions, and the information they will have when they must take these actions, is important (e.g. games with sequential moves)