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Managerial Economics Economics of Strategy and Games Decoding Strategy Patrick McNutt Follow @tuncnunc www.patrickmcnutt.com Abridged © What is game theory? • Observed behaviour in a game dimension. G • Identify the players in the game and the players type • Finding the patterns in rival behaviour • Updating belief systems. • Independent decision making v interdependence; one-shot v repeated play Decoding Strategy and Strategic Analysis • Knowledge of the identity of near rival: Actionyou -> Reactionrival -> NashReplyyou Why the focus?At the frontier of economic analysis….. • Understand management as ‘they are’ not as theory hitherto ‘assumed them’ to be • Management can be ranked (by type) and are faced with indifference trade-offs => something must come ‘top of the menu’: the 3rd variable or z. Trade off (x, y) to max z. • Firms are conduits of information flows (vertical chain) • Supply chain capacity constraints and technology-lag • Reducing price does not necessarily lead to an increase in revenues (elasticity) • Prices are primarily signals (observed behaviour) • Companies understand the competitive threat as (recognised) interdependence (zero-sum and entropy) Workshop Lesson plan…. • • • • • Learning Plan is to follow Besanko’s Economics of Strategy 6th Edition ..selected Chapters and cases/examples. Day 1 : Synopsis of E-Tutorials and Revision of Chapters 3 and 4 (Vertical Boundaries of the Firm, Agency and Co-ordination) and Introduce Chapter 2 (Economies of Scale and Scope) Day 1: Game Dimension and Introduce Workshop Case Analysis Day 1: Introduction and setting the scene using McNutt’s Decoding Strategy 2nd Edition Chapters 1 to 9 as required Day 2 & 3: Focus on Besanko Part II: Chapters 5,6,7 and 8 and link into Units 3 and 4 Workshop Focus • Management type and relevance of TCE: Unit 1. Besanko Ch 3 & 4 and 5, McNutt Ch 1 • Cost leadership and economics of capacity: Unit 2. Besanko Ch 2 and McNutt Ch 5 • Market-as-a-game…market structure, oligopoly, and dynamic games…Units 3 and 4. Besanko Ch 5,6,7 and 8 and McNutt Ch 6,7,8 and 9 • Real Time case Analysis…go to Page 45 of colourcoded Storybook Example A: What is type? If you believe it to be true that Leo the Liar will never tell the truth, how do you respond to his helping hand as you cling for your life over the precipice of a cliff? Do you ignore his helping? Do you rely instead on the many apps on your smartphone, so tightly grasped in your other hand, trying to make contact with your best friend to come and rescue you? Define Strategy Cooperation arises in this instance if you and Leo as players in a game can infer from past behaviour that both of you are likely to be trustworthy. Leo may forgo the short term gain of keeping to type for the long term benefit of your friendship. He rescues you from the cliff. You, however, will use the experience in order to determine whether or not to believe Leo in the future. Example B: Player’s belief system Your company’s strategy is s1: delayed launch of a new innovative product for 2 years. Rumors do appear of an impending launch date. You do not deny such rumors. In the interim, an article appears a reputable trade journal reporting that a not dissimilar product is about to be launched by your competitor in the next few weeks. Define Strategy Do you stop and think about s1? Do you reshape your strategy to s2: launch the product as soon as possible? Minimax criteria. If you look at examples in the book Decoding Strategy pp148-151 we discuss this for Samsung v Apple but it can be applied here also in any market-as-a-game Strategy Simply, identify the near rival [reacting first] and set up the game tree assuming that near-rival plays minimax, that is, confining you to the least of the greatest market shares in the game - so then you play maximin, to maximise the least loss. The competitive threat! • Traditional Analysis is biased towards answering this question for Company X: what market are we in and how can we do better? • Economics of strategy (GEMS) asks: what market should we be in? Management Models • Understand Penrose effect • Understand Bounded Rationality • Go to Table 1.2 pp21 McNutt DecodingStrategy Compare with Next Slide where you add in Williamson/TCE Behavioural Baumol Marris Williamson Objective Multiple goals TR:Sales Growth:gd Managerial Utility or Value Approach Satisficing – subject to Profit Constraint Maximisation– subject to Profit Constraint Maximisation - subject to Security Constraint Maximisation - subject to Profit Constraint Principal Agent Issue Yes Yes Yes Yes Short v Long Term Varies Short and also dynamic Long Short Reaction & Interaction Yes Partial Partial Partial Decision Making Coalitions Yes Management and zero-sum Relevance of shareholders Yes,..TCE Lets’ begin! Unit 1: Why the emphasis on behaviour (of players)? • • • • The Firm as a ‘nexus of contracts’ Vertical chains and agency costs Shareholders and management-as-agent Make-buy dilemma and incomplete contracting • Type of management and Bounded rationality • Co-ordination Coase asked in ‘ The Nature of Firms’ in 1937: Why are not all economic transactions coordinated by markets? • • • When transaction costs are too high, exchange to be coordinated by organisations Transaction costs: costs of negotiating, monitoring and enforcing contracts. Behavioural assumptions: bounded rationality & opportunism. The relative cost of organising transaction through different forms of governance determined by: • Extent to which complete contracts are possible. Where contract refers to agreement between two parties which could be explicit or not. • Extent to which there is a threat of opportunism by parties in the transaction. • Degree of asset specificity in the transaction. • Frequency with which the transaction is repeated. Storybook p.12 Companies as Players in a Market-as-a-game? • Principal-agent relationship • Shareholders as principals and management as agents • Who are decision makers? Management ≈ firms ≈ companies = PLAYERS (key decision makers) Costs of not being a Player • Agency costs can accrue..across the shareholders (esp institutional)..changing CEOs • 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! • Follower status ‘behind the curve’ • Technology lag and failure to differentiate ‘fast enough’ to sustain a competitive advantage Maximising Market Share: Table 1.1 p9 McNutt • Recognise zero sum constaint and entropy (redistribution within market shares) • Market Shares (before): 40+30+20+10 • Zero-sum (after): 30+40+20+10 • Entropy (after): 30+35+25+10 • Iff {∆qi/∆Q} > 0 market exhibits nonprice competition: • Check {∆qNOKIA/∆QSmartphones} < 0 Total Cost £ Total Revenue Min Profit Constraint Output Sales driven beyond the point of max profit but within the minimum profit constraint Profit/Loss Precis on a Marris model… • McNutt Ch 4: Understand balanced equation gc = gd to identify parameters of profitability • Supply of capital: debt v equity • Demand for capital: R&D exp v dividends • Instrumental variables influencing growth – visit Diageo case in Kaelo v2.0 • KFIs: profits/output and output/capital • Tobins q and Marris v ratio U1 U2 U3 U4 Valuation ratio V1 Shareholders perference x Best to management y V2 Valuation curve V(min) 0 G1 G2 Growth rate Marris equations/dividends paradox • Calculating share price by DCF formula • P = eps/r : Static firm no growth opportunities • P = eps/r + PV(GO): Dynamic firm with growth opportunities…this is a Marris firm • Common denominator is the plough-back ratio (PBR) = 1 – divs/eps…This is a Marris equation • More dividends can signal an absence of R&D growth • But more R&D from G1 to G2 can accrue an agency cost as Bayesian shareholders SELL as value falls V1 to V2. Bridge Unit 1 and Unit 2 • • • • Shareholder as principals expect max value Management to minimise the agency costs Positive Learning Transfer, PLT Nomenclature on type: Baumol type (signal = price), Marris type (signal = dividends). • Cost leadership type (link into Besanko Ch 11 & 13 on strategic cost advantage) Unit 2: Cost leadership [CL] as a type (of player) • Profitabiltiy v scale and (size and scope) • Production as a Cost-volume constraint • Understanding the economcis of productivity as exemplar for incentives • Normalisation equation • Sources of Cost Efficiency [next slide] • Cost leadership checklist..McNutt p78 Sources of cost efficiency • Measure of the level of resources needed to create given level of value Capacity utilisation How much to produce given capital size? Other Economies of scale X-inefficiencies, location, timing, external environment, organisation discretionary policies How big should the scale of the operation be? Transaction costs Production-cost relationship Economies of scope Which are the vertical boundaries of the firm? What product varieties to produce? Learning and experience factors How long to produce for? MES Point: Production - demand - production to attain cost leadership £ SAC1 SAC 2 Lower per unit cost for more units sold SAC 3 LAC Av.Cost = marginal cost 0,0 q1 qt Current plan of plant closures to lower cost base not completed q 2 Q Why? Capacity Constraints: • Case A: Unexhausted economies of scale due to product differentiation • Case B: Firm-as-a-player does not produce large enough output to reach MES • Case C: Firm-as-a-player restraints production (deliberate intent)..McNutt’s dilemma as production drives demand…(Veblen monopoly type) • Convergence of technology increases the firmspecific risk of Case C: • Strategic Choice A or B or C? Unit 3: Game type and signalling • Decisions 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 v Baumol model of TR max • Scale and size: cost leadership • Dividends as signals in a Marris model Oligopoly and Game Theory T3 + GEMS • • 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 • Equilibrium. Every player plays her best strategy given the strategies of the other players. Objective. To explore oligopolistic industries from a game embedded strategy (GEMS) perspective. The use of T3 framework, which considers 3 key dimensions (Type, Technology & Time), will allow oligopolists to better predict the likely strategic response of competitors when analysing competition from game embedded strategy perspective. • • Bridging Unit 1 and Unit 3: Game analysis • Binary reaction; Will Player B react? Yes or No? • If YES, decision may be parked • If NO, decision proceeds on error • Surprise • Non-binary reaction: Player B will react. Probability = x% • Decision taking on conjecture of likely reaction • No Surprise 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 • Accommodation v entry deterrence • Reaction, signalling and Nash equilibrium: ‘best you can do, given reaction of competitor’ Type of Players • Incumbent type v entrant type • Dominant type v predatory incumbent • De novo entrant type and geography of the market • Potential entrant type and the threat of entry as a credible threat • Contestable markets, newborn players and extant (incumbent) type • • • • • • Entry Deterrent Strategy & Barriers to entry Reputation of the incumbents Capacity building Entry function of the entrant De novo and entry at time period t Potential entrant - forces reaction at time period t from incumbent Coogan’s bluff strategy (classic poker strategy) and enter the game. • • • • Limit Pricing Model in Besanko pp207-211 and McNutt pp85-88 Outline the game dimension: dominant incumbents v camouflaged entrant type Define strategy set for incumbents Allow entry and define the equilibrium Preference - entry deterrent strategy v accommodation [next slide] 0,10 Do Not Enter 1 Agressive -7,2 Enter 2 Accommodating 5,8 Game Strategy • • • • • When in a game? – recognise interdependence? 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]. n Player B S4 Player A: S1 S2 S3 Column maximum Minimax strategy by B S5 S6 S7 95 60 30 5 70 35 50 55 30 40 90 10 95 70 55 90 Row Minimum Maximin strategy by A 5 55 10 Continuing with Unit 4: Define a price war • Determine the Bertrand reaction function: • Besanko Fig 5.3 pp190 and McNutt Fig 9.4 p143 • Compute a Critical Time Line (CTL)from observed signals..Examples of CTL in McNutt in the Appendix • Find a price point of intersection • Case Analysis of Sony v Microsoft at McNutt pp 141-144 and also in Kaelo v2.0 Nash Equilibria • Define the Nash equilibria [next slide] • Analyse the Payoff matrix (B,Y) > (A, X) • Commitment and chat: one-shot and repeated play • Punishment ‘grim’ strategy • Strategy Set in terms of credible mechanisms Player 2 Strategy A Strategy X Strategy Y 0,0 8,-5 -5,8 10,10 Player 1 Strategy B Prisoners’ Dilemma Player 2 Don’t Confess Confess Player 1 Confess 8 Don’t confess 20 8 0 0 20 3 3 •Would outcome change if the game is repeated? • Apply Prisoners’ Dilemma to Pricing Policy: Independent v Interdependent Firm 2 Firm 1 High Price Low Price High Price 8 8 0 20 Low Price 20 0 3 3 Visit Kaelo v2.0 and Games/Signalling • Examples: Critical Time Line the Appendix of McNutt’s text Decoding Strategy. • Play a PD game and investment game in Kaelo v2.0 • Selfish gene [one-shot], dominant strategy to cheat. • Altruism, fairness – repeated play/learning. • Understand the ‘no signalling’ payoff matrices [next slide] The ‘no signalling’ payoffs • Simultaneous game between A & B who must decide on how to spend the evening . B A • • • in out in 10,5 2,4 out 0,1 4,8 Problem of coordination where players have different preferences but common interest in coordinating strategies. One key application includes the battles for standards: • VHS by JVC vs Betamax by Sony in the 1980s • BlueRay DVD by Sony vs HD DVD by Toshiba in 2008 Effect of sequentialisation? Solution. Commitment? Signalling? Application of ‘no signalling’ game • Two pharmaceutical companies must simultaneously decide which products to research. A O A -2,-2 20,10 O 10,20 -1,-1 • Does this example illustrate the concept of ‘first mover advantage[FMA]? • How could companies signal? Signing contracts with leading universities, hiring expert. Games as Strategy: Strategic ToolBox • Segmentation strategy to obtain FMA • Relevance of chain-store paradox • Dark Strategy and 3 Mistakes in McNutt pp117-118 • Second Mover Advantage, SMA v FMA • Fig 9.7 pp161 McNutt Strategic ToolBox in terms of identifying the competitive threat v cartel coordination on (High. High)..Cheating Player 2 Low Prices Low Prices High Prices 2,2 13,0 0,13 10,10 Player 1 High Prices Absence of price wars? Link into the HBR articles • Hypothesis: Bertrand Price Wars occur due to a mis-match in price signals. • Mismatch can occur due to (i) declining volumes ∆qi/∆Q < 0; (ii) uncompetitive cost structure; (iii) decreasing productivity; (iv) management type (predator); (v) calling-my-bluff Final Scenarios for YOUR Company…… • The Rationale • The Strategy Markets evolve Non-binary • The Rationale • The Strategy Type, Technology and Game metrics, Time feedback & analytics • The Rationale Know your near-rival • The Strategy GEMS Thank you for participating……… Sapere aude ‘That which one can know, one should dare to know’