Managerial Economics of Strategy and Games Economics of

Managerial Economics of Strategy and Games Economics of Strategy Patrick Mc. Nutt 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

Game Embedded Strategy and Strategic Analysis • Knowledge of the identity of near rival: Actionyou -> Reactionrival -> Nash. Replyyou

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 3 rd 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…. • • • Plan is to follow Besanko’s Economics of Strategy 6 th Edition Day 1 : Revision of Chapters 3 and 4 (Agency and Co-ordination) and Introduce Chapter 2 (Economies of Scale and Scope) Day 1 Workshop Study Groups & Case Analysis Break-out Sessions at 330 -530 pm Day 1 and Day 2 with group Presentation Day 3 at 2 pm start Day 2 & 3: Focus on Besanko Part II: Chapters 5, 6, 7 and 8 and link into Units 3 and 4 Day 1: Introduction and setting the scene using Mc. Nutt’s Game Embedded Strategy Chapters 1 and 2

Workshop Focus • Management type and relevance of TCE: Unit 1. Besanko Ch 3 & 4 and 5, Mc. Nutt Ch 1 • Cost leadership and economics of capacity: Unit 2. Besanko Ch 2 and Mc. Nutt Ch 5 • Market-as-a-game…market structure, oligopoly, and dynamic games…Units 3 and 4. Besanko Ch 5, 6, 7 and 8 and Mc. Nutt Ch 6, 7, 8 and 9 • Real Time case Analysis…go to Page 45 of colourcoded Storybook

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?

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

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

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

Management Models • Understand Penrose effect • Understand Bounded Rationality • Go to Table 1. 2 pp 14 Mc. Nutt Game Embedded Strategy 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 Security Constraint Maximisation - subject to Profit Constraint Principal Agent Issue Yes Yes Short v Long Term Varies Short and also dynamic Long Short Reaction & Interaction Yes Partial Decision Making Coalitions Yes Management and zero-sum Relevance of shareholders Yes, . . TCE

Baumol strategy or Maximising Market Share: MMS • 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 {∆q. NOKIA/∆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… • Mc. Nutt 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 v 2. 0 • KFIs: profits/output and output/capital • Tobins q and Marris v ratio

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 G 1 to G 2 can accrue an agency cost as Bayesian shareholders SELL as value falls V 1 to V 2.

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. . Mc. Nutt p 61

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 Which are the vertical boundaries of the firm? Economies of scope What product varieties to produce? Learning and experience factors How long to produce for?

MES Point: Production - demand - production to attain cost leadership £ SAC 1 SAC 2 Lower per unit cost for more units sold SAC 3 LAC Av. Cost = marginal cost 0, 0 q 1 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). . Mc. Nutt’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?

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 3: Game type and signalling • Decisions are interpreted as signals • Observed patterns and Critical Time Line. see Nissan example pp 20 in Mc. Nutt • 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 T 3 + 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 T 3 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. • •

Describe (prices as signals) game dimension • Players and type of players • Prices interpreted as signals • Understand (price) elasticity of demand cross -price elasticity • Patterns of observed behaviour • Leader-follower as knowledge • Accommodation v entry deterrence • Reaction, signalling and ‘best you can do, given reaction of competitor’

Link Units 3 and 4: Game Dimension • • • What is a game – loss of independence? Nash premise: Action, Reaction and Reply Non-cooperative sequential (dynamic) games Introduce oligopoly and players (companies) n < 5 TR Test and Elasticity Mc. Nutt pp 36 Single shot price reduction: (i) fail TR test and revenues fall; (ii) near rival misreads the price as a signal. • Limit price [to avoid entry] and predatory pricing to force exit.

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 • Coogans bluff strategy (classic poker strategy) and enter the game.

Limit Pricing Model in Besanko pp 207 -211 and Mc. Nutt pp 71 -76 • 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]

Continuing with Unit 4: Define a price war • Determine the Bertrand reaction function: • Besanko Fig 5. 3 pp 190 • Compute a Critical Time Line (CTL)from observed signals. . Examples of CTL in Mc. Nutt pp 20 Figure 2. 1 and pp 94 Fig 7. 4 • Find a price point of intersection • Case Analysis of Sony v Microsoft at Mc. Nutt pp 114 -116 and also in Kaelo v 2. 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 • Strategic Tool. Box in terms of credible mechanisms

Prisoners’ Dilemma Player 2 Confess Player 1 Confess 8 Don’t confess 20 Don’t Confess 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 v 2. 0 and Games/Signalling • Example: Critical Time Line in Sony v Microsoft in Kaelo v 2. 0, Apple v Nokia game dimension Mc. Nutt pp 92 • Play a PD game and investment game in Kaelo v 2. 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 1980 s • Blue. Ray 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 Tool. Box • Segmentation strategy to obtain FMA • Relevance of chain-store paradox • Dark Strategy and 3 Mistakes in Mc. Nutt pp 95 -97 • Second Mover Advantage, SMA v FMA • Strategic Tool. Box in terms of identifying the competitive threat v cartel coordination on (High). . Cheating

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

Locate Your Company’S game dimension Scenario A? Scenario B? Scenario C? GEMS & T 3 Framework pp 130 -132 in Mc. Nutt

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’