Presentation is loading. Please wait.

Presentation is loading. Please wait.

Managerial Economics Economics of Strategy and Games

Similar presentations

Presentation on theme: "Managerial Economics Economics of Strategy and Games"— Presentation transcript:

1 Managerial Economics Economics of Strategy and Games
Patrick McNutt Abridged ©

2 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

3 Game Embedded Strategy and Strategic Analysis
Knowledge of the identity of near rival: Actionyou -> Reactionrival -> NashReplyyou

4 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)

5 Workshop Lesson plan…. Plan is to follow Besanko’s Economics of Strategy 6th 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 pm Day 1 and Day 2 with group Presentation Day 3 at 2pm 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 McNutt’s Game Embedded Strategy Chapters 1 and 2

6 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 colour-coded Storybook

7 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?

8 Co-ordination Coase asked in ‘ The Nature of Firms’ in 1937:
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. Why are not all economic transactions coordinated by markets? When transaction costs are too high, exchange to be coordinated by organisations Storybook p.12 8

9 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)

10 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

11 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

12 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

13 Compare with Next Slide where you add in Williamson/TCE
Management Models Understand Penrose effect Understand Bounded Rationality Go to Table 1.2 pp14 McNutt Game Embedded Strategy Compare with Next Slide where you add in Williamson/TCE

14 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 Short v Long Term Varies Short and also dynamic Long Short Reaction & Interaction Partial Decision Making Coalitions Management and zero-sum Relevance of shareholders Yes,..TCE

15 Baumol strategy or Maximising Market Share: MMS
Recognise zero sum constaint and entropy (redistribution within market shares) Market Shares (before): Zero-sum (after): Entropy (after): Iff {∆qi/∆Q} > 0 market exhibits non-price competition: Check {∆qNOKIA/∆QSmartphones} < 0

16 Total Revenue Total Cost Profit/Loss Sales driven beyond the point of max profit but within the minimum profit constraint Min Profit Constraint Output

17 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


19 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.

20 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 p61

21 Sources of cost efficiency
Measure of the level of resources needed to create given level of value Production-cost relationship Capacity utilisation How much to produce given capital size? Economies of scale How big should the scale of the operation be? Other X-inefficiencies, location, timing, external environment, organisation discretionary policies Transaction costs 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? 21

22 MES Point: Production - demand - production
to attain cost leadership Lower per unit cost for more units sold SAC1 SAC2 SAC3 LAC Av.Cost = marginal cost Q 0,0 q2 q1 qt Current plan of plant closures to lower cost base not completed 22

23 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 firm-specific risk of Case C: Strategic Choice A or B or C?

24 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)

25 Unit 3: Game type and signalling
Decisions are interpreted as signals Observed patterns and Critical Time Line.see Nissan example pp20 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

26 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. 26

27 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 ‘best you can do, given reaction of competitor’

28 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 McNutt pp36 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.

29 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

30 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.

31 Limit Pricing Model in Besanko pp207-211 and McNutt pp71-76
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]


33 Continuing with Unit 4: Define a price war
Determine the Bertrand reaction function: Besanko Fig 5.3 pp190 Compute a Critical Time Line (CTL)from observed signals..Examples of CTL in McNutt pp 20 Figure 2.1 and pp94 Fig 7.4 Find a price point of intersection Case Analysis of Sony v Microsoft at McNutt pp and also in Kaelo v2.0

34 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 ToolBox in terms of credible mechanisms


36 Prisoners’ Dilemma Would outcome change if the game is repeated?
Player 2 Confess Don’t Confess Player 1 Don’t confess Would outcome change if the game is repeated? Apply Prisoners’ Dilemma to Pricing Policy: Independent v Interdependent Firm 2 High Price Low Price Firm 1 - 36

37 Visit Kaelo v2.0 and Games/Signalling
Example: Critical Time Line in Sony v Microsoft in Kaelo v2.0, Apple v Nokia game dimension McNutt pp92 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]

38 The ‘no signalling’ payoffs
Simultaneous game between A & B who must decide on how to spend the evening. 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? B in out A 10,5 2,4 0,1 4,8 38

39 Application of ‘no signalling’ game
Two pharmaceutical companies must simultaneously decide which products to research. Does this example illustrate the concept of ‘first mover advantage[FMA]? How could companies signal? Signing contracts with leading universities, hiring expert. A O -2,-2 20,10 10,20 -1,-1 39

40 Games as Strategy: Strategic ToolBox
Segmentation strategy to obtain FMA Relevance of chain-store paradox Dark Strategy and 3 Mistakes in McNutt pp95-97 Second Mover Advantage, SMA v FMA Strategic ToolBox in terms of identifying the competitive threat v cartel coordination on (High. High)..Cheating


42 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

43 Locate Your Company’S game dimension Scenario A? Scenario B? Scenario C?
GEMS & T3 Framework pp in McNutt

44 Final Scenarios for YOUR Company……
The Rationale Markets evolve Type, Technology and Time Know your near-rival The Strategy Non-binary Game metrics, feedback & analytics GEMS

45 Thank you for participating………
Sapere aude ‘That which one can know, one should dare to know’

Download ppt "Managerial Economics Economics of Strategy and Games"

Similar presentations

Ads by Google