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’