harvard professor michael e. porter argued that, “theories or models that require restrictive...
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Harvard Professor Michael E. Porter argued that, “Theories or models that
require restrictive assumptions are untenable…Standard economic models of firms and product markets have captured little of the complexity and dynamism of
actual competition.” Hence, the AHP/ANP model framework is a way
around the “standard” approach.
Examples of
Modeling with AHP
AHP Model 1: Predicting the Future of the U.S. Automotive Industry
Goal: To Predict the Future of the Automotive Industry
Actors (Criteria 1): Each factor has there own objectives, which forms a second level criteria.
- Management- Government- Unions- Foreign Competition- Consumers
AHP Model 1: Predicting the Future of the U.S. Automotive Industry
Objectives (Criteria 2):
• For Management: (a)_Maintain/Increase Profits, (b)_Industry Expansion in the U.S., (c)_Diversification of Risk, and (d)_Continuation of Automotive Firms.
• For Government: (a)_Economic Prosperity, (b)_Maintain/Increase the Level of Industry Employment, (c) Technology Development, and (d)_Provide/Improve Methods of Transportation.
• For Unions: (a)_Desire to Maximize Employment, (b)_Continuation of Auto Firms, and (c)_Improve Employee Benefits.
AHP Model 1: Predicting the Future of the U.S. Automotive Industry
Objectives (Criteria 2):
• For Foreign Competitors : (a)_Penetrate the U.S. Market/Increase Market Share, (b)_Increase their Profit, and (c)_Continuation of the Health of Their Firm.
• For Consumer: (a)_Cost, (b)_Value, and (c)_Status.
AHP Model 1: Predicting the Future of the U.S. Automotive Industry
Alternatives (Likely Scenarios):
• Weaker - with increasing loss of market share to imports,
• Status Quo - with steady loss of market share to imports,
• Stronger - with better products to stem the tide of imports and challenge imports in their home markets.
AHP Model 1: Predicting the Future of the U.S. Automotive Industry
W eaker
S ta tus Q uo
S tronger
Inc rease /M a inta inP ro f its
W eaker
S ta tus Q uo
S tronger
Indus tryE xpans ion
W eaker
S ta tus Q uo
S tronger
D ive rs if ica t iono f R isk
W eaker
S ta tus Q uo
S tronger
C ont inua t ion o fC om pany
M anagem ent
W eaker
S ta tus Q uo
S tronger
P rospe rty
W eaker
S ta tus Q uo
S tronger
E m p loym ent
W eaker
S ta tus Q uo
S tronger
T echno logy
W eaker
S ta tus Q uo
S tronger
T ransporta t ionIm provem ent
G ove rnm ent
W eaker
S ta tus Q uo
S tronger
E m p loym ent
W eaker
S ta tus Q uo
S tronger
C ont inua t ion o fC om pany
W eaker
S ta tus Q uo
S tronger
B ene f its
Union
W eaker
S ta tus Q uo
S tronger
M arke t S hare
W eaker
S ta tus Q uo
S tronger
P ro f its
W eaker
S ta tus Q uo
S tronger
C ont inua t ion o fC om pany
F ore ign C om pe t ito rs
W eaker
S ta tus Q uo
S tronger
C os t
W eaker
S ta tus Q uo
S tronger
V a lue
W eaker
S ta tus Q uo
S tronger
S ta tus
C onsum ers
A u to Industry F u tu re
Source: The Hierarchon; A Dictionary of Hierarchies, Saaty and Forman, 1996 (Revised Edition)
While this is a framework for understanding and forecasting
the industry, it takes an organizational perspective more than an economics
perspective.
Can We do Better From an Economics Perspective?
Let’s Set Our Forecast Objective and Alternatives.
And Then Let’s Assemble the Key Economic Factors About the Industry that We Want to
Model.
Let’s be more specific and clearer.
Questions to Think About:
(1) What do we mean by a domestic automotive industry?
(2) What do we mean by domestic sales?
(3) What is the forecast horizon?
Was that Previous Model Well Specified?
How might we reformuate that forecast objective? The modeling goals could be:
(1) Industry Profits (by whom or from where? -- home or abroad?),
(2) Domestic Demand,
(3) Market Share (of whom? -- Companies that Domestically Produce or Share of Output that is Domestically Owed)
What are Possible Objectives from Economic Theory?
How Do We Measure and Model Competition?
Competitiveness of an industry must be evaluated in terms of the same industry in other regions, “clusters,” or countries (cross-sectional analysis). The competitiveness of an industry may be
inferred from the competitiveness of the main firms in the industry.
• Australian Government’s Bureau of Industrial Economics (1993) defined competitiveness based on three quantitative indicators: (1)
growth rate of sales, (2) the profit/sales ratio, and (3) the profit growth/turnover ratio and six qualitative indicators: (1) product quality
and performance, (2) customer satisfaction, (3) product range, (4) profits, (5) costs, and (6) production flexibility.
• Markusen (1992) defined industry international competitiveness as: “(1) An industry is competitive if it has a level of total factor
productivity equal to or higher than that of its foreign competitors. (2) An industry is competitive if it has a level of unit (average) costs equal
to or lower than its foreign competitors.
AHP Model 2: An AHP Model of Automotive Demand and Supply to Forecast Price Changes Over a One-Year Horizon
3-5% H ike
2 -3% H ike
1 -2% H ike
0 -1% H ike
0 -1% Ro llback
S trong
3 -5% H ike
2 -3% H ike
1 -2% H ike
0 -1% H ike
0 -1% Ro llback
"C oopera t ive"
3 -5% H ike
2 -3% H ike
1 -2% H ike
0 -1% H ike
0 -1% Ro llback
W eak
C om pe tit iveP ressu res
(F rom Incen t ives , Do l la r , etc .)
3 -5% H ike
2 -3% H ike
1 -2% H ike
0 -1% H ike
0 -1% Ro llback
N e wD em and
3-5% H ike
2 -3% H ike
1 -2% H ike
0 -1% H ike
0 -1% Ro llback
R ep lacem entD em and
D om esticM arket
3 -5% H ike
2 -3% H ike
1 -2% H ike
0 -1% H ike
0 -1% Ro llback
E xports
D em andC ond it ions
3 -5% H ike
2 -3% H ike
1 -2% H ike
0 -1% H ike
0 -1% Ro llback
O n P lan
3 -5% H ike
2 -3% H ike
1 -2% H ike
0 -1% H ike
0 -1% Ro llback
S hortages
P roduc t ion
3 -5% H ike
2 -3% H ike
1 -2% H ike
0 -1% H ike
0 -1% Ro llback
Too M uch
3-5% H ike
2 -3% H ike
1 -2% H ike
0 -1% H ike
0 -1% Ro llback
O n P lan
3 -5% H ike
2 -3% H ike
1 -2% H ike
0 -1% H ike
0 -1% Ro llback
Too L it t le
C hange inInvento r ies
3 -5% H ike
2 -3% H ike
1 -2% H ike
0 -1% H ike
0 -1% Ro llback
Fore ign G row thS trong
3 -5% H ike
2 -3% H ike
1 -2% H ike
0 -1% H ike
0 -1% Ro llback
Fore ign G rw othM odera te
3 -5% H ike
2 -3% H ike
1 -2% H ike
0 -1% H ike
0 -1% Ro llback
Fore ign G row thW eak
Im ports
S upp lyC ond it ions
S trong E conom yP a th
3 -5% H ike
2 -3% H ike
1 -2% H ike
0 -1% H ike
0 -1% Ro llback
S trong
3 -5% H ike
2 -3% H ike
1 -2% H ike
0 -1% H ike
0 -1% Ro llback
"C oopera t ive"
3 -5% H ike
2 -3% H ike
1 -2% H ike
0 -1% H ike
0 -1% Ro llback
W eak
C om pe tit iveP ressu res
(F rom Incen t ives , Do l la r , etc .)
3 -5% H ike
2 -3% H ike
1 -2% H ike
0 -1% H ike
0 -1% Ro llback
N e wD em and
3-5% H ike
2 -3% H ike
1 -2% H ike
0 -1% H ike
0 -1% Ro llback
R ep lacem entD em and
D om esticM arket
3 -5% H ike
2 -3% H ike
1 -2% H ike
0 -1% H ike
0 -1% Ro llback
E xports
D em andC ond it ions
3 -5% H ike
2 -3% H ike
1 -2% H ike
0 -1% H ike
0 -1% Ro llback
O n P lan
3 -5% H ike
2 -3% H ike
1 -2% H ike
0 -1% H ike
0 -1% Ro llback
S hortages
P roduc t ion
3 -5% H ike
2 -3% H ike
1 -2% H ike
0 -1% H ike
0 -1% Ro llback
Too M uch
3-5% H ike
2 -3% H ike
1 -2% H ike
0 -1% H ike
0 -1% Ro llback
O n P lan
3 -5% H ike
2 -3% H ike
1 -2% H ike
0 -1% H ike
0 -1% Ro llback
Too L it t le
C hange inInvento r ies
3 -5% H ike
2 -3% H ike
1 -2% H ike
0 -1% H ike
0 -1% Ro llback
Fore ign G row thS trong
3 -5% H ike
2 -3% H ike
1 -2% H ike
0 -1% H ike
0 -1% Ro llback
Fore ign G rw othM odera te
3 -5% H ike
2 -3% H ike
1 -2% H ike
0 -1% H ike
0 -1% Ro llback
Fore ign G row thW eak
Im ports
S upp lyC ond it ions
S low G row tho r R ecess ion
A v e ra g e P ric e o f a V e h ic le(G o a l: To D e te rm in e th e M ag n itu de o f th e A n n ou n ce d P ric e C h a n g e )
AHP Model 2: Level 1 & 2 CriteriaObjective: Forecast Price Change over One-Year
C om petit iveP ressures
(F rom Incen tives , Do lla r , etc .)
D em andC ond it ions
S upp lyC ond it ions
S trong E conom yP ath
C om pe tit iveP ressures
(F rom Incen tives , Do lla r , etc .)
D em andC ond it ions
S upp lyC ond it ions
S low G row thor R ecess ion
A ve ra g e P rice o f a V e h ic le(G o a l: To D e te rm in e th e M ag n itu de o f th e A n n ou n ce d P rice C h a n g e)
Level 1 Question: What is the Likelihood of Slow Growth/Recession in One Year?
Level 2 Question: How Strong on the Market Conditions?
Economy-wide Criteria ------>
Form the Matrix of Pairwise Comparison for the Level 1 Criteria
Strong Economy Weak/Recession
Strong Economy 1 1/N
Weak/Recession N 1
Using the 1-9 Saaty Scale, What is the Consensus in the Class on the Likelihood that Weak Growth/Recession is More Likely than Strong Growth?
Determine Weights…
How Do You Determine the Respective Weights?
Use a consensus forecast for the chance of a recession/slowdown,
Use your own judgment/forecast,
Base the determination on leading indicators,
Or, as we will do here take a survey of class opinion.
Determining if your pairwise comparisons are consistent
Calculate the Consistency Index and CI/RI measure.
Evaluate the CI/RI ratio as follows if >0.10 (or maybe 0.20) then rethink you
assigned comparisons.
Saaty’s Calculated Random Index Measures for Various
Sizes of “N”
Average Random Consistency Index (R.I.)n 1 2 3 4 5 6 7 8 9 10
R.I. 0 0 .52 .89 1.11 1.25 1.35 1.40 1.45 1.49
--------------------------------------------------
AHP Model 2: Level 1 CriteriaObjective: Forecast Price Change over One-Year
3-5% H ike
2 -3% H ike
1 -2% H ike
0 -1% H ike
0 -1% Ro llback
S trong
3 -5% H ike
2 -3% H ike
1 -2% H ike
0 -1% H ike
0 -1% Ro llback
"C oopera t ive"
3 -5% H ike
2 -3% H ike
1 -2% H ike
0 -1% H ike
0 -1% Ro llback
W eak
C om pe tit iveP ressu res
(F rom Incen t ives , Do l la r , etc .)
3 -5% H ike
2 -3% H ike
1 -2% H ike
0 -1% H ike
0 -1% Ro llback
N e wD em and
3-5% H ike
2 -3% H ike
1 -2% H ike
0 -1% H ike
0 -1% Ro llback
R ep lacem entD em and
D om esticM arket
3 -5% H ike
2 -3% H ike
1 -2% H ike
0 -1% H ike
0 -1% Ro llback
E xports
D em andC ond it ions
3 -5% H ike
2 -3% H ike
1 -2% H ike
0 -1% H ike
0 -1% Ro llback
O n P lan
3 -5% H ike
2 -3% H ike
1 -2% H ike
0 -1% H ike
0 -1% Ro llback
S hortages
P roduc t ion
3 -5% H ike
2 -3% H ike
1 -2% H ike
0 -1% H ike
0 -1% Ro llback
Too M uch
3-5% H ike
2 -3% H ike
1 -2% H ike
0 -1% H ike
0 -1% Ro llback
O n P lan
3 -5% H ike
2 -3% H ike
1 -2% H ike
0 -1% H ike
0 -1% Ro llback
Too L it t le
C hange inInvento r ies
3 -5% H ike
2 -3% H ike
1 -2% H ike
0 -1% H ike
0 -1% Ro llback
Fore ign G row thS trong
3 -5% H ike
2 -3% H ike
1 -2% H ike
0 -1% H ike
0 -1% Ro llback
Fore ign G rw othM odera te
3 -5% H ike
2 -3% H ike
1 -2% H ike
0 -1% H ike
0 -1% Ro llback
Fore ign G row thW eak
Im ports
S upp lyC ond it ions
S trong E conom yP a th
3 -5% H ike
2 -3% H ike
1 -2% H ike
0 -1% H ike
0 -1% Ro llback
S trong
3 -5% H ike
2 -3% H ike
1 -2% H ike
0 -1% H ike
0 -1% Ro llback
"C oopera t ive"
3 -5% H ike
2 -3% H ike
1 -2% H ike
0 -1% H ike
0 -1% Ro llback
W eak
C om pe tit iveP ressu res
(F rom Incen t ives , Do l la r , etc .)
3 -5% H ike
2 -3% H ike
1 -2% H ike
0 -1% H ike
0 -1% Ro llback
N e wD em and
3-5% H ike
2 -3% H ike
1 -2% H ike
0 -1% H ike
0 -1% Ro llback
R ep lacem entD em and
D om esticM arket
3 -5% H ike
2 -3% H ike
1 -2% H ike
0 -1% H ike
0 -1% Ro llback
E xports
D em andC ond it ions
3 -5% H ike
2 -3% H ike
1 -2% H ike
0 -1% H ike
0 -1% Ro llback
O n P lan
3 -5% H ike
2 -3% H ike
1 -2% H ike
0 -1% H ike
0 -1% Ro llback
S hortages
P roduc t ion
3 -5% H ike
2 -3% H ike
1 -2% H ike
0 -1% H ike
0 -1% Ro llback
Too M uch
3-5% H ike
2 -3% H ike
1 -2% H ike
0 -1% H ike
0 -1% Ro llback
O n P lan
3 -5% H ike
2 -3% H ike
1 -2% H ike
0 -1% H ike
0 -1% Ro llback
Too L it t le
C hange inInvento r ies
3 -5% H ike
2 -3% H ike
1 -2% H ike
0 -1% H ike
0 -1% Ro llback
Fore ign G row thS trong
3 -5% H ike
2 -3% H ike
1 -2% H ike
0 -1% H ike
0 -1% Ro llback
Fore ign G rw othM odera te
3 -5% H ike
2 -3% H ike
1 -2% H ike
0 -1% H ike
0 -1% Ro llback
Fore ign G row thW eak
Im ports
S upp lyC ond it ions
S low G row tho r R ecess ion
A v e ra g e P ric e o f a V e h ic le(G o a l: To D e te rm in e th e M ag n itu de o f th e A n n ou n ce d P ric e C h a n g e )
But even this framework does not capture all of the industry dynamic. How about role of leasing? Should that be explicit? How about the CAFÉ regulations that governed fuel efficiency? Should that be incorporated? What else might be need?
Recap: Why AHP/ANP?
• AHP is a framework to assemble statistical and judgmental information.
• The framework models the process in a more flexible mode.
• It greatest benefit is that it gets you thinking about the industry structure!
• But, it has drawbacks.
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