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![Page 1: G](https://reader036.fdocuments.us/reader036/viewer/2022062704/5562b222d8b42a15548b545e/html5/thumbnails/1.jpg)
“Blessed are the flexible, for they will never be bent out of shape”
![Page 2: G](https://reader036.fdocuments.us/reader036/viewer/2022062704/5562b222d8b42a15548b545e/html5/thumbnails/2.jpg)
Managing Operational Flexibility Under Demand Uncertainty
Dissertation Defense:
Manu Goyal
![Page 3: G](https://reader036.fdocuments.us/reader036/viewer/2022062704/5562b222d8b42a15548b545e/html5/thumbnails/3.jpg)
Chapter 2: Strategic Technology Choice and Capacity Investment under Demand Uncertainty.
Analytically studies the impact of competition on the adoption of product flexibility in an environment characterized by uncertain demand.
Chapter 3: Deployment of Manufacturing Flexibility: an Empirical Analysis of the Automotive Industry.
Empirically tests the findings of the second chapter. Evidence suggests that product and volume flexibility may be linked.
Chapter 4: Capacity Investment and the Interplay between Volume Flexibility and Product Flexibility.
Analytically explores the intertwined nature of volume flexibility and product flexibility.
![Page 4: G](https://reader036.fdocuments.us/reader036/viewer/2022062704/5562b222d8b42a15548b545e/html5/thumbnails/4.jpg)
Chapter 2
Strategic Technology Choice and Capacity Investment under Demand Uncertainty.
![Page 5: G](https://reader036.fdocuments.us/reader036/viewer/2022062704/5562b222d8b42a15548b545e/html5/thumbnails/5.jpg)
PT Cruiser
Chrysler
Town & Country
Honda
Odyssey CR-V
Ford
Ford Freestar Ford Escape
![Page 6: G](https://reader036.fdocuments.us/reader036/viewer/2022062704/5562b222d8b42a15548b545e/html5/thumbnails/6.jpg)
Research Questions …• Does the technology investment decision (flexible vs
dedicated) depend on what competition is doing?• Is the impact of problem parameters different with and
without competition?• Will every firm adopt flexible technology in the
equilibrium?
..and answers• It does• It is• No
![Page 7: G](https://reader036.fdocuments.us/reader036/viewer/2022062704/5562b222d8b42a15548b545e/html5/thumbnails/7.jpg)
The Model
One flexible
or
two dedicatedplants
One flexible
or
two dedicated plants
i j
2y
1y
Two markets
Uncertain Demand Curve
Uncertain Demand Curve
2 2 2
2 2 2 1
,
.
i jQ q q
P A Q Q
1 1 1
1 1 1 2
,
.
i jQ q q
P A Q Q
![Page 8: G](https://reader036.fdocuments.us/reader036/viewer/2022062704/5562b222d8b42a15548b545e/html5/thumbnails/8.jpg)
Decision timeline for each of two firmscompeting in two markets
time
Decide choice of technology, Dedicated (D) or Flexible (F)
fic
ic
Choose capacity
: Cost of flexible capacity per unit
: Cost of dedicated capacity per unit
Decide production qty
for both markets
q1i, q2i
Technology Game
Production Game
Capacity Game
Prices determined as per Cournot competition. Profits gleaned
Demand Curve realized
Flexible Firm: one decision
Ded. Firm: two decisions
![Page 9: G](https://reader036.fdocuments.us/reader036/viewer/2022062704/5562b222d8b42a15548b545e/html5/thumbnails/9.jpg)
The Technology Game
D
F
F
D
Firm i
Firm j
dj
di ,
fj
fi ,
mjf
mid ,
mjd
mif ,
![Page 10: G](https://reader036.fdocuments.us/reader036/viewer/2022062704/5562b222d8b42a15548b545e/html5/thumbnails/10.jpg)
The Technology Game Profits
2
1
2
)1(3
2
y
jiyd cc
)1(16
)(
)1(18
)42( 221
221
ifjm
d
cc
)1(18
2
)1(9
)2(12
22
21
2
1
2
y
fifjyf cc
)1(8
2
)1(32
)(
)1(18
)42(12
22
21
221
221
fijmf
cc
Firm profit in (D,D) market
Firm profit in (F,F) market
Dedicated Firm profit in (D,F) market
Flexible Firm profit in (F,D) market
![Page 11: G](https://reader036.fdocuments.us/reader036/viewer/2022062704/5562b222d8b42a15548b545e/html5/thumbnails/11.jpg)
The Stochastic Effect Profits (symmetric costs and distribution)
D F
D
F
9
2 ,
9
2 22 cc
9
2
9 ,
9
2
9
2222ff cc
9
22 ,
9
22
4
222 cccc ff
2 222 2 2 2
, 9 4 9f fc c c c
9
2
9
22fc
Stochastic Deterministic
![Page 12: G](https://reader036.fdocuments.us/reader036/viewer/2022062704/5562b222d8b42a15548b545e/html5/thumbnails/12.jpg)
Infeasible Region
2
fc
c
critfc
The Best Response Functions - When
Competitor invests in dedicated technology
,,cc f
Dedicated
Flexible
,,cc fM
Monopolist
Flexible
Dedicated
![Page 13: G](https://reader036.fdocuments.us/reader036/viewer/2022062704/5562b222d8b42a15548b545e/html5/thumbnails/13.jpg)
Infeasible Region
2
fc
c
critfc
Dedicated
Flexible
,,cc f ,,cc fM
Monopolist
The Best Response Functions - When
Competitor invests in flexible technology
Flexible
Dedicated
![Page 14: G](https://reader036.fdocuments.us/reader036/viewer/2022062704/5562b222d8b42a15548b545e/html5/thumbnails/14.jpg)
The Nash Equilibrium
![Page 15: G](https://reader036.fdocuments.us/reader036/viewer/2022062704/5562b222d8b42a15548b545e/html5/thumbnails/15.jpg)
(D,D)
2
fc
c
Infeasible Region
(F,F)
critfc
,,cc fM
,,cc f
,,cc f
(D,F) and (F,D)
Pure Flexible Market
Mixed Market
The Nash Equilibrium
![Page 16: G](https://reader036.fdocuments.us/reader036/viewer/2022062704/5562b222d8b42a15548b545e/html5/thumbnails/16.jpg)
Other Effects
• Market size effect– Pulls threshold curves down.– Additional (F,F) and (D,D) equilibrium is
simultaneously possible.
• Product Substitutability Effect.– Amplifies both the stochastic and market size
effects
• The Cost Effect.– Induced by asymmetries in the costs of firms.
![Page 17: G](https://reader036.fdocuments.us/reader036/viewer/2022062704/5562b222d8b42a15548b545e/html5/thumbnails/17.jpg)
(D,D)
(F,F)
(D,F) and (F,D)
(D,D) and (F,F)21
fic ficfMc
2T
c
fc
Equilibrium with market size effect
![Page 18: G](https://reader036.fdocuments.us/reader036/viewer/2022062704/5562b222d8b42a15548b545e/html5/thumbnails/18.jpg)
Other Effects
• Market size effect– Pulls threshold curves down.– Additional (F,F) and (D,D) equilibrium is
simultaneously possible.
• Product Substitutability Effect.– Amplifies both the stochastic and market size
effects
• The Cost Effect.– Induced by asymmetries in the costs of firms.
![Page 19: G](https://reader036.fdocuments.us/reader036/viewer/2022062704/5562b222d8b42a15548b545e/html5/thumbnails/19.jpg)
ic
jc
(D,D)
(F,F)
(D,F) and (F,D)(F,D
)
(F,D)
(F,D)
fic
fic
fjc
fjc
cost
2T
I
V
IV
III
VIVII
The cost effect
![Page 20: G](https://reader036.fdocuments.us/reader036/viewer/2022062704/5562b222d8b42a15548b545e/html5/thumbnails/20.jpg)
fjfi cc
fic
fjc
2T
c
cost
fic
fjc
![Page 21: G](https://reader036.fdocuments.us/reader036/viewer/2022062704/5562b222d8b42a15548b545e/html5/thumbnails/21.jpg)
Summary and Conclusions• The paper covers three levels of firm decisions: strategic
(technology investment), tactical (capacity investment) and operational (production decisions).
• Distilled the impact of competition on the technology choice of firms– Flexibility is more valuable if competitor uses dedicated
technology, less valuable if competitor uses flexible technology– Technology choice decision cannot be made in isolation.– Flexible and dedicated technologies can co-exist in equilibrium.
• The differential Impact (under competition) of:– Product substitution– Market Size– Costs
![Page 22: G](https://reader036.fdocuments.us/reader036/viewer/2022062704/5562b222d8b42a15548b545e/html5/thumbnails/22.jpg)
Chapter 3
Deployment of Manufacturing Flexibility: an Empirical Analysis of the Automotive Industry.
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The Hypotheses
• H1: The use of flexibility is associated with higher uncertainty in demand for individual products.
• H2: The use of flexibility is associated with lower demand correlation for individual products.
• H3a: The use of flexibility is associated with a larger number of flexible competitors.
• H3b: Under moderate demand uncertainty, the use of flexibility is associated with fewer flexible competitors.
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Hypotheses (cont)..
• H4: The use of flexibility is associated with lower mean demand for products.
• H5: Flexibility is associated with lower difference in mean demand (demand differential) for products.
• H6a: Under high demand uncertainty, the use of flexibility is associated with higher product substitutability in the marketplace
• H6b: Under a low demand differential, the use of flexibility is associated with lower product substitutability in the market place.
![Page 25: G](https://reader036.fdocuments.us/reader036/viewer/2022062704/5562b222d8b42a15548b545e/html5/thumbnails/25.jpg)
The Data
• Primary Sources– Harbour Reports– Ward’s Automotive.
• The “Big Three” US Manufacturers.• Years 1996-2003.• Over 70 manufacturing facilities in North
America.• Unit of analysis is a given plant in a given year
(plant-year combinations, 483 in numbers).
![Page 26: G](https://reader036.fdocuments.us/reader036/viewer/2022062704/5562b222d8b42a15548b545e/html5/thumbnails/26.jpg)
Measures
• Flexibility: “Demonstrated” vs. “Potential”
Assembly Line Flexibility (ALF): 1 if the number of platforms manufactured in a plant is greater than the number of assembly lines, and 0 otherwise.
• Other Ways?
![Page 27: G](https://reader036.fdocuments.us/reader036/viewer/2022062704/5562b222d8b42a15548b545e/html5/thumbnails/27.jpg)
0%
5%
10%
15%
20%
25%
30%
35%
40%
45%
1995 1996 1997 1998 1999 2000 2001 2002 2003 2004
Years
% F
lexi
ble
Cap
acit
y GM
FORD
DCX
Observed Flexibility Over Time
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Measures (cont)..
• Demand Uncertainty: Coefficient of Variation of de-seasoned monthly sales.
• Correlation.• Mean demand.• Demand Differential.
• Competition: number of flexible competitors.
• Substitutability. Price difference.
![Page 29: G](https://reader036.fdocuments.us/reader036/viewer/2022062704/5562b222d8b42a15548b545e/html5/thumbnails/29.jpg)
Control Variables
• Plant Capacity
• Plant Utilization.
• Manufacturer dummies.
![Page 30: G](https://reader036.fdocuments.us/reader036/viewer/2022062704/5562b222d8b42a15548b545e/html5/thumbnails/30.jpg)
The Analysis:Descriptive Statistics
Minimum Maximum Mean Std. Dev.
Mean Demand 471 79836 17045 16133
Demand Uncertainty
0.03 1.56 0.45 0.28
Correlation -1.00 1.00 0.3632 .4630
Competition 0.00 7.00 1.35 1.27
Demand Differential
46 511365 31018 62764
Substitution 8 26352 2677 3619
Capacity 33088 327120 208602 61527
Utilization 0.15 1.67 0.91 0.28
![Page 31: G](https://reader036.fdocuments.us/reader036/viewer/2022062704/5562b222d8b42a15548b545e/html5/thumbnails/31.jpg)
Competition Utilization Correlation SubstitutionDemand
Uncertainty
Demand Differ.
Mean Demand
Utilization 0.02
Correlation -0.02 0.08
Substitution -0.17** 0.02 -0.11*
Demand Uncertai
nty0.006 0.33** 0.05 -0.06
Demand Different
ial0.22** 0.13** -0.08 -0.12** 0.29**
Mean Demand -0.07 0.24** 0.10* 0.03 0.56** 0.16**
Capacity 0.24** 0.21** 0.13** -0.19** 0.10* -0.01 -0.14**
Correlations
![Page 32: G](https://reader036.fdocuments.us/reader036/viewer/2022062704/5562b222d8b42a15548b545e/html5/thumbnails/32.jpg)
Univariate Test
Univariate Test of Differences in Means (dependent variable: ALF)
Mean: ALF = 0Mean: ALF
= 1P-value for test of mean difference
Competition 1.25 1.90 0.00
Correlation 0.38 0.24 0.01
Demand Uncertainty
0.44 0.48 0.37
Demand Differential
31150.90 30236.34 0.91
Mean Demand 17538.14 14138.23 0.10
![Page 33: G](https://reader036.fdocuments.us/reader036/viewer/2022062704/5562b222d8b42a15548b545e/html5/thumbnails/33.jpg)
Logit Regression (N=483)Column 1 Column 2 Column 3
Intercept -1.899*** (0.645) -2.00*** (0.704) -2.078*** (0.766)
Competition 0.3243*** (0.098) 0.276** (0.123)
Demand Correlation -0.600** (0.275) -0.598** (0.284)
Demand Uncertainty 1.367** (0.596) 1.612** (0.694)
Demand Differential -0.00 (0.00) -0.00 (0.00)
Mean Demand -0.00 (0.00) -0.00 (0.00)
Substitution -0.00 (0.00)
Substitution × Coefficient of Variation.
0.00 (0.00)
Substitution × Difference of Means.
-0.00 (0.00)
Utilization -0.900** (0.481) -0.907* (0.543) -0.962* (0.550)
Capacity 0.00 (0.00) 0.00 (0.00) 0.00 (0.00)
GM 0.189 (0.356) 0.137 (0.389) 0.162 (0.405)
Ford 0.152 (0.283) 0.331 (0.40) 0.399 (0.416)
Significance 0.22 0.007 0.0047
![Page 34: G](https://reader036.fdocuments.us/reader036/viewer/2022062704/5562b222d8b42a15548b545e/html5/thumbnails/34.jpg)
Logit Regression
• Evidence suggests that plants that are observed to be flexible have:– Higher demand uncertainty (H1).– Lower correlation (H2).– Higher (flexible) competition (H3a).
• Control Variables:– Flexible plants have lower utilization.– No significant differences between the “big three”.
![Page 35: G](https://reader036.fdocuments.us/reader036/viewer/2022062704/5562b222d8b42a15548b545e/html5/thumbnails/35.jpg)
Productivity Analysis
• Study the implications of deploying flexibility, measured against extant theories.
• Hours per Vehicle (HPV) as a measure of productivity.
![Page 36: G](https://reader036.fdocuments.us/reader036/viewer/2022062704/5562b222d8b42a15548b545e/html5/thumbnails/36.jpg)
YEAR 2003 2002 2001 2000 1999 1998 1997
50
40
30
20
DCX
GM
Ford
Mean HPV
HPV over the years
![Page 37: G](https://reader036.fdocuments.us/reader036/viewer/2022062704/5562b222d8b42a15548b545e/html5/thumbnails/37.jpg)
Mismatches..
• Measure mismatch benchmarked against six environmental variables: – Demand Uncertainty (H1)– Demand Correlation (H2)– Flexible Competition (H3a)– Competition with moderate uncertainty (H3b).– Mean Demand (H4).– Demand differential (H5).
![Page 38: G](https://reader036.fdocuments.us/reader036/viewer/2022062704/5562b222d8b42a15548b545e/html5/thumbnails/38.jpg)
Regression
• Regress HPV against these six mismatches (OLS).
• Control Variables:– Flexibility– Utilization– Plant Capacity– Companies– Years– Number of Chassis Configurations.
![Page 39: G](https://reader036.fdocuments.us/reader036/viewer/2022062704/5562b222d8b42a15548b545e/html5/thumbnails/39.jpg)
N=375 Controls only All Variables
Intercept 7.995*** (0.359) 7.899*** (0.349)
Mismatch: Competition -0.115*** (0.031)
Mismatch: Competition and Moderate Uncertainty
0.057 (0.098)
Mismatch: Uncertainty 0.043** (0.026)
Mismatch: Correlation 0.015 (0.025)
Mismatch: Mean Demand 0.006 (0.026)
Mismatch: Demand Differential -0.062***(0.023)
GM -0.122*** (0.026) -0.154*** (0.027)
FORD -0.183*** (0.027) -0.210*** (0.028)
Assembly Line Flexibility 0.068** (0.036) 0.046(0.037)
Body Line Flexibility 0.126*** (0.042) 0.154*** (0.042)
Chassis 0.022*** (0.005) 0.014*** (0.005)
LOG (Capacity) -0.366*** (0.028) -0.371*** (0.029)
LOG (Utilization) -0.223*** (0.028) -0.234*** (0.029)
Year 1998 0.011 (0.061) 0.050 (0.060)
Year 1999 -0.055 (0.061) -0.025 (0.060)
Year 2000 -0.066 (0.061) -0.027 (0.060)
Year 2001 -0.119** (0.061) -0.089 (0.060)
Year 2002 -0.178*** (0.061) -0.152** (0.060)
Year 2003 -0.223*** (0.061) -0.186*** (0.060)
Adjusted R2 0.592 0.614
F-Statistic 42.829*** 32.316***
![Page 40: G](https://reader036.fdocuments.us/reader036/viewer/2022062704/5562b222d8b42a15548b545e/html5/thumbnails/40.jpg)
Results
• In the absence of the environmental variables, flexible plants have significantly higher HPV than inflexible plants.
• Adjusting for deviations from the benchmarks determined by the six environmental variables, flexibility is no longer significant.
• Flexibility by itself does not cause lower productivity
![Page 41: G](https://reader036.fdocuments.us/reader036/viewer/2022062704/5562b222d8b42a15548b545e/html5/thumbnails/41.jpg)
The six benchmarks
• Uncertainty: not matching flexibility deployment to environmental uncertainty decreases productivity.
• Competition: Responding to flexible competition with flexibility decreases productivity.
• Demand Differential: Contrary to theory.
![Page 42: G](https://reader036.fdocuments.us/reader036/viewer/2022062704/5562b222d8b42a15548b545e/html5/thumbnails/42.jpg)
The Control Variables
• Plants with higher capacity and utilization have higher productivity.
• Productivity has been increasing over the past years.
• GM and Ford have higher productivity than DCX.
![Page 43: G](https://reader036.fdocuments.us/reader036/viewer/2022062704/5562b222d8b42a15548b545e/html5/thumbnails/43.jpg)
Summary
• One of the first studies to formalize the deployment of manufacturing flexibility.– Demand uncertainty– Correlation.
• Though flexibility is used as a competitive weapon (flexible plants have higher flexible competition), evidence also suggests that this could be a cause of lower productivity.
• Flexible plants have lower utilization, a possible reason is the presence of volume flexibility in conjunction with product flexibility.
![Page 44: G](https://reader036.fdocuments.us/reader036/viewer/2022062704/5562b222d8b42a15548b545e/html5/thumbnails/44.jpg)
Chapter 4
Capacity Investment and the Interplay between Volume Flexibility and Product Flexibility.
![Page 45: G](https://reader036.fdocuments.us/reader036/viewer/2022062704/5562b222d8b42a15548b545e/html5/thumbnails/45.jpg)
Product Flexible Technologywith volume flexibility (VP)
K
K+εK-ε
Demand for product 1
Demand for product 2
product 1
product 2
![Page 46: G](https://reader036.fdocuments.us/reader036/viewer/2022062704/5562b222d8b42a15548b545e/html5/thumbnails/46.jpg)
Product Flexible (P) Technology
Demand for product 1
Demand for product 2
product 1
product 2
![Page 47: G](https://reader036.fdocuments.us/reader036/viewer/2022062704/5562b222d8b42a15548b545e/html5/thumbnails/47.jpg)
Total Capacity fixed
Capacity Allocated to Product 1
Capacity Allocated to Product 2
Product Flexibility
![Page 48: G](https://reader036.fdocuments.us/reader036/viewer/2022062704/5562b222d8b42a15548b545e/html5/thumbnails/48.jpg)
-ε
-ε
+ε
+ε
Demand for product 1
Demand for product 2
product 1
product 2
Volume Flexible Technology (V)
![Page 49: G](https://reader036.fdocuments.us/reader036/viewer/2022062704/5562b222d8b42a15548b545e/html5/thumbnails/49.jpg)
The Dedicated (D) Technology
Demand for product 1
Demand for product 2
product 1
product 2
![Page 50: G](https://reader036.fdocuments.us/reader036/viewer/2022062704/5562b222d8b42a15548b545e/html5/thumbnails/50.jpg)
Volume and Product Flexibility• Both types of flexibility help cope with demand
uncertainty.– Ample literature on capacity investment into product
flexibility.– Virtually non-existent literature on volume flexibility.– When would a firm prefer one flexibility to another?
• A plant may possess (to some extent) both flexibility types.– No analytical models combining two flexibility types.– When would a firm add one flexibility over another?
![Page 51: G](https://reader036.fdocuments.us/reader036/viewer/2022062704/5562b222d8b42a15548b545e/html5/thumbnails/51.jpg)
The Model
Choice of Technology
D,V,P or VP
i
2y
1y
Two markets
Uncertain Demand Curve
Uncertain Demand Curve
2111 qqAP
1222 qqAP
,
![Page 52: G](https://reader036.fdocuments.us/reader036/viewer/2022062704/5562b222d8b42a15548b545e/html5/thumbnails/52.jpg)
Decision timeline
time
Decide choice of technology, Dedicated (D), Product-Flexible (P), Volume-Flexible (V), Vol & Prod-Flexible (VP),
xc
Choose capacity
: Cost of capacity per unit
x={D,V,P,VP}
Adjust and/or allocate capacity
Choice of Technology
ProductionCapacity Investment
Demand Curves realized
![Page 53: G](https://reader036.fdocuments.us/reader036/viewer/2022062704/5562b222d8b42a15548b545e/html5/thumbnails/53.jpg)
The Problem Formulation
Firm i invests in V technology Firm i invests in VP technology
2
1
2~
2
1
~
)3(
~~
21,
)(
)(
max21
yyvyv
y
yvvyyvyv
vvvvAKK
v
KKc
KKKA
KKcEvv
vpvpvp
vpvp
yyvpvpyyvpyvp
vpvpvpAK
vp
Kqqts
KKc
qqqA
KcEvp
~
21
2~
2
1)3(
..
)(
)(
}{max
As c→,
Volume Flexible →Dedicated
As c→,
Vol-Product Flexible → Product Flexible
Frictional cost of capacity adjustment
![Page 54: G](https://reader036.fdocuments.us/reader036/viewer/2022062704/5562b222d8b42a15548b545e/html5/thumbnails/54.jpg)
Expected Profits
)1(4
)(
)1(4
)()(2
221
22
21
dd
d
cc
)1(8
2
)1(4
)(
)1(4
)()(12
22
21
2
221
22
21
pp
p
cc
))1((4
2)1)((
2)1(4
)(
)1(4
)()(22
1222
21
2
2
221
22
21
c
c
c
ccc vvvv
)21)(1(4
)(2)1)((
4)1(4
)(
)1(4
)()(12
22
21
2
2
221
22
21
c
cc
c
ccc vpvpvpvp
D
P
V
VP
DeterministicStochastic
Leverage
![Page 55: G](https://reader036.fdocuments.us/reader036/viewer/2022062704/5562b222d8b42a15548b545e/html5/thumbnails/55.jpg)
The cost thresholds
Variance
Cost
DedicatedVolume Flexible
Dedicated Vs Volume Flexible
Dedicated Vs Product Flexible
Dedicated
Product Flexible
How do these thresholds behave?
![Page 56: G](https://reader036.fdocuments.us/reader036/viewer/2022062704/5562b222d8b42a15548b545e/html5/thumbnails/56.jpg)
Comparing D,V and P - Large Correlation
xpv ccc
,,,,2* ccv ,,,2*pc
Dedicated
Volume
Flexibility
Volume
Flexibility
Variance
D>(V,P) V>D>P
V>P>D
Cost of flexibility
With large aggregate uncertainty in demand Volume Flexibility is more useful
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,,,2*pc
DedicatedVolume Flexibility
Volume
Flexibility
Product Flexibility
Variance
xpv ccc
D>(V,P)
V>D>P
V>P>D
P>V>D
,,,,2* ccv
Comparing D,V and P - Medium Correlation
Cost of flexibility
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,,,2*pc
Volume Flexibility
Dedicated Product
Flexibility Product
Flexibility
Variance
xpv ccc
D>(V,P)
P>D>V
V>P>D
P>V>D
,,,,2* ccv
Comparing D,V and P - Low Correlation
Cost of flexibility
With small aggregate uncertainty in demand Product Flexibility is more useful
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Technology upgrade (addition)
Aggregate uncertainty is fixed
Profit VP - Profit P0,
Profit VP - Profit P0.
Incremental value of Volume Flexibility:
Aggregate uncertainty is fixed
Profit VP - Profit V0,
Profit VP - Profit V0.
Incremental value of Product Flexibility:
Additional volume flexibility helps when aggregate demand uncertainty is large but individual demand uncertainty does not matter.
Additional product flexibility helps when aggregate demand uncertainty is small and individual demand uncertainty is large.
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Key Findings• Match flexibility to the environment (preference):
– Product flexibility - individual demand uncertainty.– Volume flexibility - aggregate demand uncertainty.
– Product flexibility - substitutable products (VCR and DVD Player)– Volume flexibility - complementary products (VCR and TV)
• Incremental Product flexibility may be harmful even if it is costless (V>VP).
• Linking: Quick Response (volume flexibility) and Variety Postponement (product flexibility).
• Empirical study on the adoption of flexibility in the automotive industry is in progress.
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Appendix
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Total Capacity not fixed
Capacity Allocated to Product 1
Capacity Allocated to Product 2
Vol-Product Flexibility
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Flexibilities as “Building Blocks” and Technologies
Volume Flexible
Product Flexible
D
V
P
VP
X X
X
X
Dedicated
Volume Flexible
Product Flexible
Volume and Product Flexible
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The Problem Formulation
2
1)3(
21,
)(
max21
yyddyydyd
ddddAKK
d
KKKA
KKcEdd
..
)(max
}{max
21
2
1)3(
, 21
ppp
yyppyypy
qqp
pppAK
p
Kqqts
qqqA
KcE
pp
p
Firm i invests in D technology Firm i invests in P technology
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Model of Volume Flexibility
Adjusted Capacity,
Cost of flexibility
Kyv
2~
yvyv KKc
K+ε=K~
K
yvK~
K-ε=K~
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Frictional Cost of Volume Flexibility
(Source: The Second Century, Holweg and Pil)Capacity
LevelChange over year
Change over week
50% 75.5 % 78.7%
80% 90.0% 92.2%
100% 100% 100%
110% 105.1% 106.1%
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Financials
• The typical scale of operation is about 200-250,000 vehicles per year.
• In year 2002, the average incentive for the US automotive industry was $1873 per vehicle (The Second Century, Holweg and Pil).– The average incentives for the Big Three was $2300
per vehicle.
• The pretax profit per vehicle ranged from $226 (DCX) to $2069 (Nissan) per vehicle in 2002 (The Harbour Report, 2004).
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Product Flexible Technologywith volume flexibility (VP)
K
K+εK-ε
Demand for product 1
Demand for product 2
product 1
product 2
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Product Flexible (P) Technology
Demand for product 1
Demand for product 2
product 1
product 2
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Total Capacity fixed
Capacity Allocated to Product 1
Capacity Allocated to Product 2
Product Flexibility
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-ε
-ε
+ε
+ε
Demand for product 1
Demand for product 2
product 1
product 2
Volume Flexible Technology (V)
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The Dedicated (D) Technology
Demand for product 1
Demand for product 2
product 1
product 2