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  • REINFORCE THESE ARE IMP, HENCE PAY SPECIAL ATTENTION HERE. TALKING ON WHAT CAMPETITION CAN DO, TWO SWORN ENEMIES, GM AND CHRYSTLER ARE NOW COLLABORATING ON DEVELOPING A HYBRID TOGETHER TO COUNTER THE LEAD TAKEN BY TOYOTA!
  • Let me enlarge the figure for you
  • All the possible equilibrium in the tech game. If variance is low and the cost of flexibility is high, we get the pure dedicated market, If however, the variance is high and the cost is low, we get the pure flexible market. The intermediate case is interesting where we have an asymmetric equilibrium. Both technologies co-exist. EXPLAIN THAT IN THIS AREA WE HAVE DEDICTATED AS VARIANCE IS LOW AND COST IS HIGH ENOUGH ETC The flexible firm makes more money in the mixed market if the cost of flexibility is below a certain threshold
  • Let me make clear what I mean by product flexibility and what choice of technology we are modeling here. We consider fully flexible and fully dedicated. Some papers like Netessine et al and Bassok et al consider partially flexible resource where one class of resource can satisfy its own class of demand as well as lower class of demand. E.g. a full size car can satisfy own demand and demand for mid size but not the luxury segment.
  • The cost of changing production could be thought to be inbuilt in the capacity cost of product flexible capacity.
  • Let me make clear what I mean by product flexibility and what choice of technology we are modeling here. We consider fully flexible and fully dedicated. Some papers like Netessine et al and Bassok et al consider partially flexible resource where one class of resource can satisfy its own class of demand as well as lower class of demand. E.g. a full size car can satisfy own demand and demand for mid size but not the luxury segment.
  • The technology choice is therefore a choice between product flexible or dedicated technology. This paper has three key ingredients, the choice of technology as defined above, demand uncertainty and competition.
  • Always the bridesmaid, never the bride. Example of VP plant: BMW at Leipzig. Labour flexibility plus product flexibility (can manufacture any of the 10 model series of BMW)
  • SAY MORE ON DEMAND CURVE. The demand is modeled to be linear in price. Price is A- q where q is the total quantity in the market, Higher the q lower the price. Also as you see, the cross price term also influences price. NO LOST SALES EXCEPT FOR LOST PROFITS Any demand curve ought to work as long as the profit function is convex in the random variable. Valid for a wide class of functions with additive or multiplicative random shock.
  • As before, there are three sequential decisions, but without competition now.
  • The little c is exogenous to the model. Endogenizing c is certainly an interesting question and is best studied for competition. But not something that we talk about here. Taylor approximation.
  • The deterministic component is very similar..increases in mean and decreases in costs and I will not talk about it. It is surprising that stochastic component is increasing in variance. But this was shown in 1961 by Oi. Because of endogenous pricing, it is convex increasing in the random variable inducing a risk seeking behavior. Etc. Though the deterministic component looks very similar, there are no similarities on the stochastic component. Moreover, the volume flexible technologies also have the leverage component that derives from their ability to adjust ex-post capacities. It is clear as to how these components trade-off with one another and which technology is preferred over which. For instance, one would have expected that the volume only flexible technology to be independent of the correlation. Note that in order to analyze volume flexibility, we needed just one product. Then we would have missed the impact of correlation on volume flexibility. Traditional literature modeled only one side demand correlation. Note that by that we would have missed the impact that the market plays. It is important to model market dynamics. This leads us to an unintuitive result that higher inspite of two independent lines, the problem depends on the market correlation. So what I am now going to do is a most fundamental comparison. I will put the costs of volume flexible only and product flexible only technologies to be the same and compare them to a dedicated technology. I will also assume that dedicated capacity is the cheapest. Hence, I will measure the cost of volume and product flexible technologies as cost premiums over dedicated technology.
  • We show that the decision threshold or the solution to the choice of technology is a line and is convex Along the y axis, I have the cost of capacity investment. This is the premium a firm is willing to pay over a dedicated technology. The green curve is the threshold we get by comparing V and D. The brown is the threshold we get by comparing P and D. I am going to play around with beta and rho. I can also play around with c. How do these behave? DO these cross each other, etc.
  • For large rho, they do not cross.
  • Note that now product flexibility starts to dominate volume. Talk about why low investment cost, product flexibility is favored but for high volume flexibility is favored, even though cost of investment is the same.
  • Negative rho indicates that total variability is small even if there is individual variability. Hence, it suggests that product flexibility handles individual variability better while volume flexibility handles total variability better. I can do a similar thing by changing beta.
  • The contribution is of course in the modeling
  • So whats the big deal about
  • My aim is to study the inter-twined nature of v and p. Towards that end, I am going to use volume and product flexibility as building blocks to construct four technologies. My comparing these four, we will reveal the embedded similarities and differences between volume and product flexibility.
  • Big Pi is the profit in the capacity game. We maximize the expected profit of the ex-post production game, net of investment costs. Little pi is the ex-post profit. Since it is ex-post uncertainty resolution, for each realization of A we can solve this. It is a two stage stochastic program with recourse.
  • Blanchard (1983) models convex cost of changing production. Visit to the GM plant. My experience with bottling plant. Chemical plants. With linear changeover costs, analytically difficult to handle. We will comment more on how this will impact the findings. People typically argue that there is a cost to downside flexibility. Some like Hall (2000) argue that it is concave and some like Blanchard say it is convex. Suarez et al note that volume flexibility responds to a whole new dynamics (compared to other flexibility types such as new-product and mix).
  • This explains the strong incentive not to reduce capacity use when demand drops, but rather to push volumes out and gamble that – despite costly incentives – the resulting sales will help cover the fixed cost.
  • Let me make clear what I mean by product flexibility and what choice of technology we are modeling here. We consider fully flexible and fully dedicated. Some papers like Netessine et al and Bassok et al consider partially flexible resource where one class of resource can satisfy its own class of demand as well as lower class of demand. E.g. a full size car can satisfy own demand and demand for mid size but not the luxury segment.
  • The cost of changing production could be thought to be inbuilt in the capacity cost of product flexible capacity.
  • Let me make clear what I mean by product flexibility and what choice of technology we are modeling here. We consider fully flexible and fully dedicated. Some papers like Netessine et al and Bassok et al consider partially flexible resource where one class of resource can satisfy its own class of demand as well as lower class of demand. E.g. a full size car can satisfy own demand and demand for mid size but not the luxury segment.
  • The technology choice is therefore a choice between product flexible or dedicated technology. This paper has three key ingredients, the choice of technology as defined above, demand uncertainty and competition.
  • Transcript

    • 1. “ Blessed are the flexible, for they will never be bent out of shape”
    • 2. Managing Operational Flexibility Under Demand Uncertainty Dissertation Defense: Manu Goyal
    • 3. 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.
    • 4. Chapter 2 Strategic Technology Choice and Capacity Investment under Demand Uncertainty.
    • 5. PT Cruiser Chrysler Town & Country Honda Odyssey CR-V Ford Ford Freestar Ford Escape
    • 6. 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
    • 7. The Model One flexible or two dedicatedplants One flexible or two dedicated plants Two markets Uncertain Demand Curve Uncertain Demand Curve
    • 8. Decision timeline for each of two firms competing in two markets time Technology Game Production Game Capacity Game Demand Curve realized Decide choice of technology, Dedicated ( D ) or Flexible ( F ) Choose capacity : Cost of flexible capacity per unit : Cost of dedicated capacity per unit Decide production qty for both markets q 1i , q 2i Prices determined as per Cournot competition. Profits gleaned Flexible Firm: one decision Ded. Firm: two decisions
    • 9. The Technology Game D F F D Firm i Firm j
    • 10. The Technology Game Profits 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
    • 11. The Stochastic Effect Profits (symmetric costs and distribution) Stochastic Deterministic F D F D
    • 12. The Best Response Functions - When Competitor invests in dedicated technology Infeasible Region Dedicated Flexible Monopolist Flexible Dedicated
    • 13. The Best Response Functions - When Competitor invests in flexible technology Infeasible Region Dedicated Flexible Monopolist Flexible Dedicated
    • 14. The Nash Equilibrium
    • 15. (D,D) Infeasible Region (F,F) (D,F) and (F,D) Pure Flexible Market Mixed Market The Nash Equilibrium
    • 16. Other Effects
      • Market size effect
        • Pulls threshold curves down.
        • Additional ( F,F ) and ( D,D ) equilibrium is s imultaneously possible.
      • Product Substitutability Effect.
        • Amplifies both the stochastic and market size effects
      • The Cost Effect.
        • Induced by asymmetries in the costs of firms.
    • 17. Equilibrium with market size effect (D,D) (F,F) (D,F) and (F,D) (D,D) and (F,F)
    • 18. Other Effects
      • Market size effect
        • Pulls threshold curves down.
        • Additional ( F,F ) and ( D,D ) equilibrium is s imultaneously possible.
      • Product Substitutability Effect.
        • Amplifies both the stochastic and market size effects
      • The Cost Effect.
        • Induced by asymmetries in the costs of firms.
    • 19. The cost effect (D,D) (F,F) (D,F) and (F,D) (F,D) (F,D) (F,D) cost I V IV III VI VII
    • 20. cost
    • 21. 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
    • 22. Chapter 3 Deployment of Manufacturing Flexibility: an Empirical Analysis of the Automotive Industry.
    • 23. 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.
    • 24. 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.
    • 25. 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).
    • 26. 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?
    • 27. Observed Flexibility Over Time
    • 28. 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.
    • 29. Control Variables
      • Plant Capacity
      • Plant Utilization.
      • Manufacturer dummies.
    • 30. The Analysis: Descriptive Statistics 0.28 0.91 1.67 0.15 Utilization 61527 208602 327120 33088 Capacity 3619 2677 26352 8 Substitution 62764 31018 511365 46 Demand Differential 1.27 1.35 7.00 0.00 Competition .4630 0.3632 1.00 -1.00 Correlation 0.28 0.45 1.56 0.03 Demand Uncertainty 16133 17045 79836 471 Mean Demand Std. Dev. Mean Maximum Minimum
    • 31. Correlations -0.14** -0.01 0.10* -0.19** 0.13** 0.21** 0.24** Capacity 0.16** 0.56** 0.03 0.10* 0.24** -0.07 Mean Demand 0.29** -0.12** -0.08 0.13** 0.22** Demand Differential -0.06 0.05 0.33** 0.006 Demand Uncertainty -0.11* 0.02 -0.17** Substitution 0.08 -0.02 Correlation 0.02 Utilization Mean Demand Demand Differ. Demand Uncertainty Substitution Correlation Utilization Competition
    • 32. Univariate Test Univariate Test of Differences in Means (dependent variable: ALF) 0.10 14138.23 17538.14 Mean Demand 0.91 30236.34 31150.90 Demand Differential 0.37 0.48 0.44 Demand Uncertainty 0.01 0.24 0.38 Correlation 0.00 1.90 1.25 Competition P-value for test of mean difference Mean: ALF = 1 Mean: ALF = 0
    • 33. Logit Regression (N=483) 0.0047 0.007 0.22 Significance 0.399 (0.416) 0.331 (0.40) 0.152 (0.283) Ford 0.162 (0.405) 0.137 (0.389) 0.189 (0.356) GM 0.00 (0.00) 0.00 (0.00) 0.00 (0.00) Capacity -0.962* (0.550) -0.907* (0.543) -0.900** (0.481) Utilization -0.00 (0.00) Substitution × Difference of Means. 0.00 (0.00) Substitution × Coefficient of Variation. -0.00 (0.00) Substitution -0.00 (0.00) -0.00 (0.00) Mean Demand -0.00 (0.00) -0.00 (0.00) Demand Differential 1.612** (0.694) 1.367** (0.596) Demand Uncertainty -0.598** (0.284) -0.600** (0.275) Demand Correlation 0.276** (0.123) 0.3243*** (0.098) Competition -2.078*** (0.766) -2.00*** (0.704) -1.899*** (0.645) Intercept Column 3 Column 2 Column 1
    • 34. 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”.
    • 35. Productivity Analysis
      • Study the implications of deploying flexibility, measured against extant theories.
      • Hours per Vehicle (HPV) as a measure of productivity.
    • 36. HPV over the years
    • 37. 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).
    • 38. Regression
      • Regress HPV against these six mismatches (OLS).
      • Control Variables:
        • Flexibility
        • Utilization
        • Plant Capacity
        • Companies
        • Years
        • Number of Chassis Configurations.
    • 39. 32.316*** 42.829*** F-Statistic 0.614 0.592 Adjusted R 2 -0.186*** (0.060) -0.223*** (0.061) Year 2003 -0.152** (0.060) -0.178*** (0.061) Year 2002 -0.089 (0.060) -0.119** (0.061) Year 2001 -0.027 (0.060) -0.066 (0.061) Year 2000 -0.025 (0.060) -0.055 (0.061) Year 1999 0.050 (0.060) 0.011 (0.061) Year 1998 -0.234*** (0.029) -0.223*** (0.028) LOG (Utilization) -0.371*** (0.029) -0.366*** (0.028) LOG (Capacity) 0.014*** (0.005) 0.022*** (0.005) Chassis 0.154*** (0.042) 0.126*** (0.042) Body Line Flexibility 0.046(0.037) 0.068** (0.036) Assembly Line Flexibility -0.210*** (0.028) -0.183*** (0.027) FORD -0.154*** (0.027) -0.122*** (0.026) GM -0.062***(0.023) Mismatch: Demand Differential 0.006 (0.026) Mismatch: Mean Demand 0.015 (0.025) Mismatch: Correlation 0.043** (0.026) Mismatch: Uncertainty 0.057 (0.098) Mismatch: Competition and Moderate Uncertainty -0.115*** (0.031) Mismatch: Competition 7.899*** (0.349) 7.995*** (0.359) Intercept All Variables Controls only N=375
    • 40. 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
    • 41. 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.
    • 42. 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.
    • 43. 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.
    • 44. Chapter 4 Capacity Investment and the Interplay between Volume Flexibility and Product Flexibility.
    • 45. Product Flexible Technology with volume flexibility ( V P) K Demand for product 1 Demand for product 2 product 1 product 2 K+ ε K- ε
    • 46. Product Flexible (P) Technology Demand for product 1 Demand for product 2 product 1 product 2
    • 47. Product Flexibility Total Capacity fixed Capacity Allocated to Product 1 Capacity Allocated to Product 2
    • 48. Volume Flexible Technology (V) - ε - ε + ε + ε Demand for product 1 Demand for product 2 product 1 product 2
    • 49. The Dedicated (D) Technology Demand for product 1 Demand for product 2 product 1 product 2
    • 50. 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?
    • 51. The Model Choice of Technology D,V,P or VP Two markets Uncertain Demand Curve Uncertain Demand Curve
    • 52. Decision timeline time Decide choice of technology, Dedicated ( D ) , Product-Flexible ( P ), Volume-Flexible ( V ) , Vol & Prod-Flexible ( VP ), Choose capacity : Cost of capacity per unit x= { D,V,P,VP} Choice of Technology Production Capacity Investment Demand Curves realized Adjust and/or allocate capacity
    • 53. The Problem Formulation Firm i invests in V technology Firm i invests in VP technology As c->  , Volume Flexible ->Dedicated As c->  , Vol-Product Flexible -> Product Flexible Frictional cost of capacity adjustment
    • 54. Expected Profits D P V VP Deterministic Stochastic Leverage
    • 55. The cost thresholds Variance Cost Dedicated Volume Flexible Dedicated Vs Volume Flexible Dedicated Vs Product Flexible Dedicated Product Flexible How do these thresholds behave?
    • 56. Comparing D,V and P - Large Correlation 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
    • 57. Dedicated Volume Flexibility Volume Flexibility Product Flexibility Variance D>(V,P) V>D>P V>P>D P>V>D Comparing D,V and P - Medium Correlation Cost of flexibility
    • 58. Volume Flexibility Dedicated Product Flexibility Product Flexibility Variance D>(V,P) P>D>V V>P>D P>V>D Comparing D,V and P - Low Correlation Cost of flexibility With small aggregate uncertainty in demand Product Flexibility is more useful
    • 59. Technology upgrade (addition) Incremental value of Volume Flexibility: 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.
    • 60. 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.
    • 61. Appendix
    • 62. Vol-Product Flexibility Total Capacity not fixed Capacity Allocated to Product 1 Capacity Allocated to Product 2
    • 63. 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
    • 64. The Problem Formulation Firm i invests in D technology Firm i invests in P technology
    • 65. Model of Volume Flexibility Adjusted Capacity, Cost of flexibility K yv K+ ε =K ~ K K- ε =K ~
    • 66. Frictional Cost of Volume Flexibility (Source: The Second Century, Holweg and Pil) 106.1% 105.1% 110% 100% 100% 100% 92.2% 90.0% 80% 78.7% 75.5 % 50% Change over week Change over year Capacity Level
    • 67. 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).
    • 68. Product Flexible Technology with volume flexibility ( V P) K Demand for product 1 Demand for product 2 product 1 product 2 K+ ε K- ε
    • 69. Product Flexible (P) Technology Demand for product 1 Demand for product 2 product 1 product 2
    • 70. Product Flexibility Total Capacity fixed Capacity Allocated to Product 1 Capacity Allocated to Product 2
    • 71. Volume Flexible Technology (V) - ε - ε + ε + ε Demand for product 1 Demand for product 2 product 1 product 2
    • 72. The Dedicated (D) Technology Demand for product 1 Demand for product 2 product 1 product 2

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