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© 2006 Prentice Hall, Inc. 8 – 1
Operations
Management
Chapter 8 –
Location Strategies
© 2006 Prentice Hall, Inc.
PowerPoint presentation to accompany
Heizer/Render
Principles of Operations Management, 6e
Operations Management, 8e
© 2006 Prentice Hall, Inc. 8 – 2
Outline
 Global Company Profile:
Federal Express
 The Strategic Importance
Of Location
© 2006 Prentice Hall, Inc. 8 – 3
Outline – Continued
 Factors That Affect Location
Decisions
 Labor Productivity
 Exchange Rates and Currency Risks
 Costs
 Attitudes
 Proximity to Markets
 Proximity to Suppliers
 Proximity to Competitors (Clustering)
© 2006 Prentice Hall, Inc. 8 – 4
Outline – Continued
 Methods Of Evaluating Location
Alternatives
 The Factor-Rating Method
 Locational Break-Even Analysis
 Center-of-Gravity Method
 The Transportation Method
© 2006 Prentice Hall, Inc. 8 – 5
Outline – Continued
 Service Location Strategy
 How Hotel Chains Select Sites
 The Telemarketing Industry
 Geographic Information Systems
© 2006 Prentice Hall, Inc. 8 – 6
Learning Objectives
When you complete this chapter, you
should be able to:
Identify or Define:
 Objective of location strategy
 International location issues
 Clustering
 Geographic information systems
© 2006 Prentice Hall, Inc. 8 – 7
Learning Objectives
When you complete this chapter, you
should be able to:
Describe or Explain:
 Three methods of solving the location
problem
 Factor-rating method
 Locational breakeven analysis
 Center-of-gravity method
 Describe the factors affecting location
decisions
© 2006 Prentice Hall, Inc. 8 – 8
Federal Express
 Central hub concept
 Enables service to more locations with
fewer aircraft
 Enables matching of aircraft flights with
package loads
 Reduces mishandling and delay in transit
because there is total control of
packages from pickup to delivery
© 2006 Prentice Hall, Inc. 8 – 9
Location Strategy
 One of the most important decisions
a firm makes
 Increasingly global in nature
 Long term impact and decisions are
difficult to change
 The objective is to maximize the
benefit of location to the firm
© 2006 Prentice Hall, Inc. 8 – 10
Location and Innovation
 Cost is not always the most important
aspect of a strategic decision
 Four key attributes when strategy is
based on innovation
 High-quality and specialized inputs
 An environment that encourages
investment and local rivalry
 A sophisticated local market
 Local presence of related and
supporting industries
© 2006 Prentice Hall, Inc. 8 – 11
Location Decisions
 Long-term decisions
 Decisions made infrequently
 Decision greatly affects both fixed
and variable costs
 Once committed to a location,
many resource and cost issues are
difficult to change
© 2006 Prentice Hall, Inc. 8 – 12
Location Decisions
Country Decision Critical Success Factors
1. Political risks, government
rules, attitudes, incentives
2. Cultural and economic
issues
3. Location of markets
4. Labor availability,
attitudes, productivity,
costs
5. Availability of supplies,
communications, energy
6. Exchange rates and
currency risks
Figure 8.1
© 2006 Prentice Hall, Inc. 8 – 13
Location Decisions
Region/
Community
Decision
Critical Success Factors
1. Corporate desires
2. Attractiveness of region
3. Labor availability, costs,
attitudes towards unions
4. Costs and availability of utilities
5. Environmental regulations
6. Government incentives and
fiscal policies
7. Proximity to raw materials and
customers
8. Land/construction costs
MN
WI
MI
IL IN
OH
Figure 8.1
© 2006 Prentice Hall, Inc. 8 – 14
Location Decisions
Site Decision Critical Success Factors
1. Site size and cost
2. Air, rail, highway, and
waterway systems
3. Zoning restrictions
4. Nearness of services/
supplies needed
5. Environmental impact
issues
Figure 8.1
© 2006 Prentice Hall, Inc. 8 – 15
Factors That Affect
Location Decisions
 Labor productivity
 Wage rates are not the only cost
 Lower productivity may increase total cost
Labor cost per day
Productivity (units per day)
= cost per unit
Connecticut
= $1.17 per unit
$70
60 units
Juarez
= $1.25 per unit
$25
20 units
© 2006 Prentice Hall, Inc. 8 – 16
Factors That Affect
Location Decisions
 Exchange rates and currency risks
 Can have a significant impact on cost
structure
 Rates change over time
 Costs
 Tangible - easily measured costs such as
utilities, labor, materials, taxes
 Intangible - less easy to quantify and
include education, public transportation,
community, quality-of-life
© 2006 Prentice Hall, Inc. 8 – 17
Factors That Affect
Location Decisions
 Attitudes
 National, state, local governments toward
private and intellectual property, zoning,
pollution, employment stability
 Worker attitudes towards turnover, unions,
absenteeism
 Globally cultures have different attitudes
towards punctuality, legal, and ethical
issues
© 2006 Prentice Hall, Inc. 8 – 18
Factors That Affect
Location Decisions
 Proximity to markets
 Very important to services
 JIT systems or high transportation costs
may make it important to manufacturers
 Proximity to suppliers
 Perishable goods, high transportation
costs, bulky products
© 2006 Prentice Hall, Inc. 8 – 19
Factors That Affect
Location Decisions
 Proximity to competitors
 Called clustering
 Often driven by resources such as natural,
information, capital, talent
 Found in both manufacturing and service
industries
© 2006 Prentice Hall, Inc. 8 – 20
Growth Competitiveness
Index of Countries
Country 2004 Rank 2003 Rank
Finland 1 1
USA 2 2
Sweden 3 3
Taiwan 4 5
Japan 9 11
UK 11 15
Germany 13 13
Canada 15 16
New Zealand 18 14
France 27 26
Russia 70 70
© 2006 Prentice Hall, Inc. 8 – 21
Clustering of Companies
Industry Locations Reason for clustering
Wine makers Napa Valley (US)
Bordeaux region
(France)
Natural resources of
land and climate
Software firms Silicon Valley,
Boston, Bangalore
(India)
Talent resources of
bright graduates in
scientific/technical
areas, venture
capitalists nearby
Race car
builders
Huntington/North
Hampton region
(England)
Critical mass of talent
and information
Table 8.3
© 2006 Prentice Hall, Inc. 8 – 22
Clustering of Companies
Industry Locations Reason for clustering
Theme parks Orlando A hot spot for
entertainment, warm
weather, tourists, and
inexpensive labor
Electronic firms Northern Mexico NAFTA, duty free
export to US
Computer
hardware
manufacturers
Singapore, Taiwan High technological
penetration rate and
per capita GDP,
skilled/educated
workforce with large
pool of engineers
Table 8.3
© 2006 Prentice Hall, Inc. 8 – 23
Clustering of Companies
Industry Locations Reason for clustering
Fast food
chains
Sites within one
mile of each other
Stimulate food sales,
high traffic flows
General aviation
aircraft
Wichita, Kansas Mass of aviation skills
Table 8.3
© 2006 Prentice Hall, Inc. 8 – 24
Factor-Rating Method
 Popular because a wide variety of factors
can be included in the analysis
 Six steps in the method
1. Develop a list of relevant factors called
critical success factors
2. Assign a weight to each factor
3. Develop a scale for each factor
4. Score each location for each factor
5. Multiply score by weights for each factor for
each location
6. Recommend the location with the highest
point score
© 2006 Prentice Hall, Inc. 8 – 25
Factor-Rating Example
Critical Scores
Success (out of 100) Weighted Scores
Factor Weight France Denmark France Denmark
Labor
availability
and attitude .25 70 60 (.25)(70) = 17.5 (.25)(60) = 15.0
People-to
car ratio .05 50 60 (.05)(50) = 2.5 (.05)(60) = 3.0
Per capita
income .10 85 80 (.10)(85) = 8.5 (.10)(80) = 8.0
Tax structure .39 75 70 (.39)(75) = 29.3 (.39)(70) = 27.3
Education
and health .21 60 70 (.21)(60) = 12.6 (.21)(70) = 14.7
Totals 1.00 70.4 68.0
Table 8.3
© 2006 Prentice Hall, Inc. 8 – 26
Locational
Break-Even Analysis
 Method of cost-volume analysis used for
industrial locations
 Three steps in the method
1. Determine fixed and variable costs for
each location
2. Plot the cost for each location
3. Select location with lowest total cost for
expected production volume
© 2006 Prentice Hall, Inc. 8 – 27
Locational Break-Even
Analysis Example
Three locations:
Akron $30,000 $75 $180,000
Bowling Green $60,000 $45 $150,000
Chicago $110,000 $25 $160,000
Selling price = $120
Expected volume = 2,000 units
Fixed Variable Total
City Cost Cost Cost
Total Cost = Fixed Cost + Variable Cost x Volume
© 2006 Prentice Hall, Inc. 8 – 28
Locational Break-Even
Analysis Example
–
$180,000 –
–
$160,000 –
$150,000 –
–
$130,000 –
–
$110,000 –
–
–
$80,000 –
–
$60,000 –
–
–
$30,000 –
–
$10,000 –
–
Annual
cost
| | | | | | |
0 500 1,000 1,500 2,000 2,500 3,000
Volume
Akron
lowest
cost
Bowling Green
lowest cost
Chicago
lowest
cost
Figure 8.2
© 2006 Prentice Hall, Inc. 8 – 29
Center-of-Gravity Method
 Finds location of distribution
center that minimizes distribution
costs
 Considers
 Location of markets
 Volume of goods shipped to those
markets
 Shipping cost (or distance)
© 2006 Prentice Hall, Inc. 8 – 30
Center-of-Gravity Method
 Place existing locations on a
coordinate grid
 Grid origin and scale is arbitrary
 Maintain relative distances
 Calculate X and Y coordinates for
‘center of gravity’
 Assumes cost is directly
proportional to distance and volume
shipped
© 2006 Prentice Hall, Inc. 8 – 31
Center-of-Gravity Method
x - coordinate =
∑dixQi
∑Qi
i
i
∑diyQi
∑Qi
i
i
y - coordinate =
where dix = x-coordinate of location i
diy = y-coordinate of location i
Qi = Quantity of goods moved to
or from location i
© 2006 Prentice Hall, Inc. 8 – 32
Center-of-Gravity Method
North-South
East-West
120 –
90 –
60 –
30 –
–
| | | | | |
30 60 90 120 150
Arbitrary
origin
Chicago (30, 120)
New York (130, 130)
Pittsburgh (90, 110)
Atlanta (60, 40)
© 2006 Prentice Hall, Inc. 8 – 33
Center-of-Gravity Method
Number of Containers
Store Location Shipped per Month
Chicago (30, 120) 2,000
Pittsburgh (90, 110) 1,000
New York (130, 130) 1,000
Atlanta (60, 40) 2,000
x-coordinate =
(30)(2000) + (90)(1000) + (130)(1000) + (60)(2000)
2000 + 1000 + 1000 + 2000
= 66.7
y-coordinate =
(120)(2000) + (110)(1000) + (130)(1000) + (40)(2000)
2000 + 1000 + 1000 + 2000
= 93.3
© 2006 Prentice Hall, Inc. 8 – 34
Center-of-Gravity Method
North-South
East-West
120 –
90 –
60 –
30 –
–
| | | | | |
30 60 90 120 150
Arbitrary
origin
Chicago (30, 120)
New York (130, 130)
Pittsburgh (90, 110)
Atlanta (60, 40)
Center of gravity (66.7, 93.3)
+
© 2006 Prentice Hall, Inc. 8 – 35
Transportation Model
 Finds amount to be shipped from
several points of supply to several
points of demand
 Solution will minimize total
production and shipping costs
 A special class of linear
programming problems
© 2006 Prentice Hall, Inc. 8 – 36
Worldwide Distribution of
Volkswagens and Parts
Figure 8.4
© 2006 Prentice Hall, Inc. 8 – 37
Service Location Strategy
1. Purchasing power of customer-drawing area
2. Service and image compatibility with demographics
of the customer-drawing area
3. Competition in the area
4. Quality of the competition
5. Uniqueness of the firm’s and competitors’ locations
6. Physical qualities of facilities and neighboring
businesses
7. Operating policies of the firm
8. Quality of management
© 2006 Prentice Hall, Inc. 8 – 38
Location Strategies
Service/Retail/Professional Location Goods-Producing Location
Revenue Focus Cost Focus
Volume/revenue
Drawing area; purchasing power
Competition; advertising/pricing
Physical quality
Parking/access; security/lighting;
appearance/image
Cost determinants
Rent
Management caliber
Operations policies (hours, wage
rates)
Tangible costs
Transportation cost of raw material
Shipment cost of finished goods
Energy and utility cost; labor; raw
material; taxes, and so on
Intangible and future costs
Attitude toward union
Quality of life
Education expenditures by state
Quality of state and local
government
Table 8.4
© 2006 Prentice Hall, Inc. 8 – 39
Location Strategies
Service/Retail/Professional Location Goods-Producing Location
Techniques Techniques
Regression models to determine
importance of various factors
Factor-rating method
Traffic counts
Demographic analysis of drawing area
Purchasing power analysis of area
Center-of-gravity method
Geographic information systems
Transportation methods
Factor-rating method
Locational break-even analysis
Crossover charts
Table 8.4
© 2006 Prentice Hall, Inc. 8 – 40
Location Strategies
Service/Retail/Professional Location Goods-Producing Location
Assumptions Assumptions
Location is a major determinant of
revenue
High customer-contact issues are
critical
Costs are relatively constant for a
given area; therefore, the revenue
function is critical
Location is a major determinant of
cost
Most major costs can be identified
explicitly for each site
Low customer contact allows focus
on the identifiable costs
Intangible costs can be evaluated
Table 8.4
© 2006 Prentice Hall, Inc. 8 – 41
How Hotel Chains Select Sites
 Location is a strategically important
decision in the hospitality industry
 La Quinta started with 35 independent
variables and worked to refine a
regression model to predict profitability
 The final model had only four variables
 Price of the inn
 Median income levels
 State population per inn
 Location of nearby colleges
r2 = .51
51% of the
profitability is
predicted by
just these four
variables!
© 2006 Prentice Hall, Inc. 8 – 42
Telemarketing/Internet
Industries
 Require neither face-to-face contact
nor movement of materials
 Have very broad location options
 Traditional variables are no longer
relevant
 Cost and availability of labor may
drive location decisions
© 2006 Prentice Hall, Inc. 8 – 43
Geographic Information
Systems (GIS)
 New tool to help in location analysis
 Enables more complex demographic
analysis
 Available data bases include
 Detailed census data
 Detailed maps
 Utilities
 Geographic features
 Locations of major services
© 2006 Prentice Hall, Inc. 8 – 44
Geographic Information
Systems (GIS)

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Chapter 8 Location Strategy.ppt

  • 1. © 2006 Prentice Hall, Inc. 8 – 1 Operations Management Chapter 8 – Location Strategies © 2006 Prentice Hall, Inc. PowerPoint presentation to accompany Heizer/Render Principles of Operations Management, 6e Operations Management, 8e
  • 2. © 2006 Prentice Hall, Inc. 8 – 2 Outline  Global Company Profile: Federal Express  The Strategic Importance Of Location
  • 3. © 2006 Prentice Hall, Inc. 8 – 3 Outline – Continued  Factors That Affect Location Decisions  Labor Productivity  Exchange Rates and Currency Risks  Costs  Attitudes  Proximity to Markets  Proximity to Suppliers  Proximity to Competitors (Clustering)
  • 4. © 2006 Prentice Hall, Inc. 8 – 4 Outline – Continued  Methods Of Evaluating Location Alternatives  The Factor-Rating Method  Locational Break-Even Analysis  Center-of-Gravity Method  The Transportation Method
  • 5. © 2006 Prentice Hall, Inc. 8 – 5 Outline – Continued  Service Location Strategy  How Hotel Chains Select Sites  The Telemarketing Industry  Geographic Information Systems
  • 6. © 2006 Prentice Hall, Inc. 8 – 6 Learning Objectives When you complete this chapter, you should be able to: Identify or Define:  Objective of location strategy  International location issues  Clustering  Geographic information systems
  • 7. © 2006 Prentice Hall, Inc. 8 – 7 Learning Objectives When you complete this chapter, you should be able to: Describe or Explain:  Three methods of solving the location problem  Factor-rating method  Locational breakeven analysis  Center-of-gravity method  Describe the factors affecting location decisions
  • 8. © 2006 Prentice Hall, Inc. 8 – 8 Federal Express  Central hub concept  Enables service to more locations with fewer aircraft  Enables matching of aircraft flights with package loads  Reduces mishandling and delay in transit because there is total control of packages from pickup to delivery
  • 9. © 2006 Prentice Hall, Inc. 8 – 9 Location Strategy  One of the most important decisions a firm makes  Increasingly global in nature  Long term impact and decisions are difficult to change  The objective is to maximize the benefit of location to the firm
  • 10. © 2006 Prentice Hall, Inc. 8 – 10 Location and Innovation  Cost is not always the most important aspect of a strategic decision  Four key attributes when strategy is based on innovation  High-quality and specialized inputs  An environment that encourages investment and local rivalry  A sophisticated local market  Local presence of related and supporting industries
  • 11. © 2006 Prentice Hall, Inc. 8 – 11 Location Decisions  Long-term decisions  Decisions made infrequently  Decision greatly affects both fixed and variable costs  Once committed to a location, many resource and cost issues are difficult to change
  • 12. © 2006 Prentice Hall, Inc. 8 – 12 Location Decisions Country Decision Critical Success Factors 1. Political risks, government rules, attitudes, incentives 2. Cultural and economic issues 3. Location of markets 4. Labor availability, attitudes, productivity, costs 5. Availability of supplies, communications, energy 6. Exchange rates and currency risks Figure 8.1
  • 13. © 2006 Prentice Hall, Inc. 8 – 13 Location Decisions Region/ Community Decision Critical Success Factors 1. Corporate desires 2. Attractiveness of region 3. Labor availability, costs, attitudes towards unions 4. Costs and availability of utilities 5. Environmental regulations 6. Government incentives and fiscal policies 7. Proximity to raw materials and customers 8. Land/construction costs MN WI MI IL IN OH Figure 8.1
  • 14. © 2006 Prentice Hall, Inc. 8 – 14 Location Decisions Site Decision Critical Success Factors 1. Site size and cost 2. Air, rail, highway, and waterway systems 3. Zoning restrictions 4. Nearness of services/ supplies needed 5. Environmental impact issues Figure 8.1
  • 15. © 2006 Prentice Hall, Inc. 8 – 15 Factors That Affect Location Decisions  Labor productivity  Wage rates are not the only cost  Lower productivity may increase total cost Labor cost per day Productivity (units per day) = cost per unit Connecticut = $1.17 per unit $70 60 units Juarez = $1.25 per unit $25 20 units
  • 16. © 2006 Prentice Hall, Inc. 8 – 16 Factors That Affect Location Decisions  Exchange rates and currency risks  Can have a significant impact on cost structure  Rates change over time  Costs  Tangible - easily measured costs such as utilities, labor, materials, taxes  Intangible - less easy to quantify and include education, public transportation, community, quality-of-life
  • 17. © 2006 Prentice Hall, Inc. 8 – 17 Factors That Affect Location Decisions  Attitudes  National, state, local governments toward private and intellectual property, zoning, pollution, employment stability  Worker attitudes towards turnover, unions, absenteeism  Globally cultures have different attitudes towards punctuality, legal, and ethical issues
  • 18. © 2006 Prentice Hall, Inc. 8 – 18 Factors That Affect Location Decisions  Proximity to markets  Very important to services  JIT systems or high transportation costs may make it important to manufacturers  Proximity to suppliers  Perishable goods, high transportation costs, bulky products
  • 19. © 2006 Prentice Hall, Inc. 8 – 19 Factors That Affect Location Decisions  Proximity to competitors  Called clustering  Often driven by resources such as natural, information, capital, talent  Found in both manufacturing and service industries
  • 20. © 2006 Prentice Hall, Inc. 8 – 20 Growth Competitiveness Index of Countries Country 2004 Rank 2003 Rank Finland 1 1 USA 2 2 Sweden 3 3 Taiwan 4 5 Japan 9 11 UK 11 15 Germany 13 13 Canada 15 16 New Zealand 18 14 France 27 26 Russia 70 70
  • 21. © 2006 Prentice Hall, Inc. 8 – 21 Clustering of Companies Industry Locations Reason for clustering Wine makers Napa Valley (US) Bordeaux region (France) Natural resources of land and climate Software firms Silicon Valley, Boston, Bangalore (India) Talent resources of bright graduates in scientific/technical areas, venture capitalists nearby Race car builders Huntington/North Hampton region (England) Critical mass of talent and information Table 8.3
  • 22. © 2006 Prentice Hall, Inc. 8 – 22 Clustering of Companies Industry Locations Reason for clustering Theme parks Orlando A hot spot for entertainment, warm weather, tourists, and inexpensive labor Electronic firms Northern Mexico NAFTA, duty free export to US Computer hardware manufacturers Singapore, Taiwan High technological penetration rate and per capita GDP, skilled/educated workforce with large pool of engineers Table 8.3
  • 23. © 2006 Prentice Hall, Inc. 8 – 23 Clustering of Companies Industry Locations Reason for clustering Fast food chains Sites within one mile of each other Stimulate food sales, high traffic flows General aviation aircraft Wichita, Kansas Mass of aviation skills Table 8.3
  • 24. © 2006 Prentice Hall, Inc. 8 – 24 Factor-Rating Method  Popular because a wide variety of factors can be included in the analysis  Six steps in the method 1. Develop a list of relevant factors called critical success factors 2. Assign a weight to each factor 3. Develop a scale for each factor 4. Score each location for each factor 5. Multiply score by weights for each factor for each location 6. Recommend the location with the highest point score
  • 25. © 2006 Prentice Hall, Inc. 8 – 25 Factor-Rating Example Critical Scores Success (out of 100) Weighted Scores Factor Weight France Denmark France Denmark Labor availability and attitude .25 70 60 (.25)(70) = 17.5 (.25)(60) = 15.0 People-to car ratio .05 50 60 (.05)(50) = 2.5 (.05)(60) = 3.0 Per capita income .10 85 80 (.10)(85) = 8.5 (.10)(80) = 8.0 Tax structure .39 75 70 (.39)(75) = 29.3 (.39)(70) = 27.3 Education and health .21 60 70 (.21)(60) = 12.6 (.21)(70) = 14.7 Totals 1.00 70.4 68.0 Table 8.3
  • 26. © 2006 Prentice Hall, Inc. 8 – 26 Locational Break-Even Analysis  Method of cost-volume analysis used for industrial locations  Three steps in the method 1. Determine fixed and variable costs for each location 2. Plot the cost for each location 3. Select location with lowest total cost for expected production volume
  • 27. © 2006 Prentice Hall, Inc. 8 – 27 Locational Break-Even Analysis Example Three locations: Akron $30,000 $75 $180,000 Bowling Green $60,000 $45 $150,000 Chicago $110,000 $25 $160,000 Selling price = $120 Expected volume = 2,000 units Fixed Variable Total City Cost Cost Cost Total Cost = Fixed Cost + Variable Cost x Volume
  • 28. © 2006 Prentice Hall, Inc. 8 – 28 Locational Break-Even Analysis Example – $180,000 – – $160,000 – $150,000 – – $130,000 – – $110,000 – – – $80,000 – – $60,000 – – – $30,000 – – $10,000 – – Annual cost | | | | | | | 0 500 1,000 1,500 2,000 2,500 3,000 Volume Akron lowest cost Bowling Green lowest cost Chicago lowest cost Figure 8.2
  • 29. © 2006 Prentice Hall, Inc. 8 – 29 Center-of-Gravity Method  Finds location of distribution center that minimizes distribution costs  Considers  Location of markets  Volume of goods shipped to those markets  Shipping cost (or distance)
  • 30. © 2006 Prentice Hall, Inc. 8 – 30 Center-of-Gravity Method  Place existing locations on a coordinate grid  Grid origin and scale is arbitrary  Maintain relative distances  Calculate X and Y coordinates for ‘center of gravity’  Assumes cost is directly proportional to distance and volume shipped
  • 31. © 2006 Prentice Hall, Inc. 8 – 31 Center-of-Gravity Method x - coordinate = ∑dixQi ∑Qi i i ∑diyQi ∑Qi i i y - coordinate = where dix = x-coordinate of location i diy = y-coordinate of location i Qi = Quantity of goods moved to or from location i
  • 32. © 2006 Prentice Hall, Inc. 8 – 32 Center-of-Gravity Method North-South East-West 120 – 90 – 60 – 30 – – | | | | | | 30 60 90 120 150 Arbitrary origin Chicago (30, 120) New York (130, 130) Pittsburgh (90, 110) Atlanta (60, 40)
  • 33. © 2006 Prentice Hall, Inc. 8 – 33 Center-of-Gravity Method Number of Containers Store Location Shipped per Month Chicago (30, 120) 2,000 Pittsburgh (90, 110) 1,000 New York (130, 130) 1,000 Atlanta (60, 40) 2,000 x-coordinate = (30)(2000) + (90)(1000) + (130)(1000) + (60)(2000) 2000 + 1000 + 1000 + 2000 = 66.7 y-coordinate = (120)(2000) + (110)(1000) + (130)(1000) + (40)(2000) 2000 + 1000 + 1000 + 2000 = 93.3
  • 34. © 2006 Prentice Hall, Inc. 8 – 34 Center-of-Gravity Method North-South East-West 120 – 90 – 60 – 30 – – | | | | | | 30 60 90 120 150 Arbitrary origin Chicago (30, 120) New York (130, 130) Pittsburgh (90, 110) Atlanta (60, 40) Center of gravity (66.7, 93.3) +
  • 35. © 2006 Prentice Hall, Inc. 8 – 35 Transportation Model  Finds amount to be shipped from several points of supply to several points of demand  Solution will minimize total production and shipping costs  A special class of linear programming problems
  • 36. © 2006 Prentice Hall, Inc. 8 – 36 Worldwide Distribution of Volkswagens and Parts Figure 8.4
  • 37. © 2006 Prentice Hall, Inc. 8 – 37 Service Location Strategy 1. Purchasing power of customer-drawing area 2. Service and image compatibility with demographics of the customer-drawing area 3. Competition in the area 4. Quality of the competition 5. Uniqueness of the firm’s and competitors’ locations 6. Physical qualities of facilities and neighboring businesses 7. Operating policies of the firm 8. Quality of management
  • 38. © 2006 Prentice Hall, Inc. 8 – 38 Location Strategies Service/Retail/Professional Location Goods-Producing Location Revenue Focus Cost Focus Volume/revenue Drawing area; purchasing power Competition; advertising/pricing Physical quality Parking/access; security/lighting; appearance/image Cost determinants Rent Management caliber Operations policies (hours, wage rates) Tangible costs Transportation cost of raw material Shipment cost of finished goods Energy and utility cost; labor; raw material; taxes, and so on Intangible and future costs Attitude toward union Quality of life Education expenditures by state Quality of state and local government Table 8.4
  • 39. © 2006 Prentice Hall, Inc. 8 – 39 Location Strategies Service/Retail/Professional Location Goods-Producing Location Techniques Techniques Regression models to determine importance of various factors Factor-rating method Traffic counts Demographic analysis of drawing area Purchasing power analysis of area Center-of-gravity method Geographic information systems Transportation methods Factor-rating method Locational break-even analysis Crossover charts Table 8.4
  • 40. © 2006 Prentice Hall, Inc. 8 – 40 Location Strategies Service/Retail/Professional Location Goods-Producing Location Assumptions Assumptions Location is a major determinant of revenue High customer-contact issues are critical Costs are relatively constant for a given area; therefore, the revenue function is critical Location is a major determinant of cost Most major costs can be identified explicitly for each site Low customer contact allows focus on the identifiable costs Intangible costs can be evaluated Table 8.4
  • 41. © 2006 Prentice Hall, Inc. 8 – 41 How Hotel Chains Select Sites  Location is a strategically important decision in the hospitality industry  La Quinta started with 35 independent variables and worked to refine a regression model to predict profitability  The final model had only four variables  Price of the inn  Median income levels  State population per inn  Location of nearby colleges r2 = .51 51% of the profitability is predicted by just these four variables!
  • 42. © 2006 Prentice Hall, Inc. 8 – 42 Telemarketing/Internet Industries  Require neither face-to-face contact nor movement of materials  Have very broad location options  Traditional variables are no longer relevant  Cost and availability of labor may drive location decisions
  • 43. © 2006 Prentice Hall, Inc. 8 – 43 Geographic Information Systems (GIS)  New tool to help in location analysis  Enables more complex demographic analysis  Available data bases include  Detailed census data  Detailed maps  Utilities  Geographic features  Locations of major services
  • 44. © 2006 Prentice Hall, Inc. 8 – 44 Geographic Information Systems (GIS)