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Lehrstuhl für Industrie, Energie und Umwelt
Universität Wien Fakultät für Wirtschaftswissenschaften Lehrstuhl für Industrie, Energie und Umwelt Brünner Straße 72, 1210 Wien
International Industrial Management I -
Location Decisions I
| Prof. Franz Wirl |
Email: [email protected] Homepage: http://bwl.univie.ac.at/ieu
Int. Ind. Management I Chair Industry, Energy & Environment
| Prof. Wirl WS 2015/16 Page 2
Overview | Location Decisions
Choice of locations Introduction A class of locational choice problems Factors for locations Methods
Check lists Benefit analysis (simple, additive) Location break-even analysis Transportation method Steiner-Weber Model Location-alloction Model of Cooper and extensions Hotelling Model
Choice of locations with the firm The basic problem CRAFT Layouts
Int. Ind. Management I Chair Industry, Energy & Environment
| Prof. Wirl WS 2015/16 Page 3
Location Decisions - Objective
Choose the location that maximizes
the firm’s benefit
There are only three important things concerning locations: 1) Location, 2) Location, 3) Location.
Int. Ind. Management I Chair Industry, Energy & Environment
| Prof. Wirl WS 2015/16 Page 4
Location Decisions
Importance: Location decisions do not only result in real estate and investment costs but influence in particular fixed and variable costs. Transportation costs
rentals
Wages
Taxes, etc.
Links to the environment (universities, clusters, etc.)
Int. Ind. Management I Chair Industry, Energy & Environment
| Prof. Wirl WS 2015/16 Page 5
Choosing the United States by Michael E. Porter and Jan W. Rivkin, HBR, March 2012, 81-93
In deciding whether to move existing business activities out of the United States, our HBS alumni respondents reported
certain factors made the difference. Leading reasons for moving out of the U.S. Lower wage rates (in the destination country) 70% Proximity to customers 34% Better access to skilled labor 31% Higher productivity of labor 30% Faster-growing market 29% Lower tax rates 25% More-generous incentives from local authorities 24% Fewer or less expensive regulations 22% Proximity to suppliers 19% Proximity to other company operations 16% Leading reasons for not moving Proximity to U.S. customers 32% Less corruption 30% Better access to skilled labor 29% Greater safety for people and property 27% Stronger intellectual property protection 24% Proximity to home market 22% Similar language and/or culture 22% Better transportation infrastructure 19% Proximity to other company operations 18%
Int. Ind. Management I Chair Industry, Energy & Environment
| Prof. Wirl WS 2015/16 Page 6
Example: Automobile Industry
Source: Dyer, J.H.,Dedicated Assets: Japan‘s Manufacturing Edge , Harvard Business Review, Nov.-Dec., 1994, S.174ff.
Int. Ind. Management I Chair Industry, Energy & Environment
| Prof. Wirl WS 2015/16 Page 7
Example: Automobile Industry cont.
Source: Dyer, J.H., Dedicated Assets: Japan‘s Manufacturing Edge , Harvard Business Review, Nov.-Dec., 1994, S.174ff.
Int. Ind. Management I Chair Industry, Energy & Environment
| Prof. Wirl WS 2015/16 Page 8
Example: Automobile industry cont. Comparing locations of production and organizational units of the
automobile industry in Japan and the US (Dyer, 1994) finds and argues the following:
The huge success of the Japanese car industry is to a large extent due to the close relations with its suppliers and in particular the geographical vicinity.
There exist large differences concerning the average distance between locations of Japanese and American car manufacturers. In particular, the entire ring of Toyota and its suppliers fits between two GM locations.
Inventory as a share of turnover is much larger at US car producers which implies more bound capital. These distances in turn make it hard to implement Just-in-Time Management (see later), which further increases inventory costs.
Int. Ind. Management I Chair Industry, Energy & Environment
| Prof. Wirl WS 2015/16 Page 9
Example: Automobile industry cont.
Closeness implies much better contacts between relevant people and organizations (including suppliers). It is a grave misunderstanding that personal contacts become redundant once an industry can actually choose its supply in aglobally integrated world by a mouse click; remember this for the following discussion about clusters. Biology/Evolution!!!
If GM had a similar ratio between inventory and sales it would save US$ 6 billions which amounts to annula cost saving of the order between US$ 400 – 500 Millions depending on costs of capital ranging between 6% to 8%.
Int. Ind. Management I Chair Industry, Energy & Environment
| Prof. Wirl WS 2015/16 Page 10
Introductory Example I
Table: Example of a location decision l
Feasible locations
Distance from procurement center
Transport costs (in 1000 MU)
Distance to center of demand
Transport costs (in 1000 MU)
Sums
Aachen
150
(150*1500*1)= 225
650
(650*1000*1,2)= 780
1005= 4th rank
Braunschweig 270 405 625 750 1155= 6th rank
Dortmund 10 15 650 780 795= 1st rank Erfurt 420 630 380 456 1086= 5th rank
Munich 650 975 10 12 987= 3rd rank
Nürnberg 480 720 170 204 904= 2nd rank
Assumptions: Procurement centered around Dortmund. Volume = 1.500 t and transport cost are 1 MU per t and km. Demand in Munich, Volume = 1000 t, transport cost are 1.2 MU per t and km.
Int. Ind. Management I Chair Industry, Energy & Environment
| Prof. Wirl WS 2015/16 Page 11
Interdependences (Source Lüder, S.31)
Produktionsprogramm
Produktpreise
Transportwege Transportmengen
Transportmengen
Innerbetriebliche Standorte*
Löhne, Steuern usw.
Investitionsprogramm
Investitionsausgaben je Projekt
Innentransportkosten
Kapitaleinsatz
Sonstige aufwandsgleiche Kosten
+ (Aufwand≠Kosten)
Externe Transportkosten
Aufwand
Ertrag
Profitability of a firm for a given configuration of locations
*: Optimierungsproblem
* Optimization problem
Int. Ind. Management I Chair Industry, Energy & Environment
| Prof. Wirl WS 2015/16 Page 12
Assumptions (given): A set of locations:
A set of organisational units:
Location of the organisational units:
Objective: Find a mapping that assigns to each unit bi a location
from the set S that maximizes a given objective function:
Mathematical formulation of Location Decisions I
{ }njsS j ,,1; ==
{ }mibB i ,,1; ==
( ) Ssbs ji ∈=
( ) SbsbSB
ii ⊂→
→∑:
Int. Ind. Management I Chair Industry, Energy & Environment
| Prof. Wirl WS 2015/16 Page 13
Mathematical formulation of Location Decisions II
Further assumptions: O is the set of given locations that are connected to locations bi e.g. customers:
The sets O, S and B are independent (in practice however there are many
interdependencies and feedbacks). Further constraints such as those on capacity.
Objective: Maximize/Minimize
e.g. the locations of the organizational units are chosen in order to minimize the transport costs.
e.g. the (incremental) benefit from the choice of a particular location or locations should be maximized.
{ }rpoO p ,,1, ==
( ) ( ) ( )[ ]mbsbsbsfZ ,,, 21 =
Int. Ind. Management I Chair Industry, Energy & Environment
| Prof. Wirl WS 2015/16 Page 14
Examples of Constraints: Organizational units that must be close to the market
Public Police, ambulance, fire brigade post
Retail and Services Fast food, gas stations, super markets Pharmacies, shopping malls.
Services M.D., lawyers, barbers Banks (?), mechanics, hotels
Int. Ind. Management I Chair Industry, Energy & Environment
| Prof. Wirl WS 2015/16 Page 15
Evaluation of locations
Methods
Check lists
(Cost-) Benefit analysis
Location Break-Even Analysis
Transportation Method
Steiner-Weber Model
Location-Alloction Model von Cooper
Hotelling
Etc.
Int. Ind. Management I Chair Industry, Energy & Environment
| Prof. Wirl WS 2015/16 Page 16
Factors crucial for locations
Market size
Expected profits
Openess of markets
Stability
bureaucracy
Labour (quality and work ethics)
Infrastructure
Technological know how
Labor costs
Resources, primary inputs
Availability of qualified labor
Reserach institutes
Quality of life
Venture-Capital
Costs
Technology
IT-Infrastructure
Bureaucracy
Suppliers & partners
Subsidies
Arthur Anderson Deloitte Touche
Int. Ind. Management I Chair Industry, Energy & Environment
| Prof. Wirl WS 2015/16 Page 17
(Cost-) Benefit Analysis - additive
Four steps: 1. Scaling: Evaluation via scale (say 1 – 10) the benefits of location with respect
to a particular factor which allows to rank and evaluate also qualitative factors. 2. Weighting: Assign weights {gi} to each individual factor entering the analysis
and to differentiate between important and less important ones. 3. Aggregate: Multiply points the scale in (1) with the weights in (2) and add up
which gives the measure of benefit associated with a particular location: N(sj) = n1j*g1 + n2j*g2 + .....
4. Choose the location with the highest benefit = highest value of N.
Int. Ind. Management I Chair Industry, Energy & Environment
| Prof. Wirl WS 2015/16 Page 18
A simple example Labor Sales Subsidies
Locations s1 7 2 1
s2 5 1 9
s3 10 4 6
s4 5 7 8
Weights 0.3 0.5 0.2
N(s1) = 7*0,3 + 2*0,5 + 1*0,2 = 3,3 N(s2) = 5*0,3 + 1*0,5 + 9*0,2 = 3,8 N(s3) = 10*0,3 + 4*0,5 + 6*0,2 = 6,2 N(s4) = 5*0,3 + 7*0,5 + 8*0,2 = 6,6 Therefore, location 4 should be chosen.
Extension: Multi-criteria optimization (or decision making)
Int. Ind. Management I Chair Industry, Energy & Environment
| Prof. Wirl WS 2015/16 Page 19
Check lists
Precise evaluation of the benefits associated with each factor. Similarly to the the above benefits analysis – hierarchical
Int. Ind. Management I Chair Industry, Energy & Environment
| Prof. Wirl WS 2015/16 Page 20
Benefit analysis
Weights allow to mitigate for outliers Ranking without weights:
C – B – A - D Ranking with weights:
A – C – D – B
Int. Ind. Management I Chair Industry, Energy & Environment
| Prof. Wirl WS 2015/16 Page 21
Location Break-Even Analysis I
Comparison of the costs at different locations depending on the rate of utilization.
Example Production of a new Volkswagen model. 3 potential locations with their respective costs Assume a sales price Profit:
Standort Fixe Kosten Variable Kosten Verkaufspreis E(Menge)Poznan € 3.000.000 € 7.500,00 € 12.000,00 2.000Pamplona € 6.000.000 € 4.500,00Wolfsburg € 11.000.000 € 2.500,00 Standort Gesamtkosten* Gewinn*
Poznan € 18.000.000 € 6.000.000Pamplona € 15.000.000 € 9.000.000Wolfsburg € 16.000.000 € 8.000.000
* bei einer Menge von 2.000 Stk.
Int. Ind. Management I Chair Industry, Energy & Environment
| Prof. Wirl WS 2015/16 Page 22
Location Break-Even Analysis II
1. Given a fixed quantity of 2000 pieces Pamplona yields the highest profits.
2. Since the assumption of 2000 pieces depends on a marketing study it is unreliable. Therefore, the management wants to know whether Pamplona remains the most profitable with less or higher production.
Location Break-Even Analysis This procedure calculates the intersections of the cost curves
associated with the different locations depending on the rate of production.
This yields capacity bounds where which location is efficient as well as the minimal costs over all locations contingent on production.
Int. Ind. Management I Chair Industry, Energy & Environment
| Prof. Wirl WS 2015/16 Page 23
Location Break-Even Analysis III
PoznanPamplona
Wolfsburg
1.000.000
4.000.000
7.000.000
10.000.000
13.000.000
16.000.000
19.000.000
22.000.000
0 500 1000 1500 2000 2500 3000 3500
Menge (Stk.)
Ges
amtk
oste
n
Poznan
Pamplona
Wolfsburg
Depending on production volumes different locations turn out to be the most profitable ones:
Int. Ind. Management I Chair Industry, Energy & Environment
| Prof. Wirl WS 2015/16 Page 24
1) Countries
2) Regions
3) Final location
Sequential (hierarchical) location decisions
Int. Ind. Management I Chair Industry, Energy & Environment
| Prof. Wirl WS 2015/16 Page 25
Match Product & Country
Braun Household Appliances
Firestone Tires Godiva Chocolate Haagen-Dazs Ice Cream Jaguar Autos MGM Movies Lamborghini Autos Alpo Petfoods
1. Great Britain 2. Germany 3. Japan 4. United States 5. Switzerland 6. India 7. Italy 8. Denmark
Int. Ind. Management I Chair Industry, Energy & Environment
| Prof. Wirl WS 2015/16 Page 26
Match Product & Country
Braun Household Appliances
Firestone Tires Godiva Chocolate Haagen-Dazs Ice Cream Jaguar Autos MGM Movies Lamborghini Autos Alpo Petfoods
1. Great Britain 2. Germany 3. Japan 4. United States 5. Switzerland 6. India
Int. Ind. Management I Chair Industry, Energy & Environment
| Prof. Wirl WS 2015/16 Page 27
A few international comparisons
Productivity Growth Countries Cities Economic liberty Corruption
Int. Ind. Management I Chair Industry, Energy & Environment
| Prof. Wirl WS 2015/16 Page 28
Christian Thimann, The Microeconomic Dimensions of the Eurozone Crisis and Why European Politics Cannot Solve Them Journal of Economic Perspectives—Volume 29, Number 3—Summer 2015—Pages 141–16
Int. Ind. Management I Chair Industry, Energy & Environment
| Prof. Wirl WS 2015/16 Page 29
Int. Ind. Management I Chair Industry, Energy & Environment
| Prof. Wirl WS 2015/16 Page 30
Growth Competitiveness Index – 2006-2007 – Top 20 World Economic Forum
Int. Ind. Management I Chair Industry, Energy & Environment
| Prof. Wirl WS 2015/16 Page 31
Growth Competitiveness Index – 2006-2007, Rank >100
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| Prof. Wirl WS 2015/16 Page 32
Business Competitiveness Index – 2006-2007
Int. Ind. Management I Chair Industry, Energy & Environment
| Prof. Wirl WS 2015/16 Page 33
Global Competitiveness Index 2009
Int. Ind. Management I Chair Industry, Energy & Environment
| Prof. Wirl WS 2015/16 Page 34
Business Competitiveness
Int. Ind. Management I Chair Industry, Energy & Environment
| Prof. Wirl WS 2015/16 Page 35
International Productivity by Sectors
Martin Neil Baily und Robert M. Solow, International Productivity Comparisons Built from the Firm Level, Journal of Economic Perspectives, 15/3, 151-172, 2001.
Int. Ind. Management I Chair Industry, Energy & Environment
| Prof. Wirl WS 2015/16 Page 36
Labor Productivity and Wages
Int. Ind. Management I Chair Industry, Energy & Environment
| Prof. Wirl WS 2015/16 Page 37
International labor costs in automobile industry €/h
42.2935.52
24.68 28.9436.61 30.71 34.51
21.9912.06
31.46 31.6623.95
€ 0.00€ 10.00€ 20.00€ 30.00€ 40.00€ 50.00
Germ
any
Fran
ce Italy
The N
ether
lands
Belgium UK
Sweden
Spain
Portu
gal
Austria
U.S.A
Japa
n
Int. Ind. Management I Chair Industry, Energy & Environment
| Prof. Wirl WS 2015/16 Page 38
Corruption
5 Best: Denmark New
Zealand Sweden Singapur Finland
5 Worst: Afghanistan Haiti Iraq Myanmar Somalia
Corruption index 2008
Denmark / New Zealand/ Sweden 9,3 Singapore 9,2 Finland/Switzerland 9,0 Iceland/Netherlands 8,9 Australia/Canada 8,7 Luxembourg 8,3 Austria/Hong Kong 8,1 Germany/Norway 7,9 Ireland/UK 7,7 Belgium/Japan/US 7,3 Afghanistan 1,5 Somalia 1,0 10 = No corruption
Int. Ind. Management I Chair Industry, Energy & Environment
| Prof. Wirl WS 2015/16 Page 39
Economic Freedom I
2010
Int. Ind. Management I Chair Industry, Energy & Environment
| Prof. Wirl WS 2015/16 Page 40
Economic Freedom II
Int. Ind. Management I Chair Industry, Energy & Environment
| Prof. Wirl WS 2015/16 Page 41
Economic Freedom - graphical HONG KONG keeps its top position in the Economic Freedom Index compiled by the Fraser Institute, a Canadian think-tank. The index ranks the policies of 141 countries according to how much they encourage free trade, both internally and with other territories. Countries with fewer taxes, strong property rights, low regulation and sound money score best. Britain and America tie with Canada for fifth place in the list. Germany is ranked 18th—on a par with El Salvador but above Japan. Most of the low-ranking countries are African, except Myanmar and Venezuela, which are both in the bottom ten.
Int. Ind. Management I Chair Industry, Energy & Environment
| Prof. Wirl WS 2015/16 Page 42
Ranking of Cities
Source: European Cities Monitor 2006: Citiy 2006 2005 1990 Index2006
London 1 1 1 0,91
París 2 2 2 0,59
Frankfurt 3 3 3 0,36
Barcelona 4 5 11 0,27
Brussels 5 4 4 0,24
Amsterdam 6 6 5 0,23
Madrid 7 7 17 0,20
Berlín 8 8 15 0,18
Munich 9 9 12 0,18
Zurich 10 10 7 0,16
Int. Ind. Management I Chair Industry, Energy & Environment
| Prof. Wirl WS 2015/16 Page 43
Another ranking of cities
London and Paris maintain their position as Europe's two top cities to locate a business Warsaw can expect the biggest influx of international companies over the next five years.
Barcelona is also the city perceived as doing the most in Europe to improve itself as a business location, followed by Prague and Madrid
Int. Ind. Management I Chair Industry, Energy & Environment
| Prof. Wirl WS 2015/16 Page 44
Hardship Rating
Int. Ind. Management I Chair Industry, Energy & Environment
| Prof. Wirl WS 2015/16 Page 45
Austria (WIFO)
Advantages Disadvantages
Part of the common market Bureaucracy
Active in Eastern Europe Duration until receiving operating permits
Availability of high quality labor Costs of telecomm (not any more!)
Availability of highly qualified labor High costs for unskilled labor
Consensus seeking society Environmental regulations
Rule of law Lack of venture capital
Environmental quality Little competition in energy markets
Cultural and leisure activities Lack of reforms (and willingness to reform)
Public safety Public administration
Political stability (?) Energy costs
Int. Ind. Management I Chair Industry, Energy & Environment
| Prof. Wirl WS 2015/16 Page 46
Austria (US-Investor Confidence Study)
Advatantages Disadvatantages Knowledge of foreign languages Tax deductions of investments
Access to Eastern European markets Real estate prices
Sales in Austria Cost of living
Qualifications and effort (of labor) Operating permit (length)
Transport Labor permits for Non-EU residents
Culture and leisure activities Opening hours
Political stability Income taxes
Social peace Labor laws
Costs of electricity
Wages, payroll taxes and other ancillary labor costs
Int. Ind. Management I Chair Industry, Energy & Environment
| Prof. Wirl WS 2015/16 Page 47
Eastern Europe vs Asia •As in the previous five years, economies in eastern Europe and Central Asia have consistently seen the fastest pace of positive reform. •On average, it takes 21 days to register a business in eastern Europe, which is 27 days faster than in East Asia. Setting up a company in Indonesia costs 77.9% of the average annual income per person; in Georgia it costs 4%—though there is the small matter of political risk to factor in. Firing a worker costs an average of 53 weeks’ salary in East Asia, compared with 27 in eastern Europe. All this cutting of red tape has brought results: Poland now has as many registered businesses relative to its population as Hong Kong does. •Eastern Europe’s rapid progress due to the accession requirements imposed by the European Union (EU), e.g., the EU requires new members to create a “one-stop shop”. Before Macedonia became a candidate for EU membership in 2005, it took 48 days to start a business there. After three years of reforms, it now takes nine days. •East Asian countries still have the edge in some respects: it is easier to move goods across their borders, for example. Businesses in East Asia also face lower taxes. Taxes on profits in eastern Europe are among the lowest in the world, typically around 10%, but labour taxes and compulsory pension contributions increase the overall tax burden on business. •Of course, a few East Asian economies are still miles ahead of eastern Europe. Singapore 1st, Hong Kong 4th but Georgia, Estonia, Lithuania and Latvia in the top 30, Russia = 120th and Azerbaijan was the top reformer.
Int. Ind. Management I Chair Industry, Energy & Environment
| Prof. Wirl WS 2015/16 Page 48
Countries
Regions
Specific location
1. Political risks, regulation, incentives. 2. Cultural and economical. 3. Location relative to markets (sales and procurement). 4. Labor: availability, productivity, costs, behavior. 5. Availability of suppliers, communication, energy. 6. Exchange rates and their risks. 1. Specifics views and demands of the firm. 2. Atractiveness of region (culture, climate, taxes, etc.) 3. Labor: availability, productivity, costs, unions. 4. Availability and costs of materials. 5. Environmental regulation at federal and city level. 6. Incentives (by regions, cities). 7. Availability and distance to primary inputs. 8. Costs for real estates and construction. 1. Location specific costs contingent on the size of the unit. 2. Air, rail, road and water transport networks. 3. Zoning, in particular restrictions. 4. Availability and distance to suppliers and service providers. 5. Environment and environmental constraints.
Factors crucial for location decisions
Int. Ind. Management I Chair Industry, Energy & Environment
| Prof. Wirl WS 2015/16 Page 49
Case Study | BMW Spartanburg, USA I
Location decision of BMW Production of BMW Z3
in the USA, mid 1990ies. Expansion to include
BMW X5 und Z4.
Int. Ind. Management I Chair Industry, Energy & Environment
| Prof. Wirl WS 2015/16 Page 50
Case Study | BMW Spartanburg, USA II
3) Final decision for Spartanburg
2) Choice of South Carolina
1) Choice of the US
Int. Ind. Management I Chair Industry, Energy & Environment
| Prof. Wirl WS 2015/16 Page 51
Case Study | BMW Spartanburg, USA III Factors decisive for choosing USA
Market: Market size: USA is the world‘s largest market for luxury cars Growing versus declining markets: US growing market due to baby
boomers. Labor:
Lower labor and production costs: (US: US$ 17/h, DEU: US$ 27/h)
High labor productivity (Holidays: US 11, Germany: 31)
Additionally: Low transport costs (US$ 2.500,- less per vehicle) New facilities improve productivity and thus lower the costs per car
(around US$ 2.000-3.000.-) Insurance (‚hedging‘) against high Dollar-Euro exchange rates.
Int. Ind. Management I Chair Industry, Energy & Environment
| Prof. Wirl WS 2015/16 Page 52
Case Study | BMW Spartanburg, USA IV Factor in favor of South Carolina
Labor: Low wages in South Carolina
Public subsidies: US$ 135 Mio. in terms of tax deductions.
Free trade zone: Duties neither on imported goods nor on car
exports. Infrastructure:
Access to freeway and via the freeway to the airport Charlotte from which Lufthansa operates direct flights to Munich. Port Charleston serves for exports and the imports of engines and gearboxes from Europe
8585
2626
85
Int. Ind. Management I Chair Industry, Energy & Environment
| Prof. Wirl WS 2015/16 Page 53
Labor Productivity
Keyword: level of labor costs
Cheaper employees => higher profit?
However, cheap labor is NOT everything – countries with cheap labor are often characterized by low labor productity that can erode partially or totally the advantage in terms of labor cost. Compare: Gregory Clark, Farewell to Alms, textile production in England and colonial India. South vs North Italy (Alfa Romeo Sud, see below).
‚Skills‘ of workers, good infrastructure, and technology are often more important to many industries than plain labor costs.
Int. Ind. Management I Chair Industry, Energy & Environment
| Prof. Wirl WS 2015/16 Page 54
Case Study | Labor productivity
Quality Coils Inc., CT, USA Coil production for electrical equipments 2 potential locations:
Expanding a the present location in Connecticut New factory in Juarez (one of the fastest growing cities in Mexiko along the US border due
to the Maquiladoras) Comparison based on labor costs:
Historical Example: Alfa Romeo - Alfasud
Wage/d Output/worker
Labor cost/ piece
Connecticut Plant US$ 70.- 60 units US$ 1.17/unit
Juarez Plant US$ 25.- 20 units US$ 1.25/unit
unit per costday) per (units tyProductivi
day per Cost LabortyProductivi Labor ==
Int. Ind. Management I Chair Industry, Energy & Environment
| Prof. Wirl WS 2015/16 Page 55
Cos
t Red
uctio
n C
onsi
dera
tions
High
Low High Low
Local Responsiveness Considerations (Quick Response and/or Differentiation)
Standardized product Economies of scale Cross-cultural learning Examples Texas Instruments Caterpillar Otis Elevator
Global Strategy Transnational Strategy Move material, people, ideas
across national boundaries Economies of scale Cross-cultural learning Examples Coca-Cola Nestlé
International Strategy
Import/export or license existing product
Examples U.S. Steel Harley Davidson
Multidomestic Strategy Use existing
domestic model globally Franchise, joint ventures,
subsidiaries Examples Heinz The Body Shop McDonald’s Hard Rock Cafe
Four International Operations Strategies
Int. Ind. Management I Chair Industry, Energy & Environment
| Prof. Wirl WS 2015/16 Page 56
Steiner-Weber Model I
Geometric, continuous Model based on the works of the German geometricians and regional scientists: Launhardt (1882), Steiner-Weber (1909) & Lösch, Christaller (1940er)
Model assumptions: The set location where to delivery to, is given. The set of potential locations (S) is the entire plane (infinitely many, actually
uncountable many). The decision involves only a single location s. Transport costs are proportional to the Euclidean distance.
Problem – minimize transport costs: Find the optimal location determined by the coordinates x*, y*
that minimizes from the chosen location the transport costs to the sinks Op with the coordinates xp, yp (p=1,…r).
{ }rpoO p ,1, ==
Ss ∈*
Int. Ind. Management I Chair Industry, Energy & Environment
| Prof. Wirl WS 2015/16 Page 57
Steiner-Weber Modell II
The objective function depends on: Volume (delivered or for delivery) from the given location p, ap, Normalized transport cost (e.g. EUR/ton/km) kt, Distance measures in terms of direct connection (Euclidean), dp.
Objective
∑∑==
==r
pppt
r
ppTT dakKK
11**
( ) ( )22ppp yyxxd −+−=
dp
xp
x
yp y
(xp, yp)
(x, y)
Int. Ind. Management I Chair Industry, Energy & Environment
| Prof. Wirl WS 2015/16 Page 58
Steiner-Weber Modell III
Objective min:
Differentiation with respect to x and y and equating to zero yields the first order optimality condition.
Result: two nonlinear equations that require numerical means (e.g. Newton‘s iteration scheme)
Fortunately, Excel does it! (via the Solver).
( ) ( )∑=
−+−=r
pppptTyx
yyxxakK1
22
,*min
( ) ( )
( ) ( )∑
∑
=
=
=−+−
−=
∂∂
=−+−
−=
∂∂
r
p pp
ppt
T
r
p pp
ppt
T
yyxx
yyak
yK
yyxx
xxak
xK
1
!
22
1
!
22
0)(
0)(
Int. Ind. Management I Chair Industry, Energy & Environment
| Prof. Wirl WS 2015/16 Page 59
Steiner-Weber Modell V - extensions
Nonlinear transport costs but distance depending, e.g., quadratic, or including set up costs for each connection:
It can make sense to link the transport costs to particular sinks p to account for differences in deliveries (e.g., scrap versus sensitive final prducts): A further extension is to allow for the deliveries of multiple goods from the source (i.e., the sought location) s to sinks p. Accounting for the last two recommendations leads to the following cost minimization:
pqkqq
qpT sink toproduct ofcost transport products,,1
:where
=
( ) ( ) ∑∑ ∑∑== ==
−+−==q
qqpqpT
q
q
r
ppppqpqpT
r
pTyx
akyyxxdakK11 1
22
1,***min
( )ppTpT dkk =
( )pkk tt =