Case Study TwoGroup One Presentation 2 9th July 2010

Richard HodgettBusiness and Product

Development Manager

Aleksandra Arcipowska Environmental Manager

Xiaoqian Sun Technical Manager

Guila LucertiniEconomical and Political

Manager

Ana Passuello Scientific Manager

Claudia Ceppi Urban and Regional Planning

Manager

The Team Members

Meet

Slavo• Car Manufacturer since 1956.

• Developed ABS Technology in 1980’s.

• The current business is in hybrid and electric cars.

• French company 60% France 30% rest of Europe 10% rest of the world

• Main objective of the company is to provide innovative products. (c.a. 6% R&D)

• Prototype of ABS electric car has been developed.

But there is a problem which Slavo has been asked to solve...

“To choose a location to

manufacture the new electric

car design.”

Problem:

1.Discuss the project aim.

2.Study the provided data (reports, literature & internet).

3.Formulate the decision problem.

a) Alternatives b) Criteria c) Alternative data in relation to each criteria.

4. Discuss the Decision Maker’s Preferences.

5.Choose an appropriate MCDA method for analysis.

6.Aggregation process i.e. recommend the “best” solution(s)

Decision Problem Approach

MacroeconomicModel

QualitativeModel

Quantitative model

PRF modelMarket

Number of alternatives

14 6 (2) 8 (6) 8 (6)

Country orCity as the alternative

Country City location City location City location

Number of criteria

19 (3) 26 (4) 19 (5) 49(4)

Group of criteria Political and Economic Environment, Industrial Environment and Human resources.

Human resources, Expatriates, Risk andConnectivity.

Recruiting incomesManufacturingInvestmentsComponentsDistribution

ComponentsManufacturingInbound logisticsOutbound logistics

The Data Provided..

France

Spain

Port

ugal

Russia

Poland

Ukraine

Croatia Serbia

Belarus

CzechSlovakia

HungaryRomania

Bulgaria

SelectionProcedure

1. Select Country(-ies)

2. Select City

Country Alternatives

14 Countries(from Macroeconomic Model)

Country selection

Political regulation

Risk of investment

Finance

Industrial environmen

t

Social

Labour costsLabour costs

CompetitivenessCompetitiveness

EngineersEngineers

Access to EUAccess to EU

Corporate TaxesCorporate Taxes

GDP growth in 2020

GDP growth in 2020 Quality of lifeQuality of life

Current account deficit

Current account deficit

Inbound logistics Inbound logistics

Outbound logistics

Outbound logistics

Criteria for Country Selection..

Country Criteria Representation Criteria Source Unit

Access to EU In the European Union Boolean Logic

Corporate taxes Photius Coutsoukis, Based on data published by Forbes Magazine. Tax Burden, 2009

GDP growth 2020 Macroeconomic Model Forecasted GDP per capita in 2020

Budget deficit in 2010 Budget Deficit of GDP 2010, CIA World Factbook 2010 Percentage

Labour costs Macroeconomic Model Overtime Labour Cost / Average Labour Cost

Inbound logistic Scale of 1-5, According to distance.

1= Close to Supplier,5 = Distant from Supplier.

Outbound logistic Scale of 1-5,

According to the countries market. 1= Most important market, 5= Least important market.

Competitiveness World Economic Forum Global Competitiveness Index 2008-2009

Engineers Education at a Glance (OECD INDICATORS), 2009

Based upon adding the mean scores of scientific and mathematical results from students in said country.

Quality of life Quality of Life Index (International Living), 2010

Based upon values calculated for Cost of Living, Leisure & Culture, Economy, Risk & Safety, Environment, Freedom, Health, Infrastructure and Climate per

country.

City selection

Human resources

Social

Infrastructure

Mediaavailability

Mediaavailability

Workforce availabilityWorkforce availability

Environment

Site characteristicsSite characteristicsSecuritySecurity

Criteria for City Selection..

Method Selection

[Sen and Yang, 1998]

TOPSIS Weight Selections

Results

Eq

ual

Eco

nom

ic

Soci

al an

d P

olit

ical

KeyPoland

PLCzech Republic CZHungary

HU Slovakia

SK Russia

RU Ukraine

UA Belarus

BY Serbia

SB Croatia

HR Bulgaria

BR Romania

RO Spain

ES Portugal

PT France

F

Conclusions· The decision problem has been redefined.· Two step procedure of the location selection have been proposed.· Results shows Hungary as the best country location (for 3 independent preference models).· The other possible locations are: Czech Republic, Bulgaria and Portugal.

Future Work· The data for city location need to be collected.· The specific site location needs to be decided, taking into consideration the city criteria mentioned earlier. (e.g. Human resources, Infrastructure and Environment).

Everything should be made as simple as possible, but not more so.Albert Einstein

It is a common credo that in predicting the future, one should use as muchinformation as possible and feed it into the most sophisticated computer.

A complex problem demands a complex solution, so we are told.In fact, in unpredictable environments, the opposite is true.

Gerd Gigerenzer

A new scientific truth does not triumph by convincing it opponents and makingthem see the light, but rather because its opponents eventually die, and a

new generation grows up that is familiar with it.Max Planck

Informed decision-making comes from a long tradition of guessing and then blaming others for inadequate results.

Scott Adams

A good decision is based on knowledge and not on numbers. Plato

There is no such uncertainty as a sure thing.Robert Burns

Men are only as good as their technical development allows them to be. George Orwell

A picture is worth a thousand words. An interface is worth a thousand pictures. Ben Shneiderman

Poland Czech Republic Hungary Slovakia Russia Ukraine Belarus Serbia Croatia Bulgaria Romania Spain Portugal France

PL CZ HU SK RU UA BY SB HR BR RO ES PT F Source UnitP.1 Access to EU max 1 1 1 1 0 0 0 0 0 1 1 1 1 1 - Boolean logic

P.2 Corporate taxes min 19 15 19 19 20 25 18 18 18 10 16 30 26.5 34.4 from data published by Forbes Magazine. Tax Burden, 2009

R.1 GDP growth 2020 max 3.07 4.01 3.35 3.86 1.82 1.06 1.66 1.00 3.21 1.83 1.14 5.00 5.00 5.00 Macroeconomic Forecasted GDP per capita in 2020

R.2 Budget deficit in 2010 min 2.31 4.71 4.07 5.24 8.07 6.93 1.53 0.47 3.76 1.32 6.68 10.51 6.78 8.20Budget deficit % of GDP

2010, CIA World fact book 2010

%

F.1 Labour costs min 4.64 3.73 1.91 4.64 1.00 1.00 1.00 2.00 5.00 2.82 2.82 4.64 1.00 4.64 macroeconomic Overtime labor cost/ average labor cost ratio

F.2 Inbound logistic min 3 2 3 3 5 4 4 3 2 4 4 3 4 1 - 1= close, 5 = far

F.3 Outbound logistic min 4 5 5 5 5 5 5 5 5 5 5 2 4 1 -according to the countries market, 1=

most important market, 5= less important market

I.1 Competitiveness max 4.28 4.62 4.22 4.40 4.31 4.09 2.80 3.90 4.22 4.03 4.10 4.72 4.47 5.22 World Economic Forum Global Competitiveness Index 2008-2009

I.2 Engineers max 847 833 949 940 991 960 871 782 795 995 1006 980 986 996 Education at a Glance (OECD INDICATORS), 2009

based upon adding the mean scores of scientific and mathematical results

from students in said country.

S.1 Quality of life max 69 65 76 73 82 70 67 54 62 54 71 69 74 73 Quality of Life Index (International Living), 2010

based upon values calculated for Cost of Living, Leisure & Culture, Economy,

Environment, Freedom, Health, Infrastructure, Risk & Safety and

Climate.

The Data for Country Selection..

Analytic Hierarchy Process(AHP)

Multiple Attribute UtilityTheory(MAUT)

Simple AdditiveWeighting

(SAW)

Technique for Order Preference by Similarity

to Ideal Solution (TOPSIS)

Advantages

Reduces the complex problem to a series of

one-to-one comparisons.

Provides an alternative way for representing

DM’s preference information.

Simplistic. Easy to Use and understand.

Produces a clear preference order of

competing alternatives.

Disadvantages

Does not consider correlated preferences

between attributes.

Requires each alternative to be

compared with all others, this can cause

an inconsistency problem.

Suffers from rank reversal (if we decide to add more data to

the model).

It’s difficult to obtain an accurate utility function

for each attribute.

The utility functions of all attributes are

independent to each other.

Sensitive to the weights of attributes.

The attribute values must be both numerical and comparable.

Does not consider the correlation between

attributes.

Sensitive to the weights.

Assumes each attribute’s utility as

monotonic.

Sensitive to weights.

Method Selection..

TOPSIS Methodology

Step 1: Create normalized decision matrix.

Step 2: Formulate weighted decision matrix.

Step 3: Define the ideal point and the negativeideal point.

Step 4: Calculate the distance of an alternativeto the ideal point

And the distance of the design from thenegative ideal point

Step 5: Calculate the relative closeness of each

design to the ideal point. Step 6: Rank the alternatives based on the

magnitude of closeness .

(Technique for Order Preference by Similarity to Ideal Solution)

TOPSIS based on Euclidean distances to the ideal and negative-ideal solutions [Hwang, 1981]