oligopolistic competition

Oligopolistic Competition

between Strategic Alliances

Andreas Größler

Oligopolistic Competition between Strategic Alliances

Andre

as G

röß

ler,

2010

Some thoughts about results and process of a

consulting project using system dynamics

• Focus is on process

– Work in progress

– Confidentiality

• Model complexity

• Indexed variables


Andre

as G

röß

ler,

2010

Six honest men...

I Keep six honest serving-men:

(They taught me all I knew)

Their names are What and Where and When

And How and Why and Who.

Rudyard Kipling, 1902


Andre

as G

röß

ler,

2010

Men 1 to 6

1. What: a case study in a major industry within the

transportation sector

2. Where: actual client (alliance headquarter) is located in

Germany but alliance is international

3. When: project started beginning 2010, still going on

4. How: a system dynamics analysis, of course

5. Why: it is a very interesting topic, methodological and

content wise (OK, there is money here as well)

6. Who: me as a member of Radboud University consulting

a group of consultants that consult the actual client (i.e.

the alliance)


Andre

as G

röß

ler,

2010

So, why is it so interesting content wise?

Cf. Gomes-Casseres, 2006

Structure of the market

Structure

of players

in the market

One player Few players Many players

Single

firms

Constellation

of firms

Traditional

Monopoly

Traditional

Oligopoly

Traditional

Perfect

Competition

Industry

Cartel

Collective

Competition


Andre

as G

röß

ler,

2010

So, why is it so interesting methodologically?

• Dynamics involved in situation

– Classical strategy tools are static

– Classical economic analysis has an equilibrium perspective

• Increasing complexity of model

– Face validity

– Parameterization

– Interpretability

• Using more than two (or three) actors in an competitive

analysis

– Game theory

– Subscripts in Vensim and their visual representation

– Structural rigidity in system dynamics?


Andre

as G

röß

ler,

2010

Standing on the shoulders of giants (i)

Cf. Warren, 2008


Andre

as G

röß

ler,

2010

Standing on the shoulders of giants (ii)

Cf. Bossel, 2004

PopulationA

PopulationBgrowth of A loss of A growth of Bloss of B

competition

GROWTHRATE A

GROWTHRATE B

COMPETITIONEFFECT ON A

COMPETITIONEFFECT ON B

CARRYINGCAPACITY OF A

CARRYINGCAPACITY OF B

STARTINGVALUE POP A

STARTINGVALUE POP B


Andre

as G

röß

ler,

2010

Finally: the model...

Market

SuppliersDemand

88 variables and 1 subscript (defining 5 classes)


Andre

as G

röß

ler,

2010

The demand view

Total ActualDemand Airtrafficdemand change

endogeneouschanges to demand

exogeneouschanges to demand

demand changesdue to population

demand changesdue to GDP

toMarket

view

fromMarket

view

demand changesdue to travel affinity

<not-satisfieddemand effect

industry>

IniDemand

effect of price ondemand

fromSupplier view

max/min effectprice

price effectindustry

<AvgPriceIndustry><AvgIniPriceIndustry>

demand changesdue to seasonality

demand changes dueto exogenous shocks


Andre

as G

röß

ler,

2010

The market view

not-satisfieddemand effect

industry

<Total ActualDemand Airtraffic>

fromDemand view

attractiveness

attribute price

attractiveness

attribute productattractiveness

attribute network

Realised

Demandrealising

demand

fraction unrealiseddemand

<Ticket Price><capacityoffered>

fromSupplier view

fromSupplier view

toSupplier view

IniRealisedDemand

toDemand view

attractiveness

competitor

effect of unrealiseddemand

<capacityoffered>

fromSupplier view

market share

competitor

preference

price

preference

product preference

network


Andre

as G

röß

ler,

2010

The suppliers view

AC

operationalAC on order

ordering AC supplying AC retiring AC

production

delayAC lifetime

seats per AC

legs per AC per

month

seat capacity

capacity

offered

toMarket

view

costs per leg

fixed costs

fromMarket

view

capacity

utilization

fromMarket

view

revenues

generated

profit

Ticket Priceprice change

price adjustment

elasticity

variable costs

costs per pax

minimum ticket

price

toMarket

view

IniTicketPrice

IniACOnOrder IniACOperational

<realising

demand>

<realising

demand>

costs per AC

legs per month

<costs per

pax>

growth

percentage

target revenue

per leg

profit margin

revenue per

leg

AvgPriceIndustry

AvgIniPriceIndustry

toDemand view


Andre

as G

röß

ler,

2010

... and a validation run

120 AC

550 Dollar/Pax

3 M Pax/month

110 AC

525 Dollar/Pax

2 M Pax/month

100 AC

500 Dollar/Pax

1 M Pax/month

33

33

33

33 3 3 3 3 3

2 2 2 22

22

22

2

2

22

1111

11

1

1

1

1

1

1

1

0 12 24 36 48 60 72 84 96 108 120

Time (month)

AC operational: validationRun AC1 1 1 1 1 1

Ticket Price: validationRun Dollar/Pax2 2 2 2 2 2

realising demand: validationRun Pax/month3 3 3 3 3


Andre

as G

röß

ler,

2010

1.5 B

1.125 B

750 M

375 M

0

5

5

5

5

55

5 5

4

4

4

44

44 4

33

33

3 3 3 3

22

22 2 2 2 2

2

11

11 1 1 1 1

1

0 12 24 36 48 60 72 84 96 108 120

Do

llar

/mo

nth

1,500

1,125

750

375

0

55

5

5

5

5

5

5

4 4 4 4 4 44 4

3 3 3 3 3 3 3 3 32 2 2 2 2 2 2 2 21 1 1 1 1 1 1 1 1

0 12 24 36 48 60 72 84 96 108 120

Dol

lar/

Pax

140

125

110

95

80

5 55

55

55 5

4 44

44

44

44

3 33

33

33

33

2 2 22

22

22

2

1 1 11

11

11

1

0 12 24 36 48 60 72 84 96 108 120

AC

2.5 M

2.125 M

1.75 M

1.375 M

1 M

5 5 5 55

5

5

5

4

4

44 4 4

44

3

3

3

3

33 3

3

2

2

2

2

22

2 2

1

1

1

1

11

11

1

0 12 24 36 48 60 72 84 96 108 120

Pax

/mon

th

A simulation experiment: different target revenues

Realising demand

Profit

Ticket price

Operational capacity


Andre

as G

röß

ler,

2010

An illustrative (but real) simulation result

20 B

15 B

10 B

5 B

0 55

55

55

5

44

44

44

4

33

33

33

3

2

2

2

2

2

22

1

1

1

1

1

1

1

1

2010 2012 2014 2016 2018 2020

Time (month)

US

D/m

onth

overall profit[1] : test 1 1 1 1 1 1overall profit[2] : test 2 2 2 2 2 2 2overall profit[3] : test 3 3 3 3 3 3 3overall profit[4] : test 4 4 4 4 4overall profit[5] : test 5 5 5 5 5 5

4

oligopolistic competition

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