Groupe de Recherche en Economie Théorique et appliquée – UMR CNRS 5113 Coevolution of supply and...

Groupe de Recherche en Economie Théorique et appliquée – UMR CNRS 5113

Coevolution of supply and demand: the case of

environmental innovations

Maïder Saint JeanGREThA, Bordeaux University

[email protected]

DIMETIC, 19th october 2007, Maastricht, The Netherlands


References

• Belis-Bergouignan M-C., Oltra V., Saint Jean M., 2004, Trajectories towards clean technology: example of volatile organic compound emission reductions, Ecological Economics, 48, pp201-220.

• Saint Jean M., 2005, Coevolution of suppliers and users through an evolutionary modelling – The case of environmental innovations, European Journal of Economic and Social Systems, 18 (2), pp255-284.

• Saint Jean M., Polluting emissions standards and clean technology trajectories under competitive selection and supply chain pressure, Forthcoming in Journal of Cleaner Production.


Outline of the presentation

1. Some stylised facts on environmental innovations

2. The main building blocks of the model

3. Results

4. Further developments: analysis of policy instruments

5. Conclusions


1. Some “stylised facts” on environmental innovations

• Environmental innovations: innovations that consist of new or modified processes, practices, systems and products which benefit the environment and contribute to environmental sustainability regulatory push-pull effect

• Clean technology vs end-of-pipe technology– Clean technology implies an integrated change in the

production process and a reduction of pollution at source;– End-of-pipe technology controls and treats pollution after it

has been generated

multi-dimensionality of clean technology; innovation offsets

• Environmental R&D dedicated to the improvement of environmental quality of processes and products

• “Green paradigms” for the generation of heat, electricity and motion radical questioning of existing production processes; technological irreversibility and lock-in


Evolution of anti-pollution investments

0,00

200,00

400,00

600,00

800,00

1 000,00

1 200,00

1 400,00

source: SESSI

Mil

lio

ns

Eu

ros Specific investments

Anti-pollution share ofintegrated investments

Total of anti-pollutioninvestments

Evolution of environmental R&D

-

500

1 000

1 500

2 000

Source: Ifen, Commission des comptes et de l’économie de l’environnement, avril 2006 –

Ministère chargé de la Recherche.

Mill

ion

Eu

ros

Administration

Firms

Total

Environmental R&D of firms (% share in the total R&D)

0

0,5

1

1,5

2

2,5

Source: Ifen, Commission des comptes et de l’économie de l’environnement, avril 2006 – Ministère chargé de la Recherche.

%


The space of clean technology trajectories


Case 1: the paintings

• Diversity of users and market segments

• Public concern• Significant range of

environmental innovations with no or low solvents

• Change in the knowledge base of the producers and the users: paintings organic chemicals


Case 2: the surface treatment activities

• Clean technologies for the surface treatment, ex.: low temperature plasma

• SMEs of the metal-work sector subcontractors of car manufacturers and aerospace firms

• Technological irreversibilities in the solvent paradigm

• Obstacles to the adoption of clean technology:– High adopion costs related

to weak financial and absorptive capacities

– Product performance constraints


2. The main building blocks of the model

Scheme of supply-demand interactions

SUPPLY n firms DEMAND m firms

Purchase Defection

Preferences

Requirement Levels: maximum

price, minimumquality standards,

environmentalregulatorystandards

Allocation of R&DInvestment

Process/Productinnovation

Competition among

suppliers

Performance achievedfor each characteristic

Marketshare

Average performance of industry

Profile of each client:


Procedure of supplier’s selection by a client at time t

Supplier t-1 of client j: S(t-1)

Requirement thresholds of client j at time t At time t, performances of supplier S

Requirement thresholds reached?

YES NO

Product replacementwith the same supplier S

Defection of client j

Transfer of informationfrom client j to S(t):

priority characteristics

Selection of a new supplier remaining on the market on

the basis of its global performance

Transfer of informationfrom client j to S’(t)

Choice of a new supplier S’


Models of reference

• Chiaromonte F., Dosi G., 1993, Heterogeneity, competition and macroeconomic dynamics, Structural Change and Economic Dynamics, 4, 39-46.

• Malerba F., Nelson R., Orsenigo L., Winter S., 1999, ‘ History-friendly ’ models of industry evolution: the computer industry, Industrial and Corporate Change, 8, 3-40.

• Laffond G., Lesourne J. and Moreau F., 1998, Stratégies de différenciation environnementale et dynamique des structures de marché, Colloque AFSE, Toulouse, May.

• Valente M., 1999, Evolutionary economics and computer simulations - A model for the evolution of markets, PhD thesis, University of Aalborg, Denmark.


Table of correspondence

1. R&D investments and innovation activities of suppliers

2. The product price

3. Technology space

4. Decision rules of clients

5. Inter-firm interactions

6. Exit process


1. R&D investments and innovation activities of suppliers

Innovation is a mean to acquire dominant position and technological lead

R&D activities are an important source of innovation

P is the price of the product i at time t and B the install base of firm I at time t. Mu is the fraction of turnover allocated to R&D.

Environmental R&D dedicated to the improvement of environmental performance of processes and products is mainly financed by firms and performed independently. It is often a response to government regulation

Amount of resources allocated to the characteristic h

Research level achieved for the characteristic h

The innovation process is characterised by radical uncertainty

Probability of innovation

Innovative activities take place within paradigms so that they are strongly selective, finalised in rather precise directions and often cumulative

Technological change is firm-specific, cumulative and path-dependent

Performance level performed by firm i for the characteristic h at time t:

Innovation output:

Experience:

tiBtiPitiRD ,.,.,

tiRDhti

htiRD ,.,,

htiR

htiRDh

tiR 1,).1(,.,

)),.4exp(.32(1,htiR

hti

htiX ,

3)1,max.(2),.(1),.(0,

h

tiXhXh

tiEhtiR

htiX

AptiE

AptiRMaxE

AptiE 1,).1(),.(,


2. The product price

Mark-up rule over the production costs

Teta is the mark-up rate of firm i

)11,1).(1(, tiXitiP


3. Technology space

Different paradigms are competing or coexisting with different environmental and technological opportunities

Competence-destroying effect when changing paradigm

Cf. figure

The switch carried out by a firm in the paradigm with high environmental potential leads to three effects: a shift in the frontier achievable on the dimension ‘environmental quality of process’, a drop in the product performance and a decrease in the cumulated experience.

X3max2

X3max1

Productive efficiency of the process

Environmental quality of the process

PARADIGM 2

PARADIGM 1


4. Decision rules of clients

a) Purchase Clients take into account the product characteristics they perceive from the suppliers and evaluate the product according to their preferencesMimetic behaviour and/or switching costs affect the product’s selection

Purchase probability:

Preference that client j attributes to the characteristic

Parameter e expresses the intensity of ‘bandwagon effect’ that a supplier with high market shares may exert on client.

b) Product replacement Durable goods are only replaced after a certain period of use

Each client replaces its product after T periods, with T settled randomly between 1 and 10.

c) DefectionThe continuation of the relationships is conditional to the achievement of some minimum requirements imposed by demand or regulationImplicit threat of an exit/voice mechanism governing interfirm relationships

If the supplier fulfils the client’s requirement criteria, then the supplier records a sale

while its install base remains unchanged.

If not, the supplier loses one client from its stock

eti

xti

xti

xti

xti

itj MSXXXPoba jjjj ).()

~.()

~.().()1(Pr 1,

41,

31,

21,1,,

4321

1jx

2jx

3jx

4jx

n

i tiBtiBtiMS1 ,,,

1, tiN

1, tiB


5. Inter-firm interactions

a) Transfer of information Supplier’s R&D allocation are guided by demand needs both in terms of the priority characteristics for the client and in terms of the minimum quality standard required in the industry

Gathering of data: a positive score is given to characteristics that are both priority for the clients and represent a source of technological lead for the supplier;

A negative score is registered for the characteristic with a performance level below the one required by the client

b) Evolution of the allocation of R&D investment of suppliers Bounded rationalityAdaptive decision rules through individual learning and demand feedback

Adjustment of R&D index:

: Speed of adjustment; : the relative importance attributed to the positive indicators compared to the negative ones

c) Evolution of minimum requirements of clients under the influence of technological advances in the industry Social diffusion or collective learning

Increase in the requirement level of a client

Average performance of the industry:

1, htiZ

1, htiW

)).1(.()).1(.().1( ,,,,1,,

h

hti

h

hti

hti

hti

hti

hti WZWZRDIndexRDIndex

h

htiRDIndexh

tiRDIndexhti ,,,

)))1,.(,0.(max(1,,htjlevelXh

tXhjx

htjlevelXh

tjlevelX

n

i

htiXtiMSh

tX 1 ,.,


6. Exit process

Inefficient firms do not survive

Exit both when the install base is equal to 0, i.e. the user stock of the supplier is exhausted, and when the sales are equal to zero for a minimum of four periods.


3. Results

• Protocol of simulation: parameter initialisation, battery of simulations– The reference configuration: 12

suppliers, 200 clients, 2 groups of clients

• Two scenarios or market configurations:– scenario ‘ homogeneous oligopoly ’– scenario ‘ market segmentation ’


Scenario HO

0%

10%

20%

30%

40%

0 100 200 300 400 500

Iterations

Mark

et

sh

are

s

F1 F2 F3

0

1

2

3

4

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

Productive efficiency

En

vir

on

men

tal q

uality

of

pro

cess

F1 F2 F3

0

5

10

15

0 100 200 300 400 500

Iterations

Pro

du

ct

perf

orm

an

ce

F1 F2 F3

0

2

4

6

8

10

0 100 200 300 400 500

Iterations

En

vir

on

men

tal q

uality

of

pro

du

ct

F1 F2 F3


Scenario MS

0%

20%

40%

60%

80%

100%

0 100 200 300 400 500

Iterations

Mark

et

sh

are

s

F1 F2

0

5

10

15

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

Productive Efficiency

En

vir

on

men

tal q

uality

of

pro

cess

F1 F2

0

5

10

15

0 100 200 300 400 500

Iterations

Pro

du

ct

perf

orm

an

ce

F1 F2

0

5

10

15

0 100 200 300 400 500

Iterations

En

vir

on

men

tal q

uality

of

pro

du

ct

F1 F2


4. Further developments: policy implications

• The impact of tighter standards:– Process standards– Product standards– Policy timing

The rise in the environmental requirements of clients, generated by tighter environmental standards, has different impacts according to the nature and timing of the standards

• The role of procurement policy:– Critical mass of ‘green’ users– Strategic niche management (Kemp, Schot

and Hoogma, 1998)

• Taxes, subsidies, diffusion of information, etc.


Process standards

0

1

23

4

5

6

0 2 4 6 8 10 12 14 16

Productive efficiency (Ap)

Pro

cess

env

iron

men

tal

qual

ity (I

p)

Reference case Standard Ip/100 Standard Ip/200

Scenario HO

0

1

2

3

4

5

0 2 4 6 8 10 12 14 16

Productive efficiency (Ap)

Proc

ess

envi

ronm

enta

l qu

ality

(Ip)

Reference case Standard Ip/100 Standard Ip/200

Scenario MS


Product standards

0

2

4

6

8

1 40 80 120

160

200

240

280

320

360

400

440

480

Iterations

Aver

age

proc

ess

envi

ronm

enta

l qua

lity

(Ip)

Reference case Standard Im/100 Standard Im/200

Scenario HO

0

1

2

3

4

5

1 40 80 120

160

200

240

280

320

360

400

440

480

Iterations

Ave

rage

pro

cess

en

viro

nmen

tal q

ualit

y (Ip

)

Reference case Standard Im/100 Standard Im/200

Scenario MS


Limitations• Methodological problems related to simulations :

- the stochastic characteristic of the dynamics;- the high number of parameters;- the empirical calibration of the model.

• Limits of the model:- no sectoral differences are taken into account;- there’s no real price strategies of firms;- effective financial constraints do not apply;- the role of final consumers is not explicitly incorporated;- no new innovative entrants are considered.

• Regarding environmental innovations:- the anticipation of environmental regulation by firms and its

impact on firm’s innovation strategy;- the issue of “transition management” and system innovations.


5. Conclusions

• An evolutionary model of supply and demand coevolution

• Process/product innovations with characteristics of environmental quality

• Related questions cf. M. Schwoon (fuel cell vehicles, role of infrastructures), E. Brouillat (recycling, product life extension), impact of REACH (Registration, Evaluation, Autorisation and Restriction of Chemicals) on innovation

• Empirical validation?

Groupe de Recherche en Economie Théorique et appliquée – UMR CNRS 5113 Coevolution of supply and...

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