MEASURING THE PERFORMANCE OF
BRAZILIAN DISTRICTUAL SYSTEMS
João Amato Neto, Ph.D.
University of São Paulo, Brazil
AGENDA :
Research aims
Research questions
Theoretical approach
The fundamental presupposal
Research methodology
Integrated set of matrices
The cases (clusters of SP state - Brazil)
Main conclusions
RESEARCH AIMS:
Development of a reference model (*) for
management of local production and innovation
systems, from a selected small and medium
enterprises (SMEs) clusters set in the São Paulo
state - Brazil .
(*) A systematic set of concepts, principles and indicators
which can guide public and private actor´s actions in
order to promote and improve such kind of productive
arrangements.
RESEARCH QUESTIONS (I):
1.) What are the basic requirements to transform
small and medium enterprises (SMEs) clusters in
local production and innovation systems?
2.) What is the relationship degree among
enterprises that belong to a local production
and innovation system (the frequency and the
intensity of their joint actions)?
RESEARCH QUESTIONS (II):
3.) What are the different governance
structures and settings which could be found in
such systems, and its local and regional links
with other global regions ?
4) What is the role of the Science, Technology
& Innovation National System (including the
Basic Technology Industry requirements Standards,
Metrology
and
Industrial
Certification) in the SMEs modernization
process inserted in local production and
innovation systems?
BORDERS AND VERTICES OF ANALYSIS
)
(Epistemological pole
REGIONAL
ECONOMICS
INDUSTRIAL
CLUSTERS
&
COOPERATION NETWORKS
INDUSTRIAL
ORGANIZATION
PRODUCTION
ENGINEERING
THEORETICAL APPROACH
1. NEW ECONOMIC GEOGRAPHY, Krugman, (1991, 1998), Marshall
(1920): clusters are induced by the presence of local external economies
(incidental).
2. COMPANIES STRATEGIES (Porter, 1998), locational strategies are a
part of wide strategies of companies defined according to the business branch .
They are also market forces which determine the clusterted producers
performance.
3. REGIONAL ECONOMY (Scott, 1998), differential element: the
recognition of the extra-market coordination and public policies importance.
4. COLLECTIVE EFFICIENCY (Schmitz, 1989), emphasizes the
deliberated forces which intensify the enterprises competitive capacity, which
come from the cooperation, consciously sought among private ans public
agents.
THEORETICAL APPROACH
5. INDUSTRIAL DISTRICTS ( Belussi, F. 2000; 2005; Gottardi,G.
2000, Lombardi,M., 2003) Learning and knowledge transfer
process at Local Production Systems. Models of localized
technological change.
6. SOCIAL CAPITAL (Silva, 2006; Marteleto e Silva, 2004;
Bourdieu, 1998; Degenne, 2004). Interpersonal or intergroup
relationship cooperation networks in which its members are
governed by certain rules,systems, beliefs, values, feelings (like
recognition, respect, friendship) and confidence.
FUNDAMENTAL PRESUPPOSAL
JOINT ACTIONS
(companies, government,
development agencies,
universities,
technical schools, other social agents)
POSITIVES
EXTERNALITIES
(qualified work-force and
abundant raw material supply,
among others)
COLLECTIVE EFFICIENCY
strengthening of clusters
Local and regional development
RESEARCH METHODOLOGY
Mapping clusters in the state of SP through survey.
• Research Instrument (I) : self-administered
questionnaire in order to examine some
characteristic aspects of the different clusters.
• Instrument Research (II): qualitative research,
supported by the multiple case study method
(GIL, 1995; YIN, 1998), using semi-structured
questionary.
RESEARCH PLAN
• Documentary research with public agencies,
local institutions of support, trade unions, NGOs,
SEBRAE (Brazilian System to Support SMEs),
universities, research centers and so on.;
• Clusters analysis (their externalities; joint
actions; degree of cooperation, links with
institutions and external agents, etc.).
• Clusters comparative analysis.
INTEGRATED SET OS MATRICES
analysis of the main features of clusters
•
•
•
•
•
•
reference for public and private policies.
Stakeholders:
Market sector associations
Clusters responsables agents
Public institutions
Local associations and offices
Local governments (public offices)
Local industry associations
Clusters in SP state (Brazil)
Set of Matrices
Set of Matrices
Main goals:
• Contemplate all
characteristic
dimensions
• Be independent of
time, industry or
original geography
• Results that range
between 0 and 4 pts
• Be self-explainning
and user-friendly
Identification Code
Characteristic evaluated
G1
Proximity of raw material sources
Matrix
Distance (in km) between the main raw material sources and the
cluster
0 points
1 point
2 points
3 points
4 points
More than
200
Between
100 - 200
Between 50
- 100
Between 50
- 20
Less than
20
Identification Code
Characteristic evaluated
I3
Marketing and Advertisement actions
Matrix
Participation and availability of marketing institutions
0 points
1 point
2 points
3 points
4 points
Don’t
exist
Work
partially
Not
sufficient
Exist and
sufficient
Work
completely
Possible Classifications
• Development Stage
Embryonic
Emergent
Expansion
Maturity
• Organizational Level
INFORMAL
ORGANIZED
INNOVATIVE
Main analysis
São José dos Campos
IGG
4,00
ICGG
IEG
3,00
2,00
1,00
IGovG
IIG
0,00
SJ dos Campos
IIntG
ISG
IAG
ITG
Main analysis
São Carlos
IGG
4,00
ICGG
IEG
3,00
2,00
1,00
IGovG
IIG
0,00
S Carlos
IIntG
ISG
IAG
ITG
Main analysis
Americana
IGG
4,00
ICGG
IEG
3,00
2,00
1,00
IGovG
IIG
0,00
Americana
IIntG
ISG
IAG
ITG
Main analysis
Indaiatuba
IGG
4,00
ICGG
IEG
3,00
2,00
1,00
IGovG
IIG
0,00
Indaiatuba
IIntG
ISG
IAG
ITG
Main analysis
4,00
3,50
3,00
Indaiatuba
2,50
Americ ana
2,00
1,50
Ibitinga
1,00
C erquilho/Tiete
0,50
Tabatinga
IC
G
G
G
ov
IG
tG
I In
G
IA
G
IT
G
IS
I IG
G
IE
IG
G
0,00
Main analysis
CLASSIFICATIN GRAPHIC
Comparision
among industries
(same region)
Limeira – Jewelry
CLASSIFICATION GRAPHIC
Comparision
among regions
Franca
Birigui
Limeira - Machines
Ourinhos
Jaú
Comparision
among different
industries
CLASSIFICATION GRAPHIC
Furniture
average
CLASSIFICATION GRAPHIC
Cluster evolution
(per year)
Red Ceramic
average
High tech
production average
2004
2000
1996
Clusters classification
Cluster/
APL
APL
Índice
Global
Cluster/
APL
APL
Índice
Global
1
SJ dos Campos
0,81
13
Franca
0,59
2
Plástico/ABC
0,75
14
Mirassol
0,59
3
Birigui
0,72
15
Tabatinga
0,58
4
Americana
0,72
16
Porto Ferreira
0,55
5
São Carlos
0,71
17
Tambaú
0,55
6
R.M.S.P /Móveis
0,70
18
SJ Rio Preto
0,52
7
Ibitinga
0,69
19
Salto/Itu
0,51
8
Ribeirão Preto
0,69
20
Itatiba
0,51
9
Jau
0,66
21
Cerquilho/ Tiete
0,47
10
Santa Gertrudes
0,63
22
Limeira
0,47
11
Vargem Grande
do Sul
0,62
23
Indaiatuba
0,43
12
Sorocaba
0,60
Informal Organized Innovator
Organizational levels
Clusters evolution levels
Q9
Q10
Q11
Q12
1
5
8
Q5
Q6
15
23
Q1
21
22
Q2
Q7
9
10
11 18
Embryonic
Expanding
4
13 14
12
16
20
Emerging
Clusters development stages
Q8
7
6
Q3
17
19
3
2
Maturity
Q4
Main conclusions
• Limitations for the application:
– Partiality of some qualitative matrices
– Knowledge of a ‘specialist’ of the cluster
– Data availability
• Main implications:
– Extension of the study to clusters of other countries
– Statistical study to determine the exact correlation between the
classifications and the size or format of the ‘ocurrence zone’
THANKS
SEBRAE /SP Staff
•
•
•
•
•
Paulo Eduardo Stabile de Arruda ( Diretor Técnico)
Caio César Massao Ito
Joaquim Batista Xavier Filho
Renata Moreira Contatori dos Santos
Rose Mary Estácio
Post - Graduated Program
in Production Engineering (EPUSP) Students
•
•
•
Cláudio Roberto Leandro
Luciana Pereira
Luciana Telles
THANKS
Profa. Sandra Rufino dos Santos (PRO– EPUSP)
Undergraduate studentes
(Production Engineering - PRO - EPUSP)
•
•
•
Fábio Bortolotti (2005)
Ricardo Santa Maria Correa da Fonseca (2006)
Thiago Miranda (2007)
Trainee
Vivian de Souza Pontes
Thank you !
RESEARCH GROUP :
COOPERATION NETWORK AND
KNOWLEDGE MANAGMENT
Coordinator : João Amato Neto, Ph.D.
http/www.pro.usp.br/redecoop
e-mail: amato@usp.br
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