Transcript Document

The application of CIS to Portugal:
Survey Implementation and
Results Analysis - Innovation vs. Productivity
Manuel João Bóia
[email protected]
Pedro Faria
[email protected]
Science and Technology Policy Program
MSc Engineering Policy and Management of Technology
5th November 2004
Outline
Part 1 – Innovation Indicators
1.
Innovation Indicators
2.
The Community Innovation Survey
3.
Students Presentation
4.
5.
Results (CIS 3),

Innovative Enterprises by Sector and CIS Trajectories in the
European Context

Input vs. Output of Innovation in Europe

Some Innovation Characteristics

Other Strategic and Organizational Important Changes

Innovation Sources

Innovation Barriers
Lessons Learned and Conclusions
Outline
Part 2 - Innovation and Productivity:
What can we learn from the CIS 3 Results for
Portugal?
1.
Innovation and Productivity Theory
2.
A model for the analysis of innovation and productivity in the
short run
3.
Results with CIS 3 data
4.
Lessons Learned and Conclusions
Innovation Indicators
1.1
The exponential growth of S&T indicators at the international level
Decades
Main indicators used
50s and 60s
Re&D
70s
Re&D
Patents
Technological balance
of payments
80s
90s
Re&D
Patents
Technological balance
of payments
High-tech products
and sectors
Bibliometrics
Human resources
Re&D
Patents
Technological balance
of payments
High-tech products
and sectors
Bibliometrics
Human resources
Innovation surveys
Innovation surveys
Innovations mentioned in
technical literature
Surveys of production
technologies
Government support to
industrial technology
Intangible investment
Indicators of information
and communication
technologies
Input-Output matrixes *
Productivity *
Venture capital *
Mergers and acquisitions *
* Indicators mutuated from economic analysis.
CIS 3
2.1
Portugal
What Survey Target Population?
•
All Manufacturing and Service firms with more than 10 employees
How to establish a Survey Sample?
•
Initial Sample: 4727 firms stratified by firm size and sector
(INE–1999 Data) prepared by “Instituto Nacional de Estatística”
•
Corrected sample: 4127 firms; prepared by the Support Team (OCES and
outsourced survey enterprise)
What Sectors were surveyed?
•
Mining and Quarrying (NACE 10-14)
•
all Manufacturing (NACE 15-37)
•
Utilities (NACE 40-41)
•
Wholesale Trade (NACE 51)
•
Transport, Storage and Communication (NACE 60-64)
•
Financial Intermediation (NACE 65-67)
•
Computer and Related Activities (NACE 72)
•
Research and Development (NACE 73)
•
Architectural and Engineering Activities (NACE 74.2)
•
Technical Testing and Analysis (NACE 74.3)
Services
CIS 3
2.2
Portugal
How was the Survey implemented?
•
Institutions involved:
- Observatório da Ciência e Ensino Superior (funding and support team),
- IN+ (Scientific and operational coordination; data treatment and analysis;
reporting);
- Instituto Nacional de Estatística (sample preparation);
- outsourced survey enterprise (infrastructure, logistics, communications,
support team Management, databases);
•
Data acquisition Phases:
- From 1st October 2001 to 15th April 2002
- Sample verifying and validation (Name and Address) and identification of
a contact person
- Mailing of Questionnaire with innovations examples and a postage free
envelope for replying (fax reply also accepted)
- Systematic phone reminders plus two fax reminders and an additional
questionnaire re-mailing
- Support provided in working days by phone, fax or e-mail by a
multidisciplinary team of 6 trained staff people (3 Engineers, 1 Economist
and 2 Sociologists)
CIS 3
2.3
Portugal
Innovation Definition Used:
•
Market introduction of a product (Good or Service) new or significantly
improved, or the introduction of new or significantly improved processes,
based on new technological developments, new combinations of existing
technologies or on the use of other type of knowledge acquired.
The innovation should be new to the company and not necessarily to the market.
CIS 3
2.4
Portugal
Questionnaire
•
Harmonized questionnaire (the same for Services and Manufacturing and
other industries)
•
Questions regarding:
General Information
Companies Characteristics
Basic Economic Information
Product and Process Innovation
Innovation Extension
Patents and Other Protection Methods
Innovation Activities and Expenditure
Intramural R & D
Companies Options
Other Strategic and Organizational Important Changes
Effects of Innovation
Public Funding
Innovation Co-operation
Sources of Information for Innovation
Hampered Innovation Activity
Systemic Characteristics
CIS 3
2.5
Portugal
Survey Data Processing:
•
Unit Non-respondents analysis
•
Non-respondents survey for results calibration (only if Resp. Rate < 70%)
•
Respondents and Non-respondents distribution of responses analysis
•
Statistical software SAS routines testing and implementation
•
Data consistency checks and first data processing
•
Data imputation of missing variables (Item Non-respondents)
•
Final data processing and tabulations
•
Data validation (Eurostat)
•
Final Database and Codebook
CIS 3
2.6
Portugal
Response Rates
CIS 3 PT Valid Answers and Response Rates by Sector and Size
Sector
Small
Medium
Large
Resp.
Resp.
Resp.
Valid
Valid
Valid
Rate
Rate
Rate
10(12)-14
23 46,0%
22 52,4%
0 0,0%
15-37
623 45,1%
455 45,2%
198 52,5%
40-41
9 29,0%
8 57,1%
4 66,7%
51, 60-67, 72-73, 74.2, 74.3 313 41,8%
158 48,9%
62 53,9%
NACE
Mining and Quarring
Manufacturing
Electricity, Gas and Water Distribution
Services
All Sectors
Sub-Total
Valid Resp. Rate
45
1276
21
533
47,87%
46,16%
41,18%
44,90%
968 43,8% 643 46,4% 264 52,8% 1875 45,8%
Small
– 10 to 49 Employees
Medium
– 50 to 249 Employees
Large
- over 250 Employees
5.1
Lessons Learned from the CIS III Implementation:
•
Unreliable Initial Sample (1999 Data)
•
Non-Enforcement of the Policy regarding Mandatory Surveys
•
Biased General perception of Innovation Definition (“Radical” Innovation)
•
Services misperception of Innovation Definition (Product = Service or Goods)
•
Non-Disclosure Policy of Financial Data
•
Lack of Qualifications of the Questionnaire Filling Contact Person (“Cultural”
bias towards Non Response or Non Innovation)
•
Lack of correspondence between the surveyed data/indicators and Companies
data/indicators gathering.
•
Mergers and Acquisitions (Availability of Contact Person and Data)
•
Huge paperwork!
•
In Data Processing,
High values of “Item Non-response” in some strata
(CAE 2 Digits*Dimension) of the realized sample for some variables,
”Exports Sales”, “Innovation Expenditure”, “Level of importance in
Cooperation”, “Innovation Hampering Factors (partially)” and Patents
Unreliable missing values imputation methodology and routines provided by
Eurostat, surpassed in cooperation with other member states.
Students Presentations
Results - Innovative Enterprises by Sector and
CIS Trajectories in the European Context
4.1
80%
CIS II
Ireland
60%
Austria
Upward
Trajectory
Luxemburg
Proportion of
Service Innovating
Enterprises
CIS III
Germany
UK
40%
The Netherlands
Greece
France
Portugal
Sweden
Upward and
Downward
Trajectory
Italy
Denmark
Spain
Downward
Trajectory
Norway
Finland
20%
Belgium
0%
20%
40%
60%
80%
Proportion of Manufacturing Innovating Enterprises
Note:
The CIS 3 data is not directly comparable to CIS 2 data due to the enlargement of the
CIS sample. Enterprises in between 10 and 19 employees in Manufacturing and selected
sectors (NACE 63, 73, 74.3 and all the 64 in addition to 64.2) in Services were included
in the exercise.
4.2
Results – Input vs. Output of Innovation in Europe
Manufacturing Sector
80%
Porportion of Innovative Enterprises
IRL
DE
AT
NL
60%
UK
SE
DK
40%
LU
NO
CIS II
FR
CIS III
ES
FI
IT
BE
GR
PT
20%
0%
0.0%
2.0%
4.0%
6.0%
8.0%
Expenditure in Innovating Activities as Share of Turnover
Results – Some Innovation Characteristics
4.3

Innovation is Firm Size dependent
(larger firms innovate more)

Innovation has sector specificities

The integration of the firm in a network
(e.g., integration into a group)
increases the probability to innovate

The level of competition in a market influences a firm’s
probability to innovate
(Highly competitive markets provide more innovative
firms)
Non-Innovators
Manufacturing
Services
Innovators
Changed
Organizational
Structures
New Corporate
Strategies
Significant
Aesthetics' Change
Advanced
Management
Techniques
Changing
Enterprise's
Marketing
Concepts/Strategies
Changed
Organizational
Structures
New Corporate
Strategies
Significant
Aesthetics' Change
Advanced
Management
Techniques
Changing
Enterprise's
Marketing
Concepts/Strategies
Proportion of Enterprises (%)
Results - Other Strategic and Organizational Changes
4.4
70.0
60.0
50.0
40.0
30.0
20.0
10.0
-
1995-1997
Europe Average 1995-1997
1998-2000
Government or Private
non-profit institutes
Universities and other
Hugher Education
Institutions
Professional
Conferences,
meetings and journals
Competitors
Suppliers
Fairs and Exhibitions
Other Enterprises
within the Enterprise
Group
Clients
Within the Enterprise
Innovating Enterprises with Highly important Sources (%)
Results - Innovation Sources of Highly Importance for Manufacturing
50
45
40
35
30
25
20
15
10
5
0
4.5
CIS III PT
0
CIS II PT
CIS III EU Average
Customer
Responsiveness
Regulations and
Standards
Information on
Markets
Economic Risks
Information on
Technology
Sources of
Finance
Innovation Costs
Organisational
Rigidities
Qualified
Personnel
Proportion of Enterprises (%)
Results - Innovation Barriers of Highly Importance
4.6
50
45
40
35
30
25
20
15
10
5
5.2
Lessons Learned and Conclusions:
1.
The CIS is a good evolving instrument for benchmarking and follow up of
the best practices, although incomplete in what concerns the systemic
characteristics of innovation.
2.
A significant increase in the innovation extension and in the firms
innovation expenditure was achieved for Portugal in CIS III compared to
CIS II.
3.
In the innovation process, both sources and barriers to innovation profiles
remain consistent with the CIS II data, where the
most relevant
are
respectively “Within the Enterprise” and financial constraints.
4.
Innovation expenditure has reached a milestone above which innovation
effectiveness appears to be more correlated with factors of systemic
nature.
5.
Technological
innovation
appears
to
Organizational Innovation and Change.
be
strongly
correlated
with
Outline
Part 2 - Innovation and Productivity:
What can we learn from the CIS 3 Results for
Portugal?
1.
Innovation and Productivity Theory
2.
A model for the analysis of innovation and productivity in the
short run
3.
Results with CIS 3 data
4.
Lessons Learned and Conclusions
Innovation vs. Productivity
Technological Innovation
+
Productivity
Long
Run
Short
Run
Three theories explain the short relationship between
Innovation and Productivity:
- Learning
- Technology and Organizational Rigidities
- Adjustments Costs
Theories
Arguments
Main References
Innovation - new skills - productivity decrease
Learning
Time and costs of the adoption process not
neglegetable - learning cost
Jovanovic and Nyarko (1996)
Ahn (1999, 2001)
Innovation implies the execution of non-productivity
activities - drop in productivity in the short run
More productive firms have difficulties to change
technology
Technology and Organizational Rigidities
When technologies appear perform less effectively
than the technologies already diffused
Technology transfer imply a change on management
techniques in order to synchronize the firm
characteristics with the innovation
More productive firms may be reluctant to switch to
new technologies that would imply significant
productivity losses
More productive firms are those that stick more
closely to existing routines
Leonard-Barton (1988, 1992)
Utterback (1994)
Christensen and Bower (1996)
Christensen (1997)
Young (1991, 1993)
Benner and Tushman (2002)
Tripsas and Gavetti (2002)
Decision not to innovate level of productivity and level of organizational rigidity
Periods of adoption of new technologies adjustment costs and decrease of levels of output
Adjustment Costs
positive relationship between levels of productivity
and innovation
negative relationship between innovation and levels of productivity
New skills necessary to adopt correctly new
technologies
May be a lag between the growth in investment and
its benefits
Adjustment costs costs related to setting up new equipment, training of
employees (resources used to fully utilize the capital)
During the introduction of the innovation stage,
innovative firms will have a lower rate of productivity
growth than non-inovative firms
More productive firms are those that are more
capable to deal with adjustments costs and liquidity
constrains
Bessen (2001)
Bernstein et al. (1999)
Hall (2002)
Leung (2004)
Theoretical arguments
that explain
the negative relationship
between innovation and
productivity
Econometric Model (1)
1) Endogeneity: Hausman Test
OLS – inconsistent
2) Equation System:
Log(PrdG)i   0  1 Inovi   2 Expi  3 NFi   4GPi  5 EDi   6CS  S i   i
Pr(Inovi  1)  0  1 Log _ Turn _ Inici   2 NFi  3GPi   4 Si  i
3) Covariance Correction:
Murphy-Topel Method - two step estimation method for mixed
models that include limited dependent
variables
Econometric Model (2)
Log(PrdG)i   0  1 Inovi   2 Expi  3 NFi   4GPi  5 EDi   6CS  S i   i
Pr(Inovi  1)  0  1 Log _ Turn _ Inici   2 NFi  3GPi   4 Si  i
Where:
Prdg – Productivity Measure – log (Turnover / nº Workers)
Inov – Innovation Dummy Variable
Exp – Exports / Turnover
NF – Dummy Variable that indicates if the firm was created in 1998-2000
GP – Dummy Variable that indicates if the firm is part of a group
ED – Share of the Workforce engaged in specialized tasks
CS – Gross Investments in Capital Goods
S – Sector Dummy Variables
Log_Turn_Inic – Critical Identification Variable - log (Turnover 1998)
The CIS 3 Data
Advantages of the survey data:
1) Data on innovation and productivity for a two year period
(1998-2000);
2) Separation between firms that do not innovate, those that
have attempted to innovate and innovative firms;
3) Gathering information, not only about radical innovations
linked to patents applications, but also about not radical
innovations in the context of the market but new to the firm;
4) Inquiring firms, not only from the manufacturing sector, but
also from the service sector, making possible a more
complete analysis from the Portuguese economic reality;
5) Existence of information that allows the creation of
instruments to correct endogeneity;
6) Differentiation between product and process innovation
Results
Note: * Significant at 10%; ** 5%; *** 1%; Sector Dummies Variables included but not reported
Conclusions
• In the universe of Portuguese firms enquired by the CIS III,
innovative firms have a lower degree of productivity growth
when compared with non-innovative firms
• The more productive firms are more innovative – result coherent
with the Adjustment Costs theory
• The inclusion of the variable Gross Investment in Capital Goods
gives robustness to the model
Additional Slides
Results - Innovation Extension
Innovation Extension
Manufacturing
Services
National (3)
1995-1997 1998-2000 (1) 1998-2000 (2)
1995-1997 1998-2000 (1) 1998-2000 (2)
1995-1997 1998-2000 (1) 1998-2000 (2)
Proportion of the total of firms that:
Introduced Innovation
Product Innovation
Process Innovation
were involved in Inovating Activities
Ongoing or Abandoned Innovating Activities
25.8
15.1
22.9
28.5
8.3
48.4
31.1
37.5
50.7
21.3
42.4
26.8
31.1
44.8
17.8
28
35.6
11.1
48.9
31.9
30.3
50.1
17.2
48.7
31.6
30.6
50.1
17.6
26.7
31.4
9.4
48.4
30.9
34.8
50.3
19.5
44.3
27.9
31.1
46.4
17.7
Proportion of the total of firms that were involved in Innovating Activities that:
Introduced Innovation
Product Innovation
Process Innovation
Ongoing or Abandoned Innovating Activities
90.4
52.9
80.3
29.2
95.5
61.4
73.9
42
94.6
59.8
69.4
40.4
78.7
31.1
97.5
63.6
60.5
34.3
95.7
63.1
61.2
35.2
85
30.1
96.3
61.4
69.1
38.7
95.5
60.2
67.1
38.1
Note: in CIS 2 (1995-1997), by opposition to CIS 3 (1998-2000), two separate questionnaires were used for Manufacturing and Services. In the latter, a distinction between process and product was not asked, therefore these
values are not available.
(1) For comparison with the data of 1995-1998 some Service sub-sectors (NACE 63, 73, 74.3 and 64 except 64.2) and the Manufacturing firms in between 10 and 19 employees that were surveyed in 1998-2000 are not
included.
(2) Includes the results not considered in (1).
(3) Includes also the results of Minning and Quarring (NACE 10 to 14) in (2) and Electricity, Gas and Water Distribution (NACE 40 and 41) in (1) and (2).
Results – Product and Process Innovation in Manufacturing
100,0
Proportion of Process Innovators (%)
80,0
60,0
Transport Equipment
Machinery and
Equipment NEC
Wood, Pulp and
Publishing
40,0
Basic Metals and
Fabricated Metal
Products
Rubber and Other
Non-Metallic
Textiles and Leather
Food products;
Beverages and
Tobacco
20,0
Electrical and Optical
Equipment
Coke and Chemicals
Manufacturing NEC
and Recycling
-
20,0
40,0
60,0
Proportion of Product Innovators (%)
80,0
100,0
Proportion of Innovating Enterprises (%)
Results - Innovation by Firm Size
90
80
70
60
50
40
30
20
10
0
1995-1997
1998-2000
(1)
1998-2000
(2)
1995-1997
Manufacturing
Proportion of Innovating Enterprises (%)
Small
1998-2000
(1)
1998-2000
(2)
1995-1997
Services
Medium
Large
1998-2000
(1)
1998-2000
(2)
National (3)
Manufaturing Total
Services Total
National Total
100
90
80
70
60
50
40
30
20
10
0
1995-1997
1998-2000
(1)
1998-2000
(2)
1995-1997
1998-2000
(1)
Manufacturing
1998-2000
(2)
1995-1997
Services
1998-2000
(1)
1998-2000
(2)
National (3)
10 to 19
20 to 49
50 to 99
100 to 249
More than 500
Manufacturing Total
Services Total
National Total
250 to 499
CIS 3
Portugal
CIS3 Final data - All Sectors
( % )
NACE Breakdown
Proportion
of
Innovating
Enterprises
Mining & Quarring
37.2
Manufacturing
42.4
Small
35.3
Medium
62.2
Large
72.0
Food products;
Beverages and tobacco
47.8
Textiles and leather
31.1
Wood, pulp & publishing
36.1
Coke and chemicals
66.0
Rubber & other non-metallic
47.9
Basic metals and
fabricated metal products
53.3
Machinery and equipment NEC
50.4
Electrical and
optical equipment
49.2
Transport equipment
50.3
Manufacturing NEC
and recycling
51.0
Electricity, Gas & Water Sup. 70.3
Services
48.7
Small
44.0
Medium
72.2
Large
76.9
Wholesale Trade
46.1
Transport & Storage
41.1
Post & Telecommunications
92.7
Financial Intermediation
70.5
Computer & related Activity
74.1
Research & Development
100.0
Engineering Services
61.1
Test and Analysis
42.9
Share
of Turnover
due to New
or Improved
Products
Share
of Turnover
due to Novel
Products
Innov.
Expenditure/
Turnover
Innovation
Intensity
1.2
15.5
7.4
9.0
23.1
1.1
11.4
2.8
5.7
18.8
2.6
2.9
3.4
2.5
2.9
6.4
7.7
5.8
8.7
11.8
2.6
4.6
2.6
5.9
8.0
2.2
2.2
6.0
2.0
2.3
12.4
19.7
6.0
13.2
1.9
4.5
29.3
46.6
21.1
44.7
3.1
2.4
21.8
39.6
12.3
9.4
13.9
12.7
10.4
12.2
9.7
12.4
60.9
23.4
16.5
14.4
39.5
7.3
4.4
11.6
6.2
7.6
2.2
5.9
5.9
59.0
16.9
16.3
3.2
0.5
2.7
1.2
1.3
4.0
0.9
12.3
2.8
2.6
6.3
3.8
4.7
5.3
High and Medium-High
Medium-Low
Technological Sectors
Low
Textiles and
Leather
Wood, Pulp
and
Publishing
Food
products;
Beverages
and Tobacco
Manufacturing
NEC and
Recycling
Rubber and
Other NonMetallic
Basic Metals
and
Fabricated
Metal
Electrical and
Optical
Equipment
Transport
Equipment
Machinery
and
Equipment
NEC
Coke and
Chemicals
Proportion of Innovating Enterprises (%)
Results – Innovation by Technological Intensity (Manufacturing)
70
60
50
40
30
20
10
0
Results – Education and Innovation by Sector
Proporção de Emprego Terciário vs. Proporção de Empresas Inovadoras
Indústrias Extractivas
Indústrias Alimentares, Bebidas e Tabaco
120.00%
Têxteis e Couro
Madeira, pasta de papel e publicações
Coque e Indústria Química
100.00%
Borrachas e outros Não-metais
Proporção de Empresas Inovadoras
Metais Básicos e Fabricação Metálica
Maquinaria e Equipamento N.E.
80.00%
Electricidade e Óptica
Equipamento de Transporte
Fabricação N.E. e Reciclagem
Distribuição de Electricidade, Água e Gás
60.00%
Comércio por Grosso e Retalho
Transportes e Armazenagem
Correios e Telecomunicações
40.00%
Intermediação Financeira
Actividades Informáticas e Conexas
Investigação e Desenvolvimento
20.00%
Actividades de Engenharia e Arquitectura
Testes e Análises Técnicas
0.00%
0%
10%
20%
30%
40%
50%
60%
Proporção de empregados com o Ensino Superior (média)
70%
80%
Results – Qualifications and Innovation by Sector
1995-1997
Europe Average 1995-1997
1998-2000
Government or
Private non-profit
institutes
Universities and
other Hugher
Education
Institutions
Professional
Conferences,
meetings and
journals
Fairs and
Exhibitions
Competitors
Suppliers
Other
Enterprises
within the
Enterprise Group
Clients
Within the
Enterprise
Innovating Enterprises with Highly important Sources (%)
Results - Innovation Sources of Highly Importance for Services
50
45
40
35
30
25
20
15
10
5
0
Proportion of Enterprises (%)
Results - Patenting
12.0
9.9
10.0
7.5
8.0
4.0
5.7
5.3
6.0
4.2
3.6
2.9
1.9
2.0
0.0
Non-Innovators
Innovators
Non-Innovators
Manufacturing
Innovators
Services
Enterprise applied for at least a Patent to Protect Inventions
Enterprise possess Valid Patents at the end of 2000
700
2,500
600
2,000
500
400
1,500
300
1,000
200
500
100
-
NonInnovators
Innovators
Manufacturing
NonInnovators
Innovators
Services
NonInnovators
Innovators
Manufacturing
NonInnovators
Innovators
Services
Number of Patent Applications for Goods/Services/Processes
Number of Valid Patents at the end of 2000 for Goods/Services/Processes
Number of Patent Applications for goods/Services
Number of Valid Patents at the end of 2000 for Goods/Services
Clear characteristic: the Portuguese companies ignore or do not choose to use patenting as a protection tool
Proportion of Enterprises Protecting
Innovations (%)
Results – Other Protection Methods Used
25.0
20.0
15.0
10.0
5.0
NonInnovators
Innovators
NonInnovators
Manufacturing
Innovators
Services
Non
Innovators
Innovators
National
Registration of Design Patterns
Trademarks
Copyright
Secrecy
Complexity of Design
lead-time advantage over competitors