Alimentar Mentalidades, Vencer a Crise Global

Transcrição

P18 Designing smart specialization
strategies in rural areas
Atas Proceedings
ISBN 978-989-8550-19-4
P18 · Designing smart specialization strategies in rural areas
Coordinators
Artur da Rosa Pires
(UA) [email protected]
Lívia Madureira
(UTAD/CETRAD) [email protected]
Martina Partoldi
(UA) [email protected]
The policy making paradigm towards rural development is changing in Europe and elsewhere (OECD, 2006). Smart specialisation strategies, the operational policy instrument to
apply the concept of place-based approach for development interventions, will deeply influence policy making in the coming years. Therefore, the design and implementation of smart
specialisation strategies in rural areas become a key issue. In fact, rural regions raise specific
challenges demanding new approaches to rural innovation. On the one hand, rural regions
tend to have less powerfull actors and weak knowledge resources. On the oher hand, rural
areas are extremely rich of latent resources (in the sense oh Hirschmann) as environment,
biodiversity, cultural resources, food, landscape, including relational resources. These characteristics are bound to have na impacto n policy design, which must be able to bring together
different actors, blend scientific and local knowledge, and act upon local resources towards
its valorization in both the local and global economy. Moreover, policy designshould be able
to stimulate collaborative approachesthat “effectively improve social capacity to guide interactions between nature and society towards more sustainable trajectories” (Madisen, 2012)
To promote the discussion and provide useful insights on the challenges, opportunities and
specificities of the next generation of rural development policies, making a contribution to
explore the relevance of the ‘new rural paradigm’ and ‘rural innovation’ in the contexto of the
current economic and socio-political crisis and to develop or improve relevant and spatially
sensitive analytic and policy-design tools.
4260 | ESADR 2013
SUSTAINABLE DEVELOPMENT AND GUIDANCE FOR ENTREPRENEURSHIP IN
UNFAVOURED REGIONS: THE CASE OF THE ALENTEJO REGION
Rui Manuel de Sousa Fragoso
University of Évora. Management Department. ICAM/CEFAGE. Apartado 94. 7000
Évora. Portugal. [email protected]
The unfavoured Portuguese regions have a level of life and economic growth rates
lower than favoured regions, and the mean of European Union and hence have less
entrepreneurial activities. The adoption of strategies of sustainable development driven
by entrepreneurship phenomena could be a viable solution. Thus, the likely
relationships between entrepreneurship and regional features were described, and
sources of entrepreneurship opportunities for strategies based on the own regional
resources and competitive advantages were identified. The paper concludes that for the
Alentejo region region, some habitat variables should be reinforced for promoting
entrepreneurship and sustainable development, and the main opportunities are related to
the economic activities that belong to the regional productive profile of specialization.
Key Words: Entrepreneurship; Sustainable development; strategic positioning; habitat
variables.
JEL Classification: M1; M13; M2 ; M20.
Atas Proceedings | 4261
VII Congresso da APDEA, V Congresso da SPER, I Encontro Lusófono em Economia, Sociologia, Ambiente
e Desenvolvimento Rural
SUSTAINABLE DEVELOPMENT AND GUIDANCE FOR ENTREPRENEURSHIP IN
UNFAVOURED REGIONS: THE CASE OF THE ALENTEJO REGION
1. Introduction
According to the Gross Domestic Production (GDP) per capita, the inner regions
of Portugal have a level of life and economic growth rates lower than littoral regions
and metropolitan regions of Lisbon and Porto, and below the mean of the European
Union (EU).
Nowadays these territories in general have lower development levels due to falls
in economic activity and employment which have led to the depopulation and hence to a
clear loss of territorial competiveness and low entrepreneurial behaviour. These
phenomena are not exclusive to the inner Portuguese regions and they can be observed
in many EU regions and in the World. In order to attempt counteract those negative
effects in the local economy and employment, the adoption of strategies of sustainable
development, driven by entrepreneurship phenomena seems to be a viable solution.
The term “sustainable development” arose for the first time at the United
Nations Conference on the Human Environment in 1972. Later it gained a great
importance in a report to the United Nations by the World Commission on Environment
and Development (WCED, 1987). Despite some controversy, sustainable development
has emerged as an increasingly influential concept in managerial and settings and has
become a mainstay of corporate strategy (Hall et al, 2010). Ambec & Lanoie (2008)
state, that the environmental responsibility is an opportunity for increasing revenues,
and indentifying some benefits from sustainability investments.
Inspired by the concept of “creative destruction” from Schumpeter (1942), some
authors argue that new sustainability pressures from society have created various types
of market failure, which open new opportunities to economic activity and for creating
new firms (Cohen & Winn, 2007; Hall & Vredenburg, 2003; Hart & Milstein, 1999;
Hart & Christensen, 2002; Senge & Carstedt, 2001). In this scope we can identify the
entrepreneurship as a mean for profiting from opportunities of market failures such as
environmental and social disruptions, in which Portuguese inner regions are very rich
and can be benefited by ameliorating its competitiveness and the welfare of their
populations.
2
4262 | ESADR 2013
Designing smart specialization strategies in rural areasP18
Based on the concepts of sustainable development and entrepreneurship, this
paper aims contributing to a better knowledge of development strategies that can be
followed in less favoured territories, such as the Portuguese and Mediterranean
unfavoured regions. The research question of this study is: which are the main regional
features that can promote the entrepreneurship phenomena in the Alentejo region,
southern Portugal? This question can be devised into the two following questions: 1)
Which are the specific advantages of the regional habitat that can be valorised for
promoting an entrepreneurial strategy? 2) Which are the regional economic activities
than could offer more sustainable entrepreneurship opportunities?
In order to response to these questions, the paper describes and compares
regional entrepreneurship variables and habitat variables within a more entrepreneurial
context, and attempts to find sources of sustainable development strategies based on
their own resources that can be driven by entrepreneurship phenomena.
The Alentejo region is a NUTS II in southern Portugal that in the European
Union is classified as an unfavoured region. This region is less developed and
entrepreneurial than the coastal favoured regions, but has also some important factors
for the sustainable development that can be considered as interesting opportunities for
entrepreneurship phenomena.
The rest of the paper is structured into five parts. Firstly we outline a brief
review
of
the
term
“sustainable
development”
and
its
relationships
with
entrepreneurship phenomena. Then the entrepreneurship dynamics and its habitat
factors are presented. The third part is devoted to the material and methods. The fourth
part presents and discusses the empirical results of the case of the Alentejo NUTS II.
The last part is devoted to main conclusions and remarks.
2. Sustainable development and entrepreneurship
According to the United Nations (WCED. 1987: 43), “Sustainable development
is development that meets the needs of the present generation without compromising the
ability of future generations to meet their own needs”. This intergenerational
relationship suggests the confluence of economic, social and environmental objectives,
which some authors place equally at the same level (Hall et al., 2010).
3
Environment and economy were considered by long time as opposed fields,
where the decision taking was based on exploring the trade-offs between the objectives
of the maximum economic growth and the minimum resource degradation. Recently,
the introductions of economic criteria in the management of environmental resources,
allowed reconcile this conflict.
The developing World is adopting development models similar to ones used by
the first World in the past. However, but the Planet does not have enough resources to
support equitable levels of development in all over the World. Balakishnan et al. (2003)
argue a significant dampening, if not a devolution of development will be need to
achieve sustainability, which means that economic growth should be reduced. Unlike,
industrial and developing countries are unable for accepting reductions on economic
growth, and consequently on the social well-being.
In order to attempt a response for this problem, innovation could promote many
of the necessary economic and social transformations, such as firms delivering
sustainable products and services. However, other authors are sceptical of existing
business and believe that changes will be driven by entrepreneurs. Nowadays there is
the perception that green, clean and low-carbon entrepreneurs will somehow give an
important contribution for not dampen economic growth and for creating more new jobs
(WWF, 2009; Stern, 2007).
The entrepreneurial economics literature offers considerable insights into how
sustainable development can be achieved (Knight, 1921; Baumol, 1990; Hall et al.,
2010; Pacheco et al., 2010; York & Venkatatraman, 2010; Hockerts & Wütenhagen,
2010; Parrish, 2010; Kuckertz & Wagner, 2010).
3. The scope of entrepreneurship and habitat factors
In many cases entrepreneurship either is associated with individual behaviour or
is related to the creation and running of one’s own firm (Davidsson, 2005).
The importance of entrepreneurship in economic growth has become a major
topic in economics after Shumpeter (1942). Since then researchers from different areas
such as accounting, finance, management, marketing, political science, psychology, and
sociology have studied the relationship between entrepreneurship and economic growth
(Ireland & Webb, 2007).
4
4264 | ESADR 2013
Many studies recognize firm creation as the most important driver of regional
entrepreneurship and economic growth (Acs & Armington, 2004; Audretsch &
Keilbach, 2005). However, the co-evolutionary theory demonstrates that an important
issue that should be considered in understanding regional entrepreneurial activities is
that firm birth and death are highly dependent on regional characteristics and
entrepreneurial habitat (Kim et al., 2012). This theory suggests that business entities and
environments influence each other and reciprocally co-evolve together and not that the
entities simply adapt to their environments, as argue some studies of adaptationselection of an organization (Lewin & Volberda, 1999; Lewin et al., 1999; Porter, 2006;
Tsai et al., 2009).
The tendency for firms to stay in their origin region is great because its resources
are established and or utilized at a local level. This geographical inertia highlights the
importance of the localized networks of contacts for entrepreneurial activities and firm
creation (Sorenson & Audia, 2000; Tamasy, 2006). Among main factors that are
associated with the arising of entrepreneurship phenomena, literature presents
population size, income level, number and type of Research and Development (R&D)
employees, educational degrees, university R&D, creativity, foreign population,
political structure, land costs, taxes, natural amenities, and other (Armington & Acs,
2002; Audretsch & Lehmann, 2005; Brixy & Grotz, 2007; Kirchhoff et al., 2007; Lay,
2003; Lee et al., 2004; Spilling, 1996; Wang, 2006; Woodward et al., 2006).
A knowledge-based society is another important factor for influencing
entrepreneurship. Among structural interpretation of regional factors, the triple helix
model that characterizes university-industry-government relationships has been
increasingly recognized as an important source of regional innovation that drives the
transformation of scientific and technological outcomes into economic outcomes. This
model has been broadly studied in the context of regional development (Etzkowitz et
al., 2000; Leydesdorff et al., 2006; Poweell & DiMaggio, 1991). Kim et al. (2012)
investigated the determinants of entrepreneurship phenomena with basis on the
interrelations among university-industry-government and conclude that the triple helix
model only has influence in lower entrepreneurial or unfavoured regions, if habitat
features and strategies had been established previously. Innovation is increasingly based
5
on the interaction among the components of the triple helix model (Etzkowitz & Zhou,
2007; Leydesdorff & Vanden Besselaar, 1994).
Habitat factors define the entrepreneurial environment in which the triple helix
model can be established. The main habitat factors that usually are considered in
previous studies include creativity and diversity indices (Lee et al., 2004), ratio of
immigrants or foreign people (Kirchhoff et al., 2007; Saxenian, 2002), crime, health
care, and climate indices (Goldstein & Drucker. 2006) and natural amenities
(Woodward et al., 2006). In addition, quality of life seems to be an important factor
among habitat related variables (Kim et al., 2012; Goldstein & Drucker, 2006).
4. Material and methods
In order to contribute to the purpose of this paper, a research strategy based on
the case of the Alentejo region (NUTS II) in southern Portugal was adopted. Alentejo is
a region near Lisbon city (140 Km by motorway) that represents one third of the
Portuguese territory, but only 7% of its population. Its geographic limits are the Atlantic
Ocean to the west, Spain to the east, the Tejo river to the north, and the Algarve region
to the south. This is a low entrepreneurial region that represents well many
Mediterranean unfavoured regions in the EU, and the challenges with which they are
faced nowadays.
The method of benchmarking is used to compare variables of the Alentejo
region (NUTS II) with the Lisbon region (NUTS II) and Portugal. According to EU
criteria, the Lisbon region is considered a favoured European region with a GDP per
capita higher than the EU27 average and hence is well suited to be considered as an
entrepreneurial benchmarking by opposite to unfavoured regions, such as the Alentejo
region. Then, in order to find sources of strategic opportunities for the sustainable
development, the market positioning and the regional productive profile are identified
with basis on regional resources and strengths.
The entrepreneurship variables are interpreted as response or dependent
variables and the habitat variables are considered as the independent variables that may
explain entrepreneurship phenomena. According to Kim et al. (2012), many studies use
as entrepreneurship variables the birth and death rates of firms. In this case the global
and sectorial firm birth rates, the firm survival rate at two years, the number of workers
6
4266 | ESADR 2013
by created firm, and the percentage of firm birth of mean and high technology were
considered. The data used are from the Indicators of Firms in 2009 (INE, 2011).
According to the literature, the habitat variables were grouped into variables of
triple helix model, population and economics.
For the triple helix, in the scope of university sphere several authors use as
variables university and college R&D expenditures (Acs et al., 2002; Goldstein &
Drucker, 2006; Kinchhoff et al., 2007; Woodwar et al., 2006) or the rate of people who
attained university degrees in the region. In the cases of government and industry, the
variables often used are government R&D expenditures and tax rate, and venture capital
investment, respectively (Kim et al., 2012; Malecki, 1990; Spilling, 1996). Due to the
structure of the available data concerning the territorial levels of the country, NUTS II
and NUTS III, we used as triple helix variables the rate of people with a university
degree, the percentage of people that are enrolled in C&T university programmes and
the percentage of the Gross Added Value (GAV) from firms of mean or high
technology.
Kim et al. (2012) use the natural log of state population, the natural state average
annual pay and the percentage of foreign people as demographic factors. In our case we
use the population size (thousand peoples), the population density, the effective growth
rate of the population, and the percentage of foreign people in the population.
The economic variables are used to frame the habitat context of entrepreneurship
phenomena and for assessing productivity of resources, and trends on regional
productive specialization. The variables considered are the percentage of GDP in the
region, the GDP per capita, work productivity, average remunerations, the human
resource utilization rate, and the percentage of GAV in agriculture and extractive
activities, industry and building and commerce, and services.
The regional strategic positioning is given by the regional market positioning of
the region and by its regional productive profile.
The market positioning depends on the regional competitive advantage (CA) and
market position in terms of the international commerce. The competitive advantage
represents the advantage of the region a (Alentejo) for a given activity j in terms of the
international commerce, and can be determined by the following indicator:
7
 =
 
×
 
Where, X are the exports, the index p is related to the reference territory (Portugal). A
CAja greater than 1 means that the activity j in the region a has a competitive advantage
over the reference territory (Portugal).
The market position (MP) reveals the market share of a regional activity in a
broadly context, which in our case are the Portuguese exports. This indicator is obtained
for a given activity at regional level from the respective net balance between exports
and imports divided by total exports of the activity:
 =
 − 

Where, X and W are the exports and imports, respectively.
Thus, considering the possible results of CA and MP we have the following four
market positioning: i) markets with competitive advantage and positive market position;
ii) markets with competitive advantage and negative market position; iii) markets
without competitive advantage and negative market position; markets without
competitive advantage and positive market position;
The regional productive profile is the productive specialization of a region in
which are relevant opportunities for entrepreneurship phenomena that can be carried out
in a context of sustainable development. These are indentified considering the
coefficient of localization and the share they have in employment, as follows:.
 =
 
×
 
Where, Y could be turnover or employment, and j, a and p are relative to the economic
activity, region (Alentejo) and reference territory (Portugal), respectively. A QL equal to
zero means that the activity j does not exist in the region a and a QL equal to 1 means
that the regional specialization degree is equal to the one of the reference territory. A
QL greater than 1 indicates that the region a is more specialized than the reference
territory p for producing the activity j.
In order to find the regional productive specialization we consider the economic
activities that have simultaneously a QL greater than 1 and represent more than 1% of
the regional employment.
8
4268 | ESADR 2013
5. Empirical results
Table 1 presents entrepreneurship and habitat variables for Portugal and NUTS
II of Lisbon and Alentejo, from which we can do some interesting observations.
Table 1. Entrepreneurship and habitat variables for Portugal and NUTS II
of Lisbon and Alentejo
Units
Entrepreneurship variables
Portugal
Lisboa
Alentejo
Firm birth rate
%
Firm birth rate in processing industry
%
Firm birth rate in building
%
Firm birth rate in commerce and services
%
Firm survival rate after 2 years
%
Average workers at firm birthed
Nº
Proportion of firms births of mean and high
%
technology
Triple helix variables
15.09
7.67
10.54
16.33
49.36
1.28
1.96
16.88
9.02
12.61
17.62
44.96
1.24
2.75
14.95
7.54
11.11
16.07
49.52
1.22
1.42
Gross Added Value in firms of mean and high
%
technology
Rate of people with an university degree
%
People enrolled in university C&T programmes
%
Population variables
10.62
15.34
3.79
31.5
28.9
44.9
28.5
21.3
21.5
Population size
Population density
Population effective growth rate
Population between 0-14 years old
Population with more than 65 years old
Proportion of foreign population
1000 people
people/Km2
%
%
%
%
%
%
Economic variables
Percentage of Gross Domestic Production - GDP
GDP per capita
Firm density
Work productivity
Average remunerations
Human resources utilization rate
Gross Added Value in agriculture and extractive
activities
Gross Added Value in industry and building
Gross Added Value in commerce and services
10.636.979 2.839.908 749.055
115.4
946
23.7
-0.01
0.32
-0.58
15.11
16.25
13.33
10.93
9.96
9.88
55.80
55.76
53.67
18.16
18.03
23.12
4.17
7.79
3.56
%
1000 Euros
Nº/Km2
1000 Euros
1000 Euros
%
%
100.0
16.19
11.5
47.43
19.50
48.39
2.4
37.1
22.71
108.3
46.09
23.70
52.33
0.4
6.5
14.85
2.1
51.39
18.20
41.63
9.4
%
%
24.6
73.0
16.9
82.7
28.2
62.4
Source: INE, 2011
Concerning entrepreneurship variables, firm birth rate in Alentejo (14.95%) is
very similar to the Portuguese average (15.09%) and 12% less than the Lisbon region.
9
The proportion of births firms of mean and high technology in the Lisbon region (2.75)
is almost double of the Alentejo and 40% more than the Portuguese average. Firm
survival rate after 2 years in Alentejo is 49.52%, this is, very close to the Portuguese
value (49.36%), while in Lisbon it is only 44.96%.
All triple helix variables in Alentejo present lower levels than ones of Lisbon
and Portugal. For instance the GAV associated to firms of mean and high technology in
Alentejo is only 3.79%, this is, five times less than in Lisbon and a tier of Portugal.
These suggest that the regional strategy of the triple helix should be redefined in order
that the activity of university organizations be more focused on the regional sustainable
development problems, and for promoting more entrepreneurial activities.
Alentejo represents only 7% of the Portuguese population, while this percentage
in Lisbon exceeds 25%. The population density is very low (23.7 people/Km2),
compared to Lisbon (946 people/Km2) and Portugal (115.4 people/Km2). In addition to
being lowly populated, Alentejo´s population is also aged with a higher percentage of
dependent people and a lower percentage of people in active age than in Lisbon and
Portugal. The population effective growth rate in Alentejo is negative (-0.58%) showing
that in the last decade the region was unattractive compared to other Portuguese regions.
Another indicator used for assessing the entrepreneurial habitat is the proportion of
foreign people in the population. Alentejo presents also the lowest value (3.56%), which
is 85% and 45% of the values of Portugal and Lisbon, respectively.
In economic terms Alentejo represents 6.5% of Portuguese GDP, which is
almost its contribution for the population. However, Lisbon, represents 26% of
population and 37.1% of the GDP. In addition, the GDP per capita in Alentejo (14.85
thousand euros) shows a level of life below Lisbon (22.71 thousand euros) and the
Portuguese average (16.19). These results can be partially explained by the low firm
density in Alentejo (2.1 firms/Km2), when compared with Portugal (11.5 firms/Km2)
and Lisbon (108.3 firms/Km2).
In Alentejo work productivity is 11% and 8% higher than in Lisbon and
Portugal, and wages are 23% and 7% lower, respectively. The highest work productivity
and the lowest average remunerations can be a competitive advantage for
entrepreneurship phenomena, namely at the level of new firm creation. Despite some
revealed competiveness in the work factor, the human resources utilization rate in
10
4270 | ESADR 2013
Alentejo is only 41.63%, this is, 20% and 14% less than in Lisbon and Portugal,
respectively. The GAV per economic sector shows for the Alentejo NUTS II a high
importance of agriculture and extractive activities (9.4%) and industry and building
activities (28.2%), and a minor importance of commerce and service activities (62,4%).
In Portugal and Lisbon, agriculture and extractive activities only represent 0.4% and
2.4% of GAV, but commerce and services has the majority of the GAV, representing
82.7% and 73%, respectively.
Table 2 presents the market positioning indicators in terms of the international
commerce for the Alentejo NUTS II
Table 2. Market positioning in the international commerce of Alentejo NUTS II
Competive
advantage
Market
position
Live animals and animal products
1.0
-3.1
Vegetable products
3.8
5.5
Animal or vegetable fats and oils waxes and others
0.8
2.4
Products of food industries, beverages, tobacco and others
1.7
5.7
Mineral products
2.9
7.1
Products of chemical industries
2.5
7.7
Plastics and rubber articles
2.2
8.9
Hides, leather, articles of travel, bags and others
1.2
-2.5
Wood, cork and articles, and basketry
0.5
1.9
Wood pulp, paper and paperboard articles
0.1
-0.4
Textiles and textile works
0.2
-0.5
Shoes, hats, umbrellas, canes and others
0.0
-0.2
Articles of stone, ceramic, and glass
0.6
2.5
Pearls, precious metals, jewellery, coins
0.0
-2.4
Base metals and articles
0.4
-1.8
Machinery and electrical equipment
0.8
0.1
Transport equipment
0.2
-12.5
Optical, photo, watches and others
0.6
1.1
Arms and ammunition. parts and accessories
0.0
-1.0
Merchandises and diverse products
0.4
2.2
Works of art, collectors' pieces and antiques
0.0
0.2
Source: INE, 2011.
11
The economic activities that have the best market positioning are those that have
a competitive advantage and a positive market position, which are in the case of the
Alentejo NUTS II the following: vegetable products; product of food industries,
beverages, tobacco and others; mineral products; products of chemical industries; and
plastics and rubber articles. These activities present a market positioning more
favourable than the Portuguese context, once they benefit from a regional competitive
advantage and from a competitive position in markets. So these activities may be
associated to the best opportunities for entrepreneurship, because they are competitive
and less exposed to competition, and have a good potential for creating more value
added.
Economic activities with competitive advantage, but with a negative market
position are in Alentejo: live animals and animal products; and hides, leather, articles
of travel bags and others. In these activities the Alentejo NUTS II has a competitive
advantage expressed by a proportion of exports greater than Portugal.
With a positive market position, but without a competitive advantage we can
find the following economic activities: wood, cork and articles, and basketry; articles of
stone, ceramic, and glass; optical, photo, watches and others; and merchandises and
diverse products. The Alentejo NUTS II does not have a competitive advantage in these
economic activities, because its exports are proportionally lower than in Portugal.
However, the market position reveals that there is a good demand for products, which
may also be an entrepreneurship opportunity.
Remaining activities are few competitive because, both regional imports are
greater that exports and there are other regions in Portugal with more competitive
advantages that produce the products better.
The regional productive specialization is defined by economic activities that
have a coefficient of localization greater than 1 and a weight on the regional
employment greater than 1%. Table 3 presents the employment structure and the
coefficient of localization in the Alentejo NUTS II by economic activity.
The Alentejo NUTS II has a very strong position into the production of activities
from the branch of agriculture, forest and fisheries given its high value of the
coefficient of localization (QL=8.7) and the weigh on the regional employment
(12.1%). Extractive industries have also a great regional specialization degree with a
12
4272 | ESADR 2013
QL equal to 11.6 and represent 1.4% of the regional employment. Manufacturing
industries have an important weight in the regional employment (20.2%) and reveal a
QL of 1.4. Accommodation, catering and similar are economic activities that are
associated to the tourism industry, and in Alentejo represents 6.6% of employment and
has a degree of specialization 30% higher than in Portugal (QL=1.3).
Table 3. Employment structure and the coefficient of localization the
NUTS II of Alentejo by economic activity
Employment
structure
Coefficient of
localization
12.1%
8.7
1.4%
11.6
20.2%
1.4
Electricity, gas steam, hot and cold water and cold air
0.0%
0.0
Collection purification and distribution of water, sanitation management
waste and pollution
0.7%
1.5
Building
11.9%
0.7
Wholesale and retail trade, repair of vehicles and motorcycles
19.0%
1.0
Transport and storage
3.2%
0.7
Accommodation, catering and similar
6.6%
1.3
Information and communication
0.3%
0.0
Financial intermediation and insurance
0.8%
0.4
Real state
0.7%
0.5
Scientific and technical activities
2.5%
0.5
Administrative and support services
3.2%
0.5
Administration, defence and compulsory social security
2.3%
5.2
Education
1.5%
0.4
10.2%
0.7
Arts, entertainment, sport and recreation
0.5%
0.4
Other services
2.9%
2.3
Agriculture, forest and fisheries
Extractive industries
Manufacturing industries
Human health and social support
Source: GEP, 2008
The regional specialization degree is also high in the activities from the branch
of administration, defence and compulsory social security, which present a QL of 5.2%
and a weight of 2.3% in the regional employment structure. The wholesale and retail
trade, repair of vehicles and motorcycles, which represent an important set of service
13
and commerce activities, show in Alentejo a degree of specialization similar to Portugal,
as well as, its weight in the employment.
6 – Conclusion
In this paper, we studied how the Alentejo region in southern Portugal can profit
from entrepreneurship phenomena for achieving a sustainable development. The likely
relationships between entrepreneurship and regional features were described, and
strategies based on the own regional resources and competitive advantages were
identified as opportunities for entrepreneurship phenomena.
Results showed that the Alentejo NUTS II, has, less entrepreneurial activities
than Portugal and the Lisbon NUTS II, but the firm survival rate after two years is
greater. The less entrepreneurial activities in the Alentejo NUTS II are clearly explained
by low performance of triple helix, population and economic variables. However, there
are some habitat variables that may help to raise more entrepreneurial activities in the
Alentejo NUTS II, such as good levels of work productivity and the proportion of
people enrolled in university C&T programmes, and lower wages and scale and scope
economies in some sectors related with production of tradable goods.
Another interesting conclusion that results suggest, is the need for redefining the
regional triple helix strategy in order for it to become more focused in regional values
and competitive advantages, namely in terms of I&D and technology transfer.
The economic strategic positioning of the Alentejo NUTS II leads us to conclude
that agribusiness, tourism business and other business in activity braches related to
specific social and environmental disruptions are important sources of entrepreneurship
commons to the entire region. In addition there are other economic activities associated
to specific local resources, skills, and economic and social relationships, such as the
cases of direct foreign investment in manufacturing industries of mean and high
technology, the University of Évora, people enrolled in C&T programmes, the industrial
complex of Sines in the Alentejo Litoral NUTS III, or the strong specialization in
extractive industries.
Results and conclusions for the Alentejo region give interesting highlights for
promoting strategies of sustainable development driven by entrepreneurship phenomena
in other Portuguese and Mediterranean regions.
14
4274 | ESADR 2013
References
Acs, Z.J., Armington, C. (2004). Employment growth and entrepreneurship activity in
cities. Regional Studies, 38: 911-927.
Acs, Z.J., Anselin, L., Varga, A. (2002). Patents and innovation counts as measures of
regional production of new knowledge. Research Policy, 31: 1069-1085.
Ambec, S., Lanoie, P. (2008). Does it pay to be green? A systematic overview.
Academy of Management Perspectives, 22(4): 45-62.
Armington, C., Acs, Z.J. (2002). The determinants of regional variation in new firm
formation. Regional Studies, 36: 33-45.
Audretsch, D.B., Keilbach, M (2005). Entrepreneurship capital and regional growth.
Annals of Regional Science, 39: 457-469.
Audretsch, D.B., Lehmann, E.E. (2005). Does the knowledge spillover theory of the
entrepreneurship hold for regions? Research Policy, 34:1191-1202.
Balakishnan, U., Duvall, T., Primeaux, P. (2003). Rewriting the bases of capitalism:
reflexive modernity and ecological sustainability as the foundations o a new
normative framework. Journal of Business Ethics, 47(4): 299-315.
Baumol, W. (1990). Entrepreneurship: productive, unproductive, and destructive.
Journal of Political Economy, 98(5): 893-921.
Brixy, U., Grotz, R. (2007). Regional patterns and determinants of birth and survival of
new firms in Western Germany. Entrepreneurship and Regional Development,
19: 293-312.
Cohen, B., Winn, M.L. (2007). Market imperfections, opportunity and sustainable
entrepreneurship. Journal of Business Venturing, 22(1): 29-49.
Davidsson, P. (2005). Researching Entrepreneurship. Springer, New York.
Etzkowitz, H., Zhou, C. (2007). Regional innovation initiator: the entrepreneurial
university in various triple helix models. In: Triple Helix 6th Conference Theme
Paper, Singapure.
Etzkowitz, H., Webster, A., Gebhardt, C., Terra, B.R.C. (2000). The future of the
university and the university of the future: evolution of ivory tower to
entrepreneurial paradigm. Research Policy, 29:313-330.
Gabinete de Estratégia e Planeamento (GEP) (2008). Quadros de Pessoal 2008.
Ministério do Trabalho e da Solidariedade Social
15
Goldstein, H., Drucker, J., 2006. The economic development impacts of universities on
regions: do size and distance matter? Economic Development Quarterly, 20: 2243.
Hall, J.K., Daneke, G.A., Lenox, M.J. (2010). Sustainable development and
entrepreneurship: Past contributions and future directions. Journal of Business
Venturing, 25: 439-448.
Hall, J.K., Vredenburg, H. (2003). The challenges of innovation for sustainable
development. Sloan Management Review, 45(1): 61-69.
Hart, S., Christensen, C. (2002). The Great Leap: driving innovation from the base of
the pyramid. MIT Sloan Management Review, 44(1): 51-56.
Hart, S., Milstein, M. (1999). Global sustainability and the creative destruction of
industries. Sloan Management Review, 41(1): 23-33.
Hockerts, K., Wütenhagen, R. (2010). Greening Goliaths versus emerging Davids –
Theorizing about the role of incumbents and new entrants in sustainable
entrepreneurship. Journal of Business Venturing, 25(5): 481-492.
INE – Instituto Nacional de Estatística (2011). Statistical Yearbool of Alentejo Region
in 2010.
Ireland, R.D., Webb, J.W. (2007). A cross-disciplinary exploration of entrepreneurship
research. Journal of Management, 33: 891-927.
Kim, Y., Kim, W., Yang, T. (2012). The effect of the triple helix system and habitat on
regional entrepreneurship: Empirical evidence from US. Research Policy, 41:
154-166.
Knight, F.H. (1921). Risk, Uncertainty, and Profit. Houghton Mifflin, Boston, MA.
Kirchhoff, B.A., Newbert, S.L, Hasan, I., Argmington, C. (2007). The influence of
university R&D on new business formations and employment growth.
Entrepreneurship Theory and Practice, 31: 543-559.
Kuckertz, A., Wagner, M. (2010). The influence of sustainability orientation on
entrepreneurial intentions – investigating the role of business experience.
Journal of Business Venturing, 25(5): 524-539.
Lay, T.J. (2003). The determinants of the interaction between entry and exist in
Taiwan’s manufacturing. Small Business Economics, 20: 319-334.
16
4276 | ESADR 2013
Lee, S.Y., Florida, R., Acs, Z.J. (2004). Creativity and entrepreneurship: a regional
analysis of new firm formation. Regional Studies, 38: 879-891.
Lewin, A.Y., Long, C.P., Carroll, T.N. (1999). The coevolution of new organizational
forms. Organization Science, 10:535-550.
Lewin, A.Y., Volberda, H.W. (1999). Prolegomena on coevolution: a framework for
research on strategy and new organizational forms. Organization Science, 10:
519-534.
Leydesdorff, L., Dolsfsma, W., Van der Panne, G. (2006). Measuring the knowledge
base of an economy in terms of triple-helix relations among technology,
organization and territory. Research Policy, 35: 181-199.
Leydesdorff, L., Vanden Besselaar, P. (1994). Evolutionary Economics and Chaos
Theory: New Directions in Technology Studies. St. Martin’s Press, New York
Malecki, E.J. (1990). New firm formation in the USA: corporate structure, venture
capital, and local environment. Entrepreneurship and Regional Development, 2:
247-265.
Pacheco, D.F., Dean, T.J., Payne, D.S. (2010). Escaping the green prision:
Entrepreneurship and the creation of opportunities for sustainable development.
Journal of Business Venturing, 25(5): 464-480.
Parrish, B.D. (2010). Sustainability-driven entrepreneurship: Principles of organization
design. Journal of Business Venturing, 25(5): 510-523.
Porter, T.B. (2006). Coevolution as a research framework for organizations and the
natural environment. Organization Environment, 19: 479-504.
Poweell, W.W., DiMaggio, P.J. (1991). The New Institutionalism in Organizational
Analysis. University Press, Chicago.
Saxenian, A. (2002). Silicon Valley’s new immigrant high-growth entrepreneurs.
Economic Development Quarterly, 16: 20-31.
Senge, P., Carstedt, G. (2001). Innovating our way to the next industrial revolution.
Sloan Management Review, 42(2): 24-38.
Shumpeter, J.A. (1942). Capitalism, Socialism and Democracy. Harper and Row, New
York.
17
Sorenson, O., Audia, P.G. (2000). The social structure of entrepreneurial activity:
geographic concentration of footwear production in the United States, 19401989. American Journal of Sociology, 106: 424-461.
Spilling, O.R. (1996). Regional variation of new firm formation: the Norwegian case.
Entrepreneurship and Regional Development, 8: 217-243.
Stern, N. (2007). The Economics of Climate: The Stern Review. The Cambridge
University Press, London.
Tamasy, C. (2006). Determinants of regional entrepreneurship dynamics in
contemporary Germany: a conceptual and empirical analysis. Regional Studies,
40: 365-384.
Tsai, F.S., Hsieh, L.H.Y., Fang, S.C., Lin, J.L. (2009). The co-evolution of business
incubation and national innovation systems in Taiwan. Technological
Forecasting and Social Change, 76: 629-643.
Wang, S.W. (2006). Determinants of new firm formation in Taiwan. Small Business
Economics, 27: 313-321.
WCED – The World Commission on Environment and Development (1987). Our
Common Future. Oxford University Press, New York.
Woodward, D, Figueiredo, O., Guimarães, P. (2006). Beyond Silcon Valley: university
R&D and high-technology location. Journal of Urban Economics, 60: 15-32.
WWF (2009). Low Carbon Jobs for Europe. World Wide Fund for Nature, London.
York, J.G., Venkatatraman, S. (2010). The entrepreneur-environment nexus:
Uncertainty, innovation, and allocation. Journal of Business Venturing, 25(5):
449-463.
18
4278 | ESADR 2013
POLICY DESIGN AND ITS INFLUENCE ON LAND USE CHANGE
IN TRADITIONAL VINEGROWING IN REMOTE AREAS OF
GREECE: AN APPLICATION OF THE THEORY OF PLANNED
BEHAVIOUR
Evgenia Michaa, Richard Trantera, Alison Baileya
School of Agriculture Policy & Development, University of Reading, Reading, UK
Keywords: Viticulture, Non-linear PCA, Farming Systems, Ordered Probit, Sample
selection
Vine-growing in Less Favoured Areas is facing multiple challenges that may cause its
abandonment. The consequences are changes in land use that affect not only the
environment and the landscape but also the economic and social structure of these areas.
Vine-growing has been proposed as a promising income and employment generator that
could also help maintain special area characteristics. European Union Rural
Development Schemes offer the opportunity to rural households to finance the
development of vine-growing activities. However, in areas where vine-growing has
growth potential, there is a decline of agricultural activities and unwillingness of
farmers to adopt Rural Development Schemes. The objective of the study this paper was
based on, was to identify farm, and policy design that affect farmers’ decision to
continue vine-growing by participating in multifunctional schemes, using the Theory of
Planned Behaviour. A cross-sectional survey explored attitudes towards viticulture and
Rural Development, in three remote areas of Greece, including insular and mountain
areas. The empirical findings highlighted the impact of the Greek financial crisis on
continuation of vine-growing, and the need for policies that encourage social change,
provide locally based marketing channels and facilitate access to decision making
centres. Administrative structure and lack of transparency in law application were found
to mostly influence the participation of vine-growers in multifunctional schemes.
INTRODUCTION
In Greece, 82.7% of the country’s total agricultural land is in Less-Favoured Areas
(LFA) and around 28.5% of its population is a permanent LFA resident (Hellenic
Ministry of Agricultural Development and Food, 2007). Agricultural systems in these
areas are traditional and extensive. Vines are a dominant perennial crop often planted on
terraces, of great aesthetic value, which, in the last 15 years is being constantly
abandoned, as farmers seek other employment opportunities. In these areas the biggest
threats to agricultural land use are scarcity of resources, soil erosion, very low
productivity, and tourism, the infrastructure requirements of which, cause great
competition with agriculture for land and labour resources (Kizos et al., 2009;
Tzanopoulos et al., 2011). Especially, for the vine-growing sector, low product prices,
high labour demands and seasonality are also important drivers of abandonment.
In recent years, a change in lifestyle of the urban population has created a demand for
traditional landscapes and ways of life. Thus, a farm does not have only a production
function but it is a multifunctional system that can fulfill many different operations in
order to cover the demands of society. Also, lately, as Greek households are faced with
economic challenges, there has been a lot of talk about residents of the LFAs returning
to farming activities, including vine-growing. However, despite the expectations for an
increase in the number of active vineyards vine-growing land continues to be abandoned.
Abandonment of vine-growing activities is interesting to various sectors. Firstly,
abandonment of viticulture could lead to the reduction of supply of grapes to the wine
manufacturing industry. Secondly, it is interesting to policy makers because not only
abandonment as a phenomenon has great impact on the social and economic structure of
these areas but more importantly has immense impact on the landscape and the
environment. Thirdly, when examined under the light of the fiscal crisis in Greece, there
is an interest in the well-being of farmers because abandonment is often related to
poverty, unemployment and policy effectiveness (Papadopoulos and Papanikos (2005).
The role of the farmer as a protector of natural environment has been recognized by the
EU since 1992, through the introduction of the second pillar of the CAP, and the
creation of measures towards a model of rural development through multifunctional
agriculture (Gidarakou et al., 2004). In an attempt to maintain the rural population and
2
4280 | ESADR 2013
promote multifunctional activities, the EU has created a Rural Development Fund that
includes several support measures for farmers in LFAs. The Rural Development Policy
is implemented in Greece through the Rural Development Program (RDP). This
includes measures for the vine-growing sector consisting of financial grants and
compensations to vine-growers that are willing and eligible to perform one or more
multifunctional strategies. Three measures are included in the program for the vinegrowing sector: a) a subsidy scheme for adoption of organic practices, which
compensates vine-growers for income losses from being organic, based on organic
certifications from authorized agencies b) a subsidy scheme for improvement or
restoration of a vineyard in the form of aid, where eligible farmers are compensated for
up to 80% of an investment made on the improvement of farm infrastructure and c) a
subsidy scheme for investment on agri-tourist activities, involving compensation of up
to 80% of investments made on non-farming activities on farm, related to tourist
accommodation or recreation. These measures were intended to be very important for
the viability of the sector in areas where it is an essential part of rural production. But,
in Greece, the adoption rate of these measures is not as high as expected by the policy
makers (Karanikolas and Martinos, 2007).
Vine-growers participation in these measures is voluntary. So, it is well established that
the success of implementation of multifunctional adjustment strategies depends on the
willingness of farmers to participate in them and this is, to an extent, related to farmers’
acceptance of their multifunctional role. In Greece, policy makers have been trying to
motivate farmers to adopt multifunctional strategies by compensating them. But, the
adoption of these functions by the farmers goes beyond profit maximization and
depends, also, on motives, attitudes and opinions, and the perception of their social
identity
This paper aims to identify the factors affecting farmers’ willingness to participate in
multifunctional schemes, by explaining their views and attitudes using the framework of
the Theory of Planned Behaviour. TPB was developed by Ajzen (1991) to explaining
human behaviour. The main construct of the theory is that a person would behave
rationally, according to their beliefs regarding a particular behaviour, divided into three
categories: behavioural beliefs, normative beliefs and control beliefs. Behavioural
beliefs are the personal beliefs of a person towards the outcome of a behaviour,
normative beliefs are related to an individual's perception of social pressure for
3
performing a specific behaviour and control beliefs refer to a person's perception of the
factors that may facilitate or impede the person's control over the behaviour.
Behavioural beliefs lead to favourable or unfavourable attitudes towards a behaviour,
normative beliefs lead to subjective norms and control beliefs produce perceived
behavioural control, which according to Ajzen (1991) are the three factors that influence
a person’s intention to behave in a particular way.
Also, this study classifies vine-growing systems and incorporates them in the analysis to
explore their influence on farmers’ intentions. Apart from these factors, the economic
recession taking place in Greece, and the existence of institutional corruption are also
taken into account as factors that may impact on farmers’ decisions. The three
adjustment strategies proposed by the RD program are also assessed here.
Most of the research on willingness to participate in multifunctional schemes in Europe,
has focused on agri-environmental schemes and examine decision making based on the
characteristics of the farmer as the decision maker. This is because in many countries
farms are family businesses in which the manager and the labour force come from
within the family (Ondersteijn et al., 2006). Four different approaches have been
identified: a) the financial approach, according to which farmers decisions are based on
profit maximization criteria (Bougherara and Latruffe, 2010; Genious et al., 2006;
Sintori et al., 2009). b) the spatial approach that examines farmers’ intentions from a
geographical point of view (Lange et al., 2013; Wilson, 2009) c) the social demographic
approach, where decision making is mainly based on demographic and structural
characteristics of the farms and on the nature of the measure to be adopted (Broch et al.,
2012; Mathijs, 2003; Tore, 2003; Vanslembrouck et al., 2002) and d) the behavioural
approach that investigates intentions through farmers behaviour views and attitudes
(Blackstock et al., 2010; Burton et al., 2008; Emery and Franks, 2012; Ingram et al.,
2013; Rehman et al., 2007).
Many of the studies using behavioural approaches use the Theory of Planned Behaviour
as their theoretical background with farm and farmers’ characteristics incorporated to
account for socio-demographic factors (Areal et al., 2012; de Graaff et al., 2010; de
Lauwere et al., 2011; Gorton et al., 2008; Hansson et al., 2012; Läpple and Kelley, 2013;
Mattison and Norris, 2007). However, although identification and classification of
farming systems appears in many studies (Morgan-Davies et al., 2012; O’Rourke et al.,
2012), there are no studies that use these systems as explanatory factors of farmers’
4
4282 | ESADR 2013
behavior. Perception of corruption is also a factor that has never been quantified and
used in behavioural studies, especially in agricultural research. Finally, perception of the
recession, also, has not been measured yet, neither has it been used in a behavioural
context.
In Greece, the decision making of vine-growers has been assessed by Papadopoulos and
Papanikos (2005) who examined labour allocation preferences of vine-growing
households on a Greek island, and Oxouzi (2008) who investigated the adoption of
organic viticulture by vine-growers of Central Macedonia first study focuses on an
island but does not include all LFA categories, and the second classifies vine-growing
systems into organic and conventional. None of the two includes behavioural factors,
interaction with authorities and perception of the financial crisis.
METHODOLOGY
Data collection
Three Greek areas with substantial vine-growing activity were chosen for the study,
namely, the mountain area of Ioannina, the island of Samos and the coastal area of
Kavala, because they represent the three types of Less Favoured Areas in Greece
(mountain, islands and areas with special handicaps).
Data collection consisted of qualitative in-depth interviews with farmers and other
sector stakeholders of the sector, followed by a survey using a questionnaire addressing
vine-growers in the areas of study. The main purpose of the face to face interviews was
to understand, the vine-growers' decision making process, and to allow farmers to
openly express their beliefs on Rural Development Schemes and the Government and to
reveal their understanding of the concept of multifunctionality.
Based on the results of the analysis of the interviews a questionnaire was designed,
which was divided in four different sections. The first section included questions about
the socio-demographic characteristics of the vine-growers and the characteristics of
their farms. The aim was to provide the variables needed for the identification and
typology of the vine-growing systems. The second section was related to the voluntary
measures of the Greek Rural Development Program, and the willingness of vinegrowers to participate in them. The third section focused on revealing the farmers' goals
and perspectives and their views and opinions on viticulture and multifunctional
schemes. The fourth, section was about farmers' perception of bureaucracy, corruption
5
and informal networks in Greece, and specifically in the agricultural sector. The last
three sections included a number of phrases that were to be rated on a 5-step Likert
scale.
The data was simplified using non-linear Principal Component Analysis (PCA). Nonlinear PCA is a data reduction methodology that functions in the same way as
traditional PCA, but it can incorporate binary and categorical variables by transforming
them into numeric ones that have a variance in the traditional sense (Linting et al.,
2007). The outcome of the non-linear PCA, is a reduced number of variables (called
Principal Components) that are correlated with the original ones but uncorrelated to
each other 1 .. The first non-linear PCA was applied to the variables related to farm
characteristics, in term of management practices, purposes of the vineyards, reasons for
their existence and structural characteristics such as size and other farming activities.
Non-linear PCA analyses were also performed on farmers’ views and opinions, and the
results were interpreted in the framework of the Theory of Planned Behaviour (TPB).
The analysis of the factors influencing farmers’ willingness to participate in the schemes
under study was based on the Random Utility Theory, according to which a vine-grower
would choose to participate in a scheme if the choice maximized their utility. Utility is
expressed as a latent variable, which is maximized using the observed data. In this case
the willingness of farmers to participate was the dependant variable, while the results of
the PCAs and a set of other variables were the explanatory ones. Given the fact that the
willingness of a vine-grower to participate in a scheme was rated on a 5-point Likert
scale, and under the assumption that the error terms are normally distributed, the most
appropriate method to estimate the results was the ordered probit model . However,
according to Greene and Hensher (2009) adoption of an innovation is not a completely
random process as farmers self-select themselves. An approach that takes into account
self-selection is used here. Therefore, vine-growers were first separated according to
their intentions to continue the activity.
1
The number of components that were used in the analysis, was based on the Cronbachs’ a criterion and the Kaiser
criterion, with the threshold value of eighen-value being 2. (Gliem, J.A. and R.R. Gliem 2003. Calculating,
Interpreting, And Reporting Cronbach’s Alpha Reliability Coefficient For Likert-Type Scales. Midwest Research-toPractice Conference in Adult, Continuing, and Community Education, 2003 Conference, Columbus, Ohio. ,
Jongeneel, Roel A., Nico B. P. Polman and Louis H. G. Slangen 2008. Why are Dutch farmers going multifunctional?
Land Use Policy 25: 81-94.
6
4284 | ESADR 2013
The univariate probit model
According to (Greene, 2004) the utility of a vine-grower can be expressed as a latent
variable:
where is the number of each observation,
value of
,
is the vector of the factors influencing the
a vector of coefficients to be estimated and
unobserved with
is disturbances that are
.
The univariate probit model is based on Random Utility Theory and it assumes that the
outcome is a binary choice:
{
Using maximum likelihood estimation we can compute the coefficients
which give
the impact of the explanatory variables on the latent variable. Here, for the univariate
probit on willingness to continue, robust standard errors were estimated, in order to
account for heteroskedasticity.
The ordered probit model
The ordered probit model is used when the outcome variable is rated on an ordered
scale. Then, the observed
is related to
as follows:
{
where is the number of ordered ranks of the observed dependent variable. The model
includes a vector of unknown coefficients
be estimated with
and unknown threshold parameters
to
. The parameters of the model can be
estimated through the maximum likelihood method. For the ordered probit models
measuring the willingness of farmers to participate in RD schemes, robust standrard
errors were estimated, in order to account for heteroskedasticity.
Ordered probit with sample selection
In the sample selected ordered probit model, utility is expressed as in equation (1), but a
selection utility equation is added to the model, so that it takes the following form:
7
where
{
is the normally distributed error terms,
|
|
and
|
|
.
|
,
The
two
probabilities are estimated jointly with the aim to obtain estimates of a vector of
parameters
and
. Τhese type of models can be estimated using maximum
likelihood estimation methods. Here, the two models are estimated in parallel, with
being the sample selection variable that is modelled for the entire dataset, and
representing the ordered choice variable, which is modelled for the subset where
. In the maximum likelihood estimation,
is estimated instead. The estimation of
where, z is normally distributed,
is not directly estimated, but atanh
, is based on Fisher’s
(
transformation
)
is the natural logarithm function and
is the
inverse hyperbolic function. The Fisher transformation is preferred because for sample
correlation it has a near-constant variance for all values of
(Buis, 2011; Cox, 2008).
We can perform a likelihood-ratio test by comparing the log likelihood of the full model
with the sum of the log likelihoods for the ordered probit and selection models. Again,
robust standard errors are estimated to account for possible heteroskedasticity.
RESULTS
Principal Component Analysis
Four consecutive PCA analyses were performed for the simplification of the original
dataset. The first PCA was performed on variables related to vineyard and farm
management characteristics and aimed at identifying vine-growing systems. It produced
6 farm types (Table 1: Description of farm times based on the results of non-linear
PCA). The second PCA was performed on farmers’ opinion on vine-growing activities,
and produced three variables interpreted in the context of the TPB, to be used in the
sample selection model. The third PCA was performed on farmers’ views and attitudes
towards the organic vine-growing subsidy scheme, and, also, produced three factors.
The fourth PCA was performed on statements related to participating in the investment
aid scheme and two factors emerged from the analysis (Table 2: Behavioural factors
8
4286 | ESADR 2013
related to intention to continue vine-growing, and
to willingness to adopt
multifunctional schemes).
Table 1: Description of farm times based on the results of non-linear PCA
Farm
type
1
2
3
4
5
6
Description
Traditional vineyards on terraces dependant on co-operatives combined
with olive trees, existing because of tradition. Insular areas
Hill-side farms combined with livestock, full time farming, existing
because of lack of choices. Mountain areas
Intensive commercial farms of table grapes dependent on contractors,
combined with perennial crops, existing for income generation. Coastal
areas
Intensive mechanized vineyards dependent on wineries, part-time
farming. All areas
Large fragmented vineyards, part of wine-making estates. Mountain and
coasts
Household vineyards combined with other household farming activities.
All areas
Table 2: Behavioural factors related to intention to continue vine-growing, and to
willingness to adopt multifunctional schemes
Factor
Description
Intention to continue vine-growing
Idealists
Farmers concerned about general issues like the area, the environment,
cultures and traditions, and find it easy to stay in their areas
Practical Farmers that find viticulture and vine-growing to be important for them
and their families, and need it for income support
Control
Farmers that find viticulture important but find social and practical
difficulties in practicing it
Intention to participate in the subsidy scheme for organic farming
Control
Farmers that find it easy to participate in the scheme, to collaborate with
the authorities and to have the necessary means to deal with Red Tape of
other institutional malfunctions
Norm
Farmers that find subsidies to be useful and find it easy to adopt to the
social requirements of farming life
Idealists
Farmers concerned about the environment, think it’s important to have a
good vineyard, and find it useful and easy to adopt organic practices
Intention to participate in the investment aid scheme
Idealists
Farmers that farmers that are interested in protecting the environment and
maintaining the landscapes, and enjoy the social aspects of farming life
Control
Farmers that find it easy to find information and apply for the subsidy
scheme, and at the same time find it important to have a good vineyard
9
All the above mentioned factors are used as numerical variables in the estimation
models. For facilitation of the interpretation all these variables were normalized on a
scale from 0 to 10 (Areal, 2012)
10
4288 | ESADR 2013
Descriptive statistics
As highlighted earlier, apart from the results of the PCA, a set of other variables was
used in each of the probit models. Some variables were common for all models (Table
3).
Table 3: Descritptive statistics of variables used in the estimation models
Variable
Description
Variables common for all models
system1
Farm type 1
system2
Farm type 2
system3
Farm type 3
system4
Farm type 4
system5
Farm type 5
system6
Farm type 6
age
Age of respondent (years)
Educ
1= college or university, 0 = basic education
Tr_vit
Training on viticulture (1= yes, 0=no)
S_fut
Situation will improve in future 1 = yes, 0=no
Main_occ
Main occupation (1= farmer, 0 = other)
Rec
Impact of Recession 1 = negative, 0=positive
Mean
Std. Dev
5,464
39,290
2,561
3,458
2,433
3,957
49,09
,37
1,70
,36
,43
,84
2,007
19,224
1,897
1,841
1,720
1,967
13,764
,485
,546
,482
,496
,369
For the univariate probit a set of explanatory variables were used that describe some
personal and socioeconomic characteristics of the farmers. The results of the relevant
PCA were also used as explanatory variables.
For the ordered probit models on willingness to participate in the subsidy schemes, the
specific explanatory variables used described the positive and negative drivers for
participation or non-participation in the scheme as rated by the participants during the
qualitative interviews2. Also, the results of the relevant PCA analysis were used in the
explanatory variables set together with education level, age and recept of the Single
Payment, perception of corruption, perception of the impact of the recession on
viticulture and optimism for the future. These variables and their descriptive statistics
2
During the in-depth interviews farmers provided a number of drives in favour or against participation
in the schemes. For the survey, these reasons were transformed into statements to be rated from 1 to 5.
For the organic farming scheme, the positive drivers were subsidy, environmental protection, helath
protection, higher product prices and better product quality, and he negative were Red tape, Corruption,
participation cost, supplies cost, lower yields, low amount of subsidies and very strict crop protection
rules. For the investment aid scheme the positive were subsidy, farm modernization, reduction of costs,
better product quality, landscape maintenance, and the negative were corruption, Red Tape, high
2
investment and participation costs and land fragmentation. After checking for statistical significance (χ ),
and correlations (Pearson), only a limited number of these drivers were kept in the analysis.
11
are presented in Table 4: Descriptive statistics of the specific variables used for
intention to continue.
Table 4: Descriptive statistics of the specific variables used for intention to
continue
Variable name Description
Mean
Std. Dev
Variables used in the univariate probit on intention to continue
Ext_age
Membership in extension agency (1= yes, ,62
,486
0=no)
Gen
Gender (1=male, 0=female)
,89
,317
Zone
Residence in the vine-growing zone (1=yes, ,75
,434
0=no)
sps
Reception of Single Payment (1= yes 0 =no)
,56
,497
hou_mem
Household members (number)
3,19
1,269
views1
TPB factor 1
6,818 2,022
views2
TPB factor 2
6,775 1,817
views3
TPB factor 3
3,141 1,937
Variables used in the ordered probit on willigness to participate in the organic farming
scheme
Org
Previous participation in the scheme
,16
,365
Corr
Corruption
,38
,486
Subsidy
Scheme subsidy
,73
,445
H_P_P
Higher product prices
,77
,419
quality
Better product quality
,43
,496
Red
Red Tape
,87
,340
Low_yield
Low yields due to management restrictions
,73
,0.31
FAC_org_1
TPB factor 1
5,284 2,1425
FAC_org_2
TPB factor 2
5,558 2,1209
FAC_org_3
TPB factor 3
4,493 1,8106
Variables used in the ordered probit on willingness to participate in the investment aid
scheme
corr_imp
Corruption
,48
,501
Imp_che
Previous participation in the scheme
,34
,474
subsidy_imp
Scheme subsidy
,90
,295
prod_cost
modern
landsc
red_tape_imp
Reduce cost of production
Vineyard modernization
Landscape preservation
Red tape
,77
,86
,59
,92
,419
,349
,493
,265
inv_cost
del
ina_vin
FACTOR1_IMP
FACTOR2_IMP
Cost of investment
Delays in payments
Vineyard doesn’t qualify
TPB factor 1
TPB factor 2
,63
,90
,24
4,869
5,496
,485
,295
,429
2,363
2,189
12
4290 | ESADR 2013
Finally, the rates of willingness to participate in both schemes are shown in Table 5:
Rates of willingness to participate in subsidy schemes.
Table 5: Rates of willingness to participate in subsidy schemes
Very unlikely
Unlikely
Uncertain
Likely
Very likely
Willingness to participate in the
scheme for organic practices (%)
35.15
30.20
9.90
11.39
13.37
Willingness to participate in the
scheme for investment aid (%)_
16.08
18.09
21.61
33.17
11.06
Estimation results
All the explanatory variables used in all models were checked for statistical significance
through χ2 tests for discrete variables and a one sample t-test for continuous ones. Also,
to account for multicollinearity issues V.I.F index of all variables was checked.
The results of the univariate probit model estimation on farmers’ intention to continue
are shown in Table 6: Determinants of farmers’ intention to continue vine-growing.
Intention of farmers to continue is found to be negatively influenced by age, a finding
that agrees with previous researchers like Ondersteijn et al. (2006). Also, an increase in
the number of household members increases the likelihood of farmers continuing vinegrowing. From the three behavioural factors, the one describing farmers that find it
important to stay in their areas, maintain the local culture and landscape and protect the
environment (views1), had a positive effect on intention to continue. This is in
agreement with earlier studies like Burton and Wilson (2006) who found that cultural
and environmental awareness positively influences farming activities. The factor
describing farmers that found vine growing to be important in terms of profit and as a
profession (views2), and the factor describing perception of behavioural control (views3)
were not statistically significant. However, the coefficients signs indicated that the first
hads positive and the second negative, as expected. Age of farmers is negatively
influencing intention to continue which is in agreement Breustedt and Glauben (2007).
In terms of systems farm types 3, 4 and 6 have positively influenced farmers’ intention
to continue, whereas system 1 has negative influence. This means that vine-growers in
Samos, with traditional vineyards, on terraces are less likely to continue, whereas
intensive vine-growers with commercial table grape vineyards are more likely to
continue. Also, vine-growers that have viticulture as a secondary activity, either as
13
income support or as a “hobby”, are more likely to continue. Coefficients associated
with views of the recession and optimism for the future had negative signs.
The atanh_ρ for the estimation of joint probabilities of the selection model and the
ordered probit for intention to participate in the organic vine-growing subsidy scheme is
statistically significant, which means that sample selection correction was necessary in
order to extract safe results. Farmers’ willingness to participate in the organic vinegrowing scheme increases with the increase of importance of the factor related to
perceived behavioural control. This means that the easier farmers find it to collaborate
with the authorities. and to overcome institutional malfunction, the more likely they are
to participate in the scheme (FAC_org_1). Willingness to participate also increases as
the importance of protection of the environment and usefulness of organic practices
increases (FAC_org_3). Subjective norms have no significant influence on participation
in organic farming, as expected. Age was also found to be irrelevant while intention to
participate decreases with those of higher education levels. Previous participation in the
scheme is also highly influential in a positive way. Regarding vine-growing systems,
farmers with hill-side vineyards on mountain areas, and farmers that use vine-growing
as a secondary income source are more likely to turn organic, while farmers with
terraced vineyards on islands or farmers with modern commercial vineyards on coasts
are less likely. Winemaking estates and “hobby” vineyards were found to be irrelevant
in terms of significance; however both coefficients had a positive sign. In terms of
collaboration with the authorities, corruption had a negative impact on farmers
intentions, while red tape, surprisingly had a positive influence. A possible explanation
for the positive sign, is that farmers that actually intend to adopt the scheme, are the
ones that already have the means to overcome potential institutional barriers, and red
tape facilitates their participation in the scheme, because they use to their advantage
(Karanikolas and Martinos, 2007). Being a full time farmer has no significant influence
on intention to participate in the scheme, similarly to the amount of subsidy, the higher
product prices and the low yields. However, all these factors had positive coefficients.
The economic recession and perception of the future situation were, also, found to be
irrelevant.
Contrary to the model on willingness to participate in organic farming, the atanh_ρ for
the estimation of joint probabilities of the selection model and the ordered probit for
intention to participate in the investment aid subsidy scheme was not statistically
14
4292 | ESADR 2013
significant, which means that correction was not necessary. However, interpretation of
the coefficients will be based on the corrected model. Intention of farmers to apply for
an investment aid increases with the increase of the factor on perceived behavioural
control (FAC_imp_2) meaning, in this case, that farmers who find it easy to acquire
information, understand the law and collaborate with the authorities are more likely to
participate. The factor describing farmers that find it important to have a modern
improved vineyard is not statistically significant (but has a positive coefficient sign),
probably because, these farmers do not necessarily relate improvement of the vineyards
with the subsidy scheme for other reasons. Previous participation in the scheme also had
positive influence. Also, willingness to participate in the scheme increased with the
concern about preserving traditional landscapes. The economic recession and optimism
for the future had both a positive impact on willingness to participate in the scheme. As
expected, intention to participate in the scheme is negatively influenced by corruption
and red tape. Age and education level are irrelevant to farmers intentions. It is worth
noticing that none of the farming systems significantly influences farmers’ willingness
to apply for an investment aid, although the ones with positive coefficients are only, the
traditional terraced vineyards of the islands and the big vineyards of winemaking estates.
The amount of subsidy, the intention to modernize the vineyard, the investment cost and
small size and land fragmentation had no significant impact on farmers’ participation in
this scheme.
Table 7: Determinants of farmers’ willingness to participate in the subsidy scheme for
organic vine-growing and
Table 8: Determinants of farmers’ willingness to participate in the investment aid
scheme show the results of the ordered probits on intention to participate in the subsidy
schemes for organic farming and for investment aid before and after sample selection
correction respectively. The sign of a coefficient indicates how an explanatory variable
influences the dependant variable. A positive sign shows an increase of the probability
whereas a negative sign has the opposite effects.
Table 6: Determinants of farmers’ intention to continue vine-growing
Explanatory variables
age
Coefficient.
***
-.039
z
-3.29
Marginal
effect
-.007***
z
-3.64
15
education_level
system1
system2
system3
system4
system5
system6
views1
views2
views3
household_members
sps
Rec
S_fut
main_occ
_cons
.122
-.156*
.011
.230**
.271***
.039
.228***
.168*
.092
-.046
.203*
.004
-.942**
-.191*
.446
-.2334896
0.39
-1.77
0.12
2.37
3.15
0.46
2.89
1.80
1.19
-0.58
1.80
0.01
-2.10
-0.63
1.21
-0.21
.021
-.030*
.013
.044**
.052***
.007
.044**
.033*
.017
-.009
.039*
.001
-.185**
-.033*
.084
0.36
-1.89
0.20
2.53
3.48
0.44
3.13
1.91
1.21
-0.67
1.87
0.02
-2.24
-0.58
1.24
*
Statistically significant at the 0.10 level of significance, **at 0.05 level and ***at 0.01 level
Intention of farmers to continue is found to be negatively influenced by age, a finding
that agrees with previous researchers like Ondersteijn et al. (2006). Also, an increase in
the number of household members increases the likelihood of farmers continuing vinegrowing. From the three behavioural factors, the one describing farmers that find it
important to stay in their areas, maintain the local culture and landscape and protect the
environment (views1), had a positive effect on intention to continue. This is in
agreement with earlier studies like Burton and Wilson (2006) who found that cultural
and environmental awareness positively influences farming activities. The factor
describing farmers that found vine growing to be important in terms of profit and as a
profession (views2), and the factor describing perception of behavioural control (views3)
were not statistically significant. However, the coefficients signs indicated that the first
hads positive and the second negative, as expected. Age of farmers is negatively
influencing intention to continue which is in agreement Breustedt and Glauben (2007).
In terms of systems farm types 3, 4 and 6 have positively influenced farmers’ intention
to continue, whereas system 1 has negative influence. This means that vine-growers in
Samos, with traditional vineyards, on terraces are less likely to continue, whereas
intensive vine-growers with commercial table grape vineyards are more likely to
continue. Also, vine-growers that have viticulture as a secondary activity, either as
income support or as a “hobby”, are more likely to continue. Coefficients associated
with views of the recession and optimism for the future had negative signs.
16
4294 | ESADR 2013
The atanh_ρ for the estimation of joint probabilities of the selection model and the
ordered probit for intention to participate in the organic vine-growing subsidy scheme is
statistically significant, which means that sample selection correction was necessary in
order to extract safe results. Farmers’ willingness to participate in the organic vinegrowing scheme increases with the increase of importance of the factor related to
perceived behavioural control. This means that the easier farmers find it to collaborate
with the authorities. and to overcome institutional malfunction, the more likely they are
to participate in the scheme (FAC_org_1). Willingness to participate also increases as
the importance of protection of the environment and usefulness of organic practices
increases (FAC_org_3). Subjective norms have no significant influence on participation
in organic farming, as expected. Age was also found to be irrelevant while intention to
participate decreases with those of higher education levels. Previous participation in the
scheme is also highly influential in a positive way. Regarding vine-growing systems,
farmers with hill-side vineyards on mountain areas, and farmers that use vine-growing
as a secondary income source are more likely to turn organic, while farmers with
terraced vineyards on islands or farmers with modern commercial vineyards on coasts
are less likely. Winemaking estates and “hobby” vineyards were found to be irrelevant
in terms of significance; however both coefficients had a positive sign. In terms of
collaboration with the authorities, corruption had a negative impact on farmers
intentions, while red tape, surprisingly had a positive influence. A possible explanation
for the positive sign, is that farmers that actually intend to adopt the scheme, are the
ones that already have the means to overcome potential institutional barriers, and red
tape facilitates their participation in the scheme, because they use to their advantage
(Karanikolas and Martinos, 2007). Being a full time farmer has no significant influence
on intention to participate in the scheme, similarly to the amount of subsidy, the higher
product prices and the low yields. However, all these factors had positive coefficients.
The economic recession and perception of the future situation were, also, found to be
irrelevant.
Contrary to the model on willingness to participate in organic farming, the atanh_ρ for
the estimation of joint probabilities of the selection model and the ordered probit for
intention to participate in the investment aid subsidy scheme was not statistically
significant, which means that correction was not necessary. However, interpretation of
the coefficients will be based on the corrected model. Intention of farmers to apply for
17
an investment aid increases with the increase of the factor on perceived behavioural
control (FAC_imp_2) meaning, in this case, that farmers who find it easy to acquire
information, understand the law and collaborate with the authorities are more likely to
participate. The factor describing farmers that find it important to have a modern
improved vineyard is not statistically significant (but has a positive coefficient sign),
probably because, these farmers do not necessarily relate improvement of the vineyards
with the subsidy scheme for other reasons. Previous participation in the scheme also had
positive influence. Also, willingness to participate in the scheme increased with the
concern about preserving traditional landscapes. The economic recession and optimism
for the future had both a positive impact on willingness to participate in the scheme. As
expected, intention to participate in the scheme is negatively influenced by corruption
and red tape. Age and education level are irrelevant to farmers intentions. It is worth
noticing that none of the farming systems significantly influences farmers’ willingness
to apply for an investment aid, although the ones with positive coefficients are only, the
traditional terraced vineyards of the islands and the big vineyards of winemaking estates.
The amount of subsidy, the intention to modernize the vineyard, the investment cost and
small size and land fragmentation had no significant impact on farmers’ participation in
this scheme.
Table 7: Determinants of farmers’ willingness to participate in the subsidy scheme
for organic vine-growing
age
Educ
Org
system1
system2
system3
system4
system5
system6
FAC_org_1
FAC_org_2
FAC_org_3
Rec
S_fut
Corr
Coef.
-.0117*
-.2455
1.5983***
-.2295***
.0712
-.2561***
.0746
.0218
.0070
.2862***
-.0414
.1280*
-.05876
.0968
-.8162***
z
-1.70
-1.12
5.50
-3.65
1.09
-3.61
1.43
0.34
0.17
5.05
-0.87
1.63
-0.21
0.58
-3.27
Corrected
Coef.
-.0085
-.4026*
1.6180***
-.2380***
.1291**
-.2237***
.1236**
.0688
.0105
.2458***
-.0282
.1192*
-.2058
.0627
-1.0695***
z
-0.90
-1.67
5.46
-3.58
1.97
-2.71
2.10
0.95
0.19
4.18
-0.47
1.49
-0.67
0.33
-3.69
18
4296 | ESADR 2013
subsidy
hp_p
quality
redtape
low_yield
main_occ
/cut1
/cut2
/cut3
/cut4
*
-.1892
.3559
.6989***
1.4528***
.1340
.3275
1.1187
2.4135
2.9071
3.6653
-0.93
1.30
3.04
4.50
0.45
1.29
-.1904
.3387
.7821***
1.4737***
.0726
.3804
1.3627
2.8231*
3.2317***
4.0004***
.1826*
-0.84
0.97
3.02
4.46
0.26
1.31
1.22
2.53
2.88
3.47
0.42
Table 8: Determinants of farmers’ willingness to participate in the investment aid
scheme
age
Educ
main_occ
Imp_che
system1
system2
system3
system4
system5
system6
FACTOR1_IMP
FACTOR2_IMP
Rec
s_fut
corr_imp
subsidy_imp
modern
red_tape_imp
inv_cost
landsc
Inapr_vin
/cut1
/cut2
/cut3
Coef.
-.0101
-.0179
.0131
.8023***
.0436
-.0112
-.0295
-.0528
.0535
-.0110
-.0152
.3499***
.5029*
.2758
-.6852***
.2818
.7731***
-.5292
.0754
.4845**
-.0644
.77145
1.8888
2.9551
z
-1.48
-0.08
0.05
3.41
0.90
-0.17
-0.49
-1.06
0.93
-0.24
-0.29
5.94
1.71
1.43
-3.40
0.84
2.87
-1.52
0.34
2.17
-0.28
Corrected
Coef.
-.0053
.2384
.1712
.8690***
.0582
.0345
.0525
-.0723
.0801
.0050
.0221
.4163***
.5721*
.4868**
-.7830***
.1429
.4960
-.3958
.2751
.6236**
-.3990
2.1698*
3.2969***
4.5992***
z
-0.60
0.87
0.62
3.67
1.00
0.47
0.77
-1.22
1.28
-0.10
0.34
5.32
1.89
2.24
-3.10
0.38
1.45
-0.99
1.31
2.27
-1.45
1.90
2.77
3.70
19
/cut4
4.7983
6.4874***
.09276
4.91
0.27
*
The fact that age and education have no significant impact on intention to participate in
RD schemes is in accordance with recent studies on adoption of agri-environmental
schemes such as Vanslembrouck et al. (2002) and Läpple and Kelley (2013). Previous
participation in schemes is found to have a positive impact, because as stated earlier by
Vanslembrouck et al. (2002), uptake of measures, especially environmental related, is
positively influences by familiarity with them.
For the behavioural aspect Läpple (2010) and Hansson et al. (2012) highlighted the
influence of psychological factors on adoption of measures. Similarly this study
identified that the less psychological constrains farmers have regarding the difficulty in
participating the more they are willing to participate. Also, organic farming was found
to be influenced by importance of environment and landscape, a finding that agree with
Burton et al. (2003) that environmental awareness increases the possibility of adopting
agri-environmental schemes.
Regarding farming systems, the results of this study can be considered to be in
accordance with researchers in the past that used farm characteristics as explanatory
variables. (Kizos et al., 2009) and (Petanidou et al., 2008) noted that terraced crops on
islands are being abandoned and that farmers are not motivated to participate in RD
schemes. For the islands Papadopoulos and Papanikos (2005) also, found that vineyards
are abandoned despite policy incentives for the opposite. Also, lowland intensive
viticulture systems have negative relation to adoption of organic farming. This is similar
to the findings of Oxouzi (2008) who said that profit orientated vineyards are not likely
to adopt organic farming.
DISCUSSION AND CONCLUSIONS
Farmers that are interested in staying in their area and maintaining their cultural values,
and have environmental concerns are more likely to continue vine-growing than those
who are profit orientated. Similarly, farmers with environmental awareness are more
willing to adopt organic vine-growing, and preserving the landscape is one of the main
reasons for participating in the investment aid scheme. Evidently, it is the cultural and
environmental identity that motivates farmers not to abandon viticulture, and to be
20
4298 | ESADR 2013
involved in Rural Development schemes. Therefore, as Burton et al. (2008).said, RD
measured would be more successful if they appealed to those identities, rather than to
the farmers interest for profit. This is so, in communities where vine-growing can have
a multiple role (producing income, maintaining the rural population, protecting the
landscape and the environment), farmers should be more aware of their role in the
community and understand its importance
Farming systems that are more likely to continue to be active are the ones with modern
infrastructure and with multiple market choices. Terraced traditional vineyards on
islands and hill-side mixed vineyards on mountains are negatively related to
continuation of vine-growing. According to farmers, the main reasons are the fact these
systems are hard to maintain, the limited access to marketing channels and the fact that
they are located in remote areas. Participants in the qualitative research explained that
the remoteness of these areas doesn’t allow young people to have their desired lifestyle,
and neither does farming. So, future RD policies should focus more on providing the
population of these areas with alternatives related to their social life, rather their farming
activities. Also, facilitation of access to marketing channels is essential, as long as they
function at local level. As Morgan-Davies et al. (2011) say, it is difficult to formulate a
single policy for marginal agricultural areas. Geographic remoteness of Greek LFAs
areas would never allow vine-growers be part of a broader market, if the channeling of
grapes to the market doesn't take place at local level.
Corruption has a negative impact on farmers’ willingness to participate in RD schemes.
Corruption in Greece is a large political issue and it is present in all sectors of public life.
The main ways of manifestation of corruption in the agricultural sector is bribery,
ambiguous legislation that often allows officials to negotiate the law with citizens and
clientelism, which is manifested through the use of informal human networks within the
system and particularly within political parties. Red tape is a part of this system because
it facilitates corruption taking place place. On the other hand, farmers that believe they
have the means to overcome the obstacles imposed by corruption or red tape are more
likely to participate in both schemes. The fight against corruption is a broader issue, that
is related to fiscal policies and there is no doubt that it should become a priority. But, as
far as the RD schemes are concerned, policies should focus in facilitating farmers find
the necessary means to overcome possible handicaps imposed by corruption.
21
The recession has a negative impact on farmers’ intentions to continue, but after sample
selection process it has a positive impact on participation in the investment aid scheme.
Farmers in Less Favoured Areas, have, since the past, looked for alternative
employment opportunities, mostly related to tourism, mainly for social reasons
(Haralambopoulos and Pizam, 1996). The current situation has caused additional
problems, which, especially for viticulture are, lack of cash flow in the market and
limited access to credit for farmers due to low incomes. Cash flow is essential for
annual investment in crop protection and infrastructure. However, because of the
seasonality of the crop and the recession in the market, vine-growers often have to
provide credit to buyers, for long periods of time, without having access to credit
themselves. So, even if viticulture seems like an attractive employment opportunity, in
reality the recession has caused the opposite effect. The investment aid scheme is a way
to have access to money. If in past years vine-growers were rejecting the idea because
of certain negative drives, today the recession is causing them to consider participating
in the scheme. Future policies should facilitate cash flow in the sector, not only in the
form of subsidies but also in the form of credit, and most importantly should ensure a
proper function of the markets.
REFERENCES
Ajzen, Icek 1991. The theory of Panned Behaviour. Organizational Behaviour and Human
Decision Process 50: 179 - 211.
Areal, Francisco J., Laura Riesgo, Manuel Gómez-Barbero and Emilio Rodríguez-Cerezo 2012.
Consequences of a coexistence policy on the adoption of GMHT crops in the European Union.
Food Policy 37: 401-411.
Blackstock, K. L., J. Ingram, R. Burton, K. M. Brown and B. Slee 2010. Understanding and
influencing behaviour change by farmers to improve water quality. Science of The Total
Environment 408: 5631-5638.
Bougherara, Douadia and Laure Latruffe 2010. Potential impact of the EU 2003 CAP reform on
land idling decisions of French landowners: Results from a survey of intentions. Land Use Policy
27: 1153-1159.
Breustedt, Gunnar and Thomas Glauben 2007. Driving Forces behind Exiting from Farming in
Western Europe. Journal of Agricultural Economics 58: 115-127.
Broch, Stine Wamberg, Niels Strange, Jette B. Jacobsen and Kerrie A. Wilson 2012. Farmers'
willingness to provide ecosystem services and effects of their spatial distribution. Ecological
Economics.
Buis, M. L. 2011. Stata tip 97: Getting at &#961's and &#963's. Stata Journal 11: 315-317.
Burton, Rob. J. F., Kuczera, Carmen, Schwarz and Gerald 2008. Exploring Farmers' Cultural
Resistance to Voluntary Agri-environmental Schemes. Oxford, ROYAUME-UNI: Blackwell.
Burton, Michael, Dan Rigby and Trevor Young 2003. Modelling the adoption of organic
horticultural technology in the UK using Duration Analysis. Australian Journal of Agricultural
and Resource Economics 47: 29-54.
22
4300 | ESADR 2013
Burton, Rob J. F. and Geoff A. Wilson 2006. Injecting social psychology theory into
conceptualisations of agricultural agency: Towards a post-productivist farmer self-identity?
Journal of Rural Studies 22: 95-115.
Cox, N. J. 2008. Stata tip 59: Plotting on any transformed scale. Stata Journal 8: 142-145.
de Graaff, Jan, Aad Kessler and Preben Olsen 2010. Farm-level adoption of soil and water
conservation measures and policy implications in Europe. Land Use Policy 27: 1-3.
de Lauwere, Carolien, Marcel van Asseldonk, Jonathan van 't Riet, Jitske de Hoop and Eric ten
Pierick 2011. Understanding farmers' decisions with regard to animal welfare: The case of
changing to group housing for pregnant sows. Livestock Science.
Emery, Steven B. and Jeremy R. Franks 2012. The potential for collaborative agri-environment
schemes in England: Can a well-designed collaborative approach address farmers’ concerns
with current schemes? Journal of Rural Studies 28: 218-231.
Genious, M., C. Pantzios and V. Tzouvelekas 2006. Information Acquisition and Adoption of
Organic Farming Practices: Evidence from Farm Operations in Crete, Greece. No 305, Working
Papers from University of Crete, Department of Economics.
Gidarakou, I., L. Kazakopoulos and A. Koutsouris 2004. Pluriactivity and succession in small
family farms: The case of two less favoured areas in Greece. In Pluriactivity and succession in
small family farms: The case of two less favoured areas in Greece, 5th European IFSA
Symposium, 151-160. Vila Real, Portugal.
Gliem, J.A. and R.R. Gliem 2003. Calculating, Interpreting, And Reporting Cronbach’s Alpha
Reliability Coefficient For Likert-Type Scales. Midwest Research-to-Practice Conference in Adult,
Continuing, and Community Education, 2003 Conference, Columbus, Ohio.
Gorton, Matthew, Elodie Douarin, Sophia Davidova and Laure Latruffe 2008. Attitudes to
agricultural policy and farming futures in the context of the 2003 CAP reform: A comparison of
farmers in selected established and new Member States. Journal of Rural Studies 24: 322-336.
Greene, W.H. 2004. Econometric Analysis. New Jersey: Prentice Hall.
Greene, W.H. and D.A. Hensher 2009. Modelling ordered choises. Cambridge: Cambridge
University Press.
Hansson, Helena, Richard Ferguson and Christer Olofsson 2012. Psychological Constructs
Underlying Farmers’ Decisions to Diversify or Specialise their Businesses – An Application of
Theory of Planned Behaviour. Journal of Agricultural Economics 63: 465-482.
Haralambopoulos, Nicholas and Abraham Pizam 1996. Perceived impacts of tourism : The case
of samos. Annals of Tourism Research 23: 503-526.
Hellenic Ministry of Agricultural Development and Food 2007. Rural Develpment Programme
of Greece, 2007 - 2013. In Rural Develpment Programme of Greece, 2007 - 2013.
Ingram, Julie, Peter Gaskell, Jane Mills and Chris Short 2013. Incorporating agri-environment
schemes into farm development pathways: A temporal analysis of farmer motivations. Land
Use Policy 31: 267-279.
Jongeneel, Roel A., Nico B. P. Polman and Louis H. G. Slangen 2008. Why are Dutch farmers
going multifunctional? Land Use Policy 25: 81-94.
Karanikolas, P. and N. Martinos 2007. The modernization process in Greek Agriculture: the
case of investment aid. Agricultural Economics Review 8: 37 - 49.
Kizos, Thanasis, Anastasia Dalaka and Theodora Petanidou 2009. Farmers’ attitudes and
landscape change: evidence from the abandonment of terraced cultivations on Lesvos, Greece.
Agriculture and Human Values 27: 199 - 212.
Lange, Andrej, Annette Piorr, Rosemarie Siebert and Ingo Zasada 2013. Spatial differentiation
of farm diversification: How rural attractiveness and vicinity to cities determine farm
households’ response to the CAP. Land Use Policy 31: 136-144.
Läpple, Doris 2010. Adoption and Abandonment of Organic Farming: An Empirical Investigation
of the Irish Drystock Sector. Journal of Agricultural Economics 61: 697-714.
23
Läpple, Doris and Hugh Kelley 2013. Understanding the uptake of organic farming: Accounting
for heterogeneities among Irish farmers. Ecological Economics 88: 11-19.
Linting, M., J. J. Meulman, P. J. Groenen and A. J. van der Koojj 2007. Nonlinear principal
components analysis: introduction and application. Psychol Methods 12: 336-358.
Mathijs, E. 2003. Social capital and farmers’ willingness to adopt countryside stewardship
schemes. Outlook on Agriculture 32: 13-16.
Mattison, Elizabeth H. A. and Ken Norris 2007. Intentions of UK Farmers toward Biofuel Crop
Production: Implications for Policy Targets and Land Use Change. Environmental Science &
Technology 41: 5589-5594.
Morgan-Davies, Claire, Tony Waterhouse and Ron Wilson 2012. Characterisation of farmers’
responses to policy reforms in Scottish hill farming areas. Small Ruminant Research 102: 96107.
O’Rourke, E., N. Kramm and N. Chisholm 2012. The influence of farming styles on the
management of the Iveragh uplands, southwest Ireland. Land Use Policy 29: 805-816.
Ondersteijn, C. J. M., G. W. J. Giesen and R. B. M. Huirne 2006. Perceived environmental
uncertainty in Dutch dairy farming: The effect of external farm context on strategic choice.
Agricultural Systems 88: 205-226.
Oxouzi 2008. Determinant factors for the adoption of organic cultivation of vine in Central
Macedonia. PhD Thesis. Agricultural Economics, School of Agriculture, Aristotle University of
Thessaloniki.
Papadopoulos, Athanasios P. and Gregory T. Papanikos 2005. The determinants of vinegrowers
employment and policy implications: the case of a Greek island. Agricultural Economics 32(1):
61-72.
Petanidou, T., T. Kizos and N. Soulakellis 2008. Socioeconomic dimensions of changes in the
agricultural landscape of the Mediterranean basin: a case study of the abandonment of
cultivation terraces on Nisyros Island, Greece. Environmental Management 41: 250-266.
Rehman, T., K. McKemey, C. M. Yates, R. J. Cooke, C. J. Garforth, R. B. Tranter, J. R. Park and P.
T. Dorward 2007. Identifying and understanding factors influencing the uptake of new
technologies on dairy farms in SW England using the theory of reasoned action. Agricultural
Systems 94: 281-293.
Sintori, A., S. Rozakis and K. Tsiboukas 2009. Multiple goals in farmers' decision making: The
case of sheep farming in western Greece. In Multiple goals in farmers' decision making: The
case of sheep farming in western Greece., The 83rd Annual Conference of the Agricultural
Economics society. . Dublin, Ireland. 30th March to 1st April 2009
Tore, Söderqvist 2003. Are farmers prosocial? Determinants of the willingness to participate in
a Swedish catchment-based wetland creation programme. Ecological Economics 47: 105-120.
Tzanopoulos, Joseph, Athanasios S. Kallimanis, Ioanna Bella, Lois Labrianidis, Stefanos Sgardelis
and John D. Pantis 2011. Agricultural decline and sustainable development on mountain areas
in Greece: Sustainability assessment of future scenarios. Land Use Policy 28: 585-593.
Vanslembrouck, I., G. Van Huylenbroeck and W. Verbeke 2002. Determinants of the
Willingness of Belgian Farmers to Participate in Agri-environmental Measures. Journal of
Agricultural Economics 53: 489-511.
Wilson, Geoff A. 2009. The spatiality of multifunctional agriculture: A human geography
perspective. Geoforum 40: 269-280.
24
4302 | ESADR 2013
ANÁLISE DA EFICÁCIA, EFICIÊNCIA E VALOR
ACRESCENTADO DE POLÍTICAS PÚBLICAS PLACE-BASED –
UMA APLICAÇÃO A TERRITÓRIOS RURAIS
ANABELA SANTOS
Economista e Consultora Financeira, Mestre em Economia, Universidade de Évora, Portugal.
Morada: Travessa da Fonte, n° 3, 7350-481 São Vicente e Ventosa, Portugal.
E-mail: [email protected] (corresponding author).
MARIA MANUEL SERRANO
Professora Auxiliar, Universidade de Évora, Departamento de Sociologia e SOCIUS – ISEG/UTL.
Morada: Universidade de Évora, Largo dos Colegiais 2, 7000-803 Évora, Portugal.
E-mail: [email protected].
PAULO NETO
Professor Auxiliar c/ agregação, Universidade de Évora, Departamento de Economia, CEFAGE-UE e
CIEO-UALG. Morada: Universidade de Évora, Largo dos Colegiais 2, 7000-803 Évora, Portugal.
E-mail: [email protected].
RESUMO
O lançamento do Programa LEADER, em 1991, imprimiu uma nova dinâmica à política
de desenvolvimento rural da União Europeia. Este instrumento, concebido para
fomentar o empreendedorismo, potenciar o crescimento económico e estimular a
inovação nas zonas rurais, distinguiu-se dos modelos clássicos por assentar numa
abordagem territorial, multissectorial e integrada.
Para esta comunicação - que tem por base uma investigação mais vasta sobre os efeitos
e resultados socioeconómicos do Programa LEADER - definiu-se como principal
objetivo a análise do valor acrescentado, da eficácia e da eficiência do Programa, na
região Alentejo, ao longo das suas três primeiras fases. Para atingir este objetivo foram
analisados a totalidade dos 2.706 projetos de investimento executados e financiados
pelo LEADER, no período de 1991 a 2006, no Alentejo1, considerando as seguintes
dimensões de análise: localização geográfica, tipo do promotor, atividade económica e
natureza da despesa efetuada.
As opções metodológicas e a recolha de dados estatísticos, junto das entidades nacionais
gestoras do Programa, permitiram a realização de uma análise descritiva de indicadores
financeiros e de impacto.
1
Agradecimentos ao Chefe do Projeto PIC LEADER +, Rui Veríssimo Batista, Gabinetes de Ação Local do Alentejo
e Direcção-Geral de Agricultura e Desenvolvimento Rural, pelos contributos e informação disponibilizada.
1
Os resultados obtidos permitiram concluir que o LEADER contribuiu para uma nova
dinâmica socioeconómica, por via de uma especialização do investimento realizado em
torno de dois setores de atividade considerados hoje estratégicos para o Alentejo: o
turismo e a agroindústria. Contudo, revelou-se pouco expressivo nas despesas com
I&DT, precisamente aquelas cujo contributo poderão alavancar a competitividade das
empresas locais.
A comunicação estrutura-se nas seguintes partes: i) enquadramento teórico-conceptual,
na qual se definem os conceitos centrais da investigação; ii) metodologia e
procedimentos metodológicos, onde se apresentam as opções metodológicas bem como
os processos de recolha e tratamento da informação; iii) análise dos resultados e iv)
conclusões e recomendações.
Palavras-chave: Eficácia, Eficiência, Valor Acrescentado, Políticas Públicas placedbased, Programa LEADER.
1. Introdução
As políticas públicas place-based, focadas nas prioridades e potencialidades de um
território ou região, têm progressivamente assumido um papel crescente, enquanto
instrumento de desenvolvimento local. Um dos exemplos mais conhecidos de políticas
placed-based aplicadas a territórios rurais é o Programa de Iniciativa Comunitária
LEADER – Ligação entre Ações de Desenvolvimento da Economia Rural (OECD,
2006: 94). Segundo o Comité Económico e Social Europeu (Avis 2011/C 376/03), ao
longo dos últimos 20 anos, a abordagem LEADER demonstrou ser viável, o que levou
este organismo a recomendar o alargamento da metodologia LEADER a outros
programas operacionais para o período pós 2013. Inclusivamente, o Quadro Estratégico
Comum (QEC), delineado pela Comissão para o período 2014-2020, pressupõe como
condição prévia de acesso ao Fundo Europeu de Desenvolvimento Regional (FEDER),
a existência de Estratégias de Investigação e Inovação Nacionais/Regionais para a
Especialização Inteligente (RIS3), em cada Estado-membro (Foray et al., 2012: 12).
O Programa de Iniciativa Comunitária LEADER surge em 1991, num contexto marcado
por profundas mutações da estrutura económico-social da sociedade rural,
nomeadamente: i) propensão para o envelhecimento populacional; ii) fraca
2
4304 | ESADR 2013
concentração demográfica e iii) reduzido rendimento per capita. Face à incapacidade
das teorias sectoriais e/ou exógenas para alterar a tendência de declínio do mundo rural,
a Comissão Europeia veio defender, no documento “O Futuro do Mundo Rural”,
publicado em 1988, a necessidade de ser experimentada uma nova abordagem para o
desenvolvimento rural, a qual deveria ter um enfoque territorial e uma intervenção das
comunidades locais na procura das soluções (Champetier, 2003). Paralelamente, assistese, na mesma data, a uma reformulação do papel dos fundos estruturais europeus com o
Regulamento CE n.° 2052/88, o qual veio prever a necessidade de uma maior
concentração dos instrumentos públicos nas regiões mais carenciadas, (…) [tornando]
quase inevitável a criação de um programa inovador para contrariar o despovoamento
e o ciclo de empobrecimento das áreas rurais (Moreno 2003:3). É neste contexto que
foi criado o Programa LEADER, o qual foi usado para canalizar recursos financeiros
para zonas mais desfavorecidas, como os territórios rurais de baixa densidade
populacional, com dificuldades de acesso ao financiamento externo (OECD, 2006). Os
sistemas de incentivos ao investimento são instrumentos de política pública que têm por
objetivo estimular o empreendedorismo, dinamizar a economia e fomentar a coesão
territorial. Segundo Marques & Santos (2011), os estímulos ao investimento podem
alavancar o desenvolvimento regional e as políticas públicas descentralizadas podem
motivar trajetórias de especialização produtiva. Contudo, Dall’erba et al (2008) já
tinham questionado a eficácia das políticas estruturais em promoverem a convergência
regional e assegurarem o crescimento económico nas regiões mais desfavorecidas.
Com o presente estudo, pretende-se contribuir para o debate público sobre a eficácia, a
eficiência e o valor acrescentado de políticas públicas place-based, vocacionadas para
territórios rurais2, mediante a análise das características do investimento realizado na
região Alentejo, no âmbito do Programa LEADER, entre 1991 e 2006.
O Alentejo3, região com forte tradição agrícola, estende-se por cerca de 27.300Km² e
ocupa cerca de ⅓ de Portugal continental. Este território registou, em 2011, uma
densidade populacional de 18,6hab/km², comparativamente a uma média nacional de
114,3hab/km², e um decréscimo da população residente, face ao período de 1970, em
2
No âmbito do Programa LEADER, entende-se por zonas rurais os territórios do interior ou litoral com uma
densidade populacional igual ou inferior a 150 habitantes por km², onde a maior parte das terras são utilizadas para a
agricultura, por atividades económicas e culturais próprias aos habitantes desta região (Barthelemy & Vidal, 1995).
3
Composto pelas sub-regiões Alto Alentejo, Alentejo Central, Alentejo Litoral e Baixo Alentejo, sem incluir o atual
NUTS III Lezíria e Vale do Tejo.
3
cerca de 14% (INE, 2012). Por outro lado, nas últimas décadas, o Alentejo não
[melhorou] a sua posição no que respeita a indicadores de competitividade territorial e
(…) não [tem] vindo a verificar sinais [significativos] de convergência para a média
nacional e da União Europeia” (Universidade de Évora, 2007: 2).
A investigação que está na base desta comunicação, procurou responder às seguintes
questões: Quais os principais beneficiários do programa? Que tipo de atividades e
despesas foram financiadas? Como influenciou o programa os investimentos em regiões
menos povoadas, mais envelhecidas ou com fraca concentração empresarial? Os efeitos
alcançados corresponderam aos objetivos pretendidos? Os recursos canalizados
conduziram aos resultados esperados?
Com o propósito de responder às questões levantadas, organizou-se a comunicação nos
seguintes pontos: i) enquadramento teórico-conceptual sobre a temática das políticas
públicas place-based e identificação das dimensões de análise destas políticas; ii)
descrição da metodologia e dos procedimentos metodológicos; iii) apresentação e
análise dos resultados e iv) análise e discussão das principais conclusões sobre a
eficácia, a eficiência e o valor acrescentado do Programa LEADER na região Alentejo.
2. Enquadramento teórico-conceptual
2.1. Políticas públicas place-based – o caso do Programa LEADER
As políticas públicas place-based assentam num modelo de governação territorial, onde
o poder de decisão se encontra descentralizado nos atores locais e o plano de ação é
delineado com base nas potencialidades e necessidades de uma identidade geográfica
definida (Reimer & Markey, 2008). Esta descentralização pode reforçar a eficácia e a
eficiência do sector público, comparativamente às políticas públicas definidas ao nível
nacional (Berthet, 2008:134). Contudo, um dos desafios com que se depara a execução
das políticas territoriais é a dificuldade de serem definidas unidades territoriais
uniformes e mobilizar diversos atores em torno de um projeto comum, sobretudo, numa
sociedade marcada essencialmente pelo individualismo (Lazarev, 2009: 204). Segundo
Barca et al. (2012: 148), para que a implementação de políticas place-based seja bemsucedida é necessário assegurar que os estímulos aos comportamentos de todos os
parceiros estejam alinhados em torno ao mesmo objetivo. Neste contexto, apenas com
uma forte articulação entre os conceitos place-based e people-based é que se
4
4306 | ESADR 2013
conseguem implementar políticas que conduzam ao desenvolvimento regional (Barca et
al, 2012: 149).
A abordagem place-based constitui a espinha dorsal da política de coesão para o
período de 2014-2020, inclusivamente a existência de “Estratégias de Investigação e
Inovação Nacionais/Regionais para a Especialização Inteligente” (RIS3) em cada
Estado-membro, constitui um requisito ex-ante de acesso aos fundos estruturais. As
estratégias RIS3 defendem que os territórios deverão dar prioridade aos recursos
endógenos, aos setores de atividade e/ou tecnologias, nos quais possuem uma vantagem
comparativa e potencial para alavancarem atividades inovadoras (Foray et al., 2012:9).
Esta iniciativa foi prevista para potenciar a inovação no sentido lado, ou seja, não
apenas no domínio da investigação, mas também no fomento a novos modelos de
negócios ou organizacionais (Foray et al., 2012:10). O conceito RIS3 foi desenvolvido
com base nas aprendizagens oriundas de anteriores Estratégias Regionais de Inovação
Europeias, cujas avaliações evidenciaram algumas limitações em termos de resultados e
de eficácia (Foray et al., 2012:11-12). Com o presente estudo procurou-se dar
continuidade às investigações realizadas sobre esta temática, mediante a análise da
eficiência, da eficácia e do valor acrescentado de um dos exemplos mais conhecido de
políticas place-based: o Programa de Iniciativa Comunitária LEADER.
Quando surge em 1991, o Programa LEADER vem defender princípios distintos dos
sustentados pelas teorias clássicas: uma abordagem bottom-up, em vez da abordagem
tradicional top-down e um enfoque territorial, em oposição ao enfoque sectorial,
conferindo-lhe a capacidade de abordar a problemática do desenvolvimento rural com
base num método inovador (Santos, 2012: 21). Nessa época, preconizava-se que a
criação de condições para o aparecimento de novas atividades complementares, ou não,
ao setor agrícola serviria de alavanca para o aparecimento de oportunidades de emprego
alternativas e outras fontes de rendimentos, com vista a melhorar a qualidade de vida no
meio rural (Champetier, 2003). Para a concretização destes objetivos, o sector privado,
o sector público e o terceiro sector, foram convidados a participar na elaboração dos
programas locais (Lazarev, 2009: 191). Estas parcerias deram origem à constituição dos
Grupos de Ação Local (GAL), entidades responsáveis pela definição, organização e
implementação da Estratégia Local de Desenvolvimento (ELD) e pela seleção dos
projetos a serem financiados (CE, 2006:10-15). A diversidade das zonas rurais e a
5
autonomia dos GAL, na transposição dos objetivos globais ao nível local, originou o
aparecimento de ELD na mesma proporção e número que estas entidades. Na União
Europeia, ao longo das três primeiras iniciativas do Programa LEADER, que
decorreram de 1991 a 20064, a sua área de intervenção passou de 367.000Km² para
1.577.386Km² e o número de GAL a atuar nessas zonas aumentou de 217 para 893 (CE,
2006: 7). Em Portugal, o LEADER I deu origem à constituição de 20 GAL, dois dos
quais localizados na região Alentejo. Com o LEADER +, Portugal passou a contar com
a presença de 52 GAL e o Alentejo com 8 entidades (Barrocas, 2008), conforme ilustra
a figura I.
Figura I – Três iniciativas LEADER na região Alentejo - mapa com a evolução das zonas de
intervenção dos GAL
Fonte: Neto, Santos & Serrano (2012: 638).
Apesar dos GAL terem autonomia para definirem as orientações da EDL, em função das
prioridades e potencialidades que identificassem para o território, os resultados finais
4
LEADER I de 1991 a 1993, LEADER II de 1994 a 1999 e LEADER + de 2000 a 2006.
6
4308 | ESADR 2013
teriam de convergir para os objetivos gerais definidos a nível comunitário para o
Programa LEADER, no Parecer CE n.º 91/C, nomeadamente: i) atenuar a desertificação
humana e o envelhecimento populacional; ii) diversificar o tecido empresarial; iii)
valorizar e promover os recursos endógenos do território; iv) estimular iniciativas e
projetos inovadores; v) desenvolver competências, mediante a formação e qualificação
dos recursos humanos ou vi) fomentar a preservação do meio ambiente. A presente
análise irá centrar-se precisamente sobre estas metas.
2.2. Dimensões de análise de políticas públicas: eficácia, eficiência e valor acrescentado
A análise das políticas públicas é geralmente baseada na apreciação de três elementos:
os recursos financeiros e não monetários (input), canalizados para a implementação e
execução de uma política ou programa, os quais se traduzem em realizações materiais e
imateriais (output) e os resultados ou efeitos (outcome) gerados numa economia ou
território (EC, 2008 e Vollet & Hadjab, 2008), conforme ilustra a figura II.
Figura II – Dimensões da avaliação de políticas públicas
SOCIEDADE
ECONOMIA
AMBIENTE
PROGRAMA
AVALIAÇÃO
Impactos
Necessidades
Problemas
Questões
Efeitos
Resultados
(Outcome)
Relevância
Pertinência
Realizações
(Output)
Recursos
(Input)
Objetivos
Coerência
Eficiência
Eficácia
Utilidade | Sustentabilidade
Fonte: Santos (2012: 35) adaptado com base em EC (2008:42) e Arnaud & Boudeville (2004: 37).
Neste contexto, a análise da eficácia e eficiência está baseada na apreciação das
relações existentes entre os inputs, outputs e outcomes (Mandl et al, 2008: 2). A análise
de eficiência verifica se os recursos mobilizados produziram os resultados, efeitos e
impactos pretendidos e a análise de eficácia examina se os objetivos fixados foram
7
alcançados (EC 2008: 42). Quando a análise de eficiência é expressa em termos
monetários, o rácio input-output é o indicador mais vulgarmente utilizado para medir a
performance da política ou programa. A sua interpretação indica quanto foi despendido
para se produzir um determinado output (Sapru, 2011:33). Este indicador corresponde
também, em sentido lato, à análise custo-eficácia, a qual tem por finalidade comparar as
despesas de um programa com os resultados obtidos, para determinar, por exemplo, o
custo por emprego criado (Euréval, 2010:1).
Neste trabalho, foram considerados como inputs os recursos financeiros utilizados na
implementação do LEADER e como outputs o investimento realizado ao abrigo deste
Programa na região Alentejo, no período de 1991 a 2006. Os outcomes assumem uma
dimensão mais qualitativa, baseada numa análise comparativa do diagnóstico5 da região
Alentejo, antes e após a implementação das três fases do programa.
Os Fundos Comunitários são suscetíveis de gerar, quando utilizados de forma acertada,
um valor acrescentado face a uma situação alternativa caracterizada pela ausência da
intervenção pública (CE, 2002: 3)6. As políticas ou programas geram outputs e
outcomes, os quais, com base neste princípio, não existiriam, total ou parcialmente, sem
os inputs que estas injetam numa determinada realidade económica e social. Segundo a
EC (2008: 42), esta situação traduz-se na utilidade da política pública, a qual está
associada à noção de valor acrescentado. A figura III resume os quatro temas-chaves
que agrupam alguns indicadores, quantitativos e qualitativos, que permitem a medição
do valor acrescentado, definidos pela CE (2002).
5
Por via da análise SWOT (Strengths, Weaknesses, Opportunities, and Threats), a qual identifica os pontos fortes,
pontos fracos, oportunidades e ameaças de uma entidade ou território; síntese realizada pelas entidades regionais
gestoras dos fundos comunitários e presente em CCRA (1986) e PORA (2008).
6
Neste contexto, segundo TCE (2010: 30) é importante também averiguar se o promotor poderia ter sido capaz de
desenvolver o projeto mesmo sem este apoio. Numa situação designada de “peso morto”, a subvenção não produz
nenhum efeito adicional, uma vez que o projeto subsidiado teria sido total ou parcialmente executado sem a
concessão desta ajuda financeira. Um forte indício da existência de um “peso morto” é o facto de o promotor já ter
iniciado o projeto antes de ter sido notificado da decisão de análise (TCE, 2010: 30). Neste estudo, em virtude de não
ser conhecido o calendário de execução de cada candidatura, partiu-se do princípio que os resultados gerados não
teriam ocorrido sem a existência do programa.
8
4310 | ESADR 2013
Figura III – Indicadores de medição do Valor Acrescentado Comunitário
 Crescimento adicional do PIB;
 Acréscimo do nível de investimento e emprego;
 Promover a igualdades de oportunidades e o
desenvolvimento sustentável;
 Reforçar a dotação em infraestruturas;
 Assegurar um incremento de competitividade e
produtividade nas empresas;
Critérios relacionados com
objetivos Comunitários
 Medição do esforço público global e evolução das
despesas de origem nacional;
 Efeito de alavanca financeiro para a mobilização do
setor privado e de cofinanciamento público nacional;
 Promover o equilíbrio entre empréstimos e subvenções.
Indicadores do Valor Acrescentado
Comunitário - VAC
Critérios relacionados com a
operacionalidade dos Fundos Europeus
 Grau de integração e coerência entre prioridades
nacionais e comunitárias;
 Grau de representatividade e eficiência das parcerias;
 Intensidade dos trabalhos de avaliação,
controlo/auditoria e sistemas de acompanhamento.

Critérios Financeiros
Critérios relacionados com a
cooperação e colocação em rede
 Valor acrescentado das atividades de cooperação;
 Efeito de alavanca de ações inovadoras em termos de
investimento mobilizado e emprego criado;
 Grau de transferência e articulação de ações comuns;
 Quantificação das iniciativas e seminários destinados à
troca de experiências.
Fonte: Elaborado pelos autores com base em CE (2002).
Contudo, o valor acrescentado do Programa LEADER não se limita ao impacto
produzido pelos incentivos financeiros introduzidos nas economias rurais. A abordagem
LEADER implica custos e riscos adicionais em relação a métodos mais tradicionais e
centralizados de execução da política de desenvolvimento rural, mas tem igualmente
potencial para gerar valor acrescentado [adicional] através das suas características
metodológicas (TCE, 2010:12), conforme ilustra a figura IV.
Figura IV – Evolução da Eficiência dos Programas-tipo LEADER versus Programas clássicos
Fonte: Adaptado com base em Öir (2004:57).
9
Segundo Wade & Rinne (2008: 82), o LEADER é um Programa cujos efeitos são mais
visíveis no longo prazo, como resultado do desenvolvimento progressivo da capacidade
e do envolvimento dos recursos humanos. Neste contexto, quanto maior é o período de
experiência e familiarização das regiões/países com o Programa LEADER, maiores são
os resultados observados (Wade & Rinne, 2008: 82).
3. Metodologia e procedimentos metodológicos
Segundo Santos (2012: 42), as avaliações realizadas ao Programa LEADER, em
Portugal, tiveram essencialmente por base a análise da taxa de execução financeira. Foi,
aliás, com base neste indicador que os técnicos apreciaram a eficácia desta iniciativa
comunitária. Os indicadores de resultados destas análises incidiram principalmente em
investimento realizado por domínios e tipo de promotor, e os indicadores de impacto
centraram-se no emprego criado e respetivo perfil (Santos, 2012: 42).
Com o presente estudo7, procurou-se realizar uma análise mais aprofundada do
investimento realizado ao abrigo deste Programa, com enfoque na região Alentejo.
Contudo, a informação necessária para este trabalho de investigação não estava
disponível nos relatórios de execução e avaliação final do Programa LEADER, pelo
que, foi necessário proceder-se à análise individual dos 2.706 projetos de investimento
executados e financiados pelo Programa LEADER na região Alentejo, entre 1991 e
2006. Desta apreciação resultou uma base de dados onde cada projeto se encontra
classificado por localização geográfica, tipo do promotor, atividade económica e
natureza da despesa efetuada. A escolha das variáveis de análise teve por base os
objetivos da iniciativa LEADER com vista a poder caracterizar-se as realizações e
resultados desta iniciativa comunitária no Alentejo.
A análise dos resultados teve por base a apreciação de indicadores de realização e
resultado e do rácio input-output, sendo este último obtido pelo quociente entre os
custos (input) e os resultados obtidos (output).
As entidades consultadas para a obtenção da informação foram os Grupos de Ação
Local a atuarem na região Alentejo; Comissão Gestora do LEADER+; Direcção-Geral
de Agricultura e Desenvolvimento Rural; Comissão Europeia – Unidade F1. Programas
7
O qual é o resultado de um trabalho de investigação mais extenso realizado no âmbito de uma dissertação de
Mestrado em Economia na Universidade de Évora (Santos, 2012).
10
4312 | ESADR 2013
de Desenvolvimento Rural (Bruxelas); ELARD - European LEADER Association for
Rural Development (Bruxelas) e Federação Minha Terra.
4. Análise dos resultados
4.1. Apresentação dos resultados globais
Ao longo das três primeiras fases do Programa LEADER, que decorreram de 1991 a
2006, foram executados e financiados 2.706 projetos de investimento na região
Alentejo, num valor total de 85,5 milhões de euros. A contribuição da CE foi
equivalente a cerca de 47 milhões de euros e a despesa privada a 27,8 milhões de euros.
Previa-se a criação de 1.177 postos de trabalho e a manutenção de 1.152 empregos.
Quadro I – Indicadores de Realização e de Resultado, LEADER I – LEADER +, região Alentejo
LEADER I
LEADER II
LEADER +
TOTAL
(1991-1994)
(1995-1999)
(2000-2006)
Indicadores de Realização (Output)
N.º projetos aprovados e executados
202
1.000
1.504
2.706
Investimento realizado
11.970.714 €
25.875.238 € 47.583.243 € 85.429.195 €
Despesa pública
Contribuição CE
Contribuição nacional
Despesa privada
Postos de trabalho criados
Emprego mantido
Indicadores de Resultado (Outcome)
Emprego médio criado por projeto
Investimento/Posto de trabalho criado
6.078.128 €
412.583 €
5.480.003 €
167
n.d.*
15.865.147 €
1.905.235 €
8.104.856 €
462
203
25.222.983 €
8.124.127 €
14.236.133 €
548
949
47.166.258 €
10.441.945 €
27.820.992 €
1.177
1.152
1
71.681 €
2
56.007 €
3
86.831 €
2
72.582 €
Fonte: Cálculos elaborados pelos autores com base em Ministério da Agricultura (1995), MADRP (2001), Autoridade
de Gestão do PIC Leader+ (2008) e Barrocas (2008). * Não disponível.
O número médio de postos de trabalho criados por projeto aumentou ao longo das 3
fases do programa, contudo o esforço financeiro necessário para a criação de um posto
de trabalho adicional também aumentou entre o LEADER II e o LEADER +. Este facto
pode ser sintomático, do ponto de vista social e do mercado de trabalho, de que o
programa ganhou em eficácia – resultados versus objetivos – mas perdeu em eficiência
– recursos versus objetivos – entre a 2ª e 3ª fase do Programa. Uma conclusão similar
pode ser sugerida pela evolução do rácio input-output, respeitante ao acréscimo do nível
de emprego, conforme informação do quadro II.
11
Quadro II – Rácio input-output, LEADER I – LEADER +, região Alentejo
LEADER I LEADER II LEADER +
Objetivo: análise do efeito de alavanca financeiro na despesa privada8
Rácio Input-Output
1,1 €
2,0 €
1,8 €
Objetivo: análise do efeito de alavanca financeiro no cofinanciamento público nacional9
Rácio Input-Output
14,7 €
8,3 €
3,1 €
Objetivo: análise do acréscimo do nível de investimento10
Rácio Input-Output
0,51 €
0,61 €
0,53 €
11
Objetivo: análise do acréscimo do nível de emprego
Rácio Input-Output
36.396 €
34.340 €
46.027 €
Fonte: Elaborado pelos autores com base no quadro I.
Contudo, do ponto de vista do efeito de alavanca financeira na despesa privada e no
cofinanciamento público nacional, assim como no acréscimo do nível de investimento,
verifica-se um aumento da eficiência do LEADER II para o LEADER +.
4.2. Análise descritiva do investimento realizado
O sector privado foi, nas três iniciativas LEADER, aquele que mais contribuiu para a
Formação Bruta de Capital Fixo na região, por via do investimento realizado. Contudo,
as entidades deste sector registaram uma diminuição do seu peso relativo,
comparativamente ao 3º setor e ao setor público. No mesmo período, os GAL foram
responsáveis por 26% do investimento realizado, assumindo a importância da despesa
realizada uma proporção tendencialmente constante.
Quadro III – Investimento realizado por tipologia de promotor, LEADER I - LEADER +,
região Alentejo
Setor Privado
Setor Público
3º Setor
GAL
LEADER I
66%
3%
8%
23%
LEADER II
41%
13%
17%
29%
LEADER +
40%
12%
23%
25%
CONJUNTO
46%
10%
18%
26%
Fonte: Cálculos elaborados pelos autores com base em Ministério da Agricultura (1995), MADRP (2001) e
Autoridade de Gestão do PIC Leader+ (2008).
8
Input = Contribuição CE | Output = Despesa privada
Input = Contribuição CE | Output = Cofinanciamento público nacional
10
Input = Contribuição CE | Output = Investimento realizado
11
Input = Contribuição CE | Output = Emprego criado
9
12
4314 | ESADR 2013
Em média, 96% do investimento realizado pelo setor privado assentou em projetos
exclusiva ou prioritariamente baseados na aquisição de equipamento e/ou de obras de
remodelação.
Os
pedidos
de
apoio,
predominantemente
fundamentados
em
investimentos nas áreas do marketing e comunicação e da aquisição de conhecimentos,
apresentam um peso relativo residual, entre 1% a 2% do investimento total. As
principais atividades económicas financiadas foram as atividades turísticas (alojamento
e animação) e a agro-indústria. O desenvolvimento de atividades no setor dos serviços
apresentou uma tendência crescente, apesar de uma média pouco representativa, inferior
a 7% do investimento total realizado pelo setor privado.
Quadro IV – Investimento realizado pelo setor privado por categoria de investimento e tipologia de
atividade/objeto do pedido de apoio, LEADER I - LEADER +, região Alentejo
Atividade
Investimento
LEADER I
LEADER II LEADER + CONJUNTO
Materiais
Aquisição de conhecimentos
Marketing e comunicação
Outras despesas
Turismo
97%
1%
2%
0%
61%
96%
1%
2%
1%
39%
96%
1%
2%
1%
35%
96%
1%
2%
1%
44%
Agroindústria
Gastronomia
Serviços
19%
23%
30%
5%
2%
2%
11%
10%
10%
2%
16%
9%
9%
8%
9%
25%
8%
7%
Comércio
Outras atividades
4%
12%
Os investimentos do setor público centraram-se, no período em análise, essencialmente
na promoção dos recursos endógenos do território e na conservação e preservação do
património, por via de investimentos em atividades de marketing e comunicação e de
investimentos materiais, como é o caso das obras de recuperação (ver quadro V).
Investimento
Quadro V – Investimento realizado pelo sector público por categoria de investimento e tipologia de
Materiais
Outras despesas
LEADER I
0%
64%
36%
0%
LEADER II
11%
67%
17%
5%
LEADER +
7%
54%
32%
7%
CONJUNTO
8%
60%
27%
6%
Continua…
13
Atividade
Conservação património
Promoção do território
Formação
Outras atividades
LEADER I
LEADER II
LEADER +
CONJUNTO
48%
49%
0%
4%
45%
21%
15%
19%
24%
32%
12%
32%
33%
29%
12%
25%
No terceiro setor, os investimentos materiais realizados representam, em média, mais de
50% do montante total despendido. A criação e o desenvolvimento do associativismo de
cariz social, cultural e desportivo, foram as atividades mais representadas, juntamente
com a promoção dos recursos endógenos, a conservação do património cultural, e a
dinamização e preservação do folclore tradicional do território.
LEADER I
LEADER II
LEADER +
CONJUNTO
Investimento
Materiais
Outras despesas
24%
57%
18%
0%
23%
38%
17%
22%
17%
60%
10%
13%
19%
53%
13%
14%
Atividade
Quadro VI - Investimento realizado pelo 3º sector por categoria de investimento e por tipologia de
Conservação património
Formação
Outras atividades
Associativismo
14%
13%
5%
68%
33%
16%
14%
12%
58%
27%
13%
7%
9%
70%
42%
14%
10%
10%
66%
36%
Os GAL foram as entidades que mais privilegiaram os investimentos imateriais, como é
o caso da aquisição e transferência de conhecimentos, nomeadamente através das
despesas associadas à contratação de quadros técnicos, à consultadoria externa e à
realização de seminários para troca de experiências. No conjunto, mais de 60% do
investimento realizado pelos GAL destinou-se ao desenvolvimento de atividades
próprias ao funcionamento destas entidades, enquanto agentes responsáveis pela política
de desenvolvimento local. A promoção dos recursos endógenos do território e a
qualificação dos recursos humanos foram também atividades com grande expressão no
14
4316 | ESADR 2013
total do investimento realizado, representando 18% e 13% do investimento total
realizado, respetivamente.
Atividade
Investimento
Quadro VII – Investimento realizado pelos GAL por categoria de investimento por tipologia de
atividade/objeto do pedido de apoio, no âmbito do LEADER I - LEADER +, região Alentejo
LEADER I
LEADER II
LEADER +
CONJUNTO
Materiais
36%
12%
33%
54%
5%
14%
53%
15%
15%
50%
11%
18%
Outras despesas
18%
26%
17%
21%
Serviços
Formação
38%
15%
35%
71%
14%
13%
65%
13%
14%
62%
13%
18%
Outras atividades
12%
2%
8%
7%
O investimento realizado nos concelhos com uma densidade populacional inferior a
15hab/km² apresenta uma tendência decrescente ao longo das três iniciativas LEADER,
apesar de, no conjunto, representar cerca de 50% do montante de investimento
realizado, conforme ilustra o quadro VIII. Os concelhos com uma densidade
populacional superior a 30 hab/km², mas inferiores a 70hab/km², registaram um
acréscimo de volume do investimento realizado nestes municípios, atingindo 20% da
despesa total no âmbito do LEADER+.
No LEADER I e LEADER II as regiões com um índice de envelhecimento inferior a
150 beneficiaram de 79% e 53% do investimento realizado, respetivamente. Neste
sentido, pode depreender-se que, dentro das zonas de intervenção dos GAL, as regiões
menos envelhecidas foram as principais responsáveis pelo dinamismo dos setores de
atividades. No LEADER + assiste-se a uma alteração significativa desta tendência, ou
seja, os concelhos com um índice de envelhecimento superior a 150 centralizaram mais
de 90% do montante de investimento realizado.
À exceção dos resultados obtidos no LEADER I, os territórios com uma reduzida
concentração empresarial na zona de intervenção do GAL canalizaram mais de 55% do
investimento realizado. O que nos leva a concluir que o programa poderá ter contribuído
para fomentar o empreendedorismo em áreas mais carenciadas.
15
Quadro VIII – Investimento realizado por localização geográfico, no âmbito do PIC LEADER I,
LEADER II, LEADER +, na região Alentejo
LEADER I
LEADER II
Escalões Densidade Populacional
< 15 hab/km²
75%
41%
15 - 30 hab/Km²
25%
44%
> 30 hab/Km²
0%
15%
Escalões Índice de Envelhecimento
< 150
79%
53%
150 – 200
17%
27%
> 200
5%
20%
Escalões Concentração Empresarial na Zona de Intervenção
< 15%
20%
67%
15% - 30%
75%
20%
> 30%
5%
13%
LEADER +
Conjunto
43%
36%
20%
50%
36%
14%
9%
49%
41%
38%
35%
27%
57%
23%
21%
50%
35%
15%
Face à análise descritiva das características do investimento realizado, e comparando os
resultados obtidos com os objetivos inicialmente definidos para o Programa LEADER,
parece evidente a eficácia deste no estímulo à diversificação de atividades económicas,
nas zonas rurais do Alentejo. O LEADER levou, inclusivamente, à especialização do
investimento privado em torno de dois setores de atividade: a agro-indústria e o turismo.
Estes sectores apresentam-se, hoje em dia, como fileiras económicas estratégicas para o
desenvolvimento da região Alentejo (PORA, 2008).
O volume de emprego nas empresas com atividade económica no domínio do
alojamento, restauração e similares, aumentou, entre 1991 e 2010, de 7.200 para 11.800
postos de trabalho, na região Alentejo (INE, 1993 e 2012). Contudo, apesar da iniciativa
LEADER ter contribuído para fomentar o empreendedorismo em zonas de menor
concentração empresarial (conforme ilustra o quadro VIII), o Programa evidenciou
algumas dificuldades em desenvolver uma cultura empresarial ancorada em estratégias
inovadora12. Segundo o PORA (2008: 42), é ainda persistente hoje em dia, no Alentejo
uma cultura empresarial deficitária no que respeita à capacidade de gestão e de
implementação de estratégias de marketing e de comercialização.
Por último, importa referir que, apesar dos resultados alcançados pelo Programa ao
nível da empregabilidade, a população residente na região Alentejo tem continuado a
12
A análise individual realizada a cada projeto permitiu evidenciar uma fraca e/ou ausência de inovação nos projetos
financiados, como aliás outros estudos realizados (TCE, 2010 e ÖIR, 2004) também já tinham demonstrado. Por
outro lado, e neste contexto, constatou-se que as despesas realizadas em I&DT revelaram ser residuais.
16
4318 | ESADR 2013
registar um decréscimo nas últimas décadas, ainda que, a partir de 1991, se tenha
verificado uma desaceleração na diminuição da população (Santos, 2012: 61). Neste
contexto, podemos concluir que o LEADER mostrou alguma eficácia no abrandamento
do ritmo do êxodo rural, ao ter contribuído para fixar alguma população nas zonas
rurais. Paralelamente, o Programa ganhou em eficiência entre o LEADER II e o
LEADER +, ao ter conseguido aumentar o volume do investimento nas zonas menos
povoadas e mais envelhecidas, conforme ilustra o quadro VIII.
5. Conclusão e recomendações
A análise realizada permitiu concluir que o LEADER, conforme já defendido por Wade
& Rinne (2008: 82), é efetivamente um Programa com efeitos de longo prazo, ou seja, a
sua eficiência tende a aumentar ao longo dos anos. Por outro lado, o estudo evidenciou
que o Programa induziu uma especialização do investimento, realizado pelo setor
privado, em torno da agro-indústria e do turismo (áreas identificadas nas ELD como de
intervenção prioritária).
Marques & Santos (2011) já tinham inclusivamente demonstrado a capacidade das
políticas
públicas
descentralizadas
para
estimularem
trajetórias
económicas
especializadas. No caso da região Alentejo, as características do território aliadas à
tendência recente de mercado em torno da valorização dos produtos agro-alimentares,
das produções locais, e do turismo, foram propícias ao desenvolvimento do setor
agroindustrial e turístico. A agro-indústria surge como uma solução para aproveitar os
recursos primários numa região com forte tradição agrícola (Santos, 2012). Ao nível
turístico, a região é detentora de um rico património natural e arquitetónico e possui
uma forte identidade cultural (PORA, 2012:45), condição sine qua non para o
desenvolvimento destas atividades. No entanto, apesar dos estímulos ao investimento, o
Programa mostrou-se pouco eficaz no fomento de atividades de preservação do
ambiente ou de projetos inovadores com perfil diferenciador. Por exemplo, os projetos
promovidos pelo setor privado tiveram, na sua maioria, como finalidade capacitarem as
empresas para o desenvolvimento de uma atividade, em vez de lhes permitirem a
obtenção de vantagens competitivas no mercado global.
A análise individual realizada a todos os projetos concretizados, permitiu verificar que a
inovação subjacente à maioria das candidaturas não pode ser vista como radical mas
17
sobretudo de natureza incremental. Não obstante, veio contribuir para a diversificação
do sector empresarial e para o aparecimento de novas atividades, numa região onde
estas eram escassas e por vezes inexistentes (Santos, 2012: 63).
Importa ainda referir que todos os beneficiários, à exceção dos GAL, privilegiaram os
investimentos de tipo material. As despesas em I&DT revelaram-se pouco expressivas
e/ou totalmente inexistentes, em parte por não terem sido consideradas diretamente
como prioritárias nas ELD e por possuírem uma elegibilidade limitada.
Com o apoio da iniciativa LEADER, o Alentejo viu algumas das suas fragilidades
serem eliminadas, sobretudo no que respeita à deficiente cobertura de infraestruturas de
apoio às atividades produtivas e de alojamento turístico. No entanto, persistem ainda
algumas debilidades quanto a: i) iniciativa e densidade empresarial; ii) falta de domínio
da cadeia de valor13, e iii) nível de investimento e despesa em I&DT (PORA, 2008:42),
que importa no futuro ultrapassar.
A melhoria dos resultados (outputs) e dos impactos (outcomes), alcançados por este tipo
de políticas públicas, poderia ter sido mais consequente, se estes programas tivessem
sido mais orientados para os resultados do que para as realizações. Por exemplo, entre
outras alternativas possíveis, mediante a atribuição de um incentivo não reembolsável
apenas perante indicadores de desempenho e mérito real. Conforme Bernini &
Pellegrini (2011) as empresas subsidiadas investiram mais do que normalmente o
fariam e aumentaram o número de emprego mais do que as empresas não subsidiadas
(…). [Contudo], a produtividade das empresas subsidiadas mostra um menor
crescimento do que nas empresas não subsidiadas. As empresas excedem o nível ótimo
de emprego afim de obterem o subsídio, o que pode afetar a eficiência e crescimento de
longo prazo (Bernini & Pellegrini, 2011: 262 – 264).
Bibliografia
Arnaud S.;
Boudeville N. (2004). Evaluer des politiques et programmes publics, Éditions de la
Performance, France.
Autoridade de Gestão do PIC Leader+ (2008). Listagem dos projectos aprovados, Lisboa.
13
A maioria das empresas não domina a cadeia de valor do seu sector/cluster, carecendo de maior conhecimento
nas áreas da organização e gestão, inovação, marketing/vendas, tecnologias de informação e comunicação, design,
investigação e desenvolvimento (PORA, 2008:42).
18
4320 | ESADR 2013
Avis du Comité économique et social européen sur le thème : «Leader en tant qu’instrument du
développement local» (avis d’initiative), (2011/C 376/03), Journal officiel de l’Union européenne n.º
C 376, 22.12.2011, p. 15-18, Bruxelles.
Barca, F.; McCann, P. and Rodrıguez-Pose, A. (2012). The Case for Regional Development Intervention:
Placed-Based Versus Place Neutral Approaches. Journal of Regional Science. Vol. 52, nr 1, 134-152.
Barthelemy, P. A.; Vidal, C. (1995). Les ruralités de l’Union Européenne, Union européenne. Disponível
em http://ec.europa.eu/agriculture/envir/report/fr/rur_fr/report_fr.htm (acesso em : 25 Março 2012).
Barrocas, C. A. S. C. (2008). 15 Anos do Programa LEADER no Alentejo: Avaliação de Impactos; Ideia
Alentejo – Associação para a Inovação e Desenvolvimento Integrado do Alentejo, Beja.
Bernini, C. ; Pellegrini, G. (2011). How are growth and productivity in private firms affected by public
subsidy? Evidence from a regional policy. Regional Science and Urban Economics, volume 41, Issue
3, May 2011, Elsevier B.V, p. 253–265.
Berthet, T. (2008). Les enjeux de l'évaluation territoriale des politiques publiques. Informations sociales,
2008/6 n° 150, p. 130-139.
CCRA (1986). Programa de Desenvolvimento Regional (documento de trabalho), Ministério do Plano e
da Administração do Território, Évora.
CE (2002). Valeur Ajoutée Communautaire dans le cadre des Poliques Structurelles – Définition et
critères d’évaluation (Document de travail), Direction Générale, Politique Régionale, Bruxelles.
Champetier, Y. (2003). L'Europe et le développement rural. Projet 2003/2 n° 274, p. 59-67.
CE (2006). L’approche Leader – Guide de base, Office des publications officielles des Communautés
européennes, Luxembourg.
Dall’Herba, S. et al. (2008). Fonds structurels, effets de débordement géographique et croissance
régionale en Europe. Revue de l'OFCE, 2008/1 n° 104, p. 241-269.
EC (2008). Evalsed, the resource for the Evaluation of Socio-Economic Development - Guide,
Directorate-General for Regional Policy, Luxembourg.
Euréval, Centre Européen d’Expertise et d’Evalution. L’Analyse coût-efficacité, fiche téchnique, France.
Disponível em http://www.eureval.fr/IMG/File/FT_ACE.pdf (acesso em: 25 Julho 2013).
Foray, D.; Goddard, J.; Beldarrain, X. G.; Landabaso, M.; McCann, P.; Morgan, K.; Nauwelaers, C.;
Ortega-Argilés, R. (2012). Guide to Research and Innovation Strategies for Smart Specialisation (RIS
3), European Union, Regional Policy. Disponível em http://s3platform.jrc.ec.europa.eu/s3pguide
(acesso em: 5 Agosto 2013).
INE (1993). Painel de Empresas 1990 – 1991, Lisboa.
INE (2012). Anuário Estatístico da Região Alentejo 2011, Lisboa, Portugal.
Lazarev, G. (2009). Promouvoir le développement des territoires ruraux. MediTERRA 2009, Presses de
Sciences Po Annuels, CIHEAM et Plan Bleu, p. 183-210.
MADRP (2001). Programa de Iniciativa Comunitária LEADER II, Relatório de Execução Final,
Comissão Nacional de Gestão, Direcção Geral de Desenvolvimento Rural, Lisboa.
Marques, C. B ; Santos, C. H. S. (2011). Políticas públicas para pensar no desenvolvimento de um sítio
local – um modelo. Estudos Regionais, Revista Portuguesa de Estudos Regionais n.º 25-26, 107-120.
19
Mandl, U.; Dierx, A.; Ilzkovitz, F. (2008). “The effectiveness and efficiency of public spending”,
Economic Paper n.º 301, European Commission, Directorate-General for Economic and Financial
Affairs, Brussels, Belgium.
Ministério da Agricultura (1995). Programa de Iniciativa Comunitária LEADER, Listagem de projectos
Financiados, Volume C e Volume C1, Comissão Nacional de Gestão, Instituto de Estruturas Agrárias
e de Desenvolvimento Rural, Lisboa.
Moreno, L. (2003). “O LEADER em Portugal Continental: contexto e elementos de uma análise
geográfica de conteúdos”, Actas do V Colóquio Hispano-Português de Estudos Rurais Futuro dos
Territórios Rurais numa Europa Alargada, Bragança 23 e 24 de Outubro de 2003.
Neto, P.; Santos. A.; Serrano, M. M. (2012). “Public Policies Supporting Local Based Networks for
Entrepreneurship and Innovation – Contributions to the Effectiveness and Added Value Assessment”,
Uddevalla Symposium 2012: Entrepreneurship and Innovation Networks, Revised papers presented at
the 15th Uddevalla Symposium, 14 – 16 June, Faro, Portugal, University West, Sweden, 627 – 648.
OECD (2006), The New Rural Paradigm: Policies and Governance, OECD Publishing.
ÖIR (2004). Methods for and Success of Mainstreaming Leader Innovations and Approach into Rural
Development Programmes, Final Report, Commissioned by European Comission, Austrian Institute
for Regional Studies and Spatial Planning, Viena.
Parecer CE (91/C 31/14), JO n.° C 31 de 06.02.1991, p. 42-43.
PORA - Programa Operacional Regional do Alentejo 2007 – 2013 (2008), Observatório do QREN –
Quadro de Referência Estratégica Nacional, Lisboa.
Reimer, B.; Markey, S. (2008). Place-based Policy: A Rural Perspective, A Report to Human Resources
and
Social
Development
Canada.
Disponível
em
http://crcresearch.org/files-
crcresearch_v2/ReimerMarkeyRuralPlaceBasedPolicySummaryPaper20081107.pdf (acesso em: 2
Junho 2013).
Santos, A. (2012). Análise dos efeitos do Programa de Iniciativa Comunitária LEADER na região
Alentejo, entre 1991 e 2006, dissertação de Mestrado em Economia, Universidade de Évora, Évora.
Sapru, R. K. (2011). Public Policy: Art and Craft of Policy Analysis, Second Edition, Eastern Economy
Edition, PHI Learning Private, Limited, New Delhi, India.
TCE (2010). Relatório Especial n.º 5/2010 - Aplicação da abordagem Leader ao desenvolvimento rural,
Luxemburgo.
Universidade de Évora (2007). Programa Operacional Regional do Alentejo 2007-2013, Avaliação ExAnte, Relatório Final, Évora, Portugal.
Vollet, D. e Hadjab F. (2008). Manuel de l'évaluation des politiques publiques, Editions Quae, France.
Wade, P. & Rinne, P. (2008). A LEADER Dissemination Guide Book based on programme experience in
Finland, Ireland and the Czech Republic, Final Report of the Transnational LEADER Dissemination
Project
for
the
Finnish
Rural
Policy
Committee.
Disponível
em
http://ec.europa.eu/agriculture/rur/leaderplus/pdf/library/cooperation/tnldp.pdf (acesso em: 28 Maio
2013).
20
4322 | ESADR 2013
Designing rural development strategies: learning also matters
Domingos Santos
Professor - Polytechnic Institute of Castelo Branco
Researcher - CICS - Social Sciences Research Centre - University of Minho
[email protected]
Abstract
There is now a considerable set of theoretical approaches concerning the need rural
world faces in the global knowledge economy. In particular, there is a rich academic
production of territorial innovation models from which we can learn, extending the
concept of regional learning to the field of developing predominantly rural areas.
The first part of this article examines the challenges rural territories are facing against
the background of modern theories of innovation and regional policies. It is argued that
the role of localized learning is of strategic importance in the promotion of endogenous
rural and regional development.
Then, departing either from the handicaps either from the assets of rural areas, this
paper argues that development in rural regions is made up of a complex set of
interactions between different actors and processes. We question whether current rural
policies are adequate to guarantee the competitiveness and sustainability of rural
territories. Studying and intervening on the rural dynamics requires a shift from
focusing on forms of knowledge and innovation outputs towards focusing on learning
and innovation dynamics, exploring the diverse dimensions of knowledge building and
promoting social capital.
Key words: rural development, rural policy, innovation policy, innovation, learning.
1. Introduction
Rural areas are highly heterogeneous, wether the criteria is agro-ecological, defined in
terms of distance from urban centres, or to do with the focus on agricultural
modernisation. Rural areas are changing, in size, structure, and capability of population,
in the pattern of economic activity, and in the degree of integration with national and
international economies. Rural development, if it is to succeed, has to catch up with
these challenges.
Rural development has emerged as a major policy field in the early 1990s and has
polarised growing attention within spatial development policies. It has been mainly
developed within CAP, as a traditional sectoral policy, enlarging its scope of action
steadily towards non-agricultural activities, thus shifting its focus from a narrowly
defined agricultural production policy to a broader array of issues and increasing links
with other policies impacting on rural regions.
The paper aims, on its first part, to systematize the main theoretical axes that vertebrate
the contribution of different territorial innovation models to regional development,
extending the concept of territorial learning to the field of developing predominantly
rural areas and, then, on its second and last part, to leave a set of reflections about the
policy-design of innovation based policies for rural areas.
2. The theoretical debate about innovation and territory – what does it bring?
The theoretical debate about the dialectics innovation-territory still remains largely at an
abstract and general level, being necessary an important operationalization effort of the
main concepts to enrich the empirical research. The implications of this problematic on
least favored regions and on rural development have seldom been analyzed. Usually, the
analysis is focused on urban-metropolitan areas on medium to high-tech sectors. The
importance of territorial innovation policies in peripheral rural regions, and the
likelihood of their acting as instruments for territorial competitiveness, have rarely been
the subjects of discussion. Yet, there is a rich academic production of territorial
innovation models from where we can learn.
During the last three decades, innovation, understood “in the broad sense to include
product, process and organizational innovation in the firm as well as social and
institutional innovation at the level of an industry, region and nation” (Morgan, 1997:
492), surpassing the strictly classical technological dimension, has become a key focal
point on the analysis of territorial development.
4324 | ESADR 2013
As innovation processes have intrinsically a strong territorial and social matrix, then it
must be emphasized the increasingly importance that an enlarged set of factors now
assume in the production of knowledge for innovation, namely the informal contacts
and the flows of tacit knowledge amongst the different kind of actors, their accepted
rules, conventions and cultural patterns (Storper and Scott, 1995), their relational capit al
and their social capital, on the sense proposed by Putnam (1993: 35): “features of social
organization, such as networks, norms and trust that facilitate coordination and cooperation for mutual benefit”. Thus, there has been a shift towards the understanding of
the innovation process as a socially constructed mechanism based on the accumulation
of knowledge (codified or tacit) through a continuous and interactive learning course
(Lawson and Lorenz, 1999; Tura and Harmaakorpi, 2005). Accordingly, Maskell and
Malmberg (1999: 20) argue that territorial competitiveness has nowadays, more than
ever before, to do “with knowledge creation and with the development of localized
capabilities that promote learning processes”.
In this sense, the innovation dynamics is based on resources that are place-specific, this
is, “it is a localized, and not a placeless process” (Asheim and Isaksen, 1997: 299), so,
territorially embedded complexes of innovation and production are increasingly the
privileged instruments to harness and recreate knowledge and intelligence across the
globe (Koschatzky, 2003).
The accumulated knowledge that production systems develop, because they are
incorporated in locally based institutions and in a generally non-mobile workforce, tend
to perpetuate certain competitive advantages but, although proximity matters, what
really is important for the upgrading of the competitive edge of localized production
systems and resource creation is organizational proximity (Kirat and Lung, 1999; Fujita
and Krugman, 2004; Carlsson, 2005, Shearmur, 2011). It is therefore important to
recognize that “knowledge transmission and collective learning may be fostered by
cultural, institutional and geographical proximities often in combination” (Keeble and
Wilkinson, 1999: 300).
So, on the last three decades, there has clearly been a change of paradigm on the
perception of the relation between industrial dynamics and regional development: longterm regional competitiveness and sustainability have less to do with cost-efficiency and
more to do with the ability of firms and institutions to innovate, or, in broader terms, to
upgrade their knowledge base. Innovation usually encompasses a strong territorial and
institutional dimension which constitutes an essential vehicle of the process of techno-
economic creation, as well as a strong path-dependency on the learning behaviors
(Santos, 2003).
It is argued that the territorial dynamics creates specific interdependences among the
actors and between the actors and the institutions that evolve into a peculiar scientific,
tech, technological and economic trajectory. Several analytical frameworks share this
particular approach, in particular the Industrial District paradigm, the Innovative Milieu
conceptual model, the Learning Region concept and the Regional Innovation Systems
approach (Santos, 2009).
These territorial innovation approaches concentrate their appreciations on two focal
points (Cooke and Morgan, 1998):
- on the one hand, the reinforcement of the associationist vision: an innovation is
highly dependent on information and knowledge; the capacity to innovate implies the
necessity to access such invisible factors through networking capacity, which can be
seen as the disposition to collaborate to achieve mutual beneficial ends;
- on the other hand, it emphasizes the growing importance of the formal and informal
mechanisms of information and knowledge production and consumption. This last
assumption is shared by Lundvall (1992) when he states that “knowledge is the most
fundamental resource and learning the most important process” and thereby the territory
must adopt a context favorable to knowledge creation and continuous learning,
reinforcing the centrality of the collective learning capability as a key strategy to
regional development.
The now widely used concept of Smart Specialisation, which has been highlighted by
the European Commission as a central pillar of the Europe 2020 Stategy, is, in our
opinion, a semantic declination of the Innovative Milieu, Learning Region and Regional
Innovation Systems models. The way in which smart specialisations strategy is
envisaged to operate as a central theme in post -2013 reformed EU Cohesion Policy is
explained in Regional Policy Contributing to Smart Growth in Europe (COM, 2010).
Here, the argument is that regions will be required to spot the sectors, the technological
domains, or the major areas of likely competitive advantage, and then focus their
regional policies as to support innovation in these fields. In particular, the argument is
crucial for the regions which are not on a major science-technology frontier, like most
traditional rural areas.
The first apparent distinctive trait of the Smart Specialisation approach relates to the
fundamental logic of the innovation system, and assumes that context matters for the
4326 | ESADR 2013
potential evolution of the system. In other words, the potential evolutionary pathways of
an innovation system depend on the inherited structures and existing dynamics
including the adjustment or even radical conversion of the system. The second apparent
perceived distinctive trait of the Smart Specialisation model is associated to the
mechanisms by which the strategy operates. The Smart Specialisation proposers
envisage that the identification of the knowledge-intensive areas for potential growth
and development are related to the function of certain classes of players (researchers,
suppliers, manufacturers and service providers, entrepreneurs, users) and to the public
research and industry science links. The players are regarded as being the agents who
employ their knowledge-acquisition facilities and resources (human assets, ideas,
academic and research networking) to scan the existing local economic and market
opportunities, to identify technological and market niches for exploitation, and therefore
proceed as a catalysts for driving the emerging transformation of the economy. The
original concept was entirely sectoral in its construction. Nevertheless, the concept
recently begun to be applied in a territorial context. Here, the adaptation of the Smart
Specialisation logic and its application to the EU regional context is largely affiliated on
the regional innovation systems logic. The Smart Specialisation approach should be
understood essentially as a local knowledge and learning enhancement concept (Foray
et alii, 2009; Wintjes and Hollanders, 2011).
So, the theoretical debate about innovation and territory besides reinforcing the
importance of innovation production, in their different modalities, emphasizes
principally the understanding of the local or regional competitiveness as a result of a
collective learning process.
2. Innovation and territory on peripheral rural regions: policy implications
A territorial systemic approach
On this part of the article, the analysis is focused on the problems and opportunities
faced by peripheral rural least-favored regions in overcoming their comparative
disadvantages with respect to innovation capacities and on the public policies that can
be developed to reduce their handicaps.
Until two decades ago, innovation policy in peripheral territories was often simply
equated as a supply-side problem, accordingly with the dominant paradigm then
accepted of the linear model of innovation. Government policies have usually been
designed to support knowledge production, for example through incentives to R&D
activities, rather than knowledge utilization.
It is now widely accepted that the promotion of the innovation capability in rural least
favoured regions also as to be addressed as a demand-side problem, the constraints to
the innovation dynamics being not so much the production of strategic information and
knowledge but, instead, its diffusion and appropriation by the regional actors. When
knowledge creation and transfer are considered the most important devices for
economic growth and well-being, creating and sustaining innovations are regarded as
the keys to improve global competitiveness Therefore, the role of innovation policies
and, especially, the tools used to promote companies and institutions’ ability to innovate
do not solely depend on the entrepreneurs, as also communities, and especially regions,
have an effect on innovation processes (Rosenfeld, 2002; Hassink, 2005).
A collective learning dynamics
Garmise and Rees (1997: 2) underline that: “for the less favoured areas of Europe and
elsewhere, their relative absence of economic dynamics is rooted in the very limited
learning capacities of their innovative systems”. The main focus of public intervention
on this ambit now relies on the promotion of interactive learning-oriented processes for
the whole of the territorial agents. Networking, design of value-added dialogue
platforms and the opening up of new interfaces between innovation support
infrastructures and industry, such supply aspects should therefore be fostered,
particularly between private and public spheres. Nevertheless, a systemic approach also
implies to take into consideration in a more pro-active way the needs of the main actors
of innovation, i.e. firms and, consequently, to adapt the supply of services and their
respective structures. In particular, innovation support should meet more intensely the
micro and SMEs needs and expectations, thus being more responsive to the composition
of the productive fabric. The aim is that this systemic and bottom-up approach favours
cooperation and leads to a better regional embeddedness of the system, a particular
challenge being the promotion of the endogenous innovative capability of the local
productive fabric.
This new approach to regional development in peripheral areas tries to redesign the
regional innovation architecture, but building upon pre-existent structures and seeking
to modify their static, task specific competences into a system of flows and processes
4328 | ESADR 2013
based on the network paradigm (Cooke, 1996). Corroborating this assertion, Morgan
(1997: 501) concludes: “I would suggest that this is precisely what innovating in the
periphery means: working with what exists, however inauspicious, in an effort to break
the traditional institutional inertia in the public and private sectors, fostering inter-firm
networks which engage in interactive learning, nurturing trust”.
Nevertheless, it seems that, at the enterprise level, the efforts of public support should
focus on the local micro and SMEs of mostly traditional sectors that haven’t yet
understood the need to innovate - in this sense the regionally based innovation policy in
least favoured areas must have, as Quévit and Van Doren (1997) point out, a
pedagogical dimension.
A clear strategic objective, thus, should be the increasing of the capability and of the
competence of the public administration to interact with an enlarged set of actors of the
innovation process, to deepen its awareness concerning the demands of the firms and to
build up broker organizations that could: “assist firms in analyzing their situations ...
and define their particular needs in relation to the innovation process” (Asheim and
Isaksen, 1997: 321).
An important operational axis of the whole innovation policy should lie on the
organizational capacities of the networks of relationship that can become a crucial
determinant of the entire institutional architecture of the regional innovation system. It
should be an important aim to involve micro and SMEs as much as possible on all the
ongoing, evolving process, to make sure that their long term needs are duly taken into
consideration. Anyway, SMEs usually face particular problems that hamper their
effective participation on the innovative dynamics, such as a difficult access to
information, lack of qualified labour force, financial and administrative constraints, etc.
It is undeniable, at least in the Portuguese context, that this dimensional group of
enterprises may require specific assistance and there is a need for additional empirical
evidence of the capacities of the different categories of SMEs so that a more pragmatic
appreciation of this sector will be gained which will be essential to formulate targeted
policy-measures aimed at stimulating greater SME participation, a sine qua non
condition for the achievement of a systemic innovation process on a territorial rural
basis. It seems important to promote consistent efforts to strengthen the technology
absorption capacity of SMEs which may involve facilitating the processes of learning
and accumulating knowledge and strengthening skills in the firms. The regional
innovation support services that now only serve a minimal part of the firms’ universe,
and therefore aren’t promoting innovation in the rural regions as efficiently as they
should, must be able to answer not only the specific demands of traditional innovators
but rather to be concentrated on the promotion of a co-operation culture and systemness
amongst the elements of the territorial innovation architecture (Asheim et alii, 2011).
A comprehensive perspective of knowledge and innovation
It has been questioned wether the current focus of learning regions is adequate to ensure
the competitiveness of rural regions in the knowledge economy (Tovey, 2008). Rural
development processes do not only require technological, expert knowledge but at the
same time indigenous knowledge about local places and locallly-embedded resources.
Studying rural regional learning therefore requires a shift from focusing on forms of
knowledge towards focussing on knowledge processes, exploring dimensions of
knowledge building, collaborative social learning and the re-embedding of knowledge.
The current focus of regional learning and innovation processes on scientific,
technological expert knowledge must therefore be challenged. We need to focus less on
research excellence, in abstracto, but more on local innovation application, valuing
local identities and the diversified typology of secular knowledges.
Rural areas also contain many assets that are extremely valued within the global
knowledge economy, such as access to resources, cultural and natural amenities and
high quality of life. Development policy that fails to acknowledge this potential possibly
makes a strong contribution to rural decline. Tapping underutilized potential is vital for
enhancing rural regional competitiveness.
There is a need, as Kelles-Viitanen (2005), argues, to promote local innovators and
recognize farmers and other rural people as legitimate experts in the area where they
work. It is absolutely vital to support them and help upscale innovative and successful
local actions. To do all this, it is also urgent to reconsider our strategies towards the
rural world. How to have a positive approach, that starts from, but is not restricted to
local ideas, which focuses on local communities’s strengths and explores the particular
opportunities open to them – rather than dwelling on their weaknesses ans problems?
How to move from problem-based programs towards stregthening the solutions to be
found in local rural communities, building upon existing stregths and initiatives and
supporting innovation? How can institutional resistance, experienced as a brake to
policy changes, be overcome? Rural reality is not what it was, is constantly changing,
that is for sure, however, some dimensions that possess a strucutural dimension do have
4330 | ESADR 2013
to beadequately addressed, with innovative tools and strategies – this also implies to
assume that territorial identity matters and concentrate on their endogenous
potentialities being, nevertheless, open to the world economy, a so-called glocalisation
dynamics, supported by networking inside the regions and beyond (Covas and Covas,
2011).
Usually, traditional theoretical frameworks fail to take account of the diversity of actors
and activities contributing to rural regional development and hence failed to reckon the
diverse types of knowledge and human skills neededed to sustain rural regions in the
globalising knowledge economy. The focus should be put, as we have mentioned
before, less on the innovation outptut production, per se, and more on the innovation
process, contextual, globally and socially considered, and on the facts that affect the
process - not on innovations, as such. Policy interventions must recognize the need for
international interfaces, while simultaneously making sure that knowledge accumulates
domestically and filter out into the economy for re-use, recombination and
experimentation.
A multi-level governance scheme
Within the rural territories, the partnership approach intrinsic to governance is
particularly necessary as no single stakeholder has the resources to tackle the multidimensional problems of rural development (Scott, 2004; Markey and Halseth, 2008;
Markey, 2010). Through adequate governance mechanisms, the actions of different
governments and agencies may complement each other. The foremost dimension in
building a successful rural regional innovation upgrading strategy seems to lie in
leadership, and this work is absolutely vital to make some innovative agents assume a
mobilizing and strategic leadership (Torre and Wallet, 2013). So, a multi-level
governance architecture is urgently needed in order to create rationality and synergies
among the innovative entrepreneurial and institutional actors.
Since the introduction of rural development into the European CAP, partnerships have
also become an increasingly common mean to govern rural regional development
processes (Dax et alii, 2011). So far, however, the governance of rural regional learning
and innovation processses in rural development has not been given attention.
Institutional learning is also a critical learning-by-learning process (Wolfe and Gertler,
2002; Miguélez et alii, 2011). Considering the high diversity of activities that contribute
to rural development, one can argue that changes in institutional arragements are vital
and must occur frequently. The focus should therefore be put on the learning-bylearning process through which institutional arrangements are (re)establhised and
operationalised, impacting proactively and positively on the rural economic basis
(Asheim and Coenen, 2006). Accordingly, the smart region that embraces this kind of
learning and innovation processes is a learning region with emphasis on contextual,
informal and collective learning processes that lead to innovation and institutional
change. Corroborating this assertion, Morgan (1997: 501) adds: “I would suggest that
this is precisely what innovating in the periphery means: working with what exists,
however inauspicious, in an effort to break the traditional institutional inertia in the
public and private sectors, fostering inter-firm networks which engage in interactive
learning, nurturing trust”.
Some authors (Cooke, 1996; Asheim and Isaksen, 1997; Quévit and Van Doren, 1997;
Tödtling and Trippl, 2005; Hauser, et alii., 2007; Prange, 2008) are consequently
underlining regional policy approaches that are context-sensitive, production-systems
oriented rather than firm-oriented and focusing on the continuous structural adaptation
of the regional institutional and economic set. This involves arguing against
recommending off-the-shelf local economic policy solutions and instead requires a
cautious analysis of regional knowledge capabilities and research competences.
A new planning approach
The philosophy of the planning approach has, consequently, to change radically
(Morgan, 1997): the question isn’t any longer of planning for the regional community
(firms and institutions) but, instead, of planning with them and, besides, due to the fact
that it involves mainly changing social and institutional inertias, results should only be
apprehended on a medium to long-term basis. We are not talking about the simple reequipment and technological upgrading of firms, we are dealing with a whole set of
incremental changes on the behavioural patterns of rural regional actors, each one of
them with its specific logics and rationalities.
It is fundamental to engage with the right targets, namely the institutionalized inertia
and the loneliness syndrome which characterizes so many rural less favored regions
(Suorsa, 2007). Definitely, it is important to understand that a territorial innovation
policy does not consist of casuistic attempts of technology transfer or of picking-thewinners strategies, but on the stimulation of the whole rural regional milieu. In this way,
it can be seen as an instrument of establishing a learning framework for all partners
4332 | ESADR 2013
involved in the construction of the socio-economic trajectory of the territory. This really
seems to be the challenge for almost all rural regions and a critical assessment must be
done to the implementation of ready-made recipes.
4. Conclusion
There is no way out: a sustainable rural economy based on innovation demands much
more of local capacity. From a value added viewpoint, local actors and institutions are
called upon to be the foundation of contextual knowledge that identifies community and
regional assets. Local capability must also hold and build up new relationships and
partnerships that signify critical sources of innovation in social and economic
development within the context of a more globalized economy. Policy design at the
rural level not only involves issues of externalities and knowledge spill-overs, it also
encompasses the information asymmetries and principal-agent problems associated with
engagement with local elites. This competitive approach, based on a collective learning
process, is therefore more complex than a simplified form of comparative advantage.
Special attention should be paid to the design of the intervention policy, trying to avoid
the classical functional top-down and supply-side approach; innovation-led rural
regional policies must basically address the questions of enhancing the territorial
capabilities to foster interactiveness among the regional actors, of engaging the actors in
processes of collective learning and of producing strategic knowledge or, more
synthetically, to promote social capital in the rural least favoured regions. Rural
innovation policies should, in essence, concentrate on catching up learning but it is
necessary to ensure that the architectures of the policy-design and of the policy-delivery
are open and inclusive.
Challenging the inevitably of rural decline demands a comprehensive understanding of
its full potential and bottlenecks, as well as new set of policies that allow for the gradual
reinforcement of the collective learning mobilisation and creation of social capital.
Perhaps, above all, the greatest challenge to this enlarged role for rural sustainable
development concerns, as Markey (2010) says, “compensating for state withdrawal
from the functions of, and responsibility for, service provision (and the technical
capacity/loss that it entails)”, knowing that abandoning communities and regions to the
vagaries of the market is short-sighted and, thus, militating against the lack of power of
rural regions to control their own futures.
References
Asheim, B.T. and Coenen, L. (2006), “The role of regional innovation systems in a
globalising economy: comparing knowledge bases and institutional frameworks of
Nordic clusters”, in Vertova G. (ed.), The Changing Economic Geography of
Globalization, pp. 148-165, London, Routledge.
Asheim B. T. and Isaksen, A. (1997), “Location, agglomeration and innovation:
towards regional innovation systems in Norway?”, European Planning Studies, vol.
5(3), 299-330.
Asheim, B.T., Smith, H.L. and Oughton, C. (2011), “Regional innovation systems:
theory, empirics and policy”, Regional Studies, vol. 45(7), 875-891.
Carlsson, B., 2005, “Innovation systems: a survey of the literature from a
Schumpeterian perspective”, in Harmusch H. and Pyka A. (eds), The Companion to
Neo-Schumpeterian Economics, Cheltenham, Elgar.
COM (2010), Regional Policy contributing to smart growth in Europe 2020, Brussels:
EC.
Cooke, P. (1996), “Building a Twenty-First Century Regional Economy in EmiliaRomagna”, European Planning Studies, 4(1): 53-62.
Cooke, P. and Morgan, K. (1998), The Associational Economy: Firms, Regions and
Innovation, Oxford: Oxford University Press.
Covas, António e Covas, Maria das Mercês (2011), A Grande Transição. Pluralidade
e Diversidade do Mundo Rural, Lisboa: Ed. Colibri.
Dax, Thomas, Kahila, Petri and Hörnström, Lisa (2011), “The evolution of EU Rural
Policy: linkages of Cohesion Policy and Rural Development policy”, paper presented
at the Regional Studies Association Annual International Conference, 17th - 20th
April, Newcastle upon Tyne, UK.
Fujita, M., and Krugman, P. (2004), “The new economic geography: past, present and
the future”, Papers in Regional Science, vol.83 (1), 139-164.
Garmise, S. and Rees, G. (1997), “The role of institutional networks in local economic
development - a new model of governance”, The Journal of the Local Economy Policy
Unit, 12(2): 43-56.
Hassink R (2005), “How to unlock regional economies from path dependency? From
learning region to learning cluster”, European Planning Studies 13: 4, 521–535.
4334 | ESADR 2013
Hauser, C., Tappeiner, G. and Walde, J. (2007), “The learning region: the impact of
social capital and weak ties on innovation”, Regional Studies, vol. 41, 75-88.
Keeble, D. and Wilkinson, F. (1999), “Collective Learning and Knowledge
Development in the Evolution of Regional Clusters of High Technology SMEs in
Europe”, Regional Studies, 33(4): 295-303.
Kelles-Viitanen, Anita (2005),
“New Challenges and Opportunities for Rural
Development”, paper presented at the IFAD Workshop What are Innovation
Challenges for Rural Development, Rome 15 to 17 November 2005.
Kirat, T. and Lung, Y. (1999), “Innovation and proximity: territories as loci of
collective learning processes”, European Urban and Regional Studies, vol. 6(1), 2738.
Koschatzky, K., 2003, “The regionalization of innovation policy: new options for
regional change?”, in Fuchs G. and Shapira P. (eds), Rethinking Regional Innovation:
Path Dependency or Regional Breakthrough?, London, Kluwer.
Lawson, C. and Lorenz, E. (1999), “Collective Learning, Tacit Knowledge and
Regional Innovative Capacity”, Regional Studies, 33(4): 305-317.
Markey, Sean (2010), Primer on Place-Based Development, Burnaby: Simon Fraser
University.
Markey, Sean and Halseth, Greg (2008), “Challenging the inevitability of rural
decline: Advancing the policy of place in northern British Columbia”, Journal of Rural
Studies, 24: 409–421.
Maskell, P. and Malmberg, A (1999) “The Competitiveness of Firms and Regions:
“Ubiquitification” and the Importance of Localized Learning”, European Urban and
Regional Studies, 6(1): 9-25.
Miguélez, E., Moreno, R. and Artís, M. (2011, “Does social capital reinforce
technological inputs in the creation of knowledge - Evidence from the Spanish
regions”, Regional Studies, vol. 45(8); 1019-1038.
Morgan, K. (1997), “The learning region: institutions, innovation and regional
renewal”, Regional Studies, 31(5), 491-503.
Prange, H., (2008), “Explaining varieties of regional innovation policies in Europe”,
European Urban and Regional Studies, vol. 15, 39-52.
Putnam, R. D. (1993) “The Prosperous Community - Social Capital and Public Life”
The Americam Prospect, 13: 35-42.
Quévit, M. and Van Doren, P. (1997), “Stratégies de politique d’innovation dans une
dynamique de développement local pour les régions périphériques de l’Union
Européenne”, in Ferrão, J. (ed), Políticas de Inovação e Desenvolvimento Regional e
Local, 53-70, Lisboa, Instituto de Ciências Sociais da Universidade de Lisboa.
Rosenfeld, Stuart (2002), Creating Smart Systems. A Guide to Cluster Strategies in
Less Favoured Regions. European Union- Regional Innovation Strategies, Brussels:
Directorate General for Regional Policy and Cohesion.
Santos, Domingos (2003), “Política de inovação: filiação histórica e relação com as
políticas de desenvolvimento territorial”, Revista Portuguesa de Estudos Regionais,
vol. 3, 25-40.
Santos, Domingos, 2009, “Teorias de inovação de base territorial”, in Costa, J. S. and
Nijkamp, P. (coords), Compêndio de Economia Regional - Teoria, Temáticas e
Políticas, 319-352, Cascais, Principia.
Scott, M. (2004), “Building institutional capacity in rural Northern Ireland: the role of
partnership governance in the LEADER II Programme”, Journal of Rural Studies, 20:
49-59
Shearmur, R. (2011), “Innovation, regions and proximity: from neo-regionalism to
spatial analysis”, Regional Studies, vol. 45(9), 1225-1243.
Storper, M. and Scott, A J. (1995), “The wealth of regions. Market forces and policy
imperatives in local and global Context”, Futures, 27(5): 505-526.
Suorsa, Katri (2007), “Regionality, innovation policy and peripheral regions in
Finland, Sweden and Norway”, Fennia, 185: 1, pp. 15-29.
Tödtling, F. and Trippl, M. (2005), “One size fits all? Towards a differentiated
regional innovation policy approach”, Research Policy, 34: 1203-1219.
Torre A., Wallet F. (2013), “Innovation and governance of rural territories”, in Coudel
E., Devautour H., Soulard C.T., Faure G., Hubert B. (eds), Renewing Innovation
Systems in Agriculture and Food: How to go towards more sustainability?,
Wageningen Academic Publishers.
Tovey, H. (2008), “Introduction: Rural Sustainable Development in the Knowledge
Society Era”, Sociologia Ruralis, 48 (3): 185-199
Tura, T. and Harmaakorpi, V. (2005), ”Social capital in building regional innovative
capability”, Regional Studies, 39: 1111-1125.
Wintjes, René and Hollanders, Hugo (2011), Innovation pathways and policy
4336 | ESADR 2013
challenges at the regional level: Smart Specialization, UNU-MERIT Working Paper.
2011-027.
Wolfe, D.A. and Gertler, M. (2002), “Innovation and social learning: an introduction”,
in M. Gertler and D.A. Wolfe (eds), Innovation and Social Learning: Institutional
Adaptation in an Era of Technological Change, Palgrave Macmillan, Basingstoke.
4338 | ESADR 2013
STRUCTURE, CONTENT AND DYNAMIC OF INNOVATION
NETWORKS IN RURAL CONTEXT
JOANA LEÃOa, LÍVIA MADUREIRAa, AURORA TEIXEIRAb and CHRYSA
LAMPRINOPOULOUc
a
University of Trás-os-Montes e Alto Douro
Centre for Transdisciplinary Development Studies (CETRAD)
E-mail: [email protected]; [email protected]
b
CEF.UP, Economics School, University of Porto; INESC Porto
E-mail: [email protected]
c
Scotland’s Rural College
SRUC Research
E-mail: [email protected]
ABSTRACT
The primary sector and the rural areas have been relatively neglected regarding the
study of innovation networks. Thepresent study it is intended to contribute to the
improvement of knowledge about networks in rural context. There are three objectives
on this research: (i) understanding and characterize the specificities of the innovative
networks in rural areas; (ii) analyse innovation networks at micro level (analysing each
one of the involved organizations individually), at meso level (analysing the network as
a whole) and at macro level (analysing its context/environment); (iii) understanding
how features and contextual factors influence the dynamic of innovative networks in the
rural context. In order to respond to these objectives, an approach of the case study is
being developed.
Key words: Innovative networks, inter-organizational structure, rural areas, innovation.
1. INTRODUCTION
This work intends to understand the structure, content and dynamic of innovation
networks in the rural context and what factors can influence positive or negatively their
structure and dynamic, namely the evolution of network, assessing the performance
outcomes that can emerge of an inter-organizational structure.
1
In the context of rural development, collective actions, including network formation,
appear as an important tool to develop and leverage the small enterprises. These
practices of collective action seem to be a way for small business to build social
relations, improve their economic performance and even growth (Brunori & Rossi,
2000). Thiele et al. (2011) approaches the functioning of multi-stakeholder platforms as
a solution to link small farmers and respond to the constant of their problems, as small
volume of production and the difficulty to answer the demand in terms of quantity,
quality and timelines of delivery. These authors define the multi-stakeholder platforms
as a space involving different actors with different roles that establish interactions with
each other to promote mutual understanding, trust and actions, and share a common
resource (Thiele et al., 2011). Regarding the network concept, in a general way, the
literature has come to agree about its definition, conceiving it as a series of nodes that
are connected to each other by relationships and by some type of exchange (Copus &
Skuras, 2006; Cannarella & Piccioni, 2008; Ojasalo, 2008; Almodovar & Teixeira,
2012). However to understand in depth how organisational network works is important
to recognize the network in three fundamental aspects: structure, content and dynamic
(Almodovar & Teixeira, 2012). Kjeldsen & Svensen (2011) argue that networking, in
the context of rural development, can be conceived as “an embedded form of social
interactions” and so it has influence on the outcomes of rural entrepreneurship.
Therefore, in relation of entrepreneurship performance it is possible to observe the
existence of two opposite visions regarding that. On the one hand, some highlight the
positive effects which lead to the implementation of an innovation, as cooperation and
resource share; Whereas. on the other hand, others highlight that closed networks can
constraint entrepreneurs by the lack of fresh ideas (Rooks et al., 2012). These latter
authors, in their study about relationship between network structure and innovative
performance, concluded that a network helps to solve information and cooperation
problems, and facilitates the access to information related with new markets,
technologies and business opportunities. (Rooks et al., 2012).
In addition to the network effects on the performance outcomes, the literature presents a
number of other types of outcomes of the networks, which include (i) economies of
scale, economies of scope and reduction of transaction costs (Brunori & Rossi, 2000;
Romeiro & Costa, 2010); (ii) access to new markets and resources (Romeiro & Costa,
2
4340 | ESADR 2013
2010; Rooks et al., 2012); (iii) enhancing the
sharing of material and financial
resources (Copus & Skuras, 2006), (iv) attainment empowerment, reputation and
information in individual business terms (Bizzi & Langley, 2012) and (v) development
of communication and relational skills of the members (Brunori & Rossi, 2000).
This study analysed the performance outcomes of networks through the model adopted
by Lamprinopoulou (2009), as well as by analysing the main factors that influence the
network evolution. The model is presented and explained in section 2. In section 3 are
presented the characterization of case studies and section 4 is dedicated to the paper
conclusions.
2. MODEL AND METHODOLOGY
2.1 Model
Lamprinopoulou (2009) argues that existing contextual factors influence the network
evolution alongside with the network features capable of influencing their performance
outcomes. According to the model, the main economic and non-economic network
outcomes are identified in the Figure I.
Contextual/environmental factors of network
Based on the model developed by Lamprinopoulou (2009) three context/environmental
factors that influence the evolution of network are identified: market conditions, social
cohesiveness and external institutional support. Market conditions consist essentially in
the analysis of five aspects: (i) the existence of final consumers that differentiate
between category of products; (ii) the existence of well differentiated substitutes
products or imitations in the market; (iii) the existence of monopolies; (iv) the existence
of physical and technological constraints that increase production and market related
costs and (v) existence of quality certification system as a pre-condition for market
entry. Second, social cohesiveness, although it being underlined the importance of
leadership, it is equally important the sharing of common ties and social relations, as
well as the sharing of a common goal, interests and perceptions. As Brunori & Rossi
(2000) highlight, pre-existing social networks are the basis for further interactions. The
last factor identified is the external institutional support that consists in the perception of
political and institutional context of the network and “refers to the nature and extent to
3
which regional and national governments ‘public support’ is offered” (Lamprinopoulou,
2009).
Network features
Regarding to performance outcomes, it is recognised in inter-organizational studies that
outcomes depend on the cultural context of network, in terms of urban/rural context
(Rooks et al., 2012). In the same stream of thought, others studies stress that
performance is influenced by regional characteristics, namely regarding to innovative
performance (Isaksen & Onsager, 2010).
Figure I. Context – Features – Performance Model
Source: Lamprinopoulou, 2009
Lamprinopoulou (2009) adopted the model of micro level analysis, related with
individual members of the network identifying member profile, member competencies
and network governance structure as critical features to performance outcomes.
Thereby, member profile characterizes by the identification of physical and attitudinal
attributes and the subsequent analysis of the homogeneity/diversity in profiles. Member
competencies consist in a diversity of skills that can be shared in a network, with special
4
4342 | ESADR 2013
emphasis of production related capabilities, marketing and entrepreneurial skills and
collective management capabilities. Finally, network governance structure addresses the
distinguish between formal and informal governance and the equilibrium between both,
guaranteeing the regulation of five important aspects: (i) power distribution, (ii)
accountability and formality, (iii) diffusion of information and knowledge, iv) resolution
of conflicts and trust building and (v) monitoring, evaluation and planning.
Performance outcomes
In addition to the outcomes aforementioned, identified through the literature, such as
economies of scale and scope and reduction of transaction costs; access to new markets
and resources; enhancing the sharing of material and financial resources; attainment of
empowerment, reputation and information, and development of communication and
relational skills of the members, the model presents the main economic and noneconomic outcomes resulting from organisations integrated in a business network.
Lamprinopoulou (2009) related the economics results with transactional outcomes and
non-economic results with transformational outcomes. The first “are enhanced resource
acquisition or gains in performance” (Human & Provan, 1997) and are divided in three
categories, financial performance, access to resource and organisational credibility. The
second, are defined as changes in the ways agents of network think and/or act (Human
& Provan, 1997).
2.2 Methodology
This work draws on the case study method and is characterized by qualitative data
collection which results on the cases description (Ojasalo, 2008). In the first step of the
research we proceeded to literature review about the networks scope. In a second step,
two case studies were being addressed and were selected according to three criteria:
localization, consolidation and scope. Regarding the selected cases, a research was
made through the media information and informal conversation with management
members. Both cases are developed in rural areas and encompass sectors such as
viticulture and horticultural. One of the main reasons that drove to the creation of these
network cases, was to respond to the critical dimension challenge, particularly regarding
the reach of new markets, namely foreign ones.
5
In order to collect specific data from the case studies selected, an in depth-interview is
being applied to organisations that compose the nodes of the networks. This interview
was based on Lamprinopoulou (2009) interview, applied in Greek agrifood sector, in
order to allow for comparative study, not presented here The interview included open
and closed questions, aiming at characterizing the network accordingly to their
structure, content and dynamic, as well as analyse the factors that influence the
evolution, the performance outcomes and the features that influence them. To answer
the mentioned goals, the interview was organized in six parts:
(i) Description of the individual organization;
(ii) Importance of cooperation and collective action;
(iii)Integration and interaction with the network;
(iv) Evolution of the interaction among organization and network members over
time;
(v) Analysis of the factors that could influence the relations dynamic;
(vi) Impacts assessment of the network and collective action on the performance of
the organization and local community.
3. CASE STUDIES CHARACTERIZATION
Case 1: Lavradores de Feitoria
Lavradores de Feitoria (LDF) is a wine company (blend and state wines) who gathers
several small Douro estates owners whose main objective was to gain a minimum scale
to achieved external markets. This business network departed from the efforts of
individuals connected with Douro Region who know the area and producer’s needs.
These needs resulted from different difficulties shared by producers, namely the
difficulty in drain the product into the market, the lack of individual producers’ capacity
and resources (most notably, insufficient size and lack of specialized technicians), and
inadequate functioning of existing wineries and cooperatives (low prices; late payments;
no preservation of grapes quality).
In a first phase the contacts with potential network members (mainly producers) were
quite informal. Several estates were contacted which in turn identified other estates with
who they maintained close relationships. All this process was accompanied by
6
4344 | ESADR 2013
Spidouro, an organization with the propose of promoting the enterprises and
investments in Douro and Trás-os-Montes region, which had a fundamental role on the
LDF network formalization. By 2000, out of those contacted during 1999, 15 accepted
to participate in the project/network and a public stock company was created. Nowadays
the acceptance of new members goes through a highly selective process (namely by
vines analysis), so it may be possible to keep up with the quality standards required.
Presently LDF is composed by 15 producers which comprise 18 estates.
The concept developed by LDF involves an innovative management model that targets
sustainability associated with a kind of cooperative character. Summing up, it allies
vanguard with tradition.
Although cooperation is at the core of this network, the business model is quite distinct
from that of traditional cooperatives. Basically, they aim at assuring that all members’
wine production is sold but high standard quality requirement need to be previously
assessed and guaranteed. Thus, LDF guaranties volume and quality (in order to achieve
the adequate dimension to export), image promotion in external markets, and the
sharing of resources and knowledge.
According to an administration member, sustainability of this network relies on the
good relationship between existing members, transparency rules and their rigorous
compliance.
Case 2: triPortugal
TriPortugal is a commercial platform who gather organizations dedicated to the fruit
production in the Centre-western region of Portugal. Those organizations since their
individual existence, share a common and strong interest, the production and promotion
of Pêra Rocha (rock pear). The creation of triPortugal platform is based on a main
objective, reach critical dimension to respond not only to the internal market but also
foreign ones. Beside answering to the problem of individual insufficient quantity, the
actors perceived that was possible, through the inter-organizational collaboration, to
give a solution to another constraints such as a stronger name in the market, more
respect by clients, commercial power, higher scale of products, quality of service, costs
reduction (e.g. bargaining the production factors, low unit prices) and the maintenance
of market position during all year.
7
The project begun in 2007 with the creation of Unirocha, ACE (Complementary
Company Group). This network involved three companies and a cooperative, whose
managers met through the market competition. In 2010, with the exit of one of them,
new ideas and improvements emerged regarding new products, new markets and ways
to approach them, turning Unirocha into triPortugal, ACE. Since then, no changes have
been detected in the network actors, although the members don’t disapprove a possible
new entry, providing the share of common vision, goals, values and trust are
maintained.
During a year, the actors involved on the original project had several meetings until
agreeing in which concept would be adopted. Although the sharing of resources and
knowledge exists between members, it is essential that each one of them maintain their
own identity, strength and growth. The structure created is not profitable and the actors
work together only regarding the commercial issues, assuring that all members’
production is sold.
The administration of the network comprises all the managers of the organisations that
compose it, those of which affirm that triPortugal network sustainability relies on three
key pillars: existence of teamwork capability, existence of transparency in information
and trust.
4. CONCLUSION
Innovation networks are often approached in literature regarding sectors of high and
medium technologies, whereas this issue is still underexplored in rural areas and
particularly in low tech activities.
Both network cases analysed in this work are closely related with agricultural activity,
an important activity in Portuguese economy, mainly in rural areas. With the evolution
of this research it's expected to describe in depth the configuration, dynamic and content
of the network in rural context, as well as understanding the way that features and
contextual factors influence the performance of the network, following the model
present in section 2. The work developed to date, allows to characterize both network
cases, regarding the main motivations to the network creation, the goals of the structure
and to identify the actors involved.
8
4346 | ESADR 2013
The conclusion of this qualitative study will enable to further understand the main
determinants for the creation of similar networks, which agents are most relevant to
stimulate its creation and development and recognize what effects these business
models can have in rural development.
REFERENCES
Almodovar, J. and A.A.C. Teixeira (2012). “Dynamics, structure and content of
innovation networks. An overview of the literature”, ch. 2, in Isabel Salavisa; Margarida
Fontes (Eds.), Social Networks, Innovation and the Knowledge Economy. (Routledge
Studies in Global Competition), Taylor and Francis, 37-68.
Bizzi, L. and A. Langley (2012). Studying processes in and around networks. Industrial
Marketing Management, 41: 224-234.
Brunori, G. and A. Rossi (2000). Synergy and Coherence through Collective Action:
Some Insights from Wine Routs in Tuscany. Sociologia Ruralis, 40: 409-423.
Cannarella, C. and V. Piccioni (2008). Innovation diffusion and architecture and
dynamics of local territorial networks. Trames, 2: 215-237.
Copus, A. and D. Skuras (2006). Business Networks and Innovation in Selected
Lagging Areas of the European Union: A Spatial Perspective. European Planning
Studies, 14: 79-92.
Human, S. and K. G. Provan (1997). An Emergent Theory of Structure and Outcomes in
Small-firm Strategic Manufacturing Networks. Academy of Management Journal, 40:
268-403.
Isaksen, A. and K. Osanger (2010). Regions, networks and innovative performance:
The case of knowledge-intensive industries in Norway. European Urban and Regional
Studies, 17: 227-243.
Kjeldsen, C. and G. L. H. Svensen (2011). Introduction: Networking private
entrepreneurs in rural areas – social capital or waste of time?. Journal of Depopulation
and Rural Development Studies, 11: 7-28.
Lamprinopoulou, C. (2009). How do SME Networks Evolve? Investigating Network
Context, Features and Outcomes amongst Agrifood SMEs in Greece. PhD Thesis on
Philosophy, Edinburgh, University of Edinburgh.
Ojasalo, J. (2008). Management of innovation networks: a case study of different
approaches. European Journal of Innovation Management, 11: 51-86.
9
Romeiro, P. and C. Costa (2010). .The potential of management networks in the
innovation and competitiveness of rural tourism: a case study on the Valle del Jerte
(Spain). Current Issues in Tourism, 13: 75-91.
Rooks, G.; A. Szirmai and A. Sserwanga (2012). Network Structure and Innovative
Performance of African Entrepreneurs: The cas of Uganda. Journal of African
Economies, 4: 609-636.
Thiele, G., A. Devaux, I. Reimoso, H. Pico, F. Montesdeoca, M. Pumisacho, J. A.
Piedra, C. Veloso, P. Flores, R. Esprella, A. Thomann, K. Manrique and D. Horton
(2011). Multi-stakeholder platforms for linking small farmers to value chains: evidence
from the Andes. International Journal of Agricultural Sustainability, 9:3, 423-433.
10
4348 | ESADR 2013
ESADR 2013. Feeding minds, overcoming the global crisis
15th -18th October, 2013, University of Évora, Évora
HIDDEN INNOVATION AND NEGLECTED INNOVATORS IN
THE PORTUGUESE RURAL AREAS
LÍVIA MADUREIRA
University of Trás-os-Montes e Alto Douro (UTAD), Department of Economics, Sociology and
Management (DESG). Centre for Transdisciplinary Development Studies (CETRAD). Portugal. E-mail:
[email protected]
TERESA M. GAMITO
Universidade Técnica de Lisboa (UTL)/Consultora, Portugal
DORA FERREIRA
UTAD/CETRAD, Portugal
IVO OLIVEIRA
UTAD/CETRAD, Portugal
ABSTRACT
The research on innovation has recently started to pay attention to non-technological
products and processes of innovation and to other innovation inputs besides R&D ones.
This view appears fundamental to achieve a broad understanding of innovation taking
place in different organisations, sectors and regions. However, to implement it, new
methodological frameworks are needed, built on broad concepts of innovation and
flexible tools to collect empirical information.
This paper presents empirical evidence on the innovation taking placing in the
Portuguese rural areas, collected through a flexible methodological framework. It is a
survey-based approach where broad concept of innovation, its inputs and outputs were
defined. In addition, the respondents (innovation managers and/or promoters) were
requested to describe innovations undertook by the organisation in order to identify
their innovation strategy and pattern(s). Instead of assuming pre-defined innovation
categories and patterns, like the approach followed by the CIS (Community innovation
survey), the identification of the innovation patterns is a result of the survey.
A sample of 120 organisations was surveyed. The organisations were selected from a
universe previously identified recurring to several information sources. The surveyed
organisations were located across all Portuguese (Continental) rural territory (rural
NUTS3 according to OECD classification). The results show different types of
innovative organisations, namely at the firm level. Some of these innovators are clearly
invisible with the current tools to identify and measure innovation, namely the
expenditure and the cooperation R&D inputs. In addition, the innovation processes tend
to mix diverse types of innovation.
The paper concludes, based on the empirical findings, that the current framework to
identity, measure and promote innovation doesn’t allow to observe certain innovation
patterns, that are important given the number of innovators undertaking it. It shows, on
the other hand, that with a flexible methodological framework adopted, encompassing:
(a) broadening the innovation concepts; (b) enlarging the unit of analysis; (c) designing
1 | 4349
Atas Proceedings
survey to collect data on the innovation processes, renders possible to uncover
important hidden innovation and currently neglected innovators.
Key-Words: Innovation, R&D, non-technological innovation, hidden innovation, rural
areas.
1.
INTRODUCTION
Research in the innovation field has recently exposed the hidden innovation and the
need for further research within this topic. Identifying and understanding the hidden
innovation entail new conceptual and methodological approaches.
This paper aims to contribute to the development of broad concepts for innovation and
flexible tools for data collection. It presents the results of a survey conducted to
innovative organisations (firms and non-firms) operating in the Portuguese rural areas,
through interviews, build on a questionnaire designed to cope with CIS limitations
regarding the gathering of data on the innovation processes.
The goals of the paper are threefold, (1) to present empirical evidence on the
innovations being undertook by firms and other type of organisations in the Portuguese
rural areas, which are neglected by the current innovation framework; (2) building on
these data, to show the importance of hidden innovation in the Portuguese rural areas;
and, (3) discuss the need to adjust concepts and data collecting tools in the innovation
field in order to gather data that inform better the agendas and policies for innovation.
The paper is organised as follows. Next, section 2 presents a synthesis of the literature
review on what is understood by hidden innovation, why it is important and how to
capture it. Section 3 introduces the methodological approach, including the presentation
of the sample and the design and implementation of the survey. Empirical results are
presented in the section 4. Finally, section 5 discusses empirical findings and offers
some suggestions on how to improve current innovation framework to allow it to
support the design of more inclusive agendas and policies for innovation.
2.
LITERATURE REVIEW ON HIDDEN INNOVATION
The available literature discloses four types of hidden innovation. The first type refers to
the commonly called non-technological types of innovation, such as marketing and
organisational, which are often highlighted in the low-tech sectors, such as the services.
2
4350 | ESADR 2013
A second type of hidden innovation is the product and process innovation not (mainly)
based on the R&D inputs. These two situations of hidden innovation have been
addressed by a number of studies and authors, for different sectors and firms types, as
well as using different methodological approaches (e.g., Jensen et al. 2007; Arundel et
al. 2008; Miles and Green, 2008; Kirner et al. 2009; Pereira and Romero, 2012; HervasOliver et al., 2011; Trigo, 2013).
The low-technological intensity innovation is commonly related to a third type of
hidden innovation, recently acknowledged by OECD (2010). This third hidden
innovation pattern consists of mixed-modes of innovation developed by organisations in
different sectors. A good example of this is the (improvement) product-driven combined
with marketing and/or organisational innovations. A fourth type of hidden innovation
noticed by the literature, is again derived from the complex nature of innovation
processes, and reports to the non-technological innovation mingled in the technological
innovation (e.g. Boer and During, 2001; Baranano, 2003; Schmidt and Rammer, 2007).
There are authors, such as Wu (2009), that support the point of view that the nontechnological innovation serves as an important bridge for a firm to develop from pure
technological innovation to a firm with effective innovation capability.
Defined what is understood by hidden innovation in the current state-of-art of literature,
a second issue is why hidden innovation matters? It does, because the hidden innovation
is mainly developed by firms in the low-tech sectors, and in particular, by the smallsized firms and these (firms and sectors) are roughly neglected by the mainstream
innovation framework, which is focused on the technological innovation. As a
consequence, public policies, agendas and incentives to promote innovation have been
tailored to address the development and implementation of technological innovation.
The fact, that at least at the EU level, there are parallel initiatives to promote social
innovation and innovation in the services highlights that there is institutional awareness
of the gap in the promotion of non-tech types and modes of innovation (e.g. CEC 2009,
2010 and 2013; UE, 2012).
The major limitation of focusing the schemes and mechanisms to stimulate innovation
in the technological and in the new-to the market innovation is that it neglects a
significant part of the actual economy, the small-scale and low-tech firms, sectors and
3
regions. Hence, given the importance of SME in EU (and in Portugal) for local and
national economies (namely in terms of employment), they need to be fully included in
the EU, national and regional agendas and policies for innovation. In particular, given
that is demonstrated the importance of innovation for the performance of the SME firms
(e.g. Rosenbusch et al., 2011).
Thereafter, a third question is how to adjust the current innovation theoretical and
methodological framework in order to make it more inclusive. This referential
framework is based on the third version of the 2005 Oslo Manual (OECD, 2005). This
guide establishes the methodological guidelines for the Community Innovation Survey
(CIS). The CIS has been implemented systematically in EU since 1997/98 (CIS2)1 and
gathers large data sets on innovation at firm level. It surveys both, innovative and notinnovative firms, allowing for comparative studies. Large samples of firms from
industry and some sectors of the services, with 10 or more employees, are surveyed in
the EU member-states with the CIS under the EUROSTAT umbrella.
The OECD (2005) employs a fairly broad definition of innovation, including marketing
and organisational innovation, and accounting for new-to the firm as well as to new-to
the market innovation. Nonetheless, the measurement of innovation is based on the
product and processes innovation, which are generally acknowledged as technological
innovation, while the marketing and organisational innovation are known as nontechnological innovation. Basically, these latter types of innovation are treated by the
CIS as complementary sources of innovation.
Nevertheless, the third version of the Oslo manual (OECD, 2005) configures a greater
improvement on the definition and measurement of innovation in respect to the former
versions of the Manual (1992 and 1997), which accounted only for technological
product and technological process innovation, the TPP innovation. The broadening of
the innovation concept across the successive versions of the Oslo Manual reflects the
OECD, and other international organisations, effort to build an operational concept able
of capturing the multiple dimensions of innovation.
In fact, the OECD (2010) acknowledges the limitations of splitting the innovation
concept into two groups: technological and non-technological innovation, given the
1
A pilot version has been conducted in 1993 (CIS Light)
4
4352 | ESADR 2013
increasingly trends for mixed modes of innovation. A large study of OECD (OECD,
2009) identified a diversity of innovation patterns, comprising product innovation
mixed with marketing/value chain innovation, combinations of marketing and
organisational innovation, as well as network-based innovation involving collaborative
approaches. The OECD worldwide dataset analysis demonstrates that, in fact,
innovation has a broad scope and comprises a large diversity of players, alongside with
an increasingly trend for collaborative partnerships and network strategies. Therefore,
the results of OECD (2009) show that the current models and policies to promote
innovation, focused on the technological innovation paradigm, in accordance with the
innovation framework that has been developed during the past 20 years (OECD, 1992,
1997 and 2005), are now clearly limited to promote innovation in the economy, namely
in the low-tech sectors and small-firms, as well as to incentivize innovative business
models built on collaborative action and networking. Therefore, knowledge is needed
on the innovation patterns and dynamics of different sectors and organisations, namely
of the small-firms. Hence, broad concepts and adjusted tools for data collecting are
needed.
3.
METHODOLOGY AND DATA COLLECTION
The main challenges faced by the research project underpinning this paper (the RUR@L
INOV project2), aiming to identify and to characterise the innovation taking place in the
Portuguese rural areas, were twofold. The first derived from the ignorance about the
universe of innovative organizations in these areas; the second was the outline of a
methodological approach able to identify and survey a diversity of innovators and
innovations.
The project benefited from previous research, conducted by the authors, on the
innovation in rural areas, which provided a basis to the identification of the innovative
initiatives and an overall picture of innovation in EU rural areas (Costa et al., 2009;
Madureira and Costa, 2009, 2009a, 2010; Marques et al., 2009; RAPIDO 2007, 2008
and 2009). This research provided interesting insights on what is innovation and who
2
RUR@L INOV – Inovar em meio rural (Innovating in rural areas). This project is being conducted by a
team of the University of Tras-os-Montes e Alto Douro in partnership with the DGADR (the
Agricultural ministry national level unit for the Agriculture and Rural Development). More information
is available on the website sites.google.com/site/inovaremmeiorural/.
5
are the innovators in the EU rural areas. In addition it disclosed a knowledge gap in
respect to the small-scale and mixed innovation developed by a diversity of innovators.
Research to overcome that knowledge gap, applied to the Portuguese case, has been
initiated in 2009 with an exploratory survey that was designed and implemented
through in-depth interviews to a small sample of innovative organisations in the
Portuguese rural areas (Madureira et al., 2012). Its main purpose was to develop a data
collection tool, a survey questionnaire-based, able to cope with diversity of players and
to capture innovation processes as a whole.
The previous research and findings supported the design of a large-scale survey to be
implemented to the innovative organisations operating in the Portuguese rural areas.
This survey stems from a two steps methodological approach. First step was the
development of procedures to identify the innovative organisations based on a broad
scope concept of innovation. The second step was the design and testing of a
questionnaire to survey innovative organisations.
To identify the population of the innovative organisations an on-line survey was
delivered, in 2012, to a broad array of entities and actors, asking them to identify and
describe very briefly the innovation cases in Portuguese rural areas they knew, whatever
the information source (that they knew directly or indirectly through media, contacts or
other sources). In parallel to this random sampling procedure, a snowball sampling
strategy was used to complement the identification of innovation cases in the
Portuguese rural areas. Different sources were used, including media notices, contacts
with experts and projects, as well as literature review (namely grey literature). Built on
these two procedures for information collection, a database of innovative organisations
in rural areas was created.
The design of the questionnaire relied, on one hand, on the CIS questionnaire and, on
the other hand, on the exploratory survey conducted in 2009/10 previously reported.
However, important inputs for the methodological options underpinning the
questionnaire, such as the concept of innovation, who the innovators are, and how the
innovation processes take place, were collected through an intense interaction with
innovators and other innovation players. This interactive process was supported by
informal contacts, visits and meetings in the focus group format. Two national level
6
4354 | ESADR 2013
focus groups were organised in the two Portuguese main cities (Lisbon and Porto), in
March 2012. The main goals of the focus groups were to understand the innovation
concepts, innovation process key aspects, and innovation accelerators and barriers, as
perceived by the innovators and other innovation stakeholders.
The questionnaire was organised in four main sections. The first identified the
organisation, including its location, legal nature an economic dimension. In the second
section the organisation was characterised in respect to its activities, products and
services, markets, value chain position and resources (human, financial and other). The
next section was devoted to collect data on the innovation inputs, processes and outputs.
This was the innovative component of the questionnaire, given it has been designed to
provide qualitative information able to be converted in quantitative data regarding the
innovation patterns and dynamics. Alternatively to the CIS approach, the innovations
were not categorised apriori and the respondents were asked to describe the innovations
developed and implemented by the organisation, including the time needed for its
implementation and the year the process was initiated. The final section addressed the
profile of the leader/manager of the innovation and his/her understanding of both the
competitive advantages and disadvantages of the organisation rural location.
The questionnaire was administrated by members of the RUR@L INOV project team to
the head/leader/chief responsibles for the innovation management in the organisations
(often the responsibles for all the management). The survey was administrated by
personnel-interviews to a 120 cases sample, between September 2012 and January
2013. The sample was selected from the abovementioned database, according to the
respective proportions regarding the location by NUTS2 and the legal nature of the
organisations (private, State and non-governmental organisations).
4.
RESULTS
The results are presented in two subsections. The first provides a description of the
sample in respect to a set of variables considered relevant for giving the reader a
snapshot of the main characteristics of the surveyed organisations, namely of the group
of innovative firms. The second subsection presents the results of a cluster analysis (Kclusters) that allowed for grouping the innovative firms according to their innovation
inputs and processes, providing evidence of significant hidden innovation.
7
4.1. Description of the innovative firms profile
As shown by Figure 1, the total 120 surveyed organisations include 94 firms, 22 nonprofit organisations and 4 organisations from the public sector.
3%
18%
79%
Private sector
Public sector
Non-Profit
Figure 1: Organisations surveyed according to their legal nature status
The data regarding the firm size show that SME are the dominant group, representing
97.9% of the total. This figure is in line with the weight of SME in the Portuguese
economy. In addition, more than half of the total companies (53.2%) are micro-firms,
meaning that they employ less than 10 workers (see Table 1).
Table 1: Economic dimension of firms (number of workers)
Firm size
Microempresas
Micro firms
Nº
%
Micro firm (2-4 workers)
26
27.5
13
17.5
Individual (no workers)
11
10.0
Sub-total
Small firm (10-49 workers)
27
26.7
Medium firm (50-249)
15
15.0
Small and medium-sized
Sub-total
Grande
Large firm (250 or more workers)
2
Large firm
Sub-total
2
Total
3.3
Nº
%
50
53.2
42
44.7
2
2
2.1
94
100
Another important feature is the multi-activity/multi-sector character of the majority of
the surveyed firms: 86% are involved in, at least, two economic activities. This is often
a result of coherently integrated production chains (vertical diversification), e.g.
agriculture combined with food-industry (e.g. in wine, olive oil sectors), or foodindustry and trade in the case of the cooperatives. But in other cases it derives from a
horizontal diversification strategy (e.g. combining agriculture and tourism). This
8
4356 | ESADR 2013
multiple-sector pattern has been previously identified as a trait of the innovative rural
organisations, namely the rural firms (Madureira and Costa, 2009, 2009a, 2010;
RAPIDO, 2009).
Regarding the firms resources, there are three aspects deserving to be highlighted. First,
the majority of the firms rely mainly on their own financial resources; That is, in
general, both the public support and the bank loans are secondary sources of funding
Second, while scarce in (very)-small firms, the human resources are highly qualified in
terms of education level (see Figure 2). And, third, the fact of the main source of
knowledge for innovation being the firm own human resources, namely the
promoter/manager together with internet-based tools (see Figure 3).
Figure 2: Funding sources according their importance (2009- 2012)
Large firm
Large firm
Medium-sized firm
Medium-sized firm
Small firm
Small firm
micro firm (5-9 workers)
micro firm (5-9 workers)
micro firm (2-4 workers
micro firm (2-4 workers
0%
20%
40%
60%
80% 100%
0%
20%
40%
60%
80%
100%
Basic education
Secondary school and technological
Higher education
Figure 3: Education level of human resources: (a) Employees; (b) Leaders/managers
The main sources of knowledge for innovation reported by the respondents are the inhouse ones: the leader/manager and the collaborators, together with ICT tools, namely
internet. This is certainly a result of the high education level of firms, in particular the
smallest ones. Internet-based resources are also placed in the group of top sources of
knowledge for innovation. The top knowledge sources combined with the resort to a
multiplicity of sources evidence that the innovative firms have a self-demanding pattern
regarding this innovation key input (see Figure 3).
9
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
Internal sources: knowledge and skill of the leader/manager
Other sources: internet and media
Internal sources: knowledge and skill of collaborators
Other sources: Conferences, fairs, expositions
Market sources: Clients
Other sources: scientific journals and technical/commercial reviews
Other sources: Local knowledge
Market sources: Consumers
Market sources: suppliers and providers of equipment and technology
Other sources: Popular knowledge
Market sources: Other firms in the same sector
Institutional sources: Universities and other higher education entities
Market sources: Consultancy and private R&D entities
Other sources: Professional or entrepreneurial associations
Institutional sources: State R&D labs and other units
Institutional sources-Local development associations
Institutional sources: Other public entities
High
Medium
Low
None
Figure 3: Sources of information for innovation according their relative importance
The mobilisation of local knowledge stated by the respondents (see Figure 3) is also
very evident on the products and services differentiation. This seems to be another
characteristic of innovative rural firms, confirming their ability to mobilise the latent
resources of rural areas, such as the local agro-climatic conditions, local knowledge,
cultural resources, environment and biodiversity.
The innovation processes highlight the mixed modes, combinations of different types of
innovation. Product and process, as well as organisational and process, are strongly
correlated innovation types (Pearson correlation coefficient significant at 0.05
significance level). On the other hand, marketing innovation comes out associated with
product innovation for new products, related with broadening the set of products and the
entrance in specific markets (Chi-Squared test significant at  0.05 significance level).
Incremental innovation is the dominant pattern, whereas still around a third of the total
firms develops radical innovation, in general alongside with incremental. The maximum
time needed to fully develop the innovation can be divided into three groups: (a) 1 year
at maximum (in 17.1% of the firms); (b) between 1 and 3 years (in 54.9% of the cases);
and, (c) more than 3 years (in 28.1% of the firms).
10
4358 | ESADR 2013
The empirical data confirm also the resilient economic performance of innovative firms,
in particular if we keep in mind that the figures for employment and turnover were
collected for a crisis period (2009 to 2011), ended by one year of severe recession in the
Portuguese economy. The Figure 4 shows both the distribution of the variation rate for
employment and sales, in the surveyed firms, between 2009 and 2012 (2011 for
turnover).
Figure 4: Variation rate in total employment and total sales between 2009 and 2012 (2011 for
sales)
These figures highlight the importance of bringing to the scene these backstage firms in
respect to the promotion of innovation, given their resilience pattern and their role for
the sustainable development of the rural areas, by maintaining and creating qualified
jobs.
4.2. Clustering innovative firms evidence hidden innovation
This subsection presents the results of a cluster analysis conducted with k-means
clustering, which is a cluster analysis that splits the observations by a pre-defined
number of clusters, k. The observations are grouped according to their proximity to the
mean of the variables used to define the clusters.
Build on the variables relevant to describe the innovation inputs, processes and outputs
different clustering were tested for different set of dummy variables and number of
clusters. The finally selected clustering has 4 clusters and it is described in Table 2.
11
Table 2: Selected clusters
Final Cluster Centers
Patents
Collaborates with R&D units
Received EU financial support
States a figure for expenditures with internal R&D
States a figure for expenditures with external R&D
States a figure with acquisition of machinery and/or equipment
Develops product innovation for new-to the market products
Develops process innovation for efficiency gains
Develops new-to the market innovation
Develops innovation continuously and sequentially
Innovation takes one year or less to be developed
Develops product innovation
Develops process innovation
Develops marketing innovation
Develops organisational innovation
Develops networking innovation
States to develop internal R&D activities
States the acquisition of external R&D
1
0
0
0
0
0
1
0
0
0
1
1
1
0
1
0
0
1
0
2
0
1
1
1
1
1
0
0
1
1
1
1
1
0
0
0
1
1
Cluster
3
0
1
1
0
1
0
0
0
0
0
0
1
0
0
0
0
1
1
4
0
0
1
0
0
1
0
1
0
1
0
0
1
1
1
0
0
0
Table 3 shows the variables used to describe the clusters to be significant, the exception
being the existence of patents.
Table 3: ANOVA analysis
ANOVA
Patents
Cluster
Mean
df
Square
0.134
3
Error
Mean
df
Square
0.086 90
Collaborates with R&D units
3.110
3
0.157
Received EU financial support
1.692
3
0.202
States a figure for expenditures with internal R&D
3.380
3
States a figure for expenditures with external R&D
States a figure with acquisition of machinery and/or
equipment
Develops product innovation for new-to the market
products
Develops process innovation for efficiency gains
1.629
0.937
F
Sig
1.561
0.204
90
19.770
0.000
90
9,385
0.000
0.131
90
25.717
0.000
3
0.169
90
9.666
0.000
3
0.173
90
5.427
0.002
0.410
3
0.179
90
2.284
0.084
2.741
3
0.127
90
21.566
0.000
Develops new-to the market innovation
0.752
3
0.198
90
3.805
0.013
Develops innovation continuously and sequentially
1.061
3
0.163
90
6.499
0.000
Innovation takes one year or less to be developed
0.704
3
0.230
90
3.059
0.032
Develops product innovation
1.547
3
0.136
90
11.400
0.000
Develops process innovation
2.240
3
0.186
90
12.045
0.000
Develops marketing innovation
0.538
3
0.242
90
2.222
0.091
Develops organisational innovation
1.662
3
0.158
90
10.490
0.000
Develops networking innovation
0.298
3
0.106
90
2.799
0.045
States to develop internal R&D activities
1.682
3
0.182
90
9.251
0.000
States the acquisition of external R&D
3.506
3
0.140
90
25.041
0.000
12
4360 | ESADR 2013
The clustering presented distinguishes four groups regarding the innovation inputs,
processes and outputs.
Cluster 1, which will be labeled as “Invisible innovators”, includes 34 firms (36.2% of
total firms). In this group expenditure with R&D, both internal and external, as well as
cooperation with I&D units, show little relevance. The majority of the firms within this
combine product and marketing innovation. Prevails an incremental, sequential and
continuous dynamic of innovation mainly related to product innovation.
Cluster 2 includes 27 cases (28.7% of the firms), and is the one where innovation is
more visible. Thus, this group will be named as the “Standard innovators”. The firms
within this group states expenditures on both, internal and external R&D inputs,
collaborate with R&D units, benefit from public funds for innovation, and present an
innovation pattern dominated by mixing product and process innovation.
The cluster 3 (with 16 firms, 17% of total firms) can be envisaged both as a
downgrading of cluster 2 or a upgrading of cluster 1. Cluster 3 is R&D less intensive in
comparison to cluster 2 and more focused on product (combined with marketing)
innovation. A possible designation for cluster 3 is “Basic innovators”, since they use
R&D inputs, but invest less on it, and, on the other hand, their focus on product
innovation reveals a more incremental innovation pattern in comparison to the cluster of
the “Standard innovators”.
Finally, the cluster 4 is a group of “Discrete innovators” configuring another type of
hidden innovation. This group combines product and process innovation to attain
efficiency gains and cost reductions. It benefits from public funding and collaborates
with R&D units, but R&D inputs do not show to be as relevant as they are in the
clusters 2 and 3.
A set of variables was tested regarding its ability to characterize the four clusters of
innovators. Table 4 presents the variables that show statistically significant to describe
the clusters.
13
Table 4: Variables tested for their ability to characterise the clusters
ANOVA
Firm dimension
Turnover 2011 (€)
Main activity
Multi-sectorial organisations
Exports
Patents
Expenditures with internal R&D (€)
Expenditures with external R&D (€)
EU public funds
Innovation leader has higher education
No of innovations
No of product innovations
No of process innovations
No of marketing innovations
No of organisational innovations
No of network innovations
Green dimension on innovations
New-to the market innovation
Continuous and sequential innovations
Collaborates with R& D units
Collaborates with firm in the same sector for
innovation
Collaborates with suppliers for innovation
Collaborates with firms from other sectors
for innovation
Sum of Squares
df
25.124 3
9764305612884.000 3
8.889 3
.064 3
.934 3
.402 3
98665522830.1 3
4308730492.83 3
5.075 3
.582 3
129.656 3
97.955 3
59.366 3
6.472 3
10.828 3
1.772 3
1.629 3
2.257 3
3.182 3
9.331 3
.846 3
2.263
.603
Mean Square
F
8.375 5.111
3254768537628.000 1,405
2.963 1.201
.021
.095
.311 1.823
.134 1.561
32888507610.0 2.441
1436243497.61 1.899
1.692 8.385
.194
.897
43.219 7.356
32.652 6.543
19.789 7.324
2.157 1.131
3.609 4.360
.591 2.084
.543 2.234
.752 3.850
.282 1.147
3.110 19.770
.282 .1,147
3
3
.754
.201
Sig.
.003
.247
.314
.963
.149
.204
.069
.135
.000
.446
.000
.000
.000
.341
.006
.108
.090
.013
.000
.000
.335
3.545
.882
.018
.454
Next tables 5 to 14 present the differences between the four clusters regarding the
variables showing significant for their differentiation.
Table 5 takes the economic dimension to explain differences between the groups of
innovators. It shows that the large majority of individual businesses (no-employees) are
in the group of the “Invisible innovators”. This group includes also a relevant
percentage of micro and medium-sized firms. “Discrete innovators” are mainly small
firms. On the other hand, the medium-large size firms are mostly comprised in the
group of “Standard innovators”. However, in this latter group one third of the firms are
micro sized, indicating that the smallness of firms is compatible with R&D based
innovation. “Basic innovators” are mostly micro-sized firms, what might evidence
difficulties of smallness in accessing R&D inputs and collaborations.
14
4362 | ESADR 2013
Table 5: Innovators clusters according to the firms economic dimension
1
26.5
29.4
8.8
29.4
5.9
0.0
100.0
Individual
Micro firm (5 -9 workers)
Small firm (10- 49 workers)
Medium-sized firm (50-249 workers)
Large firm (  250 workers)
Total
Valid Percent in each cluster
2
3
3.7
6.3
18.5
43.8
14.8
18.8
25.9
12.5
29.6
18.8
7.4
0.0
100.0
100.0
4
0.0
0.0
0.0
47.1
11.8
0.0
100.0
Table 6 presents the clusters composition according to the firm’s main economic
activity. It highlights the presence of “Standard innovators” (cluster 2) in the food
industry, and, while with lower weight, in the agriculture and forestry activities. The
“Basic innovators” include mainly firms operating in the services, including the tourism
activities, and on non-food industry. “Discrete innovators” are mainly present in the
food industry and gross and retail trade, probably indicating the presence of
cooperatives in this group. The “Invisible innovators” seem to be dispersed by a
diversity of activities, suggesting again the presence of cooperatives and small
businesses in agriculture and tourism.
Table 6: Innovators clusters according to the firms main activity
1
2
3
4
14.7
25.9
12.5
23.5
23.5
40.7
12.5
29.4
20.6
3.7
31.3
5.9
11.8
11.1
18.8
11.8
26.5
14.8
12.5
23.5
2.9
3.7
12.5
5.9
100.0
100.0
100.0
100.0
Agriculture and forestry
Food industry
Tourism
Other industry
Gross and retail trade
Services
Total
The “Standard innovators” have, as expected, a significantly larger expenditure with
internal R&D in comparison with all the other groups. Cluster 3, the “Basic innovators”,
resort to external R&D and that probably explains their low expenditure in internal
R&D in comparison with the other groups (see Table 7).
Table 7: Innovators clusters according to expenditure on internal R&D (values are in €)
2
3
27.0
16.0
N
1
34.0
Minimum
0.0
0.0
Maximum
50,0000.0
692,038.0
Mean
19,479.9
81,137.6
937.5
4,617.7
Std. Deviation
87,869.3
191,516.4
2,719.5
15,731.7
0.0
3
17.0
0.0
10,000.0 65,000.0
15
The collaboration with universities and other R&D units for innovation is 100% in the
case of “Basic innovators”, which are as already mentioned dependent on external
R&D. In the case of the “Standard innovators” two thirds of the firms report this
collaboration. The “Invisible innovators” appear to be little involved in this type of
collaboration (see Table 8).
Table 8: Collaboration with universities and other R&D units for innovation
No
1
2
3
4
88.9
33.3
0.0
29.4
Yes
11.1
66.7
100.0
70.6
Total
100.0
100.0
100.0
100.0
Cluster 2, the “Standard innovators”, is the group stating more use of UE funds to
develop innovation. In comparison, the “Invisible innovators” benefit very little from
this financial source.
Tables 9 to 13 report on the number and type of innovations and allow comparing the
four groups regarding the respective patterns of innovation. “Standard innovators” state
a large number of innovations and underline the product and process innovation. As
already stated, “Basic innovators” have a product-driven innovation, similarly to the
“Invisible innovators”. “Discrete innovators” are more committed with process and
organizational mix of innovation. The network innovation has relatively little
expression, while shows more expressive in the group of the “Discrete innovators”.
Table 9: Number of innovations
N
Minimum
Maximum
Mean
Std. Deviation
1
34
2
8
4.7
1.7
Clusters
2
3
27
16
2
1
17
9
7.1
3.9
3.2
1.9
4
17
2
10
5.4
2.6
Table 10: Number of product innovations
Clusters
N
Minimum
Maximum
Mean
Std. Deviation
1
36
0
7
2.5
1.6
2
27
0
12
3.7
3.1
3
14
0
9
2.4
2.2
4
17
0
4
0.4
1.1
16
4364 | ESADR 2013
Table 11: Number of process innovations
Clusters
N
Minimum
Maximum
Mean
Std. Deviation
1
36
0
4
0.6
0.9
2
27
0
11
2.0
2.7
3
14
0
3
0.4
0.8
4
17
0
5
1.9
1.4
Table 12: Number of organisational innovations
Clusters
N
Minimum
Maximum
Mean
Std. Deviation
1
36
0
2
0.3
0.6
2
27
0
6
0.5
1.3
3
14
0
1
0.1
0.3
4
17
0
4
1.1
1.1
Table 13: Number of networking innovations
Clusters
N
Minimum
Maximum
Mean
Std. Deviation
1
36
0
0
0.0
0.0
2
27
0
2
0.3
0.5
3
14
0
1
0.2
0.4
4
17
0
4
0.4
1.0
As expected, the radical innovation, new-to the market products (or processes), is
underlined in the group of “Standard innovators”, while and surprisingly shows to be
important also for “Basic innovators”. The later situation is probably related to the
development of new products, built on marketing innovation. Clusters 3 and 4 are
dominated by incremental innovation (see Table 14).
Table 14: Presence of new-to the market innovation
Non
Yes
Total
1
2
3
4
61.1
55.6
92.9
88.2
38.9
44.4
7.1
11.8
100.0
100.0 100.0 100.0
The “Standard innovators” exhibit a more marked profile of continuous and sequential
innovation in comparison to the others, followed by “Basic innovators”, what is again a
kind of surprising outcome.
17
The Figure 5 presents a summary of the results presented, highlighting the profile of
each of the four clusters based on the significant aspects that were described in the
sequence of tables presented along this section.
Figure 5: Profile of the selected clusters
5.
DISCUSSION AND RECOMMENDATIONS
The results of the research here presented endorse the hypothesis that the current
theoretical and methodological framework, build on the Oslo Manual, presents
important limitations in its ability to identify and measure innovation, when the concept
is broaden to all type of firms independently of their economic size, activity sectors and
to comprise the innovations processes that are not highly R&D input based. It shows
clearly insufficient to disclose the actual universe of innovators, as evidenced by the
case of the one operating in the Portuguese rural areas.
The research findings highlight two different groups of firms that hardly would be
identified as “innovators” based on the use of R&D inputs and outputs. On the other
hand, the data show that organizational innovation is often mixed with process
innovation (non-technological processes) and that this important innovation pattern is
not captured by the CIS data. They show, on other hand, that there is a group of
innovators, the “Invisible innovators”, that seems to innovate at their own initiative and
18
4366 | ESADR 2013
risk, with little support, both financial and external knowledge. This is a significant
group of innovators that deserves further analysis in order to understand what hinders
them to access innovation-related resources; and how that access could be ensured?
These are key questions for the political agendas and policies meant to promote
innovation in the real economy.
In addition, this paper demonstrates that the identification and measurement of
innovation can be significantly improved through better survey methodology and
practice. What, has been discussed, is fundamental to adjust the current theoretical and
methodological framework to enable it to be inclusive and to cope with huge diversity
of types of innovations and innovators that are present in the actual economy.
The paper highlights the importance of hidden innovation in firms acting in rural areas,
but their findings are certainly extensible to urban areas and not-rural related activities,
such as the general manufacturing industry. Therefore, more research is needed on the
hidden innovation and on how to include it in the innovation research framework.
ACKNOWLEDGEMENTS
The authors thank José Portela for his commnets and suggestions on a previous draft of
this paper. This research has been conducted under the project RUR@L INOV– Inovar
em Meio Rural, funded by the PRRN (Programa da Rede Rural Nacional).
REFERENCES
Arundel, A., Bordoy, C. and Kanerva, M. (2008), Neglected innovators: how do
innovative firms that do not perform R&D innovate? Results of an analysis of the
Innobarometer 2007 survey, nº 215, INNO-Metrics Thematic Paper, European
Commission, DG Enterprise, Brussels, 31 March.
Baranano, A.M. (2003), The non-technological side of technological innovation: Stateof-the-art and guidelines for further empirical research, International Journal of
Entrepreneurship and Innovation Management 3, pp. 107-125.
Boer, H. and During, W. (2001), Innovation, what Innovation? A Comparison between
Product, Process and Organisational Innovation, International Journal of Technology
Management 22, pp. 83-109.
19
Commission of the European Communities (CEC) (2009), Reviewing Community
innovation policy in a changing world, Brussels: Commission of the European
Communities, COM 442 final.
Commission of the European Communities (CEC) (2010), Europe 2020 Flagship
Initiative Innovation Union, Brussels: Commission of the European Communities,
COM (2010), 546 final.
Commission of the European Communities (CEC) (2013), State of the Innovation
Union 2012 - Accelerating change. Brussels: Commission of the European
Communities, COM (2013), 149 final.
Costa S., Madureira L. and Marques S.C. (2009), Innovation in rural areas and impact
on job creation: evidence from EU and Portugal, 15th Congress of Portuguese
Association of Regional Development (APDR), 6-11 July 2009, University Piaget of
Cape Verde, Cape Verde. Proceedings in CD-ROM.
European Union (2012), Strengthening social innovation in Europe, Journey to effective
assessment and metrics, Belgium.
Hervas-Oliver, J.L., Albors-Garrigos, J. and Baixauli, J.J. (2011), Beyond R&D
activities: the determinants of firms’ absorptive capacity explaining the access to
scientific institutes in low medium-tech contexts, Economics of Innovation and New
Technology 21, pp. 1–27.
Jensen, M.B., Johnson, B., Lorenz, E. and Lundvall, B.A. (2007), Forms of knowledge
and modes of innovation, Research Policy 36, pp. 680–693.
Kirner, E., Kinkel, and S., Jaeger, A. (2009), Innovation paths and the innovation
performance of low-technology-firms – an empirical analysis of German industry,
Research Policy 38, pp. 447-458.
Madureira L. and Costa S. (2009), Multifunctionality agriculture as an innovation path
for rural areas, in D. Tomic, Z. Vasiljevic and D. Cvijanovic (Eds.), “The Role of
Knowledge, Innovation and Human Capital in Multifunctional Agriculture and
Territorial Development”, Thematic Proceedings of the 113th Seminar of European
Association of Agricultural Economics (EAAE), 9-11 December 2009, Institute of
Agricultural Economics, Belgrade, Serbia.
Madureira, L. and Costa S. (2009a), Multifunctionality and innovation strategies of EU
rural organisations, 15th Congress of Portuguese Association of Regional Development
(APDR), 6-11 July 2009, University Piaget of Cape Verde, Cape Verde. Proceedings
em CD-ROM.
Madureira L. and Costa S. (2010), Innovation as a tool to promote sustainable
development in European rural areas, 57th Annual North American Meetings of the
Regional Science Association International (RSAI) November 10-13, 2010, Denver,
U.S.A.
Madureira, L. Portela, J., Ferreiro, M.F., Sequeira, T. and Ferreira, D. (2012),
Innovation in rural areas: towards a new model?, Proceedings of the 18th APDR
Congress APDR Innovation and Regional dynamics, June 14-16, 2012, University of
Algarve, pp. 344-353.
20
4368 | ESADR 2013
Marques S.C., Costa S. and Madureira L. (2009), Innovation and employment in
Portuguese rural areas: an exploratory analysis, 12th ICTPI – International Conference
on Technology Policy and Innovation, 13-14 July 2009, University of Porto, Porto,
Portugal.
Miles, I. and Green, L. (2008), Hidden innovation in the creative industries, NESTA
Research Report (London: NESTA).
OECD (1992), Proposed Guidelines for Collecting and Interpreting Technological
Innovation Data, Oslo Manual. OECD, Paris.
OECD (1997), The Oslo Manual: Proposed Guidelines for Collecting and Interpreting
Technological Innovation Data, 1st edition. OECD, Paris.
OECD (2005), The Oslo Manual: Proposed Guidelines for Collecting and Interpreting
Technological Innovation Data, 3th edition. OECD, Paris.
OECD (2009), Innovation in Firms: A Microeconomic Perspective, OECD, Paris.
OECD (2010), The OECD Innovation Strategy: getting a head start on tomorrow.
OECD, Paris.
Pereira, C. S. and Romero, F. C. (2013), Non-technological Innovation: Current Issues
and Perspectives, Independent Journal of Management & Production 4, pp. 360-376.
RAPIDO (2007), Deliverable 1: 1.1 Best practice database on case studies for
innovation development and transfer in rural areas Deliverable No.: 1.2 Evaluation
matrix to assess future initiatives and projects in the area of innovation. Prepared by
Margaretha Breil, December 2007.
RAPIDO (2008), Deliverable 3: Sectors where innovation enhances rural employment,
Prepared by Lívia Madureira, June 2008.
RAPIDO (2009), Policy Brief N° 2 – February 2009. Prepared by Ecologic - Institute
for International and European Environmental Policy.
Rosenbusch, Nina, Brinckmann, J. and Bausch, A. (2011), Is innovation always
beneficial? A meta-analysis of the relationship between innovation and performance in
SMEs, Journal of Business Venturing 26, pp. 441–457.
Schmidt, T, and Rammer, C. (2007), Non-technological and Technological Innovation:
Strange Bedfellows? ZEW Discussion Paper.
Wu, Y. (2009), The analysis of innovation efficiency and non-technological factors of
manufactory companies in the Pearl River Delta of China. PhD Thesis. Renmin
University of China: School of Statistics, the Center for Applied Statistics.
21

Alimentar Mentalidades, Vencer a Crise Global

Transcrição

Documentos relacionados

S3_rural innovation

Sua Excelência Senhora Pratibha Devisingh Patil

premium white 2014

TERMS OF REFERENCE

EXERCÍCIO 9 1- Leia o texto atentamente - pradigital

View Paper

EU Rural Networks Strategic Framework and governance bodies

“A PROJEÇÃO DO SADOMASOQUISMO NA SOCIEDADE

Create your Photobook in 4 Simple Steps

Associació de Voluntaris del Tarragones