Abstract (english) | Rural development, sustainable development and sustainability are nowadays often
mentioned in scientific publications, as well as in political discussions and media. Rural
development is considered as a priority in the European Union and is financially supported
from designated funds, while sustainability is a keyword for the European Union
processes of creating programs and policies for all human activities. The concept of
sustainable development consists in three components: ecological, economic and social,
which in ideal conditions equally contribute to the objective, but in reality, growth and
development in one component's domain negatively affects the growth and development
of the remaining sustainability factors. Due to the law of scarcity, one has to choose a way
to use the scarce resources and to establish their development priorities.
In order to determine development priorities and sustainable development components in
which a particular area falls behind, a measuring tool is necessary. Since in Croatia no
sustainable development measurement for all of its components has been conducted, it
was decided to create such model using a multicriteria analysis and the AHP method and
to test it on NUTS 3 level.
The aims of this paper are: to identify the most appropriate set of indicators for measuring
sustainable development on NUTS 3 level, to create a model for measuring sustainable
rural development on NUTS 3 level and to test the model on the example of four Croatian
counties.
In the chapter Previous Research, the author provides an overview of the research in the
domain of rural development, sustainability and sustainable development and methods
used for measuring sustainability and sustainable development.
In Materials and Methods, the multicriteria analysis is described in more detail, some of its
methods are specified, while special focus is put on the Analytical Hierarchy Process
(AHP), used for the purpose of achieving research goals. It explains the procedure of
creating the model using this method and some basic theoretical assumptions of the
method.
The chapter Research Results is divided in several subchapters to track more easily both
the process of creating the model and finally its testing on the selected counties. In the
subchapter Suggested Indicators with Explanations, based on a review of literature, a set
of 47 indicators was developed, divided in three groups: ecological, economic and social.
For each suggested indicator, there is a clarification of the importance of its measuring, a
list of authors who used it in previous research and an explanation how it would be
measured if selected by respondents as one of 15 indicators included in the model.
In the subchapter Selection of Sustainable Rural Development Indicators, the author
presents the results of the research conducted on the pattern of 47 respondents:
representatives of scientific-educational institutions, LAGs and state and county
institutions. The following 15 indicators were selected to enter the model: availability of
potable water, investment in sustainable energy sources and energetic efficiency, share of
ecological agriculture in total agriculture, existence of recycling and composting
infrastructure, biodiversity of animal and plant species, unemployment rate, availability of
infrastructure objects connected to agriculture, gross domestic product per capita,
productivity of agricultural production, diversification of economic activities on the rural
area, age structure, availability of education facilities, education structure, availability of
health facilities and population growth between two censuses.
This subchapter also lists the indicators which would enter the model if the research was
limited to a single of the abovementioned respondent groups.
The subchapter Creating a Rating Model of Sustainable Rural Development shows local
priorities of the three indicator groups, as well as of each of the 15 chosen indicators. The
most important indicator group for achieving sustainable rural development are the
economic indicators, with local priority value 0.415, followed by the social, with local
priority value 0.309, while the lowest value of local priority, 0.275, is attributed to the
ecological indicators.
Different groups of experts, formed based on their workplace, placed different value to
particular indicator groups. Thus, representatives of academic teaching personnel
consider the social group of indicators to be the most important, while the representatives
of LAGs, state and county institutions evaluated the economic indicators as the most
important.
If individual indicators are observed, the indicator with the highest value of local priority is
availability of potable water (0.286), and the lowest value is attributed to the share of
ecological agriculture in the total agriculture (0.127).
The subchapter Entering Data into the Model includes all data for individual indicators for
each of the four counties on which the model was tested (Brod-Posavina, KoprivnicaKriževci,
Vukovar-Srijem and Zadar). Along with the statistical data, the chapter contains
tables with key for assigning weight when ranking the counties by the selected indicators.
In the last subchapter, Testing the Model on Four Selected Counties, as indicated by the
title, the model was tested. Apart from the original model which includes all expert groups'
opinions, three model versions were made based on the experts' occupation, and a model
version in which all criteria and subcriteria bear equal local priority value.
Zadar County received the highest ratings among the observed counties in the original
model, as well as in all four versions. This comes from the fact that this county had the
best values of almost all indicators, and consequently, a difference in particular indicators'
local priority values in model versions had no effect on the final result. The second-placed
in all test situations was Koprivnica-Križevci, while Vukovar-Srijem and Brod-Posavina
had the lowest ratings, with very small difference among the two.
The chapter Discussion follows the chapter Research Results. Each subchapter of the
discussion points out the problems encountered during the research, describes how they
were resolved and recommends ways of possible improvement.
A comprehensive model such as this one, which was created using a multicriteria
analysis, gives a better insight into the overall state of the territory and population, and
based on the obtained comparisons an inclusive development strategy can be devised.
The advantage of the used method is that different stakeholders can take part in the
selection of indicators and evaluation of their importance in achieving sustainable rural
development, which was in actuality done when creating this model, while the
disadvantage of this research is unequal representation of each stakeholder group, which
undoubtedly affected both the indicator selection and weight assignment.
As a disadvantage of the model, one can point out a certain amount of subjectivity in
suggesting which indicators are to be included in the model, as well as the subjectivity of
each respondent in choosing the indicators and their weight assignment. This subjectivity
was not entirely avoidable, but it was substantially neutralized by heterogeneity of
respondents' professional orientation.
The paper ends with the chapter Conclusions, where the achieved aims are briefly stated,
hypotheses are reflected upon and possible further research and model improvement is
suggested.
This paper identifies the most appropriate set of indicators for measuring sustainable rural
development on NUTS 3 level. 15 indicators were selected, which were then subdivided
into three groups: ecological, economic and social. A model for measuring sustainable
rural development on NUTS 3 level was created using a multi-criteria AHP method in the
program Expert Choice 2000 which can be used, with minor adjustments, on the area of
the entire European Union. The model was tested on the territory of four counties, of
which Zadar County exhibited the best results in rural sustainability, followed by
Koprivnica-Križevci, then Brod-Posavina and Vukovar-Srijem with the lowest results. Four
versions of the model were also created, according to the opinion of the representatives of
scientific-educational institutions, LAGs and associations, state and county institutions,
and a model where all criteria and subcriteria have equal local priority values. Local
priority values of the criteria and subcriteria differ in these models according to the
professional orientation of the respondents. Economic criteria have been confirmed as the
most important in achieving sustainable rural development, but this was not critical for the
final ranking of the counties because the top-ranked county (Zadar) was also leading by
the non-economic indicators. The hypothesis that the county with the highest GDP per
capita will be the highest ranked considering the goal: achieving sustainable rural
development, was not confirmed. Further research should certainly test the model on all
Croatian counties, after which Croatia can be compared to neighbouring countries. The
model is also applicable at the local level, where it could prove problematic due to nonexistent
statistical data for such small territorial units.
The paper's scientific contribution is the creation of a model for measuring sustainable
rural development. This is the first application of such comprehensive model in Croatia.
The results obtained with the model can be of use to regional and local government in
detecting strengths and weaknesses in particular areas of economic, ecological and social
development, which is certainly a good basis for writing rural development strategies and
for the purposes of differentiation in the development policy of respective parts of Croatia.
Seeing as different parts of Croatian rural space are characterized by different problems,
the model provides a compromise in rating. In addition to this, the model can be used for a
more effective ranking of projects applying for different measures within the Rural
Development Program, primarily those whose users are local self-government units. |