Baltic Journal of Economic Studies  

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Vol. 6, No. 2, 2020 

Corresponding author:
1 Nicolaus Copernicus University, Poland.
ORCID: https://orcid.org/0000-0002-4201-8028
2 Nicolaus Copernicus University, Poland.
ORCID: https://orcid.org/0000-0002-9897-3139

DOI: https://doi.org/10.30525/2256-0742/2020-6-2-1-8

THE IMPLEMENTATION OF THE SUSTAINABLE DEVELOPMENT 
GOALS AT THE LOCAL LEVEL. THE CASE OF THE DISTRICTS  

OF KUYAVIAN-POMERANIAN PROVINCE
Joanna Marszałek-Kawa1, Piotr Siemiątkowski2

Abstract. The aim of the paper is to provide the objective assessment of progress in the implementation of the 
goals of the local sustainable development strategy by the districts of Kuyavian-Pomeranian Province. In order to 
achieve our aim, we have devised, using methods of taxonomic analysis, the synthetic indicator (taking a lot of 
different measures of sustainable development into account), which shows the degree of the accomplishment of 
goals adopted in the sustainable development goals. In the collective of units under study, there is a significant 
differentiation of the level of indicators analyzed within the framework of the sustainable development strategy.  
It must be emphasized that there are as many as 12 districts in the lower quartile of the distribution of the synthetic 
measure, i.e., its level was below 0.25. 11 self-government units were in the second quartile of the distribution, i.e., 
in range between 0.25 and 0.5 of the synthetic indicator. Relatively big taxonomic distances between synthetic 
measures for individual districts, with quite a large set of features, show significant differentiation among these parts 
of Kuyavian-Pomeranian Province in terms of local sustainable development. Despite the fact that the examined 
objects belong to the same administrative unit, which would appear to be relatively coherent, they do not develop 
at the same pace. Moreover, given a broad set of indicators, they differ significantly when it comes to the rate of 
their sustainable development. The findings of this paper highlight the use of multidimensional taxonomic analysis 
for measuring the progress of local units in the degree of the accomplishment of the sustainable development 
goals. First of all, it helps to show differences in the implementation of the development strategies across districts. 
What is more, it shows these differences on the basis of the complete set of diverse features rather than single 
parameters (e.g., pace of growth). Thus, the multidimensional approach is a lot more precise when it comes to 
showing differences among the examined objects.

Key words: sustainable development, synthetic measure, taxonomic analysis, local development.

JEL Classification: Q01, H76

1. Introduction
The principle of sustainable development must be 

considered “a pattern of development that meets the 
needs of present generations, without compromising 
the rights of future generations to fulfil their needs” 
(Brundtland, 2019, p. xv). This pattern should serve as 
a set of guidelines for governments and international 
and non-government organizations, supported by self-
governments, entrepreneurs and society. In order to 
put this idea – expressed by former Norwegian Prime 
Minister – into practice, we should consistently and 
regularly undertake extensive activities in the area of 
politics and legislation that will be in line with the 
following targets: “1. Strengthening human well-being 
and capabilities; 2. Shifting towards sustainable and 
just economies; 3. Building sustainable food systems 

and healthy nutrition patterns; 4. Achieving energy 
decarbonization and universal access to energy; 
5. Promoting sustainable urban and peri-urban 
development; 6. Securing the global environmental 
commons” (Brundtland, 2019, p. xvi).

There is no doubt that it is not an easy task to 
design solutions that will help to accomplish the 
above plans or implement the existing international 
and EU regulations and programmes (Alberti, 1996). 
However, “development issues must be seen as crucial 
by the political leaders who feel that their countries have 
reached a plateau towards which other nations must 
strive” (United Nations, p. 14; see also: Williamson, 
Radford, Bennetts, 2003, p. 16).

The principle of sustainable development is 
particularly important in developing societies. In order 



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Vol. 6, No. 2, 2020
to implement this principle at the local level effectively, 
a development strategy must be drawn up. It should 
involve spheres such as economic welfare, social balance 
and healthy living environment. What is as important as 
the pursuit of the sustainable development goals is how 
they are measured. As the issue has a variety of aspects, 
it is difficult to assess the progress of specific countries 
or their administrative parts.

In this paper, we address the following research 
problems:

P1: How should the level of local sustainable 
development be measured given the multitude of the 
goals of the sustainable development strategy and of the 
goal indicators?

P2: Do the districts of Kuyavian-Pomeranian 
Province maintain the same pace in implementing the 
assumptions of the sustainable development strategy? 

The research process required the adoption of the 
following hypotheses:

H1: The examined objects exhibit significant 
differences in taxonomic distances between the 
synthetic measure of development, which justifies the 
use of multidimensional analysis for measuring the level 
of local sustainable development.

H2: Individual districts under study significantly 
differ in the level of sustainable development despite the 
fact that they are parts of the same province.

The aim of the paper is to provide the objective 
assessment of progress in the implementation of the 
goals of the local sustainable development strategy 
by the districts of Kuyavian-Pomeranian Province. 
The term “objective” means here that progress in 
the implementation of all goals should be measured 
by a single, synthetic indicator. This means that we 
evaluate the level of local sustainable development in 
particular districts by analyzing a variety of aspects 
of this development at the same time. In order to 
achieve our aim, we have devised, using methods of 
taxonomic analysis, the synthetic indicator (taking 
a lot of different measures of sustainable development 
into account), which shows the degree of the 
accomplishment of goals adopted in the sustainable 
development goals.

The values of the indicator have allowed us to come up 
with the ranking of all districts of Kuyavian-Pomeranian 
Province according to the level of progress in the 
implementation of sustainable development goals. 

2. Literature review
The principle of sustainable development should 

be one of the most important priorities defining 
governments’ action plans both at the national and local 
level. This concept, as indicated by Yigitcanlar, Dur and 
Dizdaroglu, “plays a key role in a critical role in securing 
prosperity of our cities and societies” (Yigitcanlar, Dur, 
Dizdaroglu, 2015).

The concept of sustainable development has been the 
subject of studies conducted by representatives of many 
natural, social and economic sciences. However, the 
notion has not been defined in a uniform, comprehensive 
way yet (Bukowski, 2012). Bujak-Szwaczka and Kolas 
pointed out that its principal objective is “to reach 
prosperity, justice (intra- and intergenerational) and 
security” (Bujak-Szwaczka, Kolas, 2010). It will be 
impossible to attain sustainable development without 
ensuring: economic growth, social inclusion and 
environmental protection (United Nations Information 
Centre in Warsaw, 2015). 

Pawłowski defines that “the concept of sustainable 
development, referring to the fulfilment of rights and 
needs of future generations is considered mainly in 
three dimensions: ecological, social and economic” 
(Pawłowski, 2009). Rakoczy points out that “the principle 
of sustainable development focuses on finding normative 
solutions which will take into account legally protected 
conflicting values, at the same time having regard for the 
needs of future generations” (Rakoczy, 2015).

In his study, Sekuła argues that the implementation of 
the concept of sustainable development, which involves 
taking care of the natural environment and the respect 
of social equality, brings about a number of positive 
results of a qualitative character. It helps to reduce the 
negative consequences of the scientific-technological 
development or to prevent conflicts in the field of spatial 
management (including environmental degradation). 
It also shows that, at the local level, the principle of 
sustainable development is implemented with the use 
of many specialized instruments, such as the model 
of the simulation of pollution spread in a commune, 
environmental reliefs, or the construction of bicycle 
paths (Sekuła, 2002).

The concept of sustainable development should be 
perceived as a process of change in which the use of 
resources, investment direction, technological progress 
and institutional changes are in line with present and 
future needs (United Nations, General Assembly, 1987).

Considering all these aspects, Olejarczyk has 
stated that the principle of sustainable development 
is currently a political idea rather than a plan serving 
the purpose of drawing up a broad economic project 
reflected in the state’s policy. Sustainable development 
leads to positive qualitative and quantitative changes in 
a given area, while respecting the environmental values 
and the principle of social equality. It follows from the 
pursuit of the development which, firstly, reduces the 
negative consequences of the scientific-technological 
revolution, and, secondly, prevents conflicts in space 
management reflected mainly in environmental 
degradation (Olejarczyk, 2016).

In the document Transforming our world: the 
2030 Agenda for Sustainable Development, signed 
by 193 member states, the United Nations defined 
17 major Sustainable Development Goals: 



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Vol. 6, No. 2, 2020 
– Goal 1. End poverty in all its forms everywhere;
– Goal 2. End hunger, achieve food security and 
improved nutrition and promote sustainable agriculture; 
– Goal 3. Ensure healthy lives and promote well-being 
for all at all ages; 
– Goal 4. Ensure inclusive and equitable quality 
education and promote lifelong learning opportunities 
for all; 
– Goal 5. Achieve gender equality and empower all 
women and girls; 
– Goal 6. Ensure availability and sustainable 
management of water and sanitation for all; 
– Goal 7. Ensure access to affordable, reliable, sustainable 
and modern energy for all; 
– Goal 8. Promote sustained, inclusive and sustainable 
economic growth, full and productive employment and 
decent work for all; 
– Goal 9. Build resilient infrastructure, promote 
inclusive and sustainable industrialization and foster 
innovation; 
– Goal 10. Reduce inequality within and among 
countries; 
– Goal 11. Make cities and human settlements inclusive, 
safe, resilient and sustainable; 
– Goal 12. Ensure sustainable consumption and 
production patterns; 
– Goal 13. Take urgent action to combat climate change 
and its impacts; 
– Goal 14. Conserve and sustainably use the oceans, 
seas and marine resources for sustainable development; 
– Goal 15. Protect, restore and promote sustainable use 
of terrestrial ecosystems, sustainably manage forests, 
combat desertification, and halt and reverse land 
degradation and halt biodiversity loss; 
– Goal 16. Promote peaceful and inclusive societies 
for sustainable development, provide access to justice 
for all and build effective, accountable and inclusive 
institutions at all levels; 
– Goal 17. Strengthen the means of implementation 
and revitalize the global partnership for sustainable 
development (United Nations, General Assembly, 2015). 

Dhingra and Chattopadhyay (2016), later emphasized 
by Trindade, Hinnig, da Costa et al. (2017), have found 
that it is possible to attain sustainable development at the 
local level by way of accomplishing the following goals: 
improve the quality of life of citizens; ensure economic 
growth with more opportunities for employment; 
increase the prosperity of citizens by securing access 
to social and community services; establish an 
environmentally responsible and sustainable approach 
to development; guarantee the efficient delivery of basic 
services and infrastructure, such as public transportation, 
water supply and sanitation, telecommunication 
and other utilities; be able to address climate change 
and environmental issues; and establish the efficient 
regulatory and local government mechanism ensuring 
equitable policies (Dhingra, Chattopadhyay, 2016).

According to Pope, Annandale and Morrison-
Saunders, the progress of the implementation of the 
principle of sustainable development is assessed by 
analyzing not only the initiatives and proposals under 
preparation, but also current policies, programmes and 
plans, binding law, real practice and actions taken (Pope, 
Annandale, Morrison-Saunders, 2004).

3. Methods
The evaluation of the degree of the accomplishment 

of the local sustainable development goals according to 
the GUS (Główny Urząd Statystyczny – Main Statistical 
Office) methodology, which is consistent with the 
international methodology, consists of 22 groups of 
indicators (corresponding to four main areas), such 
as: demographic change, public health, consumption 
patterns, adequacy, income in the old age, health 
determinants, crime, road accidents, economic growth, 
participation in transportation, climate change, energy, 
air protection, biodiversity, waste management, openness 
and participation, and economic instruments. Within this 
framework, almost 180 various indicators were defined to 
follow the progress of a territorial unit (a state or its part) in 
the implementation of the idea of sustainable development.

It is extremely difficult to compare this progress as 
a whole, given the multitude of indicators. On the other 
hand, if we compare territorial units with the use of 
one or a few selected indicators, we will not get a clear 
answer to the question which districts are quicker 
and which are slower in the implementation of the 
sustainable development goals. In such a case, the so-
called multidimensional analyses come to the aid. 

In this paper, we conduct the taxonomic study of 
the local sustainable development of the districts of 
Kuyavian-Pomeranian Province in four areas: social 
order, economic order, environmental order and 
institutional-political order. To this end, we applied the 
method of linear ordering, used for assessing the level of 
diversification of objects with the application of a closed 
set of statistical features (Grabiński, Wydymus, Zielaś, 
1989). We presented the adopted method in detail 
in other studies, so there is no need to discuss it any 
further. (Siemiątkowski, 2015; Siemiątkowski, 2017; 
Siemiątkowski, Tomaszewski, 2018; Siemiątkowski, 
Jankowska, 2020). It should only be noted here that we 
standardized features based on model methods, which 
assume that there exists the reference model object 
in relation to which the taxonomic distances of the 
examined objects were determined. 

The synthetic measure was calculated according to 
Hellwig’s method, based on the formula:

d
d
d

i
i= −1 0
0

where:
di0  – the Euclidean distance of object xi  from 

reference object x0 ,



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Vol. 6, No. 2, 2020

d0  – the critical distance of a given unit from the 
reference object (Ostasiewicz, 1998).

It should also be pointed out that we have already 
conducted empirical studies concerning the selected 
aspects of sustainable development involving 
a significant number of inhabitants of Kuyavian-
Pomeranian Province (research sample of approximately 
4,500 people). Some findings of these studies have 
already been published (Siemiątkowski, Tomaszewski, 
Jurgilewicz, & Poplavska, 2019), while the others 
will be published in a monograph which is in print 
(Siemiątkowski, Tomaszewski, 2020).

4. Research results
In order to carry out the taxonomic study of the 

progress in the implementation of the sustainable 
development goals of the districts of Kuyavian-
Pomeranian Province, using the database of the Main 
Statistical Office, we preliminarily selected 89 features 
of objects (districts). It must be emphasized here that 
the list of indicators considered when building the 
synthetic measure is limited by the very assumptions 
of the sustainable development strategy. This means 
that we did not include here features other than 
those indicated in the GUS statistics, consistent 
with international recommendations concerning the 
sustainable development goals.

Social governance:
X1t – birth rate per 1,000 of population, 
X2t – the rate of migration for a permanent stay 

of people in working age per 10,000 of working age 
population, 

X3t – post-working age population per 100 of working 
age population,

X4t – non-working age population per 100 of working 
age population,

X5t – post-working age population per 100 of post-
working population,

X6t – infant mortality rate per 1,000 live births, 
X7t – deaths caused by cardiovascular diseases in 

percent of the total number of deaths, 
X8t – deaths caused by cancer in percent of the total 

number of deaths,
X9t – deaths caused by respiratory diseases in percent 

of the total number of deaths,
X10t – number of deaths of people under 65 years of 

age per 1,000 of population in this age, 
X11t – number of people in households benefiting 

from social welfare in percent of total population, 
X12t – average monthly gross salary (business entities 

with more than nine people), 
X13t – average usable floor area of a flat per one person, 
X14t – kindergarten children in percent of the total 

number of children in the age of three to five, 
X15t – kindergarten children in percent of the total 

number of children in the age of three to five in rural areas, 

X16t – pass rate of final examinations in vocational 
high schools,

X17t – pass rate of final examinations in high schools,
X18t – the long-term unemployed (longer than one 

year) in percent of the total number of the unemployed,
X19t – the registered unemployed in percent of the 

total working age population (as of December 31) – 
unemployed – women, 

X20t – number of the registered unemployed in percent 
of the total working age population (as of December 31), 
the unemployed with a university degree, 

X21t – job offers for people with disability per 
1,000 unemployed with disability,

X22t – graduates (previously non-working) in percent 
of the total number of people unemployed, 

X23t – graduates (previously non-working) in percent 
of the total number of people unemployed, female 
graduates,

X24t – registered unemployment rate,
X25t – number of passenger cars per 1,000 of 

population, 
X26t – consumption of utilities in households over 

a year per person – electricity, 
X27t – consumption of utilities in households over 

a year per person – gas, 
X28t – consumption of utilities in households over 

a year per person – water, 
X29t – the registered long-term unemployed (more 

than one year) in the age 55-64 in percent of the total 
number of people unemployed in the age 55-64,

X30t – people in post-working age in households 
benefiting from social welfare in percent of the total 
number of people in this age, 

X31t – people injured in industrial accidents per 
1,000 of working population,

X32t – health clinics per 10,000 of population, 
X33t – detection rate of offences discovered by the police, 
X34t – offences discovered by the police per 1,000 of 

population,
X35t – criminal offences discovered by the police per 

1,000 of population,
X36t – economic offences discovered by the police 

per 1,000 of population
X37t – road traffic offences discovered by the police 

per 1,000 of population,
X38t – offences against life and health discovered by 

the police per 1,000 of population,
X39t – offences against property discovered by the 

police per 1,000 of population,
X40t – road accident victims per 100,000 of registered 

vehicles – injured, 
X41t – road accident victims per 100,000 of registered 

vehicles – fatal accidents.
Economic governance
X42t – capital expenditure in enterprises (current 

prices; without business entities with up to nine 
employees) per one person of working age, 



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X43t – entities of the national economy newly 

registered in REGON (National Business Registry) per 
10,000 of working age population,

X44t – value of the foreign capital of companies per 
person of working age,

X45t – capital expenditure according to PKD (Polish 
Classification of Activity) in percent of the total capital 
expenditure of enterprises (without business entities 
with up to nine employees) – agriculture, forestry, 
hunting and fishery, 

X46t – capital expenditure according to PKD (Polish 
Classification of Activity) in percent of the total capital 
expenditure of enterprises (without business entities 
with up to nine employees) – industry and construction,

X47t – capital expenditure according to PKD (Polish 
Classification of Activity) in percent of the total 
capital expenditure of enterprises (without business 
entities with up to nine employees) – commerce, 
vehicle repair, transportation and warehousing, 
accommodation and catering, information and 
communication technology, 

X48t – capital expenditure according to PKD (Polish 
Classification of Activity) in percent of the total capital 
expenditure of enterprises (without business entities 
with up to nine employees) – financial and insurance 
activity, real estate activities,

X49t – capital expenditure according to PKD (Polish 
Classification of Activity) in percent of the total capital 
expenditure of enterprises (without business entities 
with up to nine employees) – other services,

X50t – natural persons conducting business activity 
per 100 of working age population, 

X51t – entities of the national economy registered in 
REGON according to size per 10,000 of working age 
population – total, 

X52t – entities of the national economy registered in 
REGON according to size per 10,000 of working age 
population – micro (up to nine employees),

X53t – entities of the national economy registered in 
REGON according to size per 10,000 of working age 
population – small (from 10 to 49 employees),

X54t – entities of the national economy registered in 
REGON according to size per 10,000 of working age 
population – medium (from 50 to 249 employees),

X55t – entities of the national economy registered in 
REGON according to size per 10,000 of working age 
population – large (over 250 employees),

X56t – length of bicycle paths per 10,000 sq km, 
X57t – length of bicycle paths per 10,000 of population,
X58t – length of local public roads per 100 sq km – 

paved surface,
X59t – length of local public roads per 100 sq km – 

dirt roads,
X60t – communes’ expenditure on public roads in 

percent of their total expenditure,
X61t – districts’ expenditure on public roads in 

percent of their total expenditure.

Environmental governance:
X62t – carbon dioxide emissions from plants especially 

noxious to air purity,
X63t – communes’ expenditure on the protection of 

air and climate per person,
X64t – consumption of electricity per person – total,
X65t – consumption of electricity per person – urban 

areas,
X66t – consumption of electricity per person – rural 

areas,
X67t – emissions of air pollutants from plants 

especially noxious to air purity — gases, 
X68t – emissions of air pollutants from plants 

especially noxious to air purity — particulates,
X69t – pollutants retained or neutralized in pollutant 

reduction systems in plants especially noxious to air 
purity in percent of pollutants generated – gases without 
carbon dioxide,

X70t – pollutants retained or neutralized in pollutant 
reduction systems in plants especially noxious to air 
purity in percent of pollutants generated – particulates,

X71t – forest cover,
X72t – degree of afforestation,
X73t – legally protected land in percent of the total area,
X74t – green areas in percent of the total area, 
X75t – amount of mixed municipal waste of household 

collected during the year per one inhabitant,
X76t – amount of municipal and industrial waste 

water after treatment in percent of the total amount of 
waste water to be treated,

X77t – number of domestic biological waste water 
treatment plants,

X78t – uncontrolled dumping sites (number per 
100 sq km),

X79t – uncontrolled dumping sites (area per 100 sq km).
Institutional and political governance:
X80t – number of registered foundations, associations 

and social organizations per 10,000 of population,
X81t – voter turnout in self-government elections – 

first round,
X82t – voter turnout in self-government elections – 

second round
X83t – councilwomen and councilpersons with 

higher education in percent of the legislative organs of 
communes and districts – women,

X84t – councilwomen and councilpersons with 
higher education in percent of the legislative organs of 
communes and districts – people with higher education,

X85t – revenues to communes’ budgets from service 
charges per person,

X86t – the European Union funds for financing EU 
programmes and projects obtained by communes and 
districts per person,

X87t – expenditure from the budgets of communes 
and districts on servicing public debt per 1,000 PLN 
of the total budget income of communes and districts  
(the total of communes and districts combined), 



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Vol. 6, No. 2, 2020

X88t – capital expenditure of communes and districts 
in percent of the total expenditure (communes and 
districts combined), 

X89t – area of land covered by local spatial 
development plans in percent of the total area. 

When choosing features for the construction of the 
synthetic measure of the sustainable development of 
districts, we had to select them carefully. As the features 
had to meet the requirements of the completeness of 
statistical data and of the unified methodology of data 
gathering, some of the indicators mentioned above 
could not be qualified to the subsequent stages of 
the construction of the synthetic measure. The main 

problems were the incompleteness of statistical data, 
their heterogeneity for different districts, the lack of 
any data, and the lack of information about ways of 
collecting data by authorized entities.

Among the features that met the above requirements, 
35 were recognized as stimulants, while 24 were 
deemed destimulants (see: Table 1). The remaining 
features failed to fulfil strict methodological 
requirements typical of synthetic taxonomic measures. 
The features selected for further procedure did not 
show an excessive degree of correlation towards each 
other; thus, they were all included in the synthetic 
indicator.

Table 1
The selection of features of particular districts

Governance Stimulants Destimulants

Social X1t, X12t, X13t, X14t, X16t, X17t, X25t, X32t
X3t, X4t, X5t, X7t, X8t, X9t, X10t, X11t, X18t, X19t, X20t, 
X22t, X23t, X24t, X26t, X28t, X29t, X30t, X31t

Economic 
X42t, X43t, X44t, X45t, X46t, X47t, X48t, X49t, X50t, 
X51t, X52t, X53t, X54t, X55t, X56t, X57t, X58t, X59t, X60t 

Environmental X71t, X73t, X77t X64t, X65t, X75t, X76t 
Institutional-political X80t, X83t, X84t, X88t, X89t X87t 

Source: authors’ own work

0 0.1 0.2 0.3 0.4 0.5

żniński
świecki

sępoleński
tucholski

mogileński
nakielski

radziejowski
inowrocławski

lipnowski
włocławski

rypiński
Grudziądz
Włocławek
grudziądzki
brodnicki

golubsko-dobrzyński
chełmiński
wąbrzeski

Toruń
bydgoski

aleksandrowski
toruński

Bydgoszcz

0.0622
0.0706

0.0831
0.0885

0.1155
0.1370

0.1528
0.1912
0.1982
0.2033

0.2486
0.2489
0.2560

0.2726
0.2755
0.2790

0.3303
0.3318

0.3617
0.3988

0.4478
0.4495

0.4787

Figure 1. The synthetic measure of sustainable development of the districts  
of Kuyavian-Pomeranian Province

Source: authors’ own work



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Vol. 6, No. 2, 2020 
Having carried out all necessary procedures 

(among others, the choice of the reference model, the 
standardization of features), we calculated the values 
of the synthetic measure of sustainable development, 
which were presented in Figure 1. 

The ranking presented in Figure 1 shows significant 
taxonomic distances between the synthetic measures 
of particular districts. The difference between the 
best and the worst district as expressed in the value 
of a synthetic measure was as much as 0.4165. This 
shows considerable disparities in the implementation 
of sustainable development strategies across individual 
districts. 

Another conclusion refers to the level of sustainable 
development in the districts of Kuyavian-Pomeranian 
Province. The maximum value of the synthetic indicator 
was nearly 0.48. This means that all the examined 
districts are below the second quartile of the distribution 
of the indicator value. This may be interpreted as the low 
and very low level of sustainable development.

The districts of the city of Bydgoszcz and toruński 
were at the top of the ranking. They are both highly 
urbanized areas. Aleksandrowski district was also  
ranked high, although it does not significantly  
distinguish itself with high indicator values. The 
following positions were occupied by other strongly 
urbanized districts: bydgoski and the city of Toruń.

At the bottom of the ranking, we find peripheral 
districts: żniński, świecki, sępoleński and tucholski. 
It should be pointed out that the ranking covered 
a significant number of features so, basically, it is reliable. 
Further in-depth study is required to find the cause for 
which these districts were ranked on the lowest positions 
of the ranking. It would help to identify which of the 

four most important areas of sustainable development 
weighs on their result. 

5. Conclusion
The use of multidimensional taxonomic analysis for 

measuring the progress of local units in the degree of the 
accomplishment of the sustainable development goals 
has undeniable advantages. First of all, it helps to show 
differences in the implementation of the development 
strategies across districts. What is more, it shows these 
differences on the basis of the complete set of diverse 
features rather than single parameters (e.g., pace of 
growth). Thus, the multidimensional approach is a lot 
more precise when it comes to showing differences 
between the examined objects. 

In the collective of units under study, there is significant 
differentiation of the level of indicators analyzed within the 
framework of the sustainable development strategy. It must 
be emphasized that there are as many as 12 districts in the 
lower quartile of the distribution of the synthetic measure, 
i.e., its level has been below 0.25. 11 self-government units 
were in the second quartile of the distribution, i.e., in range 
between 0.25 and 0.5 of the synthetic indicator.

Relatively big taxonomic distances between synthetic 
measures for individual districts, with quite a large set 
of features, show signifcant differentiation among these 
parts of Kuyavian-Pomeranian Province in terms of 
local sustainable development. Despite the fact that the 
examined objects belong to the same administrative 
unit, which would appear to be relatively coherent, 
they do not develop at the same pace. Moreover, given 
a broad set of indicators, they differ significantly when it 
comes to the rate of their sustainable development. 

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