Parametryczna ocena jakości środowiska mieszkaniowego wybranych obszarów zamieszkania w małych miastach województwa podkarpackiego z wykorzystaniem zintegrowanego wskaźnika jakości

Justyna Kobylarczyk, Dominika Kuśnierz-Krupa, Marcin Furtak, Marzena Nowak-Ocłoń

doi:10.37190/arc230410

Streszczenie

W artykule przedstawiono problematykę związaną z metodą oceny jakości środowiska zamieszkania wykorzystującą zdefiniowany i sprawdzony przez autorów zintegrowany wskaźnik jakości (ZWJ). Metoda ta stanowi uzupełnienie dotychczas stosowanych metod – opisowej lub/i parametrycznej. Obydwie metody nie są w pełni skuteczne w diagnozie porównawczej obszarów ze wskazaniem, który z nich zapewnia wyższą jakość. Wynika to między innymi z różnej wagi poszczególnych czynników podlegających ocenie, a składających się na jedną ocenę końcową (wynikową). Celem pracy jest wykazanie, że przy wykorzystaniu jednego wskaźnika porównawczego, zdefiniowanego przez autorów jako ZWJ, możliwe jest uzyskanie zobiektywizowanej oceny uwzględniającej oceny parametryczne wszystkich analizowanych czynników z odpowiednimi wagami. Dzięki temu porównanie wyników oceny jakości różnych obszarów mieszkaniowych jest jednoznaczne. Większa wartość ZWJ oznacza wyższą jakość środowiska zamieszkania. Wskaźnik ten pozwala w większym stopniu ocenić jakość środowiska zamieszkania człowieka niż w przypadku oceny opisowej i oceny parametrycznej oddzielnej dla każdego czynnika. Z tego powodu przedstawiona w pracy metoda poza wartością naukową ma też wartość praktyczną – ułatwia jednoznaczne wnioskowanie i w konsekwencji dążenie do poprawy warunków zamieszkania, co ma niepodważalny wpływ na dalsze badania w zakresie omawianej tematyki

Podgląd pełnego artykułu jest możliwy wyłącznie na większych ekranach.

2023

4(76)

Justyna Kobylarczyk*, Dominika Kuśnierz-Krupa**,

Marcin Furtak***, Marzena Nowak-Ocłoń****

Parametric assessment of the quality of the housing environment

of selected areas in the small towns in the Subcarpathian Voivodeship

using the integrated quality indicator

Introduction

The subject of this study is an original method of assess-

ing housing environment quality, which can be character-

ised as an objectied method. The reason for developing

this method was the necessity to take action to improve

the housing environment, especially in the context of the

current, low standards of urban planning solutions that it

is often accompanied by. Minimising the distance between

buildings, taking up open green spaces for development,

limiting daylight access in shared urban interiors, etc., are

common phenomena that accompany often visually attrac-

tive residential development.

Furthermore, it should be emphasised that the housing

environment is the area with which one feels connected. It

is therefore important to strive to make it have the highest

possible quality. Making changes to one’s area of residence,

including those for the better, requires a prior diagnosis of

the area, hence the method of its assessment is extremely

important.

The subject is also worth discussing and relevant due to

contemporary eorts to develop a highly universal meth-

od for assessing housing environment quality. This poses

a signicant research problem. Limitations in this area are

further highlighted by changing tendencies in how the hous

ing environment is designed, which often contributes to its

long-lasting transformation, adapted to new social needs.

The research methodology adopted in this study is a re-

sult of numerous analyses carried out by the authors in se-

lected housing areas of small towns in the Subcarpathian

Voivodeship. The analyses were aimed at assessing external

conditions and focused on urban planning solutions, as does

this method of housing environment quality assessment.

The method was based on an on-site visit to assess se-

lected residential areas in the central zones of 38 small

towns in the Subcarpathian region and, before that, in

three other cities. Such a large amount of material allowed

a proper selection of the elements of the housing environ-

ment to be assessed and, at the same time, the formulation

of objective conclusions in the thematic scope discussed

for smaller cities and towns. In addition to the expert as-

sessment of the quality of the housing environment, a total

of 3,300 interviews were conducted in each of the cities

covered by the study. Among other things, respondents

identied the elements of the housing environment that

they considered to be the most important and which have

an impact on its quality. The results corroborate the nd-

ings of urban analyses for the evaluation of spatial solu-

tions that aect the physical health of residents and their

mental and psychological well-being. This sizeable mate-

rial allowed for an extensive and objective outlook on the

problem under investigation.

The available literature on methods for assessing the

quality of the housing environment refers to analysing its

standard in only a limited substantive scope.

One example is the Building for a Healthy Life [1]

system, which assesses issues related to population health

DOI: 10.37190/arc230410

Published in open access. CC BY NC ND license

* ORCID: 0000-0002-3358-3762. Faculty of Architecture, Cra-

cow University of Technology, Poland, e-mail: justyna.kobylarczyk@

pk.edu.pl

** ORCID: 0000-0003-1678-4746. Faculty of Architecture, Cra-

cow University of Technology, Poland.

*** ORCID: 0000-0001-9175-1747. Faculty of Civil Engineering,

Cra cow University of Technology, Poland.

**** ORCID: 0000-0002-6877-3742. Faculty of Environmental

Engineering and Energy, Cracow University of Technology, Poland.

108 Justyna Kobylarczyk, Dominika Kuśnierz-Krupa, Marcin Furtak, Marzena Nowak-Ocłoń

and sustainability more broadly. This method, which is

also a tool for designing friendly places, signies the im-

portance of the natural environment and the accessibility

of public infrastructure, including transport and street ar-

chitecture. It also takes into account the need for mobility,

air quality and biodiversity.

Another method, which is limited to the assessment

of residential development – houses – the Home Quality

Mark [2], utilises three accepted assessment criteria: cost,

well-being and usable oor area.

In turn, the Housing Quality Indicators [3] system fo-

cuses on existing development and is also a design tool

to assess and indicate the potential of existing develop-

ment. The elements it uses to determine the quality of the

housing environment fall into three categories including

location, design, and the ecient use of the layout. It dis-

tinguishes the following factors that can be considered es-

sential to a good housing environment, namely location,

the openness of a space, accessibility, layout size, spatial

layout, access to services and daylight. Low energy con-

sumption, minimising noise pollution, use eciency and

the use of sustainable solutions are also relevant here.

The SEL (Système d’évaluation de logements) hous-

ing evaluation system is a tool that assists in the design

and comparative analysis of residential buildings. It de-

termines their utilitarian value, and considers the location

of the buildings, their qualities and also the attractiveness

of their immediate surroundings. Priority is given here to

usability and added value for residents.

NF Habitat [4] is another assessment method. It is used

to certify houses and ats. Their assessment takes into ac-

count, among other things, health-related conditions, safe-

ty and the control of expenses associated with maintaining

the home through the appropriate choice of thermal and

acoustic insulation.

The assessment method proposed in this study utilises

the Integrated Quality Index (IQI) and is only concerned

with urban planning conditions. It does not take into ac-

count architectural and technological solutions. The focus

on spatial solutions stems from the need to revise current-

ly used urban planning indicators such as the share of bio-

logically vital surface area.

In our opinion, when assessing housing areas, one

should note urban-planning conditions that shape a housing

environment’s quality and thus aect its comfort of use.

It should be noted that certication schemes often

come down solely to the assessment of urban solutions,

although there are also widely used building certication

systems, such as BREEAM (Building Research Estab-

lishment Environmental Assessment Method) and LEED

(Leadership in Energy and Environmental Design) [5].

From the point of real-estate development project plan-

ning onwards, a Life Cycle Assessment (LCA) system is

helpful to analyse the full life cycle of a building [6]. POE

(Post Occupancy Evaluation) is also used for this purpose.

The criteria adopted for this assessment include issues of

individual user needs and the need to implement a retrot-

ting process compliant with sustainability principles.

Crucially, this assessment of urban conditions is site-

specic, and they are characterised by distinct specicities

resulting from, among other things, natural conditions, in-

cluding climate, but also regional and cultural conditions,

as described by Mi-Hyang Lee et al. [7], who presented an

original research method based on AHP (Analytic Hierar-

chy Process). Similarly, the research method presented in

this paper, based on the IQI can be seen as an important

tool to objectively assess spatial conditions. The assess-

ment method proposed is universal, while AHP refers pri-

marily to the Modernized Hanok complex in Korea.

Regardless of site-specicity, there is an increasing fo-

cus on the availability of green spaces and the need to

transform cities that strive to meet public expectations. It

should be highlighted that greenery, including the size of

biologically vital surface areas, as well as water, aect the

microclimate of the surroundings (the housing environ-

ment), including its thermal conditions. Proximity to green

spaces is an important element of sustainable design in line

with the idea of sustainable development and the principles

of green urbanism. These were discussed more extensively

by e.g. Dayi Lai et al. and Steen Lehmann [8], [9], who

noted the need to respect the tenets of the green economy.

Lili Zhang et al. [10] also wrote about the need to design

and organise parks in urban spaces. Among other things,

they pointed out that a park’s outdoor thermal comfort is

an important factor that can attract people to it and encour-

age them to stay. Using eld meteorological monitoring

and surveys, they investigated the outdoor thermal com-

fort of dierent types of landscape spaces in urban parks in

Chengdu, China, in winter and summer.

Analysing numerous issues (including those listed

above, associated with green area access) that either di-

rectly or more indirectly aect thermal comfort and hous-

ing environment quality, gives us a broader perspective on

this problem, which can contribute to its in-depth, objec-

tive analysis. This reason distinguishes the proposed para-

metric method of housing environment quality assessment

based on IQI from other methods.

Contemporary trends in architectural and urban design

are largely based on adapting architectural solutions to

environmental conditions. Among others, proper building

siting, development density of distribution and the geom-

etry of the urban interiors in which buildings are located

are important in this context [11]. The importance of the

compactness of the development and street canyon pa-

rameters were demonstrated by Angelika Chatzidimitriou

and Simos Yannas, among others [12]. These elements are

important for maintaining the thermal comfort of urban in-

teriors, including the quality of the housing environment.

In addition to their academic value, the observations

that form the state of the art may be of relevance to design

and planning practice [13].

In addition, the current state of research indicates that

there have been many recent publications on the housing

environment, its problems and the prospects for its change

in the near future. In contrast, publications on research

methods themselves have been few. The analysis of the

subject matter in question, including the current state of

the art, leads us to believe that the proposed method can

be considered universal since it can be applied in any re-

search area.

Parametric assessment of the quality of the housing environment of selected areas in the small towns in the Subcarpathian Voivodeship 109

The Integrated Quality Index makes it possible to desig-

nate areas in need of re-urbanisation and improvements to

broadly understood infrastructure. When at a low value, it

indicates a necessity to take action to improve housing envi-

ronment quality in a scope dened by the given factor selec-

tion. The lower the IQI value, the greater and more urgent

the need for change, which also makes it possible to dene

an action plan with the designation of priority projects.

Based on an analysis of the state of research on housing

environment assessment methods, it should be noted that

the selection of elements for assessment is always subjec-

tive. We decided on the selection of criteria for the meth-

od proposed after performing numerous urban studies

and sociological surveys. As mentioned, 3,300 interviews

were conducted in which residents themselves identied

the elements and factors they felt were most important for

building the quality of the housing environment.

Given the above information, it is possible to hypoth-

esise that the IQI-based method proposed here allows for

an objectied assessment of the quality of the housing en-

vironment and a comparative analysis of the areas under

investigation. This method can also contribute to improv-

ing the functional and spatial solutions of the selected ar-

eas and to taking desirable and eective practical action

within them by decision-makers with a direct inuence on

the scope of the necessary interventions.

The proposed method can therefore, in addition to its

academic value, also be used eectively in the eld of

spatial planning. In doing so, it should be noted that the

scope of research using the IQI may also include resi-

dential or commercial interiors that are an integral part

of the housing environment, taking into account the rel-

evant assessment factors. It must also be highlighted that

the selection of elements for assessment in the method’s

development is closely linked with society’s pursuit of at-

taining increasingly higher standards. However, in order

for this aspiration to be eective, it is necessary to de-

ne what a high standard is, and identify contemporary

trends and the factors that inuence it. We understand

a high housing environment standard as a housing envi-

ronment that meets requirements concerning having an

urban layout composition that ensures spatial order and

comfortable microclimate conditions, and thus thermal

comfort. In addition, a high-quality housing environment

should be characterised by the aesthetics of functio-spatial

solutions and accessibility to natural areas – water fea-

tures and greenery. In doing so, it is important to identify

the type of greenery, its diversity, size and scale of oc-

currence. This aects the well-being of the area’s users,

the aesthetic qualities of the surroundings, but also their

climatic conditions (thermal comfort, insolation, humid-

ity, wind ow, which is directly relevant to the drive to

minimise energy consumption and the use of renewable

energy sources). Equally important is the selection and

denition of the type of heating, energy, HVAC (Heating,

Ventilation, and Air Conditioning) services that aect the

thermal comfort in a building (mechanical ventilation, air

conditioning). In turn, the proximity to natural elements is

directly linked to an attractive view from the window, in-

teresting development of common spaces, the aforemen-

tioned mesoclimate, and thus also the insolation of urban

interiors and their ventilation potential. The proximity of

services and pleasantly used spaces, including providing

access to essential services such as educational facili-

ties, culture centres, healthcare facilities, sports facilities,

transport services and playgrounds is a separate issue.

A quality housing environment should also provide in-

timacy and peacefulness, security, opportunities for social

interaction in the shaping of the common spaces and op-

portunities for their shared management.

All of these quality-building elements were further des-

ignated with numbers in a survey and included as IQIs.

Method

The assessment of the housing environment and its qual-

ity can be done using a descriptive and parametric method.

Our analysis found that the descriptive approach poses di-

culty in comparing housing environment quality when faced

with diering ratings of the same factors when referenced

to dierent housing areas (cities). In the second case, the

comparison is easier as factor ratings are done using a point-

based scale. In addition, we are used to numerical ratings

because they are concrete. However, these ratings apply

separately to each factor. This is where the diculty in gen-

eral assessments stems from. In order to make this possible,

we introduced the IQI into our proposed research method,

as it combines ratings of all factors by residents themselves

and, most importantly, the weights of these ratings.

Our proposed IQI-based method can be implemented in

expert eld analyses (inspections) and sociological stud-

ies, as their substantial enhancement. It should be noted

that the use of several research methods simultaneously is

eective in formulating objective conclusions.

This paper uses the results of an urban analysis and

a sociological study, which conrmed the ndings of eld

research and present the opinions of respondents on their

areas of residence, and allowed for procuring results on

the weights of specic factors for the assessment.

For the interviews, we used forms with a set of 28 el-

ements, selected subjectively, but justied by the current

state of the art and research ndings. The set was compiled

based on earlier studies by Justyna Kobylarczyk [14]. The

research described in these studies was conducted in small

towns of the Subcarpathian Voivodeship [15] as well as

in other publications on the subject. Among the elements

considered in the study, all those listed below and marked

with a number were taken into account. They were charac-

terised in the introduction of the paper when dening the

high quality standard of the housing environment. These

elements are: 1 – urban layout composition, 2 – aesthetics

of functio-spatial solutions, 3 – type, variety and amount

of greenery, 4 – attractive view from the window, 5 – site

development of common spaces, 6 – mesoclimate, 7 – inso-

lation of urban interiors, 8 – ventilation hygiene, 9 – access

to essential services, 10 – access to educational facilities,

11 – access to culture centres, 12 – access to healthcare cen-

tres and pharmacies, 13 – access to sports centres, 14 – ac-

cess to transport services, 15 – availability of playgrounds,

16 – use programme of playgrounds, 17 – proximity to

110 Justyna Kobylarczyk, Dominika Kuśnierz-Krupa, Marcin Furtak, Marzena Nowak-Ocłoń

green areas, 18 – utility programme of green areas, 19 – in-

timacy and peacefulness, 20 – security, 21 – proximity to

water features, 22 – access to and size of the courtyard,

23 – proximity to integrative spaces, 24 – proximity to nat-

ural elements, 25 – view from the window featuring natural

elements, 26 – pro ximity to monuments, 27 – possibility of

social interaction in shaping common spaces, 28 – potential

for joint management of the housing environment.

The attribution of signicance (weight) to individual

factors is very important and should therefore be as ob-

jective as possible. As the territorial scope of the survey

covered 38 cities and the sample size itself was large

(3,300 questionnaires), the survey results can be consid-

ered representative.

Sucient sample size is crucial for obtaining objective

results. Obviously, the larger the respondent count, the

more accurate the assessment. Based on the results of the

fundamental studies reported in papers [14], [15], it can be

concluded that with ten and more responses, the average

value does not change signicantly. Thus, the number of

10 samples was considered a minimum in the study in or-

der for the average values to be suciently precise.

The paper presents calculations using the IQI developed

by the authors for selected cities (Dukla, Iwonicz-Zdrój,

Ry manów, Boguchwała, Dynów, Tyczyn, Kolbuszowa,

Lu ba czów, Ustrzyki Dolne). The IQI was determined on

the basis of algebraic formulas.

The proposed method consists of two parts. The rst

relates to the formulation of general formulas used to cal-

culate the value of the IQI, and the second to the acquisi-

tion of data to determine its specic value.

Based on the results of the survey, each factor was

assigned a signicance determined by a rating score on

a scale of 1–5, denoted as a

The sum of the scores for all factors is equal:

Σa

= A

where:

A – sum of all factors,

a – factor rating,

i – factor number.

Hence, the weight of an individual factor w

is:

= a

/ A = a

Σa

where a

stands for factor i. Factor weight thus calculated

is expressed in dimensionless numbers. If we multiply it

by 100, we get the weight in percentage. Denoting it as w

we will obtain:

= 100 w

The following conditions must also be met:

Σw

= 1,00

Σw

= 100%

For practical reasons, it is better to use percentage

weights.

The ratings given by respondents to the individual m

factors are needed to calculate the IQI value. Thus, the IQI

value will be:

ZWJ = Σ

It is proposed to rate the individual factors on the fol-

lowing scale: 1 – very poor, 2 – poor, 3 – acceptable, 4– good,

5 – very good.

The “0” has been omitted from the rating scale and it

starts at 1. This is because none of the indicators examined

received a weight of 0. This means that, according to re-

spondents, all factors are important, albeit to varying de-

grees. The average values from the results are summarised

in Figure 1. The numerical values given can be directly con-

sidered as w

percentage weights, and if divided by 100, we

obtain weights expressed in dimensionless numbers.

Fig. 1. Weight of factors

expressed as percentages

(elaborated by J. Kobylarczyk)

Il. 1. Waga ocenianych

czynników wyrażona

w procentach

(oprac. J. Kobylarczyk)

Parametric assessment of the quality of the housing environment of selected areas in the small towns in the Subcarpathian Voivodeship 111

The proposed parametric method, due to its numerical

scale that relates to the individual factors, allows com-

paring the results of a varied assessment within the same

factors assessed in dierent housing areas. The calcu-

lations presented here can be used in any housing area.

This means that the method can be considered universal,

and that it has applicative value in addition to academic

value, and can be useful in determining the direction of

development and necessary interventions in specic ur-

ban areas.

Nevertheless, specic cities located in the Subcarpa-

thian Voivodeship in its various regions were selected for

analysis: Dukla, Iwonicz-Zdrój, Rymanów (towns locat-

ed in the southern part of the voivodeship), Bogu chwa-

ła, Dynów, Ty czyn (towns located in the central part of

the voivodeship), Kolbuszowa, Lubaczów and Ustrzyki

Dolne (county towns located in dierent areas of the voi-

vodeship). These are towns with populations lower than

30 thousand. Considering the size in terms of population,

they can be considered small.

Factor no.

Area analysed

values

A B C A B C

1 3.034 3.059 3.333 0.0317 0.096178 0.09697 0.105656

2 3.484 3.269 3.793 0.0376 0.130998 0.122914 0.142617

3 3.969 3.827 3.879 0.0407 0.161538 0.155759 0.157875

4 4.097 3.857 3.719 0.0429 0.175761 0.165465 0.159545

5 3.483 3.125 3.492 0.0350 0.121905 0.109375 0.12222

6 2.962 3.417 3.362 0.0362 0.107224 0.123695 0.121704

7 3 3.306 3.411 0.0354 0.1062 0.117032 0.120749

8 3.714 3.7 3.857 0.0408 0.151531 0.15096 0.157366

9 3.793 3.558 4.000 0.0398 0.150961 0.141608 0.1592

10 3.452 3.314 3.828 0.0389 0.134283 0.128915 0.148909

11 2.968 3.176 3.696 0.0363 0.107738 0.115289 0.134165

12 3.935 3.654 4.103 0.0419 0.164877 0.153103 0.171916

13 2.968 2.981 3.424 0.0305 0.090524 0.090921 0.104432

14 3.621 3.269 3.78 0.0394 0.142667 0.128799 0.148932

15 2.484 1.961 3.203 0.0310 0.077004 0.060791 0.099293

16 2.2 1.922 3.119 0.0287 0.06314 0.055161 0.089515

17 3.875 3.49 3.831 0.0399 0.154613 0.139251 0.152857

18 3.065 2.94 3.421 0.0313 0.095935 0.092022 0.107077

19 3.968 3.49 4.102 0.0404 0.160307 0.140996 0.165721

20 3.656 3.519 4.068 0.0414 0.151358 0.145687 0.168415

21 2.161 1.686 2.864 0.0244 0.052728 0.041138 0.069882

22 3.871 3.077 3.678 0.0395 0.152905 0.121542 0.145281

23 2.679 2.918 3.31 0.0324 0.0868 0.094543 0.107244

24 3.667 3.49 3.78 0.0400 0.14668 0.1396 0.1512

25 3.552 3.827 3.759 0.0414 0.147053 0.158438 0.155623

26 2.931 3.045 3.069 0.0297 0.087051 0.090437 0.091149

27 2.517 2.077 2.776 0.0268 0.067456 0.055664 0.074397

28 2.448 2.019 2.724 0.0260 0.063648 0.052494 0.070824

Σ 91.554 81.147 99.013 1.0000 3.352063 3.188569 3.603314

Table 1. Results of the study for towns from group I (A – Dukla, B – Iwonicz-Zdrój, C – Rymanów) (elaborated by J. Kobylarczyk)

Tabela 1. Wyniki badań dla miast z grupy I (A – Dukla, B – Iwonicz-Zdrój, C – Rymanów) (oprac. J. Kobylarczyk)

112 Justyna Kobylarczyk, Dominika Kuśnierz-Krupa, Marcin Furtak, Marzena Nowak-Ocłoń

Results

The paper presents only those research results that are

most relevant to the issue addressed.

Three groups of cities were considered when analysing

the weights of all factors. Three cities were included in

each group. The results of the analysis are given in Ta-

bles 1–3.

Group I includes towns in Krosno County, located in the

southern part of the province. These are: Dukla, Iwo nicz-

Zdrój and Rymanów. Group II includes towns in Rzeszów

County, located in the central part of the voivodeship.

These are: Boguchwała, Dynów and Tyczyn. In Group III,

county towns from dierent areas of the voivodeship were

included. These are: Kolbuszowa, Lubaczów and Ustrzy-

ki Dolne.

The factor number is presented in the Method section

of the paper, as are the m

values.

Based on our results, as summarised in Tables 1–3, it

can be concluded that the IQI values (IQI = Σ

) for the

dierent cities vary. This is due to the dierent ratings of

the individual factors in the cities selected for comparison

Table 2. Results of the study for towns from group II (A – Boguchwała, B – Dynów, C – Tyczyn) (elaborated by J. Kobylarczyk)

Tabela 2. Wyniki badań dla miast z grupy II (A – Boguchwała, B – Dynów, C – Tyczyn) (oprac. J. Kobylarczyk)

Factor no.

Area analysed

values

A B C A B C

1 3.52 2.679 2.931 0.0317 0.111584 0.084924 0.092913

2 3.778 3.413 3.462 0.0376 0.142053 0.128329 0.130171

3 3.593 3.59 3.591 0.0407 0.146235 0.146113 0.146154

4 3.519 3.873 3.844 0.0429 0.150965 0.166152 0.164908

5 3.24 3.163 3.063 0.035 0.1134 0.110705 0.107205

6 3.24 3.057 3.106 0.0362 0.117288 0.110663 0.112437

7 3.28 3.241 3.213 0.0354 0.116112 0.114731 0.11374

8 3.577 3.389 3.317 0.0408 0.145942 0.138271 0.135334

9 4.038 3.531 3.424 0.0398 0.160712 0.140534 0.136275

10 3.808 3.102 3.369 0.0389 0.148131 0.120668 0.131054

11 3.37 2.752 3.197 0.0363 0.122331 0.099898 0.116051

12 3.852 3.37 3.439 0.0419 0.161399 0.141203 0.144094

13 3.407 2.49 3.015 0.0305 0.103914 0.075945 0.091958

14 3.889 3.101 3.554 0.0394 0.153227 0.122179 0.140028

15 3.222 1.878 2.015 0.031 0.099882 0.058218 0.062465

16 3.148 1.687 1.776 0.0287 0.090348 0.048417 0.050971

17 3.667 3.337 3.143 0.0399 0.146313 0.133146 0.125406

18 3.16 2.538 2.619 0.0313 0.098908 0.079439 0.081975

19 4.037 3.73 3.672 0.0404 0.163095 0.150692 0.148349

20 4 3.69 3.545 0.0414 0.1656 0.152766 0.146763

21 3.407 2.044 1.862 0.0244 0.083131 0.049874 0.045433

22 3.556 3.598 3.203 0.0395 0.140462 0.142121 0.126519

23 3.12 2.841 2.672 0.0324 0.101088 0.092048 0.086573

24 3.269 3.596 3.439 0.04 0.13076 0.14384 0.13756

25 3.269 3.59 3.578 0.0414 0.135337 0.148626 0.148129

26 2.778 2.194 2.297 0.0297 0.082507 0.065162 0.068221

27 2.741 2.196 2.016 0.0268 0.073459 0.058853 0.054029

28 2.538 2.226 2 0.026 0.065988 0.057876 0.052

Σ 96.063 83.89 84.362 1.0000 3.472 3.0814 3.0967

Parametric assessment of the quality of the housing environment of selected areas in the small towns in the Subcarpathian Voivodeship 113

and, in addition, to the use of dierent weights for each

factor. The lowest average IQI values were obtained in

cities from Group II, i.e. from the county whose capital

has the largest population (Rzeszów). This, however, may

not be the rule.

The results of the analysis show that there are greater

dierences in the values of the IQI between cities in the

same county than in cities located in dierent counties.

The average IQI value for Group I cities was 3.38, while

for Group II cities it was 3.22 The same average IQI val-

ue was obtained for the county towns in Group III as for

those in Group I, i.e. 3.38. This is, of course, a coinci-

dence, as ratings of the various factors varied. It should be

noted that the dierences in IQI values are not signicant.

This applies to the cities in groups I and II. Only the dif-

ference in the average IQI value for Group III cities was

smaller than for the cities in groups I and II. There was no

signicant correlation between the mean value of the IQI

and the size of the city (population count) and its location.

The status of the city (county town or not) also appeared

to be of no signicance.

Factor no.

Area analysed

values

A B C A B C

1 2.985 3.073 3.155 0.0317 0.094625 0.0974141 0.100014

2 3.564 3.406 3.54 0.0376 0.134006 0.1280656 0.133104

3 3.755 3.516 3.854 0.0407 0.152829 0.1431012 0.156858

4 3.903 3.669 3.755 0.0429 0.167439 0.1574001 0.16109

5 3.336 3.258 3.376 0.035 0.11676 0.11403 0.11816

6 3.23 3.041 3.286 0.0362 0.116926 0.1100842 0.118953

7 3.222 3.068 3.198 0.0354 0.114059 0.1086072 0.113209

8 3.515 3.596 3.86 0.0408 0.143412 0.1467168 0.157488

9 3.845 3.865 3.71 0.0398 0.153031 0.153827 0.147658

10 3.503 3.676 3.554 0.0389 0.136267 0.1429964 0.138251

11 3.389 3.623 3.307 0.0363 0.123021 0.1315149 0.120044

12 3.839 3.994 3.673 0.0419 0.160854 0.1673486 0.153899

13 3.329 3.274 3.208 0.0305 0.101535 0.099857 0.097844

14 3.571 3.574 3.19 0.0394 0.140697 0.1408156 0.125686

15 3.121 2.968 3.11 0.031 0.096751 0.092008 0.09641

16 2.856 2.779 2.9 0.0287 0.081967 0.0797573 0.08323

17 3.695 3.256 3.792 0.0399 0.147431 0.1299144 0.151301

18 3.18 3.032 3.204 0.0313 0.099534 0.0949016 0.100285

19 3.874 3.547 3.51 0.0404 0.15651 0.1432988 0.141804

20 3.879 3.859 3.899 0.0414 0.160591 0.1597626 0.161419

21 2.626 1.974 3.248 0.0244 0.064074 0.0481656 0.079251

22 3.683 3.289 3.24 0.0395 0.145479 0.1299155 0.12798

23 3.218 3.034 2.929 0.0324 0.104263 0.0983016 0.0949

24 3.674 3.404 3.663 0.04 0.14696 0.13616 0.14652

25 3.761 3.441 3.737 0.0414 0.155705 0.1424574 0.154712

26 2.589 2.429 2.693 0.0297 0.076893 0.0721413 0.079982

27 2.878 2.359 2.31 0.0268 0.07713 0.0632212 0.061908

28 3.058 2.44 2.33 0.026 0.079508 0.06344 0.06058

Σ 95.078 91.074 92.832 1.0000 3.448257 3.295225 3.38254

Table 3. Results of the study for towns from group III (A – Kolbuszowa, B – Lubaczów, C – Ustrzyki Dolne) (elaborated by J. Kobylarczyk)

Tabela 3. Wyniki badań dla miast z grupy III (A – Kolbuszowa, B – Lubaczów, C – Ustrzyki Dolne) (oprac. J. Kobylarczyk)

114 Justyna Kobylarczyk, Dominika Kuśnierz-Krupa, Marcin Furtak, Marzena Nowak-Ocłoń

Discussion

Assessing a given housing environment using inspec-

tions and environmental studies facilitates its spatio-func-

tional diagnosis. When performing such an assessment,

one can evaluate factors that shape the space under anal-

ysis and specify problem phenomena and identify place-

based potential.

The research method proposed must be improved, as it

is subjective, for instance due to the subjective selection

of factors to be assessed.

In addition, the factors to be rated are measurable (quan-

tiable) and non-measurable (non-quantiable). For meas-

urable factors, it is possible to rate them unequivocally,

precisely and indisputably. In the case of non-quantiable

factors, their rating can vary. This is because it is dicult

to measure the aesthetics of a space, the sense of intimacy

and peacefulness, etc. This results in a heterogeneous rat-

ing, which is chiey qualitative and not quantitative [14].

The diversity of residents’ needs and ambitions, the

goals they want to pursue in their housing environment and

their preferred lifestyle, including their mode of communi-

cation, their leisure activities, their current living conditions

and their requirements for the future are also a problem in

achieving a homogeneous assessment. They can change,

just as the selection of factors for rating can change. This is

due to progress, changing trends and emerging issues.

It should be noted that the ratings given by the respond-

ents in the surveys were often dierent, although they

concerned the same area, the same elements and factors.

The needs of the residents are also dierent, as a result of

the housing conditions they currently have, the wealth of

the people doing the rating, and their education. The life-

style they lead is also signicant. It is most likely that per-

sons whose current housing conditions are high standard,

allowing them to engage in their preferred lifestyle, will

have higher demands. With this in mind, it is important in

such studies to ensure that the sample is representative.

It should be added that since present-day urban spac-

es are characterised, among other things, by an increase

in integration, diversity and cohesion while maintaining

harmony in every area, it is extremely important to select

the factors to be taken into account in spatial planning on

the basis of an integrated system [16]. For example, by

increasing the area of green space, we improve the mi-

croclimatic conditions and also provide opportunities for

physical activity to residents.

Conclusions

This paper presents a new method for the comprehen-

sive assessment of the quality of the housing environment.

To this end, an Integrated Quality Index was proposed and

dened, which takes into account all the relevant quality

determinants. Its value depends on the individual rating of

each factor and the weight assigned to it. As an innovative

research tool, the proposed method brings new values to

research, but can also be useful in design and planning

practice.

The calculation of the IQI value allows objective con-

clusions to be formulated regarding the assessment of the

quality of the residential environment. The calculations

also enable comparative analysis of areas so as to delin-

eate sites that are decient in terms of their housing en-

vironments, and to make proper decisions on necessary

interventions. The proposed research method is therefore

important not only for its academic value, but can also

be applied in practice, in determining the necessary and

priority corrective actions.

The implications of the research ndings may be par-

ticularly helpful for decision-making bodies in setting

courses of action for the development and improvement

of the housing environment. Specic indicator values can

denote courses of action. A low value of a given factor’s

rating signals the need to change site development, which

is specically a task for real-estate developers, city coun-

cils and resident councils.

Determining the numerical values of weights assigned

to each factor is a very important element of the proposed

method. These values were determined on the basis of the

results of an original study carried out in 38 cities in the

Subcarpathian Voivodeship. A total of nearly 3,300 re-

spondents took part in this survey. Thus, the study can be

regarded as authoritative and the weight values as reliable.

The weights attributed to each factor were shown to

inuence the nal assessment of housing environment

quality. In the cases analysed, the geographical location

of a city and its size (expressed in terms of population),

as well as its status (county capital or not), were found to

have no signicant impact. This further indicates the ob-

jectivity of the assessment of housing environment quality

as based on the IQI.

Translated by

Krzysztof Barnaś

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Abstract

Parametric assessment of the quality of the housing environment

of selected areas in the small towns

in the Subcarpathian Voivodeship using the integrated quality indicator

This paper presents a method of assessing housing environment quality using the Integrated Quality Index (IQI) dened and tested by the authors.

This method complements the previously used descriptive and/or parametric methods. Both methods are not fully eective in a comparative diagnosis

of areas and in determining which of them can provide higher quality. This is due, among other things, to the dierent weighting of the individual

factors that are rated and which make up the nal (resultant) assessment.

The aim of the study was to demonstrate that by using a single comparative indicator, dened by the authors as the IQI, it is possible to obtain an

objectied assessment that takes into account parametric ratings of all the factors analysed with appropriate weights. This removes the ambiguity in

the comparison of quality ratings of dierent housing areas. A higher IQI value means a higher quality housing environment. This indicator makes

it possible to assess the quality of the human housing environment to a greater extent than with a descriptive and parametric assessment separate for

each factor. For this reason, in addition to its academic value, the method presented in this paper also has a practical value – it facilitates unambiguous

conclusions and, consequently, the pursuit of improved housing conditions, which has an undeniable impact on further research into the topic under

discussion.

Key words: housing environment quality, parametric assessment, integrated quality indicator, research method

Streszczenie

Parametryczna ocena jakości środowiska mieszkaniowego

wybranych obszarów zamieszkania w małych miastach województwa podkarpackiego

z wykorzystaniem zintegrowanego wskaźnika jakości

W artykule przedstawiono problematykę związaną z metodą oceny jakości środowiska zamieszkania wykorzystującą zdeniowany i sprawdzony

przez autorów zintegrowany wskaźnik jakości (ZWJ). Metoda ta stanowi uzupełnienie dotychczas stosowanych metod – opisowej lub/i parametrycz-

nej. Obydwie metody nie są w pełni skuteczne w diagnozie porównawczej obszarów ze wskazaniem, który z nich zapewnia wyższą jakość. Wynika

to między innymi z różnej wagi poszczególnych czynników podlegających ocenie, a składających się na jedną ocenę końcową (wynikową).

Celem pracy jest wykazanie, że przy wykorzystaniu jednego wskaźnika porównawczego, zdeniowanego przez autorów jako ZWJ, możliwe jest

uzyskanie zobiektywizowanej oceny uwzględniającej oceny parametryczne wszystkich analizowanych czynników z odpowiednimi wagami. Dzięki

temu porównanie wyników oceny jakości różnych obszarów mieszkaniowych jest jednoznaczne. Większa wartość ZWJ oznacza wyższą jakość

środowiska zamieszkania. Wskaźnik ten pozwala w większym stopniu ocenić jakość środowiska zamieszkania człowieka niż w przypadku oceny

opisowej i oceny parametrycznej oddzielnej dla każdego czynnika. Z tego powodu przedstawiona w pracy metoda poza wartością naukową ma też

wartość praktyczną – ułatwia jednoznaczne wnioskowanie i w konsekwencji dążenie do poprawy warunków zamieszkania, co ma niepodważalny

wpływ na dalsze badania w zakresie omawianej tematyki.

Słowa kluczowe: jakość środowiska mieszkaniowego, ocena parametryczna, zintegrowany wskaźnik jakości, metoda badawcza