Improvement of Environmental Quality and Satisfaction of Living in New Neighbourhoods by Priority of Actions on the Basis of Residents’ Views (Case Study, Kashan)

Introduction
Historic cities and neighbourhoods in Iran couldn’t adjust themselves to quick changes of the recent decades and
have lost their quality in many aspects. Regardless of different cultural, economic and social conditions, new
neighbourhoods have been formed next to old areas of the cities. Although these new areas welcom ed new
functions, they couldn’t provide suitable environments for their residents. This paper intends to promote the
environmental quality and people satisfaction of living in neighborhood by recognizing and prioritizing the main
environmental quality factors which have effect on satisfaction of living in neighborhood. Ghotb-E-Ravandi
neighborhood where is developed in the last few decades was selected for this study. This neighborhood is
located adjacent to historical fabric of Kashan City, in center of Iran.
Materials and Methods
The research method is an evaluation of residents. To determine the required samples for the evaluation,
Cochran technique was applied. The indicators were measured by questionnaire was distributed among 164
residents or 321 housing units in Ghotb-E-Ravandi Neighbourhood. The actual samples were selected by the
systematic sampling method by mapping the housing units. Data obtained through the residents interviews were
entered into a microcomputer and then analyzed by using SPSS. Each indicator was measured by at least two
questions with five different answer levels (very high, high, moderate, low, and very low). Finally arithmetic
mean of each category of questions was obtainded and scores of each indicator was applied in factor analysis
technique.
Results and Discussion
The indicators are including physical qualities, social relationships, accessibility, place identity, vitality, safety,
security and urban facilities. These indicators, mostly qualitative in nature, were then divided into several subindicators,
based on area, city, and social and cultural contexts. To do this, the 32 indicators were selected from
other studies and literature reviews. Because of the large number of indicators, multiple linear regression
analysis cannot run in one step. Therefore, the 32 indicators were summarized in 6 factors by using factor
analysis technique (Table 1). To find the relation between residential environment quality and satisfaction of
living in neighborhood, multiple linear regression analyses were used.
In this analysis, dependent variable is satisfaction from living in new neighbourhoods and independent
variables are the 6 factors which are extracted from factor analysis technique. By using multiple linear regression
in SPSS, results of the study is summarized in 6 different models. In the models, the sixth one includes more
variable and higher adjusted R square value (75.1%) compared with others. Such figure covers 75.1% of changes
of the satisfaction from living in neighbourhood that includes highest percentage among models. Besides, the
Std. errors of the estimate are less than other models. Confidence interval in all factors is 100% and DW1
statistical test is 2.3 which are appropriate2 for this model (Table 2).
Table 1. Extracted Environmental quality factors from factor analysis technique
correlate
with factor
variables
correlate
with factor
Factor Variables
Permeability 0.903 Quality of houses 0.637
Quality of play grounds 0.867 easy and safe walking and biking 0.617
Access to green space 0.906 Sense of safety and security 0.620
Quality of green spaces 0.809 Design based on local climate 0.497
Recognition of landmarks in 0.751
neighborhood
Vacant and abandoned areas 0.463
F1: quality and
existence of
public spaces
Residents relationship 0.566 interaction with city managers 0.507
social interaction and participation in 0.677 residents’ responsibility 0.797
public activities
Sense of belonging and attachment to 0.714 A place that gives dignity 0.678
neighborhood
well-connected with important 0.711
parts of the city
Evokes memories in places 0.582
F2:
Identification
and social
relationship
Neighborhood center and sense of 0.583 Mixed use 0.583
central location
Aesthetic aspects of the neighborhood 0.712 Access to daily services 0.595
Safety and security traveling at 0.507
night
adequate open spaces between buildings 0.538
F3: Vitality in
neighbourhood
spaces
Absence of environmental pollution 0.730 Absence of noise pollution 0.808
Easy access to downtown 0.501
F4: Absence of
environmental
pollution
F5: Legibility Tendency to live in neighborhood 0.896 Legibility 0.896
No automobile dependence 0.759 Access to public transport 0.560
Access to urban facilities 0.671
F6: Access to
urban facilities
Note. Only structural coefficients above 0.40 are reported.
Table 2. Comparison of 6 regression models to show the relations between environmental quality and satisfaction of
living in neighbourhood
Model R R Square Adjusted R Square Std. Error of the
Estimate Durbin-Watson
1 .658a .433 .429 .661
2 .788b .621 .617 .541
3 .820c .673 .667 .504
4 .847d .718 .711 .470
5 .864e .746 .738 .448
6 .872f .760 .751 .436 2.034
All variables are positive and at the same direction that is shown by increasing in each factor value,
satisfaction from living in neighbourhood will be increased. Beta coefficient indicates the importance of factors
in changing the satisfaction from living in neighbourhood. Thus, if Beta coefficient of one variable is more than
another, this may show that the variable has more impact on the residents’ judgement. Regression formula
includes main phenomenon (Satisfaction from living in neighbourhood) as dependant variable. The factors as
independent variable are as follow:
Y= 0.166X1 + 0.658X2 + 0.435X3 + 0.227X4 + 0.212X5 + 0.120X6
Y: Satisfaction from living in new neighbourhood
X1: Quality and existence of public spaces
X2: Identification and social relationship
X3: Vitality in neighbourhood spaces
X4: Absence of environmental pollution
X5: Legibility
X6: Access to urban facilities
Identification and social relationship and Vitality in neighbourhood spaces have the most impact, in order, on
the satisfaction from living in new neighbourhoods.
Conclusions
Correlation of 75.1 percent between dependent and independent variables shows the impact of environmental
quality on satisfaction from living in neighbourhood. In the same way 75.1% of changes in dependent variable
could be explained through independent environmental qualities variables. Therefore, environmental quality has
direct relationship with satisfaction of living in neighbourhood.
For prioritization of indicators, Beta quotient which shows the proportion of each factor on the satisfaction
was used. Then, by multiplying the Beta quotient by the proportion of each indicator in their factor, the impact of
each indicator was recognized in the satisfaction. In the next step, by multiplying this amount by inverted
average of indicator grade, the arrangement of priority of indicators for promotion of satisfaction by living in
neighbourhood can be achieved. At the end, for promotion of the satisfaction, some solutions was recommended.
The main physical indicators that should be considered to promote the satisfaction are including
neighbourhood that is well-connected with important parts of the city, aesthetic aspects of the neighbourhood,
mixed use, neighbourhood center and sense of central location. The main social indicators are residents’
responsibility, social interaction and participation in public activities, and interaction with city managers.