Does Relative Accessibility to Service Facilities Impact
Residents’ Satisfaction? Socio-Spatial Analysis to Determine
Deprivation and Location Attachment.
Abu-Baker Rafat KHAN*1, Tomohiko YOSHIDA*2
Abstract: Access to urban facilities from residential locations has become a hot topic. Developing
countries such as Pakistan have built housing schemes on a large scale for low-income people atlocations with low proximity to service facilities. Empirical studies about the access capacity ofurbanites to service facilities are also few in number. Taking Rawalpindi-Islamabad Metropolitan Area
(RIMA), this study compares the spatial access to five service facilities between city core, mid-urban
and suburban residents by measuring the distance from the residential parcel to each facility. A totalof 435 samples were collected from nine study sites across RIMA.
Both spatial accessibility analysis and statistical analysis of household access satisfaction were
employed in this study. Spatial analysis showed significant discrepancies in access to low-order andhigh-order service facilities across RIMA. The household survey from nine study sites recorded accesssatisfaction to service facilities, degree of location attachment, satisfaction with the built environment,
and the desire to live near a Bus Rapid Transport system BRT. The findings concluded that theprovision of necessary service facilities should be considered when planning to establish affordable
housing for low-income people.
Keywords: Accessibility, deprivation, Rawalpindi-Islamabad, service facilities, spatial pattern.

(1) Introduction
The Department of Economic and Social Affairs of the United Nations published “World Urbanization
Prospects 2019,” which detailed the rapid urbanization amongst the less and least developing nations
over the past three decades (UN, 2021). Cities around the globe are now competing to provide enoughresources, such as services, facilities, and infrastructure, to enhance their residents’ quality of life (Junget al., 2015). Zeng et al. (2019) argued that affordable housing for disadvantaged groups is essential
as it is a fundamental element of the global housing development systems. For instance, Ibem (2013)stated that providing clean water, sanitation, electricity, and social infrastructure is key to building ahealthy human settlement with an appropriate living environment. Such infrastructure development__________*1 Doctoral student, Graduate School of Policy Sciences, Ritsumeikan University*2 Professor, College of Policy Sciences, Ritsumeikan University
E-mail:*1 ps0205hv@ed.ritsumei.ac.jp*2 tyoshida@sps.ritsumei.ac.jp
Received on November 26, 2021, accepted after peer reviews on April 6, 2022; published online: April 8, 2022.
©Asia-Japan Research Institute of Ritsumeikan University:
Asia-Japan Research Academic Bulletin, 2022
ONLINE ISSN 2435-306X, Vol.3, 13

1

Asia-Japan Research Academic Bulletin Volume 3, 13. April 2022

should meet residents’ demands to foster citizens’ connections to the services and the overall
community. However, for these large-scale developments to succeed, a guaranteed, large number ofregular users is critical. Mulley and Moutou (2015) cautioned that large-scale investments fordeveloping service facilities sometimes fail to achieve their goals because such facilities cannot findregular users.
City planners traditionally locate affordable housing in the urban fringes, which can cause
various social issues such as isolated low-income neighborhoods and poor access to service facilities(Woo and Kim, 2016). Local developers often fail to ensure better access to service facilities whenestablishing affordable housing, as seen in China (Ma et al., 2018; Yang et al., 2014), Chile (Martinez
et al., 2018), Nigeria (Ibem, 2013), and United States (Woo and Kim, 2016). Though several studies
spatially analyzed poor access to service facilities around affordable housing locations, they havetargeted only one facility, such as health, food, or recreational facilities, in one case study. Therefore,
a substantial examination of the access capacity to several local service facilities to identify the effectof accessibility deprivation on the quality of life demands extensive exploration. Also, it is essential toidentify the target population living in different geographical locations. Zeng et al. (2019) examined
the accessibility deprivation amongst Affordable Housing Communities in Nanjing, China, using
spatial and statistical analyses. Another study focused on household surveys in social housing units(Norris and Hearne, 2016). To date, however, no study targets the residential areas near the city coreand mid-urban and suburban regions to understand the accessibility deprivation in various
geographical locations. Thus, this study takes the case of the Rawalpindi-Islamabad Metropolitan Area
(RIMA), which fills the gap by spatially analyzing the city-wide accessibility to multiple service
facilities and statistically comparing the access satisfaction of mixed-income groups.
Besides developing affordable housing projects for disadvantaged groups, city planners facedifficulties in increasing service facility usage. Failure to upgrade the old city technologies might cause
complications in implementing the infrastructure of citizens’ choice (Angelidou, 2014). This hindrance
could be due to residents who might consider accessing services like public transportation (PT) as
unsafe, inconvenient, and time-consuming (Mulley and Moutou, 2015), the cities’ sprawl associatedwith low-density neighborhoods might cause low or no access to essential service facilities, leading tolong travel time and shifting to private vehicles (Mattingly and Morrissey, 2014). Therefore, Mulleyand Moutou (2015) insisted that local city planners regularly encourage residents to utilize service
facilities. This regular use of the neighborhood facilities can ensure attachment to the community,
resulting in a good long-term relationship because residents care about their current location and haveestablished a close bond with the environment surrounding their residence (Casakin et al., 2015).
Though existing studies have attempted to understand the degree of city attachment amongst residents
empirically, their results are usually based on sociological and psychological models that neglect theconcept of city and regional policy processing. To optimally increase service facility usage, it isessential to analyze household preferences, household dynamics, and degree of location attachment.
However, previous service management studies usually focused on the performance and quality of theurban facilities, ignoring the residents’ attitudes towards access satisfaction and travel behavior.
This study is conducted in response to the high demand for affordable housing units andassociated service facilities to meet the needs of disadvantaged groups. The latest publicly accessible
Pakistan housing policy which was released in 2001 excluded indicators such as services facilities
2

Does Relative Accessibility to Service Facilities Impact Residents’ Satisfaction? (KHAN, YOSHIDA)

associated with the locations of affordable housing projects and residents’ preferences. Pakistan is the
only country among South Asian countries that faces the highest urbanization, with an annual growthrate of 2.7% in the urban population. Pakistan's population density rose from 48.7 pp/sqkm in 1950 to
286.5 in 2020 (UN, 2019). Even with this fast growth rate, the housing development is around 0.15
million units against 0.35 million demanded housing units in urban areas (Hasan and Arif, 2018). Thissignificant shortage is mainly because of inappropriate housing policies, finances, and planning,
resulting in inaccessibility to the urban facilities and giving birth to slums and sprawls.
Additionally, the quality of PT is considered inadequate in RIMA, comprising 95% of paratransit
service, i.e., 12-seater pickup wagons and 18-seater Hiace minivans, operating irregularly on limitedroutes. There is no rail mass transit system in RIMA, but there is a fully functioning single corridor ofbus rapid transit (BRT) service launched in 2015 in a dense mixed land, having one end in the
Rawalpindi commercial area and the other in Islamabad public offices and Pakistan Secretariat. High
low-income levels in RIMA have also caused lack of PT affordability, which is a major problem (Adeel
et al., 2016)
The paper examines the degree of residents’ location attachment and satisfaction with the built
environment around the residence. Statistical models are employed to explore the association ofhousehold dynamics with service facilities access satisfaction and the degree of location attachment.
It highlights the association of service facilities with residential areas at different geographicallocations, focusing on low-income people to determine relative accessibility deprivation. The main
findings can expand the literature on accessibility deprivation in urban areas.
The remaining paper is organized as follows: Part 2 reviews the concepts of accessibility,
deprivation, and location attachment. Part 3 presents the research area, data collection, and analytical
approach. Part 4 provides the detailed findings of the city-wide accessibility score towards service
facilities, residents’ relative access satisfaction, and overall location attachment. Policy
recommendations are given in Part 5, and Part 6 concludes the paper.

2. Accessibility, Deprivation, and Location Attachment(1) Accessibility
Accessibility or the attempt to define accessibility began several decades ago when different
perspectives were established, yet no concrete definition has been put forward. Cowan (2005) statedthat accessibility eases neighborhood residents’ access to services, goods, places, and otherinfrastructure in terms of urbanism. The UN Sustainable Development Goals (SDGs) designated“accessibility” to PT as a development indicator and defined it as convenient access to PT for a certain
proportion of the population (UN, 2021). Overall, these definitions indicate that accessibility showsthe extent to which urbanites in a small city or a large metropolitan area can access services andfacilities when made available.
Accessibility to particular urban facilities has become a measuring tool to assess the quality of
housing units (Olawuni et al., 2007), residents’ livelihood (Apparicio et al., 2008; Ibem, 2012), andservice and facilities equitable distribution (Maroko et al., 2009). Knowledge and active research are3

Asia-Japan Research Academic Bulletin Volume 3, 13. April 2022

increasing into the accessibility to various service facilities for residents of multiple dynamics acrossthe globe. These research activities mainly focus on physical, financial, and economic accessibility.
Our study concentrates on physical accessibility which consists of the spatial location of the residents
and the distance covered to access various service facilities in an urban area. Apparicio et al. (2008)
and Lotfi and Koohsari (2009) also focused on these types of accessibility. Lotfi and Koohsari (2009)
argued that it is vital to consider the location of the residential area and the location of service facilities
surrounding it to determine the quality of accessibility to service facilities. Physical accessibility
explains the association between population distribution and the supply of the services (Islam and
Aktar, 2011). Therefore, it is essential to measure the service quality, distance to the services, service
location, time taken, and cost when accessing the existing services or facilities to determine the levelof physical accessibility.

(2) Deprivation
Researchers have defined “deprivation” as a socioeconomic concept that describes the lack ofaccess to urban facilities amongst disadvantaged groups. Deprivation is measured either for a specificpopulation in an area or a small society. The disadvantaged group is necessarily compared with therelatively well-off group to clearly understand the low-income group's deprivation. Though themeasurement method for deprivation has changed over time, current studies focus on measuring thelimited access to the various services ranging from food, clothing, transportation to education, housing,and other social services (Maguire et al., 2015; Ouyang et al., 2017; Yuan et al., 2018). The UK's
Multiple Deprivation Index (IMD) and the Deprivation Index (NZDep) in New Zealand are popular
indices used to measure deprivation.
Inequalities in access capacity to urban facilities affect people's overall living standards andphysical and mental health, turning deprivation into multiple deprivations. For example, Maguire et al.
(2015) showed that poor access to healthy food leads to over-consumption of less healthy types offood, leading to obesity. Xiang et al. (2018) showed that upward social mobility becomes harder toachieve with poor access to quality education. Therefore, poor access to various facilities impacts not
only low-income groups’ quality of life but also the overall development opportunities.
Previous studies have shown that establishing affordable housing at locations with little accessto service facilities may result in social issues such as poverty, high crime rate, poor living environment,
and low satisfaction level amongst low-income households compared to the financially strong group(Crook et al., 2016; Woo and Kim, 2016; Zeng et al., 2019). Most affordable housing planning andpolicies focus on providing appropriate housing units for the needy but usually overlook the provisionof adequate service facilities for low-income groups (Woo and Kim, 2016). Furthermore, the residents’satisfaction with the overall built environment and housing location is often ignored. Additionally,studies that attempted to measure the overall accessibility to service facilities lacked development
methodologies. Finally, most studies only used statistical analysis and not geographical analysis todetermine the accessibility level to service facilities. Since the studies have not focused on
geographical analysis, city planners must focus on public opinion when locating public housing units
or service facilities.

4

Does Relative Accessibility to Service Facilities Impact Residents’ Satisfaction? (KHAN, YOSHIDA)(3) Location Attachment
This study introduces the term “location attachment,” which is the same concept as that of place
attachment, space attachment, or community attachment used in previous studies to explain the longterm bond of residents with the location that they are currently living in, as described by Giuliani and
Feldman (1993). The term location attachment is part of a project examining the impact of travel
behavior in an urban form on location affordability and location attachment. Those who live in a certain
neighborhood for a long time tend to develop an attachment to that area and have a sense of belonging(Hay, 1998), making that place part of their self-identity, which shows the importance of the physicalenvironment (Proshansky et al., 1983).
Researchers gave ample attention to identifying the contributing factors that constitute location
attachment. Gustafson declared three aspects of place attachment: from one’s within, interaction witheach other, and interaction with the surroundings (Gustafson, 2001). Overall, the location attachment
variables are deeply associated with the psychology and management of the environment since they
explain how people react to an environment that they live in for a long time (Patterson and Williams,
2005; Scannell and Gifford, 2010; Trentelman, 2009). Additionally, sociocultural factors can also
identify place attachment as they explain the “place identity” and “place dependence” that overall build
the dan nature of the sociocultural dimension (Trentelman, 2009). Proshansky et al. (1983) identified
a place identity as self-dimensions, meaning the physical arrangement of the combinations of a location.
In contrast, Wijaya et al. (2018) referred to place dependence as the utility of a specific location,
meaning whether an individual or a group can use the physical arrangement of that location in a way
they desire. Nowadays, researchers are developing a model to synergize the interaction of place as alocation to perform social activities and nature. Such activities can help one format self-identity(Davenport et al., 2010; Sampson and Goodrich, .2009).
Other than place attachment, previous studies have also examined community attachment, which
explains how people connect with the residence location based on the level of socialization that creates
an emotional attachment to their homes due to social relationships. The residents’ behavior can show
this attachment to a particular community within that location (Liu et al., 1998). The residents’behavior and community participation have been declared a benchmark to assess community
attachment (Hummon, 1992; Sampson, 1988). Additionally, Gursoy and Denney (2004) suggested that
community attachment can also be determined based on how individuals feel about their surroundings
and whether they desire to continue living in that community or move somewhere else (Gursoy and
Denney, 2004). Overall, studies have shown that one’s attachment to a certain place or community andthe criteria that provide values to the attachment is very complex and depends on the size, type, andclass of the society, social interaction, participation, and residence duration.
Though studies have conceptualized accessibility to service facilities and the level of location
attachment to some extent, both elements have been discussed in separate fields with different
variables. Further, residents’ access capacity to services or facilities, satisfaction level, and attachment
to the residence location have not been explored in developing South Asian cities. Therefore, this study
aims to integrate these elements by using the case of Rawalpindi-Islamabad, Pakistan, to spatiallyassess the city-wide accessibility level of service facilities to residence location and statisticallyexamine the access satisfaction and location attachment. The results could also highlight what type ofhouseholds are deprived of what kind of service facilities. These findings can help develop suitable
5

Asia-Japan Research Academic Bulletin Volume 3, 13. April 2022

planning strategies and housing policies to locate affordable housing units at optimal locations whereservices, especially PT, provide easy access to low-income groups.

3. Research Area, Data Collection, and Methodology(1) Research Area: Rawalpindi-Islamabad Metropolitan Area
Figure 1 shows the location of RIMA, the third-largest metropolitan region in Punjab province.
The two cities are considered twin cities since they depend on each other economically and socially.
Rawalpindi is an unplanned old city comprising scattered settlements, but recently, many urban
developers have been attracted to Rawalpindi to develop planned housing communities. On the other
hand, Islamabad is a planned city well equipped with a social and economic hub where people fromvarious urban and rural areas migrate to seek employment or higher education. Together, these twincities contribute 5% to the national GDP.
RIMA has been facing rapid urbanization for the past several years, causing urban sprawl andhigh vehicle ownership. Sprawl and car dependency help reduce friction in the development of gatedcommunities in the two cities’ peripheral regions, resulting in low proximity to PT such as BRT andother informal paratransit services.
Pakistan’s national housing policies dictates the development of housing for disadvantaged
groups all around the country. However, a housing shortage remains that could facilitate a large volume
of low-income groups. Also, housing costs such as monthly rent and housing maintenance are the only
parameters mentioned in the national policy to develop affordable housing schemes. At the same time,parameters for transportation costs, land use, and built environment indicators can optimally identify
affordable housing locations near service facilities such as education, shopping, clean drinking water,transit, and other infrastructure to establish housing projects.

Figure 1 Study area: Rawalpindi-Islamabad Metropolitan Area (RIMA)
Source: Rehman and Jamil (2021)

6

Does Relative Accessibility to Service Facilities Impact Residents’ Satisfaction? (KHAN, YOSHIDA)(2) Data Collection
This study used spatial and statistical analysis to determine access capacity and location
attachment among RIMA city core, mid-urban, and suburban households. We incorporated only
frequently used service facilities, rather than including every public and private facility in the twincities usually not regularly visited. Previous studies mainly focused on education, health, shopping,PT, and recreational facilities (Zeng et al., 2019; Lotfi and Koohhsari, 2009); one facility in one casestudy. This study uses five frequently used service facilities. The names and addresses of thesefacilities were taken from government and private websites.
Education: All the levels of education facilities are included in this study since a majority of thefamilies have children who go to schools, colleges, and universities. Pakistan does not have anelementary, middle, and high school system. Instead, students receive ten years of school education(equivalent to the first year of elementary until the first year of high school). This is followed by two
years in College (equal to second and third year of high school), where students study the introductorysyllabus of the fields they wish to choose in university. Therefore, students who graduate school must
enroll in college before enrolling in a university; hence, this service is essential for study. From
university onwards, the system is the same as everywhere around the globe. The data for education
facilities were taken from eduvision.edu.pk., and rcb.gov.pk.
Health: All the levels of health facilities, i.e., hospitals and clinics, across RIMA are included inthis study, and they function the same as in any other country. The data for health facilities wereacquired from oladoc.com and healthwire.pk.
Shopping: It is challenging to define grocery stores in developing countries like Pakistan. In
developed countries like Japan and the US, the low-level stores or the convenience stores are wellestablished where people shop exactly the way they shop at supermarkets and marts. However, inPakistan, grocery stores, also known as Karyana stores (utility or general stores), are underdeveloped
and usually have only one shopkeeper. Customers usually ask the shopkeeper for the items they wantto purchase rather than picking the items on their own. The high-level supermarkets and marts function
somewhat similarly to those in developed countries. Usually, low-income people visit the grocery
stores more often because they cannot afford to shop at supermarkets for expensive monthly groceries.
Furthermore, several online phone applications for grocery shopping deliver bought groceries at home.
Since the data for the population that uses such applications are unavailable, this medium was excluded.
The names and locations were taken from lookup.pk and khappa.pk, where detailed information about
grocery stores across Pakistan is available.
BRT: We included only BRT for the analysis because the up-to-date information about the
number of buses, station names, route, working hours and fare is readily available on the official
Punjab Mass Transit Authority (PMA) website; pma.gov.pk. In contrast, up-to-date information about
low-level informal paratransit services could not be obtained; hence, we excluded these services fromthe analysis. The door-to-door taxi services called using an online application were also excluded since
residents do not walk or use any other travel mode to get to taxis.
Drinking water plants (DWPs): To our knowledge, no study has analyzed the access to DWPs
before. Since tap water at home is considered highly unreliable for drinking purposes, local authorities
have established DWPs across RIMA to allow access to and utilization of clean water free of charge,
helping the low-income groups. Though some neighborhoods can easily access this facility, others
would either purchase water bottles (around 10 gallons) at the shopping stores or hire companies todrop the bottles at households’ doorsteps. We used Google Maps to get the necessary data since nocredible website was found for DWPs.

7

Asia-Japan Research Academic Bulletin Volume 3, 13. April 2022

The addresses of all service facilities were then located using Google Maps and then geocodedin ArcGIS for further analysis. We used RIMA’s land use map to help to identify the residential parcels
in RIMA. Later, Google Earth was employed to extract 1,010 residential parcels because governmentmade sub-district boundaries of RIMA were not available. These extracted parcels were geocoded in
ArcGIS 10.5. When calculating the distances to each service facility, a centroid of each residential
parcel was formulated to use them as origins. Since the availability of the national level travel behavior
data is an issue in Pakistan, we gathered our primary data by dividing the stratified sampling into two
steps. First, we selected nine study sites for door-to-door household surveys based on the distance tothe city core, density, and development type. Figure 2 shows the spatial distribution of study sites in
RIMA. Second, three sites each were distributed five kilometers, ten kilometers, and fifteen kilometers
away from the city core. The white area between the residential parcels and greenery is a mixture ofcommercial, military, and undeveloped regions.
Table 1 describes the characteristics and sample frequency of each site. The first author noted
the household address when distributing the questionnaire survey between February 2020 and April
2020. Out of the total questionnaires of 500 given out, 435 valid responses were collected at a response
rate of 87%. The questionnaire survey was divided into three main parts: (1) household dynamics suchas age, gender, marital status, employment status, income, family size, and frequent travelers, (2)access satisfaction with the service facilities in question, and (3) location attachment to identify
satisfaction with built space of residential location, and desire to live near transit. The first author
completed all the surveys by asking questions since many households could not read or complete
English questionnaires.
Table 2 summarizes the household dynamics. Out of the total sample, male respondents
dominated all three groups, age and marital status were almost equally distributed, low-income and alarge number of family members were found to be higher in the city core group, most travelers were
within the mid-urban group, and the percentage of working adults was not significantly different.

Table 1 Study sites for surveys based on density, distance to BRT and city core and development typeDistance to city
Study Sites
Site names (sample)
Description
center (km)City core
1

Asghar Mall Scheme (48)0-5Highly dense, mixed land, unplanned settlement2
3
Mid urban
4
5

Naya Mohalla (49)Askari 10 (50)

0-5
0-5

Highly dense, mixed land, unplanned settlement
Mildly dense, planned, gated housing society

Bahria Town (51)Ghauri Town (52)

5-10
5-10

6

PHA Apt. G-11/4 (40)5-10Mildly dense, planned, gated housing society
Mildly dense, planned, informal housing society
Mildly dense, planned, mixed land, public
housing society

7

PHA Apt. G-7/1 (60)

10-15

8

PHA Apt. G-7/2 (40)

10-15

9

Sector F-10 (45)10-15

SuburbanLess dense, planned, mixed land, public housing
society
Less dense, planned, mixed land, public housing
society
Less dense, planned, formal housing society

8

Does Relative Accessibility to Service Facilities Impact Residents’ Satisfaction? (KHAN, YOSHIDA)

Table 2 Comparison of household attributes across three groups
HousingCity
MidMiddynamics
core
urban Suburban Housing dynamics
City coreurban Suburban
GenderFamily sizeMale
91.84% 94.41%
82.76% < 418.37% 12.59%
18.62%
Female
8.16%
5.59%
17.24% 4 -7
72.11% 80.42%
80.00%
Age
8 - 11
8.84%
6.99%
1.38%
< 25
1.36%
0.00%
0.69% 12 - 15
0.68%
0.00%
0.00%
25 - 44
39.46% 39.16%
40.00% Frequent travelers
45 - 6450.34% 49.65%
48.28% < 332.65% 17.48%
42.07%
65 - 84
4.08%
7.69%
8.28% 3 - 5
66.67% 65.73%
54.48%
> 85
4.76%
3.50%
2.76% 6 - 8
0.68% 16.78%
3.45%
Marital status
Vehicle ownershipa
Married90.48% 92.31%
84.14% Motorbike
71.4%
30.8%
13.1%
Unmarried
9.52%
7.69%
15.86% Car
51.7%
97.9%
97.9%
Family income
Occupation
0-49,99966%
1.4%
0.0% Working adult76.87% 75.52%
73.79%
50,000-99,999
29.3%
16.1%
13.8% Unemployed/Student
23.13% 24.48%
26.21%
100,000149,999
3.4%
30.1%
37.9%
150,000199,999
1.4%
19.6%
26.2%
>200,000
0.0%
32.9%
22.1%
Note: The family income is in Pakistani Rupees (PKR).
a, the percentages are the mean values of those who responded “Yes” to motorbike and car ownership.
Source: Authors’ analysis from questionnaire survey

Figure 2 Geographical location of study sites in RIMA

9

Asia-Japan Research Academic Bulletin Volume 3, 13. April 2022

(3) Methodology
First, the city-wide accessibility to five service facilities was examined using spatial analysis.
Figure 3 shows the location of each facility in RIMA. Then, the questionnaire survey was employed
to examine the households’ access satisfaction and attitude towards the built space of the residential
location. This integrated method of spatial and statistical analyses is not common in housing andtransportation policy studies.
1) Spatial analysis: City-wide accessibility to service facilities
The spatial analysis was conducted to determine the access level to five service facilities in the
RIMA context and compare the access satisfaction level of residents living in nine sites. Previous
studies have employed various methods to spatially determine the accessibility to service facilities(Lotfi and Koohsari, 2009; Zeng et al., 2019). The “coverage” method can count the number offacilities within a catchment by defining the catchment and determining the accessible locations tohouseholds and housing neighborhoods. The “container” method can count the number of facilities
within a designated area. The “minimum travel cost” approach requires travel survey data, including
travel time, travel mode, and road congestion. The “gravity and two-step floating catchment” methods
are the most difficult to employ since they deal with the service or facility level, making it challenging
to achieve city-wide. Finally, the “minimum distance” approach measures the distance from one point
to the nearest service with a detailed accessibility assessment. It is a widely used method in studies (Suet al., 2017; Zeng et al., 2019). Since residents face difficulty reaching any service facility, we
converted the distance, in meters, from residential neighborhoods to service into walking time inminutes. Hence, the distance method was essential for this study. The data for Pakistani district andsub-district boundaries were not available. The boundaries, shown on Google map, ranging from a few
hundred square meters to a few kilometers, contain thousands of residents. Therefore, spatial analysis
became exceptionally challenging. Thus, taking RIMA’s land use map as guidance, residential parcels
were extracted using Google Earth and recoded into ArcGIS to be utilized as analytical units todetermine accessibility.
Furthermore, the distance from the residential location to any service facility requires anoperational measure to show spatial accessibility. The standard distance tool in ArcGIS can measure
the shortest path using a road network as a medium. However, in the RIMA context, the updated
version of the shapefiles of the road network is not available. Also, it is difficult to determine the pathand travel mode that residents usually take to reach the desired facility. Therefore, this study borrows
the approach Zeng et al. (2019) adopted when estimating the distance and measuring the accessibility
from residential parcels to service facilities. Also, similar to previous studies comparing city-wideaccessibility to service facilities with residents’ satisfaction, the spatial analysis in this study does not
integrate the densities of service facilities and the RIMA population. The residential location choicetheory does not dictate that people of certain demography tend to move to a place with no schools,
hospitals, public transportation, and clean water. Therefore, regardless of density, we argue thataffordable housing should be placed in the area close to the service rather than close to other housing
communities.
Similarly, the distance was first converted into walking time since the walk to any service facility
from home determines the quality of the built environment (Su et al., 2017). This travel mode isessential because people living in the gated communities away from the city core have less or no accessto service facilities within walking distance. Therefore, they are highly dependent on private vehicles
10Does Relative Accessibility to Service Facilities Impact Residents’ Satisfaction? (KHAN, YOSHIDA)

to travel easily. Su et al. (2017) have suggested that residents are reluctant to walk with an increase in
the walking time; hence, the residents’ tolerance for walking and the walking time fit a decay function.
Additionally, an average adult walks at a speed from 55 to 110m/min, and 80m/min is the preferredwalking speed (Rose et al., 2005). Therefore, similar to Zeng et al. (2019), this study borrows the same
standard. The accessibility levels used by converting the distance and the accessibility scores of eachresidential parcel are given in Table 3. The evaluated scores for each facility compute the accessibility
scores to the facilities for city-wide residential parcels.
The five service facilities were divided into lower-, medium- and high-level dimensions
according to their types. Facilities at the lower level are usually located within the neighborhoods thatfacilitate daily needs (e.g., utility stores, clinics, and schools). Whereas the higher-level facilities
traditionally located away from the residential areas provide better and somewhat expensive services(e.g., supermarkets, hospitals, and universities). The service facilities and their divided levels are as
follows;• Education: Higher-level= Universities, Medium-level= Colleges, Lower-level= Schools• Health: Higher-level= Hospitals, Lower-level= Clinics• Shopping: Higher-level= Supermarkets, Lower-level= Grocery stores• Drinking water: Stays as it is• Bus rapid transit: Stays as it is

Figure 3 Spatial distribution of service facilities in RIMA

Determining the level of a particular service facility that satisfies the residents’ needs depends
entirely on their households’ dynamics and preferences. For instance, in RIMA, people living near thecity core could easily access small-scale shopping stores and preferred to use them rather than travelinga long distance to buy groceries in bulk at the supermarkets. The same is the case with health facilities.
On the other hand, suburbanites visit malls, supermarkets, and well-developed hospitals locatedoutside gated communities more often. Though these facilities may be expensive, they provide high11

Asia-Japan Research Academic Bulletin Volume 3, 13. April 2022

quality services compared to lower-level facilities. Nevertheless, ultimately people are free to choose
their desired level of service facilities. Therefore, city planners in RIMA must consider equal
opportunity to access the facilities at all levels regardless of whether residents choose a certain levelof service more than others.
Table 3 correspondence between distance range, walking time and accessibility scores
Level of accessibility
Accessibility measures
Very Good
Good
NormalBad≤ 300 300-600 600-1200
1200-1800
Euclidean distance to facilities (meters)≤5
5 to 1010 to 20
20 to 30
Walking time (min)
100
80
60
40
Accessibility score to each facility
Source: Zeng et al., 2019

Very Bad> 1800> 30
202) Statistical analysis: Household access satisfaction and location attachment
In addition to the spatial analysis, this study employed quantitative statistical analysis to examine
household access satisfaction and the attachment to the residence location. This analysis was further
divided into two main parts. Firstly, the access satisfaction with drinking water, shopping stores, BRT,
education, and health facilities was calculated using a dichotomous category, 0 for “Not satisfied” and1 for “Satisfied,” to examine the extent to which 435 respondents were satisfied when accessing thesefacilities. Then, the descriptives were calculated for (a) location attachment using a 5-point Likert scaleof “1=Much Worse, 2=Worse, 3=Normal, 4=Better, and 5= Much Better,” (b) location builtenvironment satisfaction also using a 5-point Likert scale of “1=Very dissatisfied, 2= Dissatisfied, 3=
Do not feel anything, 4= Satisfied, and 5= Very satisfied,” and (c) desire to live near BRT using a
dichotomous category of 0 for “No” and 1 for “Yes.” Table 4 summarizes the descriptives of accesssatisfaction across the three groups. Table 5 provides the descriptives of the households’ location
attachment across the three groups.
Secondly, the Anova test was performed for access satisfaction and location attachment variables
across the three groups to determine the significant mean difference between the satisfaction level andthe extent to which these groups are attached to the location. Levene’s test for the equality of variance(Levene, 1960) and Tukey’s test of Post Hoc (Allen, 2017) were also performed. The findings are
summarized in Table 6.

4. Results(1) Access Capacity to Services in RIMA
The accessibility scores of service facilities were calculated in RIMA and were divided based on
three groups—city core, mid-urban, and suburban. Table 4 shows the descriptive summary ofaccessibility means scores of service facilities. Except for universities, schools, hospitals, and grocery

12

Does Relative Accessibility to Service Facilities Impact Residents’ Satisfaction? (KHAN, YOSHIDA)

stores, all service facilities’ access scores and sub-types were higher within the city core region thanin other groups. The mean accessibility score of the main types across all the groups ranged from 25.24(BRT) to 65.31 (shopping) and from 36.98 (universities) to 79.39 (grocery stores) for sub-types. The
access scores for universities (41.26) and hospitals (51.37) were highest within suburban areas. The
mean scores for schools (69.52) and grocery stores (79.36) were highest among the mid-urban group.
BRT service showed the lowest because it is a single corridor line that provides access to only 8%
population within ten minutes of walking distance (Adeel et al., 2014). The remaining population who
desire to use BRT must take another travel mode to reach the nearest BRT stations. Low access toother facilities indicates accessibility deprivation for such groups.
Furthermore, Figure 4 shows the accessibility score by the residential parcel for all the sub-types,
except BRT, since this service is not spread across RIMA. The color-grading from “Red to Dark Blue”
indicates “Poor to Very Good,” representing accessibility scores. The figure shows that the red color
across RIMA indicates less well-equipped services in such areas, meaning low access to such facilities
than dark blue areas showing high proximity to several service facilities. Notably, each service facility
indicates a unique pattern within RIMA. For example, universities show low access in several parcelsof all three groups, hospitals and supermarkets show low access in the southern region of RIMA, anddrinking water plants are less in number within the outlying suburban residential parcels. In otherwords, the straight-line distance of the facilities from the nearest residential parcel is more than 1200
meters, making it difficult for the residents to walk to them. On the contrary, most parcels in all threegroups are well equipped with schools, grocery stores, and clinics, indicating that such services arewithin the range of 600 meters and easy to walk to.
Table 4 Mean accessibility scores of service facilities in RIMACity Core
Mid-urban
SuburbanService facilities
Mean
St. D.
Mean
St. D.
Mean
St. D.
Education
56.57
54.01
50.25
Universities
36.98
19.60
38.02
22.00
41.26
22.63
Colleges
68.04
21.04
54.49
22.47
42.61
25.12
Schools
64.69
18.97
69.52
20.22
66.88
22.63
Health
64.19
50.08
58.27
Hospitals
49.94
22.47
38.82
21.29
51.37
24.29
Clinics
78.44
17.41
61.34
23.83
65.17
23.08
Shopping
65.31
61.44
63.75
Supermarkets
52.63
25.69
43.53
24.86
49.12
24.94
Grocery stores
77.99
16.02
79.36
17.19
78.38
17.89
Drinking water
63.13
18.82
53.80
22.92
41.62
24.66
BRT
35.42
20.53
25.24
13.98
28.90
17.40
Note:
1. St. D. = Standard deviation.
2. The bold numbers for education, health, and shopping indicate the mean values of the mean accessibility
score of sub-types of the respective facility.
Source: Authors’ analysis

13

Asia-Japan Research Academic Bulletin Volume 3, 13. April 2022

Figure 4 Spatial distribution of accessibility score of service facilities in RIMA
Source: Authors’ analysis(2) Relative Accessibility Deprivation and Location Attachment
Day (2016) and Su et al. (2017) argued that the built environment of the residential area affects
the way people feel, behave, and go about their daily lives. The way service facilities are spread in a
built environment also impacts the residents’ satisfaction level when accessing such facilities.
Therefore, this study examined the respondents’ access satisfaction with five service facilities as a subanalysis. The descriptive summary is given in Table 5.
Overall, this cross-analysis indicates disparities in all services across the groups. The city coreresidents showed the highest satisfaction with health (51.2%) and BRT (59.2%) services compared toother groups, and suburban residents showed the highest satisfaction with education (42.0%), shopping(43.1%), and drinking water plants (45.9%) compared to the city core and mid-urban residents.
Notably, residents of all three groups did not show significant satisfaction differences with education,
shopping, and health facilities, with low satisfaction with the sample's health facilities. This result
could be because small-scale neighborhood clinics might not provide good quality services, eventhough they are accessible within walking distance, forcing urbanites to visit large-scale hospitals inremote areas. Similarly, city core residents were dissatisfied when accessing education facilities,
maybe because they did not prefer such facilities near the neighborhoods due to poor quality andinstead commuted to the institutions with higher standards away from the residential area. Surprisingly,
the city core residents indicated low satisfaction with shopping compared to other groups. Althoughspatial analysis showed a “Very Good” accessibility score for grocery stores within the residential
areas throughout RIMA, it appears that the local government did not equip neighborhoods with largescale supermarkets as per residents’ demand. Moreover, compared to a low satisfaction level with
14

Does Relative Accessibility to Service Facilities Impact Residents’ Satisfaction? (KHAN, YOSHIDA)

drinking water among city core residents and higher among other groups, the spatial accessibility scoreamong city core residents was higher than other groups (63.13 for city core vs. 53.80 for mid-urban
and 41.62 for suburban), as seen in Table 4. The reason for low access satisfaction among the city core
could be three-fold: (1) the timings of the drinking water availability might be unpredictable, (2) the
drinking water plants located within the residential area are always crowded at the time of available
water, or (3) the structure of water plants exists but does not provide clean water, forcing residents tovisit other facilities away from home. Lastly, mid-urban residents reported the lowest satisfaction with
BRT service compared to other services, possibly because of BRT’s low coverage area in RIMA.
Table 5 Descriptives of access satisfaction to service facilities
Satisfaction
City coreMid-urban
Suburbanwith service
Frequency
Percent
Frequency
Percent
Frequency
Percent
facilities
Education
Satisfied
40
23.0
61
35.1
73
42.0
Not satisfied
70
41.4
62
36.7
37
21.9
Total
110
32.1
123
35.9
110
32.1
HealthSatisfied
43
51.2
24
28.6
17
20.2
Not satisfied
104
29.6
119
33.9
128
36.5
Total
147
33.8
143
32.9
145
33.3
Shopping
Satisfied
75
26.0
89
30.9
124
43.1
Not satisfied
72
49.0
54
36.7
21
14.3
Total
147
33.8
143
32.9
145
33.3
Drinking water
Satisfied
56
18.9
104
35.1
136
45.9
Not satisfied
91
65.5
39
28.1
9
6.5
Total
147
33.8
143
32.9
145
33.3
BRT
Satisfied
132
59.2
3
1.3
88
39.5
Not satisfied
15
15.3
77
78.6
6
6.1
Total
147
45.8
80
24.9
94
29.3
Note: The Chi-square tests for all the facilities indicate 99% significant level.
Source: Authors’ analysis

Total
Frequency

Percent

174
169
343

-

84
351
435

-

288
147
435

-

296
139
435

-

223
98
321

-

The degree of dissatisfaction with access to services significantly influences residents’satisfaction with the location of the residential area where residents are currently living. Thissatisfaction depends on the degree of location attachment and the built environment of the residential
area. It also affects the citizens’ desire to live near the BRT service to reach other facilities using BRT.
The descriptives of the degree of location attachment and built environment satisfaction and desire tolive near BRT are given in Table 6. In contrast, the one-way Anova test of the satisfaction with service
facilities and location attachment indicators across the groups are provided in Table 7. Out of the total
sample, around 55% of the city core residents felt “Worse” or “Much worse” with attachment to theresidential location. Parallel to this feeling, 55% of the city core respondents also felt “Dissatisfied” or“Very dissatisfied” with the built environment of the residential location. However, the majority(87.8%) of such residents desired to live near BRT. This result could be because 71% of the city core
respondents owned motorbikes while 51.7% were car owners (Table 2). Mid-urban and suburbangroups show almost 100% car ownership. Also, all three groups showed a high percentage of working
adults in the households. If working adults in the city core use private vehicles to commute to work,
other households would have to depend on other modes to access desired destinations. Hence, they
preferred the location that provides better access to BRT.
Moreover, the residents living away from the city core showed a higher degree of location
attachment and satisfaction with the built environment; however, they markedly rejected the idea of15

Asia-Japan Research Academic Bulletin Volume 3, 13. April 2022

relocating to the neighborhoods closer to BRT. The mid-urban residents showed a high degree ofattachment to the residential location, i.e., 63.6% of “Better” or “Much better” and the suburban groupwas 61.3% “Better” or “Much better.” Similarly, the percentages of these two groups were almost thesame for “Satisfied” or “Very satisfied” with the built environment of the location. Both groups
significantly opposed the idea of relocating near BRT. This result is understandable for two primaryreasons. First, those living away from the city core report high income, meaning they own private
vehicles for mobility (Table 2). Second, households in study sites 7 and 8 could access BRT within
five kilometers. In contrast, other sites are not connected with high-quality PT, forcing the residents totravel using private vehicles. Besides, people who are not dependent on PT in RIMA showed highdissatisfaction with the overall PT service quality (Khan, 2021). Table 7 presents the one-way Anova
test, which indicates significant differences in service satisfaction, location attachments, built
environment, and desire to live near BRT at a 99% confidence level.
Table 6 Descriptive statistics of location attachment and desire to live near BRT
City coreMid-urban
Suburban
Attributes
Frequency Percent Frequency Percent Frequency Percent
Location
attachment
Much worse
24
16.3
14
9.8
7
4.8
Worse
57
38.8
11
7.7
4
2.8
Normal
44
29.9
27
18.9
45
31.0
Better
22
15.0
87
60.8
83
57.2
Much better
4
2.8
6
4.1
Built
environment
satisfaction
Very dissatisfied 24
16.3
14
9.8
6
4.1
Dissatisfied
57
38.8
12
8.4
5
3.4
Do not feel
44
29.9
28
19.6
45
31.0
anything
Satisfied
22
15.0
86
60.1
83
57.2
Very satisfied
3
2.1
6
4.1
Desire to live
near BRT
No
18
12.2
129
90.2
136
93.8
Yes
129
87.8
14
9.8
9
6.2
Source: Authors’ analysis

Total
Frequency

Percent

45
72
116
192
10

10.3
16.6
26.7
44.1
2.3

44
74
117

10.1
17.0
26.9

191
9

43.9
2.1

283
152

65.1
34.9

Thus, the result of the access capacity to service facilities in RIMA and satisfaction/attitude
towards the access to service facilities and the overall residential location can assist the local
government when establishing policies to construct low-cost housing for disadvantaged groups.
Usually, local governments in many cities develop affordable housing projects near the peripheral
regions where accessing health, shopping, recreational, and educational facilities becomes timeconsuming and expensive. This low access to services significantly impacts the residents’ quality oflife. For example, no access to large-scale shopping facilities could prevent residents from obtaining
good quality food; no access to health facilities would worsen the health of disadvantaged groups; andno access to high-quality education could jeopardize the children’s future, making it difficult tomobilize in the upper social class. However, this study did not directly analyze the correlation between
spatial accessibility analysis and health status and children’s possible bright future. Additionally, thisstudy did not ask respondents how lack of access to the service facilities in question affects their qualityof life.
16

Does Relative Accessibility to Service Facilities Impact Residents’ Satisfaction? (KHAN, YOSHIDA)

Table 7 Anova result for service facility satisfaction and location attachment
Service satisfaction and location attachment
Mean square
Educational unit
2.487
Health unit
1.189
Shopping
4.511
Drinking water
11.556
BRT/public transport
23.054
Attached to community
51.968Location BE satisfaction
51.327
Live near BRT
31.010Note: BE = Built environment*** indicate 99% confidence level.
Source: Authors’ analysis

F
10.4727.856
22.07069.849333.62459.97760.046363.376

Sig.
***
***
***
***
***
***
***
***

5. Discussion
Many urban planners believe that developing affordable housing can help low-income groups
solve their residential problems. Ball (2016) and Varady and Matos (2017) stated that developed cities
had neglected to provide Affordable Housing Communities to subsidize households. On the contrary,
Woo and Kim (2016) have argued that relocating the residents from centrally located residential areas
to newly built affordable housing at urban fringes leads to low proximity to urban facilities. This
relocation is a common practice in many developing economies such as Mexico, Brazil, and Chinathat are rapidly urbanizing and causing urban inequalities (Ma et al., 2018; Wei and Chiu, 2018). Even
though disadvantaged groups are provided with affordable housing units, their locations are markedly
inaccessible. Zeng et al. (2019) have identified that the peripheral location of Affordable Housing
Communities causes several social-spatial issues of low or no access to service facilities that in turncauses accessibility deprivation.
This study in RIMA spatially analyzed the accessibility score from residential parcels to service
facilities. It concluded that the city core region is relatively well-equipped with various service
facilities, providing better access to the mixed-income groups. Low-income households in the city core
may feel deprived of opportunities away from the convenient distance because low access to frequently
used service facilities impacts poor people more than the well-off group due to a significant increasein transportation costs. Although some service facilities are less in number in one region while inabundance in other areas, well-off residents have relatively better resources to access the desired
service than low-income residents, offsetting the influence of low access to quality of life. For instance,
the household dynamics in this study’s survey showed that a large proportion of respondents in thecity core are low-income, with three to five adult travelers in one family. This survey category implies
that they are highly dependent on PT such as BRT for their mobility. Since BRT is a single corridor
without the integration of the feeder buses, commuters usually take multiple travel modes to access
BRT stations (Khan and Shiki, 2018). Subsequently, around 53% of the mid-urban and 48.3% of thesuburban group earn more than PKR 150,000, making it affordable to bear the daily transportation
expenses. Therefore, service facilities must be located near BRT or neighborhoods of low-income
people with no car ownership. After the first phase of BRT in RIMA, the Punjab government hasestablished phase 2 to transport passengers directly to the Islamabad International Airport. The spatial
analysis in Figure 4 should dictate new policies for extending the BRT corridor towards suburban
study sites, i.e., locations 7 to 9 in Table 1. However, as Haque and Rizwan (2020) have argued, BRT
17

Asia-Japan Research Academic Bulletin Volume 3, 13. April 2022

can facilitate low-income groups and benefit the economy to some extent. Yet, it cannot mitigate traffic
congestion, as the primary transportation mode is still private vehicles.
Furthermore, after taking office in 2018, the Government of Pakistan has launched an affordable
housing scheme known as the Naya (New) Pakistan Housing Program with a vision of providing
affordable housing to low-income families across the Punjab province (seehttps://phata.punjab.gov.pk/). The size of the houses ranges from 817 square feet to 1361 square feet.
The official web page indicates that several affordable housing societies provide facilities such asutilities, roads, schools, mosques, commercial areas, fast internet, and other facilities, but they are not
located in Islamabad and inner Rawalpindi. Also, no access to BRT or different transportation modes
may impact the mobility of low-income groups, leading to accessibility deprivation.
This case study employs spatial accessibility to quantify the access capacity of RIMA residents
with five service facilities and a statistical housing survey to examine the accessibility issues of theresidents at three geographical locations—city core, mid-urban, and suburban. Though this dual
method has been used in a handful of studies (Zeng et al., 2019), it is an effective tool to identify andhighlight the socio-spatial difficulties faced by disadvantaged groups. This study’s findings helped tounderstand that residents of all three locations are facing multiple accessibility issues, and thegovernment must focus on these deprivations to establish suitable policies. This mixed-method can beused to deepen the research in the context of accessibility deprivation when aiming to provide
affordable housing units in other cities.
The research results have led to three valuable policy recommendations when planning housing
or service development projects in the future.
Social and economic opportunities: Public and private developers must not only aim to ensure
adequate housing units but also focus on providing social and economic opportunities, such as
education, health, PT, clear water, and jobs, to disadvantaged groups. The Rawalpindi and Islamabaddevelopment authorities can establish housing units and service facilities simultaneously. This idea
applies to all cities and is not limited to developing states; although this type of development plan is
not new (Woo and Kim, 2016), it is often ignored (Zeng et al., 2019).
Regular financial aid: The lack of regular funding from the provincial or local governments
causes significant challenges to developing and maintaining affordable housing units with better
proximity to service facilities (Cai et al., 2017). Wu (2015) argued that local governments acquire
substantial fees for land leasing and improved economic activities when dealing with urban
redevelopment and gentrification. That is why city officials maintain good locations in a metropolitan
area for heavy commercial activities and high-class residential areas, pushing affordable housing andrelated activities nearer to the city periphery (Fenton et al., 2013). Therefore, diversified financial
resources and a partnership with private enterprises can encourage the development of affordable
housing and associated services at appropriate locations. Subsequently, local officials must provide
attractive incentives to encourage social workers and property developers to establish education,
shopping, and health facilities at low and high order for the relocated residents to the newly built
affordable residential units.
Consulting residents’ opinions: After identifying the residents who want to relocate to affordable
housing units, it is essential to understand their views and attitudes. This consultation could help
improve the quality of housing units. Organizations such as the Rawalpindi Development Authority
and Islamabad Development Authority deal with planning and constructing residential and commercial
properties. Ouyang et al. (2017) emphasized that an adequate developing strategy ensures equity when
distributing the service facilities around the affordable housing units. Therefore, public opinion is oneof the critical elements for future planning processes.
18

Does Relative Accessibility to Service Facilities Impact Residents’ Satisfaction? (KHAN, YOSHIDA)

6. Conclusion
This case study of RIMA, Pakistan, attempted to explore the city-wide accessibility of theresidents towards several frequently used service facilities based on spatial analysis for distance fromresidential parcels to service facilities and statistical analysis for household access satisfaction. The
findings have revealed that spatial analysis of certain service facilities (Figure 4) differs from what
residents feel (Table 5). The survey highlights that residents living in various geographical locations
are very dissatisfied with the poor access to essential facilities, affecting their quality of life. This result
indicates that residents do not want to use inferior quality services within the neighborhood and instead
visit superior quality services in remote areas, especially health and education facilities. Low-income
and extremely low-income groups living in the city core feel inconvenienced with the daily, longcommuting time to access high-quality education and health services. This feeling furthers theirdissatisfaction with their residential location and contributes to failure to form a community attachment.
Thus, local government and the associated private partners must consider the location and residents’
accessibility when planning to establish service facilities within a community to enhance equity
amongst all income groups. Also, paying attention to public opinion and maintaining regard for
disadvantaged groups is essential to ensure justice in Pakistani metropolitan cities.
This case study also has some limitations. The authors did not ask the respondents whether they
visited the services located closer to a residential area. The urbanites might choose a service facility ina remote area depending on the quality of the service. Therefore, aspiring researchers in this field canfocus on household satisfaction with the quality of service facilities that residents from the city core toa suburban region often visit.
This study has concluded that residents in different geographical areas suffer from accessibility
deprivation depending on the type of service. However, further case studies should include more
service facilities and target the population living in affordable housing units in different Pakistani cities
to examine the significant differences and recommend suitable policies.

Acknowledgment
This research was supported by the International Research Fund from Ritsumeikan University. I am
grateful to Professor Yoshida for guiding me throughout the research process and to the twoanonymous reviewers for their constructive comments.

References
1) Books and articles
Adeel, M., Yeh, A.G.O., Zhang, F. 2016. Transportation disadvantage and activity participationin the cities of Rawalpindi and Islamabad, Pakistan. Transp. Policy 47, 1–12.
Angelidou, M. 2014. Smart city policies: A spatial approach. Cities, 41, S3–S11.
Apparicio, P., Abdelmajid, M., Riva, M. & Shearmur, R. 2008. Comparing alternative approaches tomeasuring the geographical accessibility of urban health services: distance type and aggregationerror issues. International Journal of Health Geographics, 7(7), 1–14.
Allen, M. 2017. Post Hoc Tests: Tukey Honestly Significant Difference Test. The SAGE
Encyclopedia of Communication Research Methods.
19

Asia-Japan Research Academic Bulletin Volume 3, 13. April 2022

Ball, M. 2016. Housing provision in 21st century Europe. Habitat International, 54, 182–188.
Cai, X., Tsai C.C. & Wu, W.N. 2017. Are they neck and neck in the affordable housing policies?
A cross case comparison of three metropolitan cities in China. Sustainability, 9(4), 542.
Casakin, H., Hernández, B. & Ruiz. C. 2015. Place attachment and place identity in Israeli
cities: The influence of city size. Cities, 42(Part B), 224–230.
Cowan, R. 2005. The dictionary of urbanism. Wiltshire: Streetwise.
Crook, T., Bibby, P., Ferrari, E., Monk, S., Tang, C. &Whitehead, C. 2016. New housing
association development and its potential to reduce concentrations of deprivation: An English casestudy. Urban Studies, 53(16), 3388–3404.
Davenport, M.E., Baker, M.L., Leahy, J.E. & Anderson, D.H. 2010. Exploring multiple
place meanings at an Illinois state park. Journal of Park and Recreation Administration,
28(1), 52-69.
Day, K. 2016. Built environmental correlates of physical activity in China: A review. Preventive
Medicine Reports, 3, 303–316.
Fenton, A., Lupton, R., Arrundale, R. & Tunstall, R. 2013. Public housing, commodification,and rights to the city: The US and England compared. Cities, 35, 373–378.
https://doi.org/10.1016/j.cities.2012.10.004.
Giuliani, M.V. & Feldman, R. 1993. Place attachment in a developmental and cultural context.
Journal of Environmental Psychology, 13, 267-274.
Górczyńska, M. 2017. Social and housing tenure mix in Paris intra-muros, 1990–2010. Housing
Studies, 32(4), 385–410.
Gursoy, D. & Denney, G.R. 2004. Host attitudes towards tourism: An Improved structuralmodel. Annals of Tourism Research 31(3): 495–516.
Gustafson, P.E.R. 2001. Meanings of place: Everyday experience and theoreticalconceptualizations. Journal of Environmental Psychology, 21(1), 5-16.
Haque, ul N. & Rizwan, M. 2020. PIDE Urban Monograph Series No. 2: Rethinking Mobility(Urban Transport Policy) in Pakistan. Pakistan Institute of Development Economics (PIDE).
https:// pide.org.pk/pdf/Urban-Monograph-Series-2.pdf
Hay, R. 1998. Sense of place in a developmental context. Journal of Environmental Psychology,
18, 5–29.
Hummon, D. 1992. Community attachment: Local sentiment and sense of place. In I. Altman & S.
Low (Eds.), Place attachment (pp. 253–278). New York: Plenum Press.
Ibem, O.E. 2013. Accessibility of services and facilities for residents in public housing in urban
areas of Ogun State, Nigeria. Urban Forum, 24(3), 407–423.
Islam, M.S. & Aktar, S. 2011. Measuring physical accessibility to health facilities—A case study on
Khulna City. World Health & Population, 12(3), 33–41.
Jung, T.H., Lee, J., Yap, M.H.T. & Ineson, E.M. 2015. The role of stakeholder collaboration in
culture-led urban regeneration: A case study of the Gwangju project, Korea. Cities, 44, 29–39.
Khan, A. R. 2021. Measuring Survey-based Trip Satisfaction of Feeder Modes for Bus Rapid Transit
in Rawalpindi Islamabad, Pakistan. Urban and Regional Planning Review, 8, 147- 164.
Khan, A.R. and Shiki, K. 2018. Integration of Paratransit into Feeder Bus Services for RawalpindiIslamabad Metro Bus Rapid Transit System in Pakistan. Journal. of Regional Information.
Research, Ritsumeikan University, 7, 97-107.
Levene, H. 1960. Robust tests for equality of variances. In I. Ingram Olkin,, & H. Hotelling, (Eds.).
Contributions to probability and statistics: Essays in Honor of Harold Hotelling (pp. 278–292).
Stanford: Stanford University Press.
Libertun de Duren, N.R.L. 2018. Why there? Developers' rationale for building social housing
in the urban periphery in Latin America. Cities, 72, 411–420.
20

Does Relative Accessibility to Service Facilities Impact Residents’ Satisfaction? (KHAN, YOSHIDA)

Liu, Q., Ryan, V., Aurbach, H. & Besser, T. 1998. The influence of local church participation onrural community attachment. Rural Sociology, 63, 432–450.
Lotfi, S. & Koohsari, M.J. 2009. Measuring objective accessibility to neighborhood facilities in
the city (A case study: Zone 6 in Tehran, Iran). Cities, 26(3), 133–140.
Ma, Z., Li, C. & Zhang, J. 2018. Affordable housing brings about socio-spatial exclusion in
Changchun, China: Explanation in various economic motivations of local governments. Habitat
International, 76, 40–47.
Maguire, E.R., Burgoine, T., & Monsivais, P. 2015. Area deprivation and the food environment overtime: A repeated cross-sectional study on takeaway outlet density and supermarket presence in
Norfolk, UK, 1990–2008. Health & Place, 33, 142–147.
Martinez, C.F., Hodgson, F., Mullen, C. & Timms, P. 2018. Creating inequality in accessibility: The
relationships between public transport and social housing policy in deprived areas of Santiago deChile. Journal of Transport Geography, 67, 102–109.
https://doi.org/10.1016/j.jtrangeo.2017.09.006.
Maroko, A.R., Maantay, J.A., Sohler, N.L. Grady, K.L. & Arno, P.S. 2009. The complexities ofmeasuring access to parks and physical activity sites in New York City: a quantitative andqualitative approach. International Journal of Health Geographics, 34(8), 1–23.
Mattingly, K. & Morrissey, J. 2014. Housing and transport expenditure: Socio-spatial
indicators of affordability in Auckland. Cities, 38, 69–83.
Mulley, C. & Moutou, C.J. 2015. Not too late to learn from the Sydney Olympics experience:
Opportunities offered by multimodality in current transport policy. Cities, 45, 117–122.
Norris, M. & Hearne, R. 2016. Privatizing public housing redevelopment: Grassroots resistance,
co-operation and devastation in three Dublin neighbourhoods. Cities, 57, 40–46.
Olawuni, P.O., Adeyinka, S.A. & Abegunde, A.A. 2007. Intra-urban variation in housing
quality: the Nigerian experience. Journal of Land Use and Development, 3(1), 69–78.
Ouyang, W., Wang, B., Tian, L. & Niu, X. 2017. Spatial deprivation of urban public services inmigrant enclaves under the context of a rapidly urbanizing China: An evaluation based on suburban
Shanghai. Cities, 60, 436–445.
Patterson, M.E. & Williams, D.R. 2005. Maintaining research traditions on place: Diversity ofthought and scientific progress. Journal of Environmental Psychology, 25(4), 361-380.
Proshansky, H.M., Fabian, A.K. & Kaminoff, R. 1983. Place-identity: Physical worldsocialization of the self. Journal of Environment Psychology, 3, 57-83.
Rehman, A. & Jamil, F. 2021. Impact of urban residential location choice on housing, travel demands
and associated costs: Comparative analysis with empirical evidence from Pakistan. Transportation
Research Interdisciplinary Perspectives, 10, 100357.
Rose, J., Morgan, D.W. & Gamble, J.G. 2005. Energetics of walking. In J. Rose, & J. G.
Gamble (Eds.). Human walking (pp. 77–102). Philadelphia, PA: Lippincott Williams & Wilkins.
Sampson, R. 1988. Local friendship ties and community attachment in mass society: A multilevelsystemic model. American Sociological Review, 53, 766–779.
Sampson, K.A. & Goodrich, C.G. 2009. Making place: Identity construction and community
formation through “sense of place” in Westland, New Zealand. Society & Natural Resources,22(10), 901-915.
Scannell, L. & Gifford, R. 2010. The relations between natural and civic place attachment andpro-environmental behavior. Journal of Environmental Psychology, 30(3), 289-297.
doi:10.1016/j.jenvp.2010.01.010.
Su, S., Pi, J., Xie, H., Cai, Z. & Weng, M. 2017. Community deprivation, walkability, and publichealth: Highlighting the social inequalities in land use planning for health promotion. Land Use
Policy, 67, 315–326.
21

Asia-Japan Research Academic Bulletin Volume 3, 13. April 2022

Sun, B., Ermagun, A. & Dan, B. 2017. Built environmental impacts on commuting mode choice
and distance: Evidence from Shanghai. Trans. Research Part D: Transport and Environment, 52,
441-453.
Trentelman, C.K. 2009. Place attachment and community attachment: A primer grounded in
the lived experience of a community sociologist. Society & Natural Resources, 22(3), 191 - 210.
Varady, D.P. & Matos, F. 2017. Comparing public housing revitalization in a liberal and a
Mediterranean society (US vs. Portugal). Cities, 64, 37–46.
Wei, Z. & Chiu, R.L.H. 2018. Livability of subsidized housing estates in marketized socialist
China: An institutional interpretation. Cities, 83, 108–117.
Wijaya, I.N.S., Purnamasari, W.D. & Sitaresmi, D. 2018. Defining place attachment incommunity base development program for urban settlement – a theoretical review. IOP Conference
Series: Earth and Environmental Science. doi :10.1088/1755-1315/202/1/012052.
Woo, A. & Kim, Y.J. 2016. Spatial location of place-based subsidized households and unevengeography of opportunities: Case of Austin, Texas in the U.S. Community Development, 47(1),45–62.
Wu, F.L. 2015. Planning for growth: Urban and regional planning in China. Abingdon:
Routledge.
Xiang, L., Stillwell, J., Burns, L., Heppenstall, A. & Norman, P. (2018). A geodemographic
classification of sub-districts to identify education inequality in Central Beijing. Computers,
Environment and Urban Systems, 70, 59–70.
Yang, Z., Yi, C., Zhang, W. & Zhang, C. 2014. Affordability of housing and accessibility of public
services: Evaluation of housing programs in Beijing. Journal of Housing and the Built
Environment, 29(3), 521–540.
Yuan, Y., Xu, M., Cao, X. & Liu, S. 2018. Exploring urban-rural disparity of the multiple
deprivation index in Guangzhou City from 2000 to 2010. Cities, 79, 1–11.
Zeng, W., Rees, P. & Xiang, L. 2019. Do residents of Affordable Housing Communities in China
suffer from relative accessibility deprivation? A case study of Nanjing. Cities, 90, 141-156.
2) Statistics, Reports and Websites
Adeel, M., Yeh, A.G.O. & Zhang, F. 2014. Public transportation disadvantage in Rawalpindi
and Islamabad: 9 Preliminary Results from Field Survey 2013. International Conference on Town
Planning and Urban Management 10 29-30 September 2014. University of Engineering andTechnology, Lahore, Pakistan.
Punjab Housing and Town Agency. Reaching the new horizon of prosperity. Available online:
https://phata.punjab.gov.pk/ (accessed on 20 September 2021).
United Nations. Sustainable Development Goals, 17 Goals to Transform Our World. Available
online: https://www.un.org/sustainabledevelopment/sustainable-development-goals/ (accessed on
15 September 2021).
United Nations. 2019. Department of Economic and Social Affairs, Population Division World
Population Prospects 2019, Online Edition. Rev. 1.
UN. 2021. World urbanization prospects 2018 revision Department of Economic and Social
Affairs, Population Division. https://population.un.org/wup/
US Department of Housing and Urban Development. 2019. Defining housing affordability.
Retrieved from https://www.huduser.gov/portal/pdredge/pdr-edge-featd-article-081417.

22