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Determination of the Financial Support Required by the Families with Disabilities to Achieve Standard Life Conditions with the AHP Method

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Maddi güçlükler, engelli bireye sahip ailelerin standart bir yaşam sürmelerini zorlaştırmaktadır. Bu çalışmada, temel tüketim grupları göz önünde bulundurularak engelli bireye sahip ailelerin, engelli bireye sahip olmayan aileler gibi hayatlarını sürdürebilmeleri için gerekli finansal desteği tahmin etmek üzere bir model geliştirilmiştir. Çalışmanın amacı, ana tüketim gruplarını göz önünde bulundurarak engelli bireye sahip ailelerin diğer ailelerle aynı yaşam standartlarına sahip olmaları için gereken finansal desteğin belirlenmesidir. Analizlerde, Türkiye İstatistik Kurumu (TÜİK) tarafından hazırlanan Hanehalkı Bütçe Anketi (HBA) verileri kullanılmıştır. Analizlere 101.504 hane dahil edilmiştir. Modelin geliştirilmesi sırasında AHP yöntemi kullanılmıştır. Ayrıca önerilen modelin kararlılığını göstermek için bir duyarlılık analizi yapılmıştır. Önerilen model, farklı sayıda bireye sahip aileleri de dikkate almaktadır.
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Mehmet Akif Ersoy Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi
Yıl: 2018, Cilt: 5, Sayı: 3, ss: 687-704
Araştırma Makalesi/Research Article
DETERMINATION OF THE FINANCIAL SUPPORT REQUIRED BY THE
FAMILIES WITH DISABILITIES TO ACHIEVE STANDARD LIFE CONDITIONS
WITH THE AHP METHOD
AHP YÖNTEMİ İLE ENGELLİ BİREYE SAHİP AİLELERİN STANDART HAYAT
ŞARTLARINA ULAŞABİLMELERİ İÇİN GEREKLİ FİNANSAL DESTEĞİN BELİRLENMESİ
Fatih ECER
Afyon Kocatepe University, Department of Business Administration, fecer@aku.edu.tr,
http://orcid.org/0000-0002-6174-3241
Ayşe Övgü KINAY
Dokuz Eylul University, Department of Computer Science, ovgu.tekin@deu.edu.tr,
http://orcid.org/0000-0001-9908-8652
Efendi NASİBOĞLU
Dokuz Eylul University, Department of Computer Science, efendi.nasibov@deu.edu.tr,
http://orcid.org/0000-0002-7273-1473
Başvuru Tarihi/Application Date:
29.05.2018
Kabul Tarihi/Acceptance Date:
13.11.2018
DOI: 10.30798/makuiibf.428401
Abstract
Financial difficulties make it difficult for families with
disabilities to live a standard life. In this study, a model is
developed to estimate the required financial support for the
families with disabilities that ensures them to have lives like
the families with non-disabilities by considering main
consumption groups. Hence, the aim of the study is to
determine the financial support for families with disabilities
that need to have the same life standards as other families
by taking into consideration main consumption groups. In
the analyses, the Household Budget Survey (HBS) data
prepared by Turkish Statistical Institute (TurkStat) are
utilized. Furthermore, 101,504 households are included in
the analysis. During the development of the model, the
AHP method is used. Besides, a sensitivity analysis is
conducted to demonstrate the stability of the proposed
model. Moreover, the suggested model considers families
having different individuals as well.
Öz
Maddi güçlükler, engelli bireye sahip ailelerin standart bir
yaşam sürmelerini zorlaştırmaktadır. Bu çalışmada, temel
tüketim grupları göz önünde bulundurularak engelli bireye
sahip ailelerin, engelli bireye sahip olmayan aileler gibi
hayatlarını sürdürebilmeleri için gerekli finansal desteği
tahmin etmek üzere bir model geliştirilmiştir. Çalışmanın
amacı, ana tüketim gruplarını göz önünde bulundurarak
engelli bireye sahip ailelerin diğer ailelerle aynı yaşam
standartlarına sahip olmaları için gereken finansal desteğin
belirlenmesidir. Analizlerde, Türkiye İstatistik Kurumu
(TÜİK) tarafından hazırlanan Hanehalkı Bütçe Anketi
(HBA) verileri kullanılmıştır. Analizlere 101.504 hane dahil
edilmiştir. Modelin geliştirilmesi sırasında AHP yöntemi
kullanılmıştır. Ayrıca önerilen modelin kararlılığını
göstermek için bir duyarlılık analizi yapılmıştır. Önerilen
model, farklı sayıda bireye sahip aileleri de dikkate
almaktadır.
Keywords: Disability, Consumption, Household Budget
Survey, AHP.
Anahtar Kelimeler:: Engellilik, Tüketim, Hanehalkı Bütçe
Anketi, AHP
Determination of the Financial Support Required by the Families
with Disabilities to Achieve Standard Life Conditions with the AHP Method
688
Mehmet Akif Ersoy Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi
Yıl: 2018, Cilt: 5, Sayı: 3, ss: 687-704
GENİŞLETİLMİŞ ÖZET
Çalışmanın Amacı: Çalışmanın amacı, ana tüketim gruplarını göz önünde bulundurarak engelli bireye sahip
ailelerin diğer ailelerle aynı yaşam standartlarına sahip olabilmeleri için gerekli olan finansal desteğin belirlenmesidir.
Finansal destek miktarını tespit etmek için AHP yöntemi temelli bir model önerisinde bulunulmuştur.
Araştırma Soruları: Engelli bireye sahip aileler ile diğer aileler arasında ana harcama gruplarına göre fark var
mıdır? Tüketim ana gruplarının önem ağırlıkları nedir? Engelli bireye sahip ailelerin ihtiyaç duydukları finansal destek
ne kadardır?
Literatür Araştırması: Son yıllarda literatürde, engellilik konusuna artan bir ilginin olduğu görülmektedir.
Aile bağlamında engellilik çalışması çerçevesinde de birçok çalışma yapılmıştır. Özellikle sosyal, psikolojik,
psikososyal ve hizmet desteği çerçevesinde yapılmış çalışmaların oldukça fazla olduğu dikkat çekmektedir. Ancak
finansal desteğe yönelik çok az sayıda çalışmanın olduğu söylenebilir.
Veri: Analizlerde kullanılan veriler, TÜİK tarafından hazırlanan hanehalkı bütçe anketinden (HBA) derlenmiş
olup 2002-2011 yılları arasındaki on yılı kapsamaktadır. Bu anketle, ailelerin tüketim alışkanlıkları, tüketim harcamaları
türleri, hanelerin sosyoekonomik özellikleri, hanehalkı üyelerinin istihdam durumu, hane halkının toplam geliri, gelir
kaynakları vb. gibi bilgiler toplanmaktadır. Veriler uzun ve zorlu bir çalışmanın ardından analizlere uygun hale
getirilmiştir. Bu süreçte, MS SQL ve MS Excel'de çeşitli programlama teknikleri kullanılmıştır.
Yöntem: Çalışmada analitik hiyerarşi yöntemi (AHP) kullanılmıştır. Önce, 12 temel harcama grubunun önem
ağırlıkları karar vericilerin değerlendirmeleri esas alınarak belirlenmiştir. Burada, değerlendirmelerin tutarlılığının da
kontrol edildiğini belirtmek gerekir. İkinci aşamada ağırlıklar normalize edilmiştir. Üçüncü aşamada, engelli bireye
sahip olan ailelerle diğer aileler arasındaki tüketim harcaması farkları hesaplanmıştır. Son aşamada ise finansal destek
miktarı hesaplanmıştır. Hesaplama yapılırken tüketim harcamalarının normalize edilmiş önem ağırlıklaile üçüncü
aşamada elde edilen değerlerden yararlanılmıştır.
Değerlendirme ve Sonuç: Çalışma sonucunda 12 temel harcama grubu inde en önemli görülen harcama
kalemleri sırasıyla giyim ve ayakkabı; mobilya, ev aletleri ve ev bakım hizmetleri ile eğitim hizmetleri olmuştur.
Restoran ve otel harcama grubunun ise en az önemli görülen harcama kalemi olduğu tespit edilmiştir. Çalışmada
ayrıca engelli bireye sahip olan aileler ile diğer aileler arasındaki harcama miktarı farkları 12 temel harcama grubu
bakımından ailelerdeki fert sayıları da dikkate alınarak hesaplanmıştır. Çalışmanın sonuçları, engelli bireye sahip olan
ailelerin diğer ailelere göre daha fazla harcama yaptıklarını göstermiştir. Özellikle sağlık grubu ile alkollü içecekler,
sigara ve tütün grubunda engelli bireye sahip olan ailelerin daha fazla harcama gerçekleştirdikleri belirlenmiştir. Elde
edilen bir diğer bulguya göre ailedeki fert sayısı arttıkça ihtiyaç duyulan finansal desteğin azalmasıdır. Bunun nedeni
olarak ailedeki fert sayısını artmasıyla birlikte çalışan birey sayısının artması ve dolayısıyla haneye giren toplam gelirin
artması olduğu söylenebilir. Çalışmada, ailelerdeki fert sayıları dikkate alınarak da analizler yapılmıştır. Buna göre
engelli bireye sahip ve iki kişilik ailelerin aylık yaklaşık 138 $ finansal desteğe ihtiyaç duydukları belirlenmiştir. Ayrıca
bu aileler en fazla yiyecek ve alkolsüz içecekler grubunda desteğe ihtiyaç duymaktadırlar. Çalışma, engelli bireye sahip
ve üç kişilik ailelerin aylık yaklaşık 97 $ finansal desteğe ihtiyaç duyduklarını ortaya koymuştur. Bu ailelerin en fazla
desteğe ihtiyaç duydukları harcama grubu giyim ve ayakkabı olmuştur. Engelli bireye sahip ve dört kişilik aileler aylık
yaklaşık 78 $ desteğe ihtiyaç duymaktadırlar ve en fazla yiyecek ve alkolsüz içecekler grubunda desteklenmeleri
gerekmektedir. Engelli bireye sahip ve beş kişilik aileler aylık yaklaşık 50 $ desteğe ihtiyaç duymakta olup en fazla
giyim ve ayakkabı grubunda desteklenmeye ihtiyaç duymaktadırlar. Aylık yaklaşık 23 $ finansal desteğe ihtiyaç duyan
engelli bireye sahip ve altı kişilik aileler en çok konut, su, elektrik, gaz ve diğer yakıtlar harcama grubunda
desteklenmelidirler. Bunlara ek olarak engelli bireye sahip olan yedi, sekiz ve dokuz kişilik aileler ise sırasıyla aylık 26
$, 15 $ ve 4 $ finansal desteğe gereksinim duymaktadırlar. Son olarak, önerilen modelin sağlamlığını ve kararlılığını
göstermek için bir duyarlılık analizi yapılmıştır. Duyarlılık analizine göre harcama gruplarının önem ağırlıkla
değiştiğinde, finansal destek miktarında farklılıklar ortaya çıkmıştır. Ancak, engelli bireye sahip aileler için finansal
destek ihtiyaçları sırası aynı kalmıştır.
Determination of the Financial Support Required by the Families
with Disabilities to Achieve Standard Life Conditions with the AHP Method
Mehmet Akif Ersoy Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi
Yıl: 2018, Cilt: 5, Sayı: 3, ss: 687-704
689
INTRODUCTION AND MOTIVATION FOR THE STUDY
The International Classification of Functioning, Disability and Health (ICF) defines disability as an
umbrella term for impairments, activity limitations, and participation restric¬tions (WHO, 2011).
However, the social model of disability defines disability as an outcome of the interaction of a person’s
functional status and their environment (Braithwaite and Mont, 2008).
More than a billion people are estimated to live with some form of disability, or about 15% of the
world’s population. This is higher than previous World Health Organization (WHO) estimates, which date
from the 1970s and suggested around 10%. According to the most recent World Health Survey around
785 million (15.6%) persons 15 years and older living with a disability and 110 million people (2.2%) of
them have very significant difficulties in func¬tioning (WHO, 2011). It is predicted that roughly one of
ten people in developing countries is disabled (Braithwaite and Mont, 2008). For instance, it is estimated
that approximately 20% of the UK’s people of working age are disabled and UK had the second highest
incidence of disability among the 15 EU countries in 2002 (Jones et al., 2007). Furthermore, there are
roughly 3 million disabled people in Italy, accounting for 5% of all people aged 5 and over living in a
family (Rosano et al., 2009). The American Community Survey (ACS) predicts that the overall proportion
of people with disabilities in the United States is 12.6% (Lewis, 2017). However, there is no enough
information on the number and proportion of disabled people and their socioeconomic characteristics in
Turkey. Yet, we merely know total disability proportion in the overall population is 12.29 % (TurkStat,
2002). Thus, there is a general lack of awareness in Turkey, concerning the needs of families with
disabilities.
In recent years, there has been an increasing interest in disability issues. Many studies have
developed around the study of disability in the family context (Holmbeck et al., 2002; Jiyeon et al., 2002;
Neely-Barnes and Marcenko, 2004; Saunders, 2005; Heller et al., 2007; Turnbull et al., 2007; Mitchell,
2007). In addition, a significant body of research has developed around the study of disability in the
support context: social (Schulz and Decker, 1985; Wilcox et al., 1994; Sugisawa et al., 1994; Braithwaite et
al., 1999; Allen et al., 2000; De Leon et al., 2001; Taylor and Scott, 2004; Yang, 2006; Lippold and Burns,
2009; Devereux et al., 2009; Bierman and Statland, 2010), psychosocial (Dalagdi et al., 2014; Patrick et al.,
1986), psychological (Campbell et al., 2012; Livneh, 2012), and service (Sloper, 1999; Gilligan and Taylor,
2008; Baxter and Glendinning, 2010; Maddison and Beresford, 2012). Financial support is one of a
number of ways that families with disabilities can be supported. However, only a few studies (Darling and
Author, 2016; Canarslan and Ahmetoğlu, 2015; Doessel and Williams, 2011; Fujiura, 2010; Braddock,
2009; Braddock, 2007; Braddock, 2002) have examined the financial support for families with disabilities.
Among these, for example, Braddock (2002) emphasized that public support for disability programs in the
United States totaled $294 billion in 1997. In addition, nationally, 52% of public long-term care financial
resources supported persons with disabilities in institutions, although great variation existed between
states and across disability groups. According to Braddock (2007), the total public spending on intellectual
disability in the United States was estimated to be $82.57 billion in 2004. Again, with respect to Braddock
(2009), public spending on institutional, nursing home facilities and the parallel system of community-
based programs for people with disabilities consumed approximately $181.7 billion in the USA in 2006.
Fujiura (2010) used data from the 2007 American Community Survey and found 32.3% of the family-
based population of adults with disabilities needed financial support. Among those meeting the support
test, approximately 4 in 10 lived in households where the primary income earner was 60 years or older.
Canarslan and Ahmetoğlu (2015) determined that the economic level of the families with disabilities had
an effect on the quality of life. Finally, Darling and Author (2016) deal with the costs of disability in
childhood.
Determination of the Financial Support Required by the Families
with Disabilities to Achieve Standard Life Conditions with the AHP Method
690
Mehmet Akif Ersoy Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi
Yıl: 2018, Cilt: 5, Sayı: 3, ss: 687-704
People with disabilities need more money in attempting to maintain or improve their quality of life.
Despite the fact that incomes are similar, families with disabilities achieve a lower standard of living than
those of non-disabled households because disability generates extra costs of living (Zaidi and Burchardt,
2005). Disabled people suffer from at least two types of material disadvantages: they earn less income than
the non-disabled, and because of their special needs, they need more income to achieve similar
functioning (Robeyns, 2006). For instance, a person with disabilities need for a mobility taxi to bring her
work represents an additional resource not required by a non-disabled worker. The difference in cost of
using the mobility taxi compared to the cost incurred by a non-disabled person (e.g., own car) represents
the additional resource required because of disability (Wilkinson-Meyers et al., 2010). Although the
relation between disability and extra demand for money has been studied previously (Matthews and
Truscott, 1990; Jones and O’Donnell, 1995; Martin and White, 1988; Klavus, 1999; Kuklys, 2005; Zaidi
and Burchardt, 2005; Saunders, 2005), financial support of families with disabilities as to consumption
expenditures has received little attention. To sum up briefly, growing demand for direct care personnel
and the dearth of affordable and accessible housing alternatives may expand the need for financial support
(Fujiura, 2010).
The efforts to facilitate daily activities of disabled people have recently increased. Examples include
reorganizing the buses and walkways, building elevators in subways and special restrooms in shopping
centers so that people using a wheelchair can move conveniently. Although these services are of great
importance from a welfare state perspective, it should also be kept in mind that financial constraints may
keep disabled people from benefiting from these services. For example, if the budget of a family with
disabilities is not good enough to afford to eat at a restaurant designed for disabled people or to send their
disabled children to a private school in which there is an elevator, all these efforts to give the disabled
individuals a better life become useless. In short, families with disabilities need financial support to have
the same life standards as the families without disabilities. Consequently, we purpose to develop a model
to determine the financial support for families with disabilities that need to have the same life standards as
other families. The model’s purpose is not to provide support for all expenditure groups for families with
disabilities. In other words, the purpose is not to give the same rate of support for all expenditure groups.
In summary, the model has been developed to provide different levels of support for different
expenditure groups. The proposed model determines the support families with disabilities need through
two stages: (i) identification of main expenditure categories (ii) Determination of financial support for
families with disabilities by identifying the differences in expenditures between families with disabilities
and other families.
The study proceeds in five parts. The next section describes the data set and methodology. The
third section presents a real world application to clarify the proposed model. The fourth section discusses
the findings and the last section concludes.
1. METHODOLOGY
1.1. Household Surveys in Turkey: Survey Design
We obtained data from a national representative data derived from the Turkish Statistical Institute
(TurkStat), Household Budget Survey (HBS), Consumption Expenditures, 2002-2011. HBS is designed
for the purpose of data collection on socioeconomic status, consumption expenditures and income
components in the Turkey by TurkStat. This survey compiles the data on the consumption habits, types of
consumption expenditures, socioeconomic characteristics of households, employment status of household
members, total income of a household, sources of income and etc. The entire members of the households
that live within the borders of Turkey are included within the scope. The household consumption
expenditure covers the purchase, consumption of their own production, consumption of the stocks of
their own production, goods and services (consumption from in kind income) taken from the working
places of the employed members, rental or property income in-kind and the purchase in order to give as a
Determination of the Financial Support Required by the Families
with Disabilities to Achieve Standard Life Conditions with the AHP Method
Mehmet Akif Ersoy Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi
Yıl: 2018, Cilt: 5, Sayı: 3, ss: 687-704
691
present/support in the survey month. On the other hand, income covers the data on the available income
obtain in the survey month and the last year. Household consumption expenditure covers the value of
purchase of various goods and services in the form of advanced or partial payment in order to meet their
needs by means of 12 expenditure groups. The outcome variables included these12 types of consumption
expenditures as follows (TurkStat, 2009):
CE1. Food and non-alcoholic beverages
CE2. Alcoholic beverages, cigarette and tobacco
CE3. Clothing and footwear
CE4. Housing, water, electricity, gas and other fuels
CE5. Furniture, household appliances, and household care services
CE6. Health
CE7. Transportation
CE8. Communication
CE9. Entertainment and culture
CE10. Education services
CE11. Restaurants and hotels
CE12. Various good and services
More detailed information about the HBS methodology can be obtained from the Turkish
Statistical Institute Web site (http://www.tuik.gov.tr).
1.2. Data and Methods
The estimation size of all HBSs was designed to represent rural and urban settlements of Turkey.
The stratified multi-stage systematic cluster sampling method was used as sampling method. Each
interviewer recorded the data on consumption expenditures and income of six sample households as a
result of 8 times of visits in a month, including 1 visit prior to the survey month, twice during the 1st and
2nd weeks, once during 3rd and 4th weeks and once following the end of the survey month (TurkStat,
2009). In addition, all surveys were conducted during 1 January-31 December of the relevant year.
Table 1. Number of people as to HBS
Date
Rural
Total
2002
1464
9555
2003
7486
25,764
2004
2559
8544
2005
2567
8559
2006
2628
8558
2007
2655
8548
2008
2591
8549
2009
3235
10,046
2010
3170
10,082
2011
3045
9918
Total
31,400
108,116
According to Table 1, it is deduced that the number of the families that are included in the HBS
questionnaire from the urban areas is more than the number of the families from the rural areas. And also,
most numbers of questionnaires were made in 2003.
Determination of the Financial Support Required by the Families
with Disabilities to Achieve Standard Life Conditions with the AHP Method
692
Mehmet Akif Ersoy Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi
Yıl: 2018, Cilt: 5, Sayı: 3, ss: 687-704
We pooled data from 10 survey years. However, the data are conditioned after a long and tough
work due to the data is not suitable to make an analysis. During this process, therefore, various
programming techniques are used in MS SQL and MS Excel.
The median response rate for these survey years is 75% (range=72%-78%). We limited our analysis
to people with disabilities in a sample size of 1855 from 81 provinces. Of the 108,116 households
sampled, 1.8% contained at least one disabled member.
1.2.1. The AHP method
As one of the most utilized and well known multi-criteria decision making (MCDM) methods, the
AHP method is developed by Saaty (1980). AHP has many advantages. For example, AHP provides a
measure of consistency in decision makers’ judgments or preferences. AHP also allows decision makers to
start from pairwise comparisons that are simple enough to work with and often are preferred by the
decision makers (Küçük and Ecer, 2008; Gao and Hailu, 2013; Ecer, 2018a; Ecer, 2018b). The basic steps
of this method are as follows (Yu et al., 2011; Barker and Zabinsky, 2011; Ecer, 2014).
Step 1: Compose AHP structure
AHP structures a complex decision situation in terms of hierarchical decision criteria and their
associated priorities, balancing the interactions among the criteria and synthesizing the information into a
vector of preferences among the alternatives. With the AHP, the objectives, criteria and alternatives are
arranged in a hierarchical structure. Usually, a hierarchy has three levels such as goal, criteria, and
alternatives.
Step 2: Establish a pairwise comparison matrix
In order to determine the relative weight of criteria, the second step is the pair comparison of
criteria. The pairwise comparison matrix contains numerical judgments assigned for each criterion, sub-
criterion and alternative. In AHP, multiple pairwise comparisons are from a standardized comparison
scale of nine levels shown in Table 2.
Table 2. The fundamental scale of pairwise comparisons
Definition
Value
1
Equal importance
3
Weak importance
5
Essential importance
7
Demonstrated importance
9
Extreme importance
2,4,6,8
Intermediate values
Suppose that
},...,2,1,{ njCC j
be the set of criteria. Evaluation matrix can be gotten, in
which every element
),...,2,1,( njiaij
represents the relative weights of the criteria illustrated:
nnnn
n
n
aaa
xaa
aaa
A
21
22221
11211
, (1)
where
),...,2,1,( njiaij
has complied with following condition:
ji
ij a
a1
,
1
ii
a
,
.aji 0
(2)
Determination of the Financial Support Required by the Families
with Disabilities to Achieve Standard Life Conditions with the AHP Method
Mehmet Akif Ersoy Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi
Yıl: 2018, Cilt: 5, Sayı: 3, ss: 687-704
693
Step 3: Calculate criteria weight
By the formula:
WAW max
. (3)
The
max
can be acquired. If the
max
is equal to n and the rank of matrix A is n, A is consistent.
In this case, the relative criteria can be discussed. The weight of each criterion will be calculated by
normalizing any of the rows or columns of the matrix A.
Step 4: Test consistency
AHP must meet the requirement that the matrix A is consistent. There are two parameter
consistency index (CI) and consistency ratio (CR). Both of them are defined as following:
1
n
n
CI max
, (4)
RI
CI
CR
, (5)
where RI is random index. For different count of criteria, it has different value demonstrated in
Table 3. If CR is less than 0.10, the result can be acceptable and the matrix A is sufficient consistency.
Otherwise, we have to return to step 1 and repeat again.
Table 3. The relationship between RI value and count of criterion
1
2
3
4
5
6
7
8
9
10
RI
0
0
0.52
0.89
1.11
1.25
1.35
1.4
1.45
1.49
1.2.2. The proposed model
The stages of the model are shown below:
Stage 1: Determining the weights
The weights of consumption items are determined at the first stage of the model. In this first stage
where we use the AHP method, 12 main consumption items are ranked through considering their
importance by the decision makers. Afterwards, the ranked items are used to generate the AHP matrix as
explained in Section 3 in details and the weights are determined.
Stage 2: Normalization of weights
At the second stage, the weights of the consumption items are normalized that are obtained in the
first stage. The normalization process is performed as formulized in Eq. 6.
max
W
W
Wi
i
,
ni ,...,1
(6)
Here, n represents the number of consumption items,
i
W
represents the normalized value of ith
consumption item, Wi represents the importance weight, Wmax represents the importance weight of the
consumption item with the highest weight.
Stage 3: Calculation of consumption differences between the families
At this stage, the consumption differences between the families with non-disabilities and families
with disabilities are calculated separately with regard to each consumption item. Eq. 7 is used in the
calculation process.
Determination of the Financial Support Required by the Families
with Disabilities to Achieve Standard Life Conditions with the AHP Method
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ii DNDiPPP
if
ii DND PP
(7)
Here,
i
ND
P
represents the consumption of families with non-disabilities,
i
D
P
represents the
consumption of families with disabilities and Pi represents the consumption difference with regard to ith
consumption group.
Stage 4: Estimating the amount of financial support
At this last stage, the amount of financial support is calculated. As the FS represents the amount of
financial support, the calculation is performed by using the following formula:
i
n
iiWPFS
1
.
, if
0
i
P
(8)
2. APPLICATION to HBSs DATA
In this part, an application of the model is given in order to clarify the suggested model. Within this
scope, the decision-making team is formed that consist of 33 individuals. The decision makers involve
people from different occupational groups (officer, house wife, lawyer, student, servant etc.) and different
age groups (18-57). The application of the model can be explained step by step as follows:
Determining the weights: Firstly, it is required to generate the AHP matrix in order to determine the
weights of main consumption weights. Within this scope, a questionnaire study is applied by using the face
to face interview with the decision makers. Firstly, the main consumption groups are numbered from 1 to
12 and the decision makers are asked to rank the consumption groups by considering their importance in
order to determine the importance weight of main consumption groups (1: very important, 12: least
important). As a result of the questionnaire study, 12 items are ranked differently by 33 different
individuals. In the next phase, the differences between the rank values are calculated in order to generate
AHP matrix due to both the size of the differences between the rankings (i.e. what is the distance of the
consumption group from another consumption group) and their directions (i.e. the importance perception
of a consumption group with regard to another consumption group) are important information. Hence, if
the main consumption groups are defined as
}12,...,1,{ jCC j
in this problem,
difference values are obtained in order to generate the upper triangle
of the matrix by using ranking information that are obtained from the questionnaires. It is required to
obtain only one value that will represent these values in the AHP matrix due to we would obtain 33 unit
difference values for the 33 questionnaires between the first main consumption group and second main
consumption group. In this study, the arithmetic mean and median values are examined and it is decided
that each difference is represented by median due to the examined values expressed close results. In the
following part, the obtained values that are potentially within the [-11,11] number interval, are transformed
into numerical form suitable for matrix values. In this part, the negative values show that the jth main
consumption group that is used when calculating the difference is more important than the (j+1)th main
consumption group. Therefore, when it is being transformed into AHP matrix through converting their
positive values into the inverse of their new values. Another important fact is that the criteria are required
to take values between [1,9] in the AHP matrix. Thus, the [0,11] interval is required to be converted. The
preferred method for the conversion in this study is given in Table 4.
12),...,1(,11,...,1),( ijiji
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with Disabilities to Achieve Standard Life Conditions with the AHP Method
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Yıl: 2018, Cilt: 5, Sayı: 3, ss: 687-704
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Table 4. Value conversion for the generation of AHP matrix
Old values
New values
1
0.821.00
2
1.64
3
2.45
4
3.27
5
4.09
6
4.91
7
5.73
8
6.55
9
7.36
10
8.18
11
9.00
The values presented in Table 4 are calculated by estimating on the basis of 9, for example, “What
is the value of 9 if it is 1 for 11?”. However, the “1” value is used instead of the first value 0.82 due to it
represent the equal importance. The conversions can be given as algorithms as follows.
Algorithm (determining the weights).
Step 0. 33x12 matrix is generated from the conducted i=1,….33 questionnaires as a result of
ranking the j=1,2,…,12 criteria.
Step 1. The difference values for (i-j), i=1,2,…,11; j=(i+1),…,12 are generated one by one for each
questionnaire.
Step 2. The median values are calculated one by one for the difference values with 66 columns that
are generated at the Step 1.
Step 3. The obtained median values are placed in the AHP matrix with their new values according to
the conversions in Table 4.
Step 4. The consistency of the AHP matrix is calculated.
The AHP matrix that is generated by taking the answers that are given in the questionnaire into
account and by using the above algorithm is shown in Table 5.
Table 5. AHP matrix
It is deduced that the generated AHP matrix is consistent (CR=0.01). Thus, the vector of weight
values that are generated for the main consumption groups are as follows.
1034.00179.01345.00899.00286.00339.00674.01648.00648.01652.00338.00955.0
T
W
According to this issue the most important three consumption groups are CE3, CE5 and CE10.
However, CE11 is evaluated as the least important consumption group.
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with Disabilities to Achieve Standard Life Conditions with the AHP Method
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Normalizing the weights: The weights of consumption groups are normalized by using the Eq. 6. The
normalized values are given in Table 6.
Table 6. Normalized values
Importance weights
(
W
)
Normalized values
(
W
)
CE1
0.095534
0.578338
CE2
0.033878
0.205089
CE3
0.165187
1.000000
CE4
0.064857
0.392628
CE5
0.164839
0.997893
CE6
0.067405
0.408053
CE7
0.033971
0.205652
CE8
0.028565
0.172925
CE9
0.089952
0.544546
CE10
0.134515
0.814320
CE11
0.017893
0.108320
CE12
0.103405
0.625988
Calculation of the consumption differences between the families by considering the disability situation: As it is
understood from the data, the number of individuals in a family might reach up to 26. However, only the
families up to 9 individuals that correspond to 93.88% of all data are included in our model in order to
prevent over-distribution. In this case 101,504 households are included in the analysis. At this step, the
calculation is performed in the light of the information that are given in the Appendix and Table 7 is
generated.
Table 7. Consumption differences ($/month) between the families with non-disabilities and other families
Determining the financial support: Table 8 is generated by using the Eq. 8 and normalized values that are
achieved at the second step. Here, it is required to mention that the negative values that are achieved at
the previous steps are not considered in this step.
In order to clarify how the calculations are done at this step, we can give an example for the
families with 2 individuals.
For CE1: 53.71*0.578338=31.06
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with Disabilities to Achieve Standard Life Conditions with the AHP Method
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For CE2: 6.66*0.205089=1.37
For CE12: 14.15*0.625988=8.86
Table 8. The financial support that will be provided to the families with disabilities ($/family)
3. DISCUSSION
If we examine Table 8, the negative values are so conspicuous. It means that, as it has been
mentioned before, the families with disabilities consumes more than other families. For example, it is
determined that the families with disabilities and having 4 individuals spend approximately $5 more with
regard to CE4 consumption group in comparison with other families.
In Fig. 1, the relationship between the number of individuals in families and the financial support
that they require is presented. Hence, the results show that as the number of individuals in a family
increases, the amount of the required financial support decreases with the exception of families with 7
individuals. The reason for this can be explained as the number of individuals in a family increases,
meaning that the number of people who can bring money for the family increases.
0
20
40
60
80
100
120
140
2
3
4
5
6
7
8
9
138.07
97.79
78.39
50.54
23.16
26.02
15.99
4.58
Number of person
Financial support ($)
Fig. 1. Relationship between financial support and number of individuals in the families
If it is required to make evaluations on the basis of number of individuals in families, it is
determined that the families with disabilities in the families with 2 individuals group need financial support
at each 12 consumption groups. The financial support that they mostly need with regard to consumption
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with Disabilities to Achieve Standard Life Conditions with the AHP Method
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items are respectively: “Food and non-alcoholic beverages”, “housing, water, electricity, gas and other
fuels” and “clothing and footwear”. The consumption items that are least required to be supported are
“alcoholic beverages, cigarette and tobacco”.
The financial support that the families with 3 individuals mostly need with regard to consumption
items are “clothing and footwear”, “housing, water, electricity, gas and other fuels”. Unlike the families
with 3 individuals, the families with 2 individuals need for the support with regard to “food and non-
alcoholic beverages” is comparatively so low. On the other hand, it is realized that the “health” is not
required to be supported due to they spend much more on that item. However, it can be interpreted as
they cut the necessary consumption of other items and shift this amount to the necessary consumption of
“health”.
When we examine the families with 4 individuals, it is realized that the families with disabilities
spend more on “health” same as the families with 3 individuals. Beside this, it is determined that they also
spend more on food and non-alcoholic beverages” in comparison with families with non-disabilities.
Housing, “housing, water, electricity, gas and other fuels”, “clothing and footwear” and “educational
services” are the consumption groups that the families in this group and with disabilities need financial
support most.
It is found that the families with disabilities make more consumption on 2 consumption groups in
comparison with the families with non-disabilities among families with 5 individuals: “various goods and
services” and “health”. The consumption groups that they mostly need financial support are respectively:
“clothing and footwear”, housing, water, electricity, gas and other fuels” and “education services”.
Besides, the families with disabilities have similar propensity to consume with the families with non-
disabilities with regard to the “alcoholic beverages, cigarette and tobacco”.
Among the families with 6 individuals the families with disabilities make more consumption on 4
consumption groups in comparison with other families: “alcoholic beverages, cigarette and tobacco”,
“clothing and footwear”, “furniture, household appliances and household care services” and “health”.
Therefore, the remained 8 consumption groups require financial support. The consumption groups that
they mostly need support are “housing, water, electricity, gas and other fuels”. Beside these consumption
group, they do not almost need any financial support for the consumption groups such as
“transportation”, “communication” and “restaurants and hotels”.
It is determined that the families with 7 individuals require financial support with regard to 9
consumption groups. The group that is required to be supports is “clothing and footwear”. Same as the
previous cases the families with disabilities make more consumption on “health” in comparison with the
families with non-disabilities. Also, all the family types have a similar propensity to consume on
“restaurants and hotels”.
We found the families with 8 individuals and disabilities make more consumption on “housing,
water, electricity, gas and other fuels” that other families. With regard to this group, “health” requires
financial support mostly. In addition, “various good and services” is the consumption group that requires
financial support mostly within all consumption items.
Finally, our results showed that the families with 9 individuals and with disabilities make
consumption on 7 groups more than other families. The most 2 high-point consumption items within
these items are “food and non-alcoholic beverages” and “health”. Also the consumption group that
requires financial support mostly is “housing, water, electricity, gas and other fuels”.
In sum, it is determined that the families with disabilities make more consumption on “health” in
general. This finding can be interpreted as the families with disabilities that already have low income
necessarily cut their consumption on other items and switch that part of their income toward “health”. If
Determination of the Financial Support Required by the Families
with Disabilities to Achieve Standard Life Conditions with the AHP Method
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Yıl: 2018, Cilt: 5, Sayı: 3, ss: 687-704
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it is required to make an overall assessment, the number of consumption groups that the families with
disabilities need financial support is too much. It is an important finding that “entertainment and culture”
is a consumption group that is required to be supported financially regardless of the number of individuals
in a family. Because the families with disabilities tend to switch their consumption towards more
compulsory consumption groups such as “health”, “food and non-alcoholic beverages” and “furniture,
household appliances and household care services” rather than consuming on “entertainment and culture”
item. The other important finding shows that the “alcoholic beverages, cigarette and tobacco” is the
following consumption group that the families with disabilities make consumption mostly after “health” in
comparison with other items. This finding can be explained by the negative psychology of the family
members.
3.1. Sensitivity Analysis
In determining the financial support for families with disabilities in the proposed model, the role of
importance weights is crucial. Hence, a sensitivity analysis is provided to check the stability of the
proposed model in this study. Therefore, a sensitivity analysis of weights is realized to follow up how the
amount of financial support behaves while importance weights of criteria are changed. To achieve this
aim, the importance weights gained from the entropy method is changed for two selection criteria while
the others are unchanging (Ecer, 2018a). In other words, the importance weight of the CE1 is changed
with CE2, CE3 and so on, sequentially, while the others are unchanging. Afterwards, the AHP method is
applied in determining final financial support. Consequently, the proposed model’s behavior against
importance weight changes is analyzed. In this study, 11 mutual importance weight change is performed
during the sensitivity analysis. Eventually, Table 9 shows the cases that considered for sensitivity analysis.
Additionally, all cases in Table 9 are analyzed and the radar plot based on Table 9 is illustrated in Fig. 2.
According to Fig. 2, financial support of families with disabilities is also changing while the importance
weights are changing reciprocatively. For instance, even CE1 and CE2’s importance weights are changed,
then the financial support of families with 2 individuals springs from 138.07 to 141.86, and families with 3
individuals springs from 95.53 to 113.57 in Scenario 6. However, the orders of financial supports do not
change. In sum, families with 2 individuals are identified as families who need the most financial support
according to the sensitivity analysis results. The financial support order of the other families does not
change. Consequently, sensitivity analysis of weights indicates that although the final order of financial
support for families with disabilities remains the same, there is only a change in the amount of financial
support.
Fig. 2. Result changes due to sensitivity analysis
0,00
20,00
40,00
60,00
80,00
100,00
120,00
140,00
160,00
Current
Scenario 1
Scenario 2
Scenario 3
Scenario 4
Scenario 5
Scenario 6
Scenario 7
Scenario 8
Scenario 9
Scenario 10
Scenario 11
23456789
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with Disabilities to Achieve Standard Life Conditions with the AHP Method
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Table 9. Sensitivity analysis results
Scenario
Variables
Criteria
CE1
CE2
CE3
CE4
CE5
CE6
CE7
CE8
CE9
CE10
CE11
CE12
CS*
w1
0.578
0.205
1.000
0.393
0.998
0.408
0.206
0.173
0.545
0.814
0.108
0.626
Ranking
F2I (138.07)
F3I (97.79)
F4I (78.39)
F5I (50.54)
F7I (23.16)
F6I (26.02)
F8I (15.99)
F9I (4.58)
1
w2
0.205
0.578
1.000
0.393
0.998
0.408
0.206
0.173
0.545
0.814
0.108
0.626
Ranking
F2I (120.50)
F3I (98.97)
F4I (79.28)
F5I (40.31)
F7I (15.53)
F6I (23.14)
F8I (7.35)
F9I (4.64)
2
w3
1.000
0.205
0.578
0.393
0.998
0.408
0.206
0.173
0.545
0.814
0.108
0.626
Ranking
F2I (151.07)
F3I (86.31)
F4I (63.31)
F5I (37.90)
F7I (17.84)
F6I (20.77)
F8I (7.94)
F9I (4.23)
3
w4
0.393
0.205
1.000
0.578
0.998
0.408
0.206
0.173
0.545
0.814
0.108
0.626
Ranking
F2I (141.92)
F3I (104.94)
F4I (83.06)
F5I (46.64)
F7I (21.39)
F6I (24.73)
F8I (4.54)
F9I (3.96)
4
w5
0.998
0.205
1.000
0.393
0.578
0.408
0.206
0.173
0.545
0.814
0.108
0.626
Ranking
F2I (154.60)
F3I (91.86)
F4I (66.22)
F5I (41.85)
F7I (17.03)
F6I (23.82)
F8I (10.22)
F9I (4.04)
5
w6
0.408
0.205
1.000
0.393
0.998
0.578
0.206
0.173
0.545
0.814
0.108
0.626
Ranking
F2I (129.81)
F3I (94.42)
F4I (74.39)
F5I (39.97)
F7I (14.49)
F6I (22.63)
F8I (7.54)
F9I (4.76)
6
w7
0.206
0.205
1.000
0.393
0.998
0.408
0.578
0.173
0.545
0.814
0.108
0.626
Ranking
F2I (141.86)
F3I (113.57)
F4I (96.66)
F5I (47.32)
F7I (16.33)
F6I (29.61)
F8I (10.08)
F9I (4.32)
7
w8
0.173
0.205
1.000
0.393
0.998
0.408
0.206
0.578
0.545
0.814
0.108
0.626
Ranking
F2I (121.91)
F3I (101.29)
F4I (81.02)
F5I (42.09)
F7I (17.38)
F6I (22.89)
F8I (7.23)
F9I (4.12)
8
w9
0.545
0.205
1.000
0.393
0.998
0.408
0.206
0.173
0.578
0.814
0.108
0.626
Ranking
F2I (136.68)
F3I (95.92)
F4I (73.53)
F5I (41.82)
F7I (16.64)
F6I (23.85)
F8I (7.57)
F9I (5.01)
9
w10
0.814
0.205
1.000
0.393
0.998
0.408
0.206
0.173
0.545
0.578
0.108
0.626
Ranking
F2I (149.56)
F3I (92.11)
F4I (67.26)
F5I (39.78)
F7I (15.69)
F6I (23.84)
F8I (8.39)
F9I (4.67)
10
w11
0.108
0.205
1.000
0.393
0.998
0.408
0.206
0.173
0.545
0.814
0.578
0.626
Ranking
F2I (120.13)
F3I (106.88)
F4I (85.79)
F5I (43.23)
F7I (18.42)
F6I (23.91)
F8I (10.58)
F9I (4.15)
11
w12
0.626
0.205
1.000
0.393
0.998
0.408
0.206
0.173
0.545
0.814
0.108
0.578
Ranking
F2I (139.95)
F3I (95.02)
F4I (72.18)
F5I (42.33)
F7I (16.27)
F6I (23.47)
F8I (7.35)
F9I (4.32)
The amounts of financial support are reported in the parenthesis. * Current situation. F2I: Families with 2 individuals,
F3I: Families with 3 individuals, etc.
CONCLUSIONS
In this study, a financial support model for families with disabilities is proposed on the basis of the
AHP model. The main idea of the model is that with disabilities may not require the same amount of
financial support for the same consumption item. The required financial support amounts are calculated
by summing the values that are obtained through multiplying the difference between the consumption
amount of the families with disabilities and consumption of families with non-disabilities, by the values
that are obtained through normalizing the weights. Indeed, as a result of the analyses that are performed
by using the HBS questionnaire data, it is deduced that the families with disabilities and with varying
number of individuals require financial support with varying amounts. The model also suggests the
required financial support with details by considering each consumption group. Herein, when the number
of individuals in a family is taken into consideration, it is determined that financial support is needed for
any consumption group in a family type while other family type make more consumption of that group
Determination of the Financial Support Required by the Families
with Disabilities to Achieve Standard Life Conditions with the AHP Method
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Yıl: 2018, Cilt: 5, Sayı: 3, ss: 687-704
701
and do not need any financial support in contrast. This model is all important due to its potential to
achieve such a crucial mission.
In order to demonstrate the robustness and stability of the proposed model, a sensitivity analysis
was performed in this study. When the importance weights were changed, there were differences in the
amount of financial support. However, the order of financial support needs for families with disabilities
remained the same. Namely, families who need the most financial support are families with 2 individuals.
Families with 3 and 4 individuals followed them, respectively.
Politicians would be able to allocate financial support with varying amounts for the families with
disabilities by using the suggested model and they would be able to quit practicing of financial support
with equal amounts. Thus, it would be possible to achieve better integration for the families with
disabilities into society that receive insufficient financial support through increasing the amount of
financial support.
The limitation of this study is the findings based on the opinion of the decision makers. In other
words, when the decision makers are replaced, the findings might change. Therefore, it is required to
select the decision makers very carefully in order to obtain realistic suggestions from the model. Herein, it
might be offered to establish a decision makers committee that includes members from different age
groups, different income levels, different genders and whose family is with disabilities and non-disabilities
etc. As a direction for future research, the fuzzy AHP method which takes into account human thoughts
and judgments can be utilized to determine financial support for the families with disabilities.
Determination of the Financial Support Required by the Families
with Disabilities to Achieve Standard Life Conditions with the AHP Method
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Disability has often been associated with poverty, but few studies examine the relationship empirically in developing countries. For example, a review of World Bank Poverty Assessments finds that while most countries acknowledge the issue, few have the data to investigate it. This paper sets forth a preferred methodology for examining disability and poverty that is in line both with a more functional approach to disability incorporated in the WHO's International Classification of Functioning and Sen's Capabilities Model. Applying that methodology to two developing countries reveals the strong connection between poverty and disability and the need for a separate poverty line for families with disabled members.RésuméOn a souvent associé le handicap à la pauvreté, mais rares sont les études qui analysent empiriquement ce lien dans les pays en développement. Ainsi, un rapport de la Banque mondiale sur les estimations de la pauvreté montre qu’en dépit de la reconnaissance du problème par la plupart des pays, peu d’entre eux disposent des données nécessaires à son étude. Cet article présente une méthodologie pour analyser le handicap et la pauvreté concordante tant avec l’approche fonctionnelle contenue dans la Classification internationale du fonctionnement, du handicap et de la santé de l’OMS qu’avec le modèle des « capabilités » de Sen. L’application de cette méthodologie à deux pays en voie de développement montre la relation forte entre pauvreté et handicap et la nécessité de disposer d’un seuil de pauvreté différent pour les familles dont certains membres sont handicapés.
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Introduction The Australian economy has experienced over 13 consecutive years of strong economic growth, following extensive deregulation of its financial, product and labour markets. Throughout this period, the Commonwealth government has tightened its targeting of income transfers and relied increasingly on competitive tendering between government and non-government agencies to deliver its social programmes, leading the world in many of its reform initiatives. The fact that the Australian welfare system has traditionally relied on an extensive array of non-government agencies has made the task of privatising welfare more manageable than some other countries have found. However, the counterpart to this is that many of Australia’s welfare structures and institutions are more fragile than elsewhere, and questions are being raised about their ability to withstand current pressures. As the middle class is required to pay for services while being income-tested out of social transfers, support for the welfare state is declining, placing pressure on government to implement further programme cuts and/or user charges that reinforce the problem. Australia's pro-market reform strategy emerged under the Hawke– Keating Labour governments of the 1980s, when the initial changes were introduced as part of an Accord between the government and the trades unions that delivered wage restraint in exchange for employment generation and a boost in the social wage. Since its election to office in 1996, the Howard government has combined an even more radical free market approach with a conservative social agenda built on notions of personal responsibility and mutual obligation. Market deregulation has been accompanied by increased real wages, but high productivity growth has meant that growth in output has not translated into employment, and unemployment remains stuck above 5%. Welfare receipt among the working-age population increased from around 11% in 1965 to over 19% in 1997 (Whiteford, 2000). Although welfare receipt has declined since then to below 16% by 2002, government policy remains focused on getting those on welfare into work. Against this background, this chapter examines the circumstances of households that contain disabled members in the context of proposed reforms to the main income support programme for disabled people, the Disability Support Pension (DSP).
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In the management of recreational fishing, multiple biophysical and socio-economic objectives need to be considered. The identification of best management options is technically challenging because of the lack of scientific tools to inform resource managers of future responses/impacts of these different options.This paper proposes a decision support system which aims at greatly improving stakeholder dialogue and decision making. The system consists of two main components: an integrated agent-based model for simulating recreational fishing behavior and reef ecosystem dynamics; and an evaluation model based on the analytic hierarchy process (AHP) together with a technique for order preference by similarity to ideal solution (TOPSIS). The evaluation component is responsible for assessing alternative strategies based on the simulation outputs generated by the former.We apply the proposed system to the assessment of management strategies for recreational fishing in the Ningaloo Marine Park, an iconic coral reef system in Western Australia. A set of management strategies, including a “business-as-usual” strategy and six alternative site closure strategies are assessed using the proposed solution. The site closure strategies evaluated vary in length and number of popular sites closed. The evaluation results illustrate the usefulness of the proposed system in tackling complex management choices. We also perform a sensitivity analysis on the stakeholder or decision maker outcome preference weights and provide measures for assessing the sensitivity of strategy ranking outcomes to changes in these weights.
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In recent decades there has been an increasing interest in cognitive deficits in schizophrenia. However, only a few studies have examined the impact of psychosocial support on the prevention of cognitive deterioration in patients who suffer from schizophrenia. The aims of the present study are: (1) to confirm the presence of cognitive deficits among patients with schizophrenia; (2) to explore any correlations between such deficits and a range of clinical and/or demographic characteristics of the patients; and (3) to investigate any association between cognitive deficits and psychosocial support. A total of 118 patients with schizophrenia (the patient group) and 102 healthy volunteers (the control group) had a cognitive assessment using a battery of neuropsychological tests. The patients were allocated to one of the following groups: (1) patients under routine outpatient follow-up; or (2) patients receiving or having recently received intensive psychosocial support, in addition to follow-up. This included daily participation in vocational and recreational activities provided by dedicated mental health day centers. The findings of the neuropsychological testing of individuals in all groups were compared, after controlling for clinical or demographic factors. The scores in the neuropsychological tests were lower overall in the patients group compared to healthy volunteers. Within the patients group, those receiving/having received psychosocial support had higher scores compared to those on routine follow-up alone. There were no significant differences between patients currently receiving psychosocial support and those having received it in the past. Lower education, age and illness duration (but not severity of positive or negative symptoms) were factors associated with lower test scores. The study provides some evidence that psychosocial support may be beneficial for the cognitive functioning of patients with schizophrenia and this benefit may be a lasting one.