LEE- Endüstri Mühendisliği Lisansüstü Programı
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Konu "analitik hiyerarşi süreci" ile LEE- Endüstri Mühendisliği Lisansüstü Programı'a göz atma
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ÖgeRanking of families applying for social aids to municipalities according to their degree of neediness(Graduate School, 2022-06-20) Aladağ Mert, Yiğit ; Aydın Karaçay, Gaye ; 507181135 ; Industrial EngineeringAlthough there is no general definition of poverty, it varies according to time and place. The concept of poverty, which is intertwined with many social variables, can be stated as being deprived of minimum living standards in general. Although there are many sub-titles of poverty, the concepts of absolute deprivation and relative deprivation are the most mentioned concepts in the literature. Absolute deprivation refers to the inability of households or individuals to meet the basic needs for their survival, while relative deprivation refers to being below the average welfare level created in the society. Various policies have been developed globally and nationally in the fight against poverty. One of the most important international common approaches is the United Nations Sustainable Development Goals (SDGs). This call to action, also known as the Global Goals; aims to protect our planet, eliminate poverty, and ensure that all people live in peace and prosperity. The legal dimension of the social security and social assistance system in Turkey has been drawn by laws and the constitution. The Social Services Law of 1983 regulates the principles and procedures regarding the social services taken to individuals in need of protection, assistance and/or care, and the authorities, duties and responsibilities of the institutions established to carry out these services. The law also states that if the service demand is more than the service supply, the priority will be determined by the degree of neediness and the order of application/detection. The General Directorate of Social Assistance and Solidarity was established in 2004, and in 2005 it was given the task of providing social assistance to special provincial administrations and municipalities. This decision has a critical importance because municipalities are important administrative units that provide the closest service to the citizens and have a direct impact on their lives. Every year, municipalities allocate a part of their annual budget to social aids. These social aids can be form of food, clothing, fuel, etc. or it can also be done directly in cash. The COVID-19 pandemic, which has started in 2019, affected both local and global economies, in terms of production, employment, social services, health, etc. There have been declines in many sectors. Turkey has also had its share from these economic fluctuations, and according to the statement of the TURKSTAT (Turkish Statistical Institute), annual inflation in 2021 was 36.08%. According to the research carried out by Türk-İş Union, in December 2021, the hunger treshold for a family of four in Turkey was determined as 4,013.26 TL (Turkish Lira) and the poverty line as 13,073 TL while in the meantime the minimum wage was 2,825 TL. Due to the above-mentioned conditions, applications for aid to municipalities have increased in the recent period. For instance, more than 1 million families applied for aid to the Istanbul Metropolitan Municipality during the pandemic period. The necessity of making a ranking for such a large number of applications is quite obvious. The aim of the study is to rank the families applying for social assistance according to their neediness with an easily applicable and consistent formula. In this context, to contribute to the effective use of the budget of the municipalities and to contribute to the literature. Fuzzy Analytic Hierarchy Process and Simple Additive Weighting methods were used for the formula. Analytic Hierarchy Process is a multi-criteria decision-making method introduced by Thomas L. Saaty in 1980. This method, which is based on pairwise comparisons, considers the problem (goal) as a hierarchical structure. In addition to its simplicity and usefulness, one of the most important reasons underlying the popularity of the method is that it can use qualitative and quantitative factors together. Although AHP's purpose is to capture expert knowledge, it is currently unable to reflect human thinking styles. As a result, F-AHP was developed as a fuzzy extension of AHP to overcome these issues. F-AHP uses the fuzzy set theory that was introduced by Lotfi A. Zadeh in 1965. According to classical set theory, the degree of belonging of an element to a set is 0 or 1. That is, this element either belongs to the set or it does not. In a fuzzy set, the degree of belonging of the elements to the set is defined by the "membership value" and varies between 0 and 1. One of the most important advantages of the F-AHP is that it can benefit from linguistic terms in pairwise comparisons. When comparing two criteria, the decision maker can make healthier comparisons with linguistic terms such as "more important", "much more important", "equally important" rather than giving crisp values. Simple Additive Weighting Method (SAW) is one of the Multi Attribute Decision Making (MADM) method introduced by Ackoff and Churchman in 1954. This method is also often known as the weighted summing method. The method is based on the weighted average. For each alternative, an evaluation score is calculated by multiplying the scaled value given to that attribute's alternative with the weights of relative importance directly assigned by the decision maker, then summing the products for all criteria. The criteria required to create the ranking formula that we have suggested were obtained by examining the social assistance regulations of various municipalities in Turkey, since there is no former study on the subject in the literature. Social assistance regulations of 27 municipalities, 14 of which are metropolitan municipalities and 13 of which are district municipalities, were examined. As a result of these examinations, the criteria were divided into two headings, economic and demographic.The sub- criteria of the economic criteria were determined as the monthly net income of the household, the amount of monthly aid received from different institutions, movable property insurance value, immovable property fair value, and the monthly rent paid by the family. While the sub-criteria of demographic criteria were determined as the number of people in the family, the number of people working in the family, the number of students in the family, the number of people with disabilities in the family, and the number of people over 70 years old in the family. The problem has been transformed into a hierarchical structure in accordance with the F-AHP. After this process, a questionnaire form was created for pairwise comparisons. The decision makers to fill out the questionnaires were determined as social service experts, sociologists, psychologists in municipalities and people in the municipality administration. In the study, which was carried out as an online questionnaire, the form was sent in Turkish, and a version translated into English was added to the study. In the study, 26 questionnaires were analyzed. The results obtained were analyzed in overall, only for metropolitan municipalities and district municipalities separately, and criteria weights were calculated. In all three scenarios, economic criteria were determined to be more important than demographic criteria. The most important among the 10 sub-criteria was the monthly net income of the household. Since families with higher scores are described as more needy in the formula created, amongst the sub-criteria, the sufficiency and deficiency criteria are determined. The normalization of these two different types of criteria will be performed differently from each other. The determination of the criteria, the survey process, the derivation of the criteria weights, and the decomposition of the criteria for normalization can be found in section 4. In section 5, the created formula is shown through a numerical example. In the example, a 100x10 value matrix was created with the answers of 100 different families assumed to have applied to 10 criteria. After eliminating those who were not in need out of 100 families in the first step, the values were normalized for the remaining 85 families and the score of each family was calculated separately. Families in the top 10 were determined. Operations were performed for the three different weightings obtained. Finally, in section 6, a sensitivity analysis was performed for reliability and consistency.