G20 Ülkelerinin Covid-19 Pandemisi ile Mücadele Performanslarının Çok Kriterli Karar Verme Yöntemleri ile Değerlendirilmesi
Seda Karakaş Geyik, Mehmet Hakan Satman, Gülin KalyoncuCovid-19 pandemisi ilk günden günümüze dünyayı etkisi altına almış ve ülkeleri birçok farklı alanda etkilemiştir. Ülkelerin pandemi ile mücadele performanslarının belirleyicileri arasında mevcut sağlık sistemlerinin gücü, ekonomik yapıları, demografik yapıları, uygulanan önlemler ve yapılan destekler gibi kriterler sayılabilir. Bu süreçte ülkelerin dâhil olduğu uluslararası organizasyonların aldığı ortak kararlar da pandemi ile mücadele aşamasında ülkeleri desteklemektedir. Çalışmanın temel amacı söz konusu uluslararası organizasyonlardan G20 topluluğundaki ülkelerin pandemi ile mücadele performanslarının çok kriterli karar verme yöntemleri (ÇKKV) aracılığıyla değerlendirilmesidir. Çalışmada öncelikle kriterler için CRITIC yöntemi ile ağırlıklandırma işlemi gerçekleştirilmiştir. En önemli kriterler sırasıyla vaka sayısı, ölüm sayısı, likidite destekleri ve sağlık sektörüne yapılan ek harcamalar olarak saptanmıştır. Sonrasında ÇKKV yöntemlerinden TOPSIS, COPRAS, ARAS, WASPAS, MOORA, MABAC yöntemleri ile analiz gerçekleştirilerek ülkelere ilişkin sıralamalar elde edilmiştir. Nihai olarak ortak bir sıralama için COPELAND yöntemi kullanılmıştır. Sonuç olarak en başarılı ülkeler sırasıyla Avusturalya, Japonya ve Çin olarak belirlenirken son sıraları Brezilya, Meksika ve Güney Afrika paylaşmaktadır.
Performance Evaluation of G20 Countries’ Fight Against COVID-19 Using Multiple Criteria Decision-Making Methods
Seda Karakaş Geyik, Mehmet Hakan Satman, Gülin KalyoncuThe COVID-19 pandemic has affected countries around the whole world in many different areas. The main determinants of a country’s performance against the pandemic can be summarized through criteria such as the strength of its current health system, economic structures, demographic structures, restrictions, and support. Countries’ strategies also involve the consensus that has been reached by international organizations. The main purpose of this study is to evaluate the performance of G20 countries using multiple criteria decision-making (MCDM) methods. The criteria were first weighted using the CRITIC method, with the number of cases, number of deaths, liquidity supports, and additional expenditures in the health sector having been determined as the most important criteria. The data were then analyzed using MCDM methods to obtain countries’ rankings. As a result, the most successful countries were respectively determined as Australia, Japan, and China, while Brazil, Mexico, and South Africa came in the respective last three places.
Since ancient times, the world has struggled with epidemics, and COVID-19 is the latest epidemic the whole world is still fighting. As with other epidemics, countries have invented new vaccines, changed and transformed themselves socioeconomically, and had to take new preventive actions. Working from home, curfews, vaccinations, protections, liquidity supports, health expenditures, and other government expenditures are among the most important actions countries have taken. Although no objective judgment or objective comparison exists about the ranks or importance levels of these measures and actions, they are considered to be important in the fight against COVID-19.
This study, first objectively examines the importance of these criteria in G20 countries’ fight against COVID-19. Of the obtained criteria weights, the number of cases, the number of deaths, and the amount of liquidity support are seen to be the most prominent criteria with the highest values. The CRITIC method has been used to obtain criteria weights using the data collected for Australia, Canada, France, Germany, Italy, Japan, South Korea, the United Kingdom, the United States of America, Argentina, Brazil, China, India, Indonesia, Mexico, Russia, Saudi Arabia, South Africa, and Turkey. The European Union (EU) as the other member of G20 countries has been omitted from the study to avoid using duplicate information, as the EU already contains some of the countries that were already mentioned. The dataset has been gathered from the World Health Organization (WHO), Our World in Data, Worldometer, and International Monetary Fund (IMF) databases and contains the most up-to-date data shared according to the data release calendar.
The other objective of this study is to rank the countries according to their criteria and criteria weights. The process of ordering is known to be defined along the set of real numbers (e.g., a sample of [1, 5, 9] are considered ordered just because 1 ≤ 5 and 5 ≤ 9). Other terms require the operations ordering and ranking to have perfectly defined binary comparison operators such as ≤, <,> and ≥. On the contrary, a sample in higher dimensions such as (1, 3), (5, 7), and (7, 1) cannot be ordered or ranked in as unique a way because the binary comparison operators are not defined for dimensions of p ≥ 2. Consequently, an infinite number of orderings can occur for the observations in such cases.
A multiple criteria decision-making method (MCDM) defines an exclusive ordering or ranking measure for ordering or ranking multivariate data with respect to predefined criteria, criteria weights, optimization directions, and a decision matrix. From this perspective, obtaining a mathematical ranking of countries with respect to a set of criteria is an ordering problem with an infinite number of solutions over a multi-dimensional space.
This study ranks countries according to the selected criteria. Due to the unique ranking process for each single method, more than one method is used to compare results. TOPSIS, COPRAS, ARAS, WASPAS, MOORA, and MABAC are the wellknown and widely applied members of the MCDM methods family in the relevant literature. Each single method results in similar but different rankings based on how the comparisons are defined. These differences regarding MCDM methods complicate how results are interpreted. For example, according to the MOORA and MABAC method, Japan ranks highest, but ranks as the second most successful country according to the TOPSIS method, fourth according to the COPRAS method, third according to the ARAS method, and second according to the WASPAS method. While all of these methods give the idea that Japan’s has had quite high success, they also pose an obstacle to forming a complete ranking.
The COPELAND method has been used to combine and interpret all the results obtained by the different methods. The COPELAND method is a summary measure that combines the results of many MCDM methods by performing pair-comparisons of the rankings. One of the most important findings of this study is the acknowledgement that Australia, Japan, and China have bene the most successful countries in the fight against COVID-19. When ranking countries’ success rates, Australia, Japan, and China are followed by Germany, South Korea, and the United Kingdom. Meanwhile, Brazil, Mexico, and South Africa were identified as relatively less successful countries in the fight against COVID-19. Turkey ranks 14th in the general ranking obtained with the COPELAND method. When separately evaluating the results obtained from the methods, Turkey’s rank is seen to vary between 12th and 15th place.
Important findings were also achieved by comparing the country rankings obtained using the MCDM methods with the results obtained using the COPELAND method. The rankings obtained using the COPRAS, ARAS, WASPAS, and MABAC methods are highly correlated to the ranking obtained using the COPELAND method, whereas TOPSIS and COPELAND have a relatively weak correlation coefficient of 74%. When examining the reported correlation matrix, the results are observed to be highly correlated, with none of the methods achieved an unexpected ranking due to the nondiagonal elements being quite far from zero.
The country rankings as obtained in this study can be a guide for other countries, and even the methods of successful countries can be adopted for fighting the pandemic in the future. Consequently, this study has also revealed the most prominent factors in the fight against COVID-19 pandemic and contributes to the literature in terms of providing a comprehensive analysis by having the model include financial data, current statistics, health data, and vaccination rates. The fact that the different MCDM methods ranked the countries differently is an important limitation for the study, and a summary measurement (i.e., COPELAND) was used to combine the rankings. Future studies may be able to obtain a final common ranking by including more methods and criteria in their analyses.
