Research Article
Seçilmiş Avrupa ve Asya Ülkelerinin COVID-19 Durumlarının Entropi ve MAUT Yöntemleri ile Değerlendirilmesi
Abstract
Bu çalışmanın amacı araştırmaya konu edilen Avrupa ve Asya ülkelerinin COVID-19 durumlarının entropi ve çok nitelikli fayda teorisi (MAUT) kullanılarak değerlendirilmesidir. Araştırma verileri Our World in Data veri tabanlarından 15 Nisan 2021 tarihi itibariyle temin edilmiştir. Literatüre paralel olarak değerlendirmede kullanılmak üzere on dört ölçüt seçilmiştir. Kriterlerin objektif ağırlıklandırılmasında entropi yöntemi kullanılmış, nüfus yoğunluğu (15.6%), yüz kişi bazında tüm dozlar aşılanmış insan sayısı (12.1%), bin kişi bazında uygulanan test sayısı (10.2%), diyabet yaygınlığı (8.9%), pozitif oranı (8.5%), kardiyovasküler ölüm oranı (8.3%), milyon kişi bazında ölüm oranı (7.3%), %), yüz kişi bazında aşılanmış insan sayısı (6.1%), milyon kişi bazında vaka sayısı (5.2%), bin kişi başına düşen hastane yatağı sayısı (4.7%), bin kişi başına düşen hemşire ve ebe sayısı (4.1%), kapanma endeksi (3.4 %), bin kişi başına düşen doktor sayısı (3.1%) ve 65 yaş üzeri nüfus oranı (2.6%) sıralaması elde edilmiştir. Ülkeler MAUT yöntemi ile sıralandığında ilk beş ülkenin Bahreyn, Sırbistan, Slovakya, İsrail ve Slovenya olduğu, son beş ülkenin ise Malezya, Norveç, Japonya, Finlandiya ve Güney Kore olduğu belirlenmiştir. Araştırma bulguları sonuç bölümünde tartışılmıştır.
Keywords
References
- Albahri, O. S., Al-Obaidi, J. R., Zaidan, A. A., Albahri, A. S., Zaidan, B. B., Salih, M. M. and Zulkifli, C. Z. (2020). Helping doctors hasten COVID-19 treatment: Towards a rescue framework for the transfusion of best convalescent plasma to the most critical patients based on biological requirements via ml and novel MCDM methods. Computer methods and programs in biomedicine, 196, 105617.
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- Breitenbach, M. C., Ngobeni, V. and Aye, G. C. (2021). Efficiency Of Healthcare Systems In The First Wave Of Covid-19-A Technical Efficiency Analysis. Economic Studies, 30(6).
- Chen, C. H. (2020). A novel multi-criteria decision-making model for building material supplier selection based on entropy-AHP weighted TOPSIS. Entropy, 22(2), 259.
- Çalış Boyacı, A . (2021). Which OECD countries are advantageous in fight against COVID-19? Erciyes Üniversitesi Fen Bilimleri Enstitüsü Fen Bilimleri Dergisi , 37(1) , 137-148 .
- Dowd, J. B., Andriano, L., Brazel, D. M., Rotondi, V., Block, P., Ding, X. and Mills, M. C. (2020). Demographic science aids in understanding the spread and fatality rates of COVID-19. Proceedings of the National Academy of Sciences, 117(18), 9696-9698.
- Erdoğan, N. K., Altinirmak, S., Şahin, C. and Karamaşa, Ç. (2020). Analyzing the financial performance of football clubs listed in BIST using entropy based copras methodology. Dumlupınar Üniversitesi Sosyal Bilimler Dergisi, 63, 39-53.
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- Fishburn, P. C. and Keeney, R. L. (1974). Seven independence concepts and continuous multiattribute utility functions. Journal of Mathematical Psychology, 11(3), 294-327.
- Ghasemi, A., Boroumand, Y. and Shirazi, M. (2020), How Do Governments Perform in Facing COVID- 19? , MPRA Pap.
- John Hopkins University Coronavirus Resource Center, 2021. https://coronavirus.jhu.edu/, Retrieved 2021, April 25.
- Keeney, R.L. and Raiffa, H, (1976). Decisions with multiple objectives. New York: Wiley.
- Konuşkan, Ö. and Uygun, Ö. (2014). Çok nitelikli karar verme (MAUT) yöntemi ve bir uygulaması. ISITES, 2014, 1403-1412.
- Li, X., Wang, K., Liu, L., Xin, J., Yang, H. and Gao, C. (2011). Application of the entropy weight and TOPSIS method in safety evaluation of coal mines. Procedia Engineering, 26, 2085-2091.
- Løken, E. (2007). Use of multicriteria decision analysis methods for energy planning problems. Renewable and sustainable energy reviews, 11(7), 1584-1595.
- Maqbool, A. and Khan, N. Z. (2020). Analyzing barriers for implementation of public health and social measures to prevent the transmission of COVID-19 disease using DEMATEL method. Diabetes & Metabolic Syndrome: Clinical Research & Reviews, 14(5), 887-892.
- Manupati, V. K., Ramkumar, M., Baba, V. and Agarwal, A. (2021). Selection of the best healthcare waste disposal techniques during and post COVID-19 pandemic era. Journal of Cleaner Production, 281, 125175.
- Marti, L. and Puertas, R. (2021). European countries’ vulnerability to COVID-19: Multicriteria decision-making techniques. Economic Research-Ekonomska Istraživanja, 1-12.
- Olson, D.L. (1996) Decision aids for selection problems. New York: Springer.
- Samanlioglu, F. and Kaya, B. E. (2020). Evaluation of the COVID-19 pandemic intervention strategies with hesitant F-AHP. Journal of Healthcare Engineering, 2020.
- Sarwar, A. and Imran, M. (2021). Prioritizing infection prevention and control activities for SARS-CoV-2 (COVID-19): A multi-criteria decision-analysis method. Journal of Healthcare Leadership, 13, 77.
- Shannon, C. E. (1948). A mathematical theory of communication. Bell System Technical Journal, 27, 379–423.
- Shirouyehzad, H., Jouzdani, J. and Khodadadi Karimvand, M. (2020). Fight against COVID-19: A global efficiency evaluation based on contagion control and medical treatment. Journal of Applied Research on Industrial Engineering, 7(2), 109-120.
- Singh, R. and Avikal, S. (2020). COVID-19: A decision-making approach for prioritization of preventive activities. International Journal of Healthcare Management, 13(3), 257-262.
- World Health Organization (2020a). Coronavirus disease 2019 (COVID-19): situationreport,72.WorldHealthOrganization. https://apps.who.int/iris/handle/10665/331685
- World Health Organization (2020b). Coronavirus disease 2019 (COVID-19): situation report, 43. World Health Organization. https://apps.who.int/iris/handle/10665/331354
- World Health Organization (2020c). Novel Coronavirus (2019-nCoV): situation report, 11. World Health Organization. https://apps.who.int/iris/handle/10665/330776
- Wu, J., Sun, J., Liang, L. and Zha, Y. (2011). Determination of weights for ultimate cross efficiency using Shannon entropy. Expert Systems with Applications, 38(5), 5162-5165.
- Zhang, H., Gu, C. L., Gu, L. W. and Zhang, Y. (2011). The evaluation of tourism destination competitiveness by TOPSIS & information entropy–A case in the Yangtze River Delta of China. Tourism Management, 32(2), 443-451.
- Zietsman, J., Rilett, L. R. and Kim, S. J. (2006). Transportation corridor decision-making with multi-attribute utility theory. International Journal of Management and decision making, 7(2-3), 254-266.
Assessment of Selected European and Asian Countries COVID-19 Statuses Using Entropy and MAUT Methods
Abstract
Purpose of this study is to assess selected European and Asian countries COVID-19 statuses by using Entropy and Multi Attribute Utility Theory (MAUT) Multi Criteria Decision Making methods. Data for the research is collected from Our World in Data databases as of April 15th, 2021. In line with the literature, fourteen criteria are selected to make the assessment. Entropy method is used for objectively weighting the criteria that returned following order: population density (15.6%), people fully vac-cinated per hundred (12.1%), total tests per thousand (10.2%), diabetes prevalence (8.9%), positive rate (8.5%), cardiovascular death rate (8.3%), total deaths per million (7.3%), people vaccinated per hundred (6.1%), total cases per million (5.2%), hospital beds per thousand (4.7%), nurses and mid-wives per thousand (4.1%), stringency index (3.4 %), medical Dr. per thousand (3.1%) and share of the population that is 65 years and older (2.6%). After processing countries by using MAUT method with the criteria weights obtained, first five countries are found to be Bahrain, Serbia, Slovakia, Israel and Slovenia, last five countries are Malaysia, Norway, Japan, Finland and South Korea. Implications of the results are discussed and future research areas are suggested.
References
- Albahri, O. S., Al-Obaidi, J. R., Zaidan, A. A., Albahri, A. S., Zaidan, B. B., Salih, M. M. and Zulkifli, C. Z. (2020). Helping doctors hasten COVID-19 treatment: Towards a rescue framework for the transfusion of best convalescent plasma to the most critical patients based on biological requirements via ml and novel MCDM methods. Computer methods and programs in biomedicine, 196, 105617.
- Arsu, T . (2021). Ülkelerin Covid-19 Pandemisine karşı mücadelesinin çok kriterli karar verme yöntemleri ile değerlendirilmesi . Bitlis Eren Üniversitesi İktisadi Ve İdari Bilimler Fakültesi Akademik İzdüşüm Dergisi, 6(1), 128-140.
- Breitenbach, M. C., Ngobeni, V. and Aye, G. C. (2021). Efficiency Of Healthcare Systems In The First Wave Of Covid-19-A Technical Efficiency Analysis. Economic Studies, 30(6).
- Chen, C. H. (2020). A novel multi-criteria decision-making model for building material supplier selection based on entropy-AHP weighted TOPSIS. Entropy, 22(2), 259.
- Çalış Boyacı, A . (2021). Which OECD countries are advantageous in fight against COVID-19? Erciyes Üniversitesi Fen Bilimleri Enstitüsü Fen Bilimleri Dergisi , 37(1) , 137-148 .
- Dowd, J. B., Andriano, L., Brazel, D. M., Rotondi, V., Block, P., Ding, X. and Mills, M. C. (2020). Demographic science aids in understanding the spread and fatality rates of COVID-19. Proceedings of the National Academy of Sciences, 117(18), 9696-9698.
- Erdoğan, N. K., Altinirmak, S., Şahin, C. and Karamaşa, Ç. (2020). Analyzing the financial performance of football clubs listed in BIST using entropy based copras methodology. Dumlupınar Üniversitesi Sosyal Bilimler Dergisi, 63, 39-53.
- Fishburn, P. C. (1967). Additive utilities with finite sets: Applications in the management sciences. Naval Research Logistics Quarterly, 14(1), 1-13.
- Fishburn, P. C. and Keeney, R. L. (1974). Seven independence concepts and continuous multiattribute utility functions. Journal of Mathematical Psychology, 11(3), 294-327.
- Ghasemi, A., Boroumand, Y. and Shirazi, M. (2020), How Do Governments Perform in Facing COVID- 19? , MPRA Pap.
- John Hopkins University Coronavirus Resource Center, 2021. https://coronavirus.jhu.edu/, Retrieved 2021, April 25.
- Keeney, R.L. and Raiffa, H, (1976). Decisions with multiple objectives. New York: Wiley.
- Konuşkan, Ö. and Uygun, Ö. (2014). Çok nitelikli karar verme (MAUT) yöntemi ve bir uygulaması. ISITES, 2014, 1403-1412.
- Li, X., Wang, K., Liu, L., Xin, J., Yang, H. and Gao, C. (2011). Application of the entropy weight and TOPSIS method in safety evaluation of coal mines. Procedia Engineering, 26, 2085-2091.
- Løken, E. (2007). Use of multicriteria decision analysis methods for energy planning problems. Renewable and sustainable energy reviews, 11(7), 1584-1595.
- Maqbool, A. and Khan, N. Z. (2020). Analyzing barriers for implementation of public health and social measures to prevent the transmission of COVID-19 disease using DEMATEL method. Diabetes & Metabolic Syndrome: Clinical Research & Reviews, 14(5), 887-892.
- Manupati, V. K., Ramkumar, M., Baba, V. and Agarwal, A. (2021). Selection of the best healthcare waste disposal techniques during and post COVID-19 pandemic era. Journal of Cleaner Production, 281, 125175.
- Marti, L. and Puertas, R. (2021). European countries’ vulnerability to COVID-19: Multicriteria decision-making techniques. Economic Research-Ekonomska Istraživanja, 1-12.
- Olson, D.L. (1996) Decision aids for selection problems. New York: Springer.
- Samanlioglu, F. and Kaya, B. E. (2020). Evaluation of the COVID-19 pandemic intervention strategies with hesitant F-AHP. Journal of Healthcare Engineering, 2020.
- Sarwar, A. and Imran, M. (2021). Prioritizing infection prevention and control activities for SARS-CoV-2 (COVID-19): A multi-criteria decision-analysis method. Journal of Healthcare Leadership, 13, 77.
- Shannon, C. E. (1948). A mathematical theory of communication. Bell System Technical Journal, 27, 379–423.
- Shirouyehzad, H., Jouzdani, J. and Khodadadi Karimvand, M. (2020). Fight against COVID-19: A global efficiency evaluation based on contagion control and medical treatment. Journal of Applied Research on Industrial Engineering, 7(2), 109-120.
- Singh, R. and Avikal, S. (2020). COVID-19: A decision-making approach for prioritization of preventive activities. International Journal of Healthcare Management, 13(3), 257-262.
- World Health Organization (2020a). Coronavirus disease 2019 (COVID-19): situationreport,72.WorldHealthOrganization. https://apps.who.int/iris/handle/10665/331685
- World Health Organization (2020b). Coronavirus disease 2019 (COVID-19): situation report, 43. World Health Organization. https://apps.who.int/iris/handle/10665/331354
- World Health Organization (2020c). Novel Coronavirus (2019-nCoV): situation report, 11. World Health Organization. https://apps.who.int/iris/handle/10665/330776
- Wu, J., Sun, J., Liang, L. and Zha, Y. (2011). Determination of weights for ultimate cross efficiency using Shannon entropy. Expert Systems with Applications, 38(5), 5162-5165.
- Zhang, H., Gu, C. L., Gu, L. W. and Zhang, Y. (2011). The evaluation of tourism destination competitiveness by TOPSIS & information entropy–A case in the Yangtze River Delta of China. Tourism Management, 32(2), 443-451.
- Zietsman, J., Rilett, L. R. and Kim, S. J. (2006). Transportation corridor decision-making with multi-attribute utility theory. International Journal of Management and decision making, 7(2-3), 254-266.
There are 30 citations in total.
Details
| Primary Language | English |
|---|---|
| Subjects | Operation |
| Journal Section | Articles |
| Authors | |
| Publication Date | December 26, 2021 |
| Acceptance Date | October 18, 2021 |
| Published in Issue | Year 2021 Volume: 18 Issue: 44 |
