Fighting the Pandemic in OECD Countries: A Comparison in Terms of Resource Efficiency
Year 2024,
, 501 - 520, 31.10.2024
Mustafa Kaya
,
Gülbiye Yenimahalleli Yaşar
Abstract
Purpose: In this study, it is aimed to comparatively examine the resource efficiency of OECD countries in the first year of their fight against the COVID-19 pandemic in terms of monthly and period-long time frames.
Methodology: Data Envelopment Analysis (DEA) was used in the research. With DEA, the efficiency scores of the countries for monthly and period-long time intervals were obtained. Then, super efficiency analysis was conducted to determine the productivity rankings of the countries and the productivity rankings of the countries in the considered time periods were obtained.
Findings: The efficiency of countries in fighting the COVID-19 pandemic has changed over time, and some countries have been seen to fail throughout the process. The USA, Colombia and New Zealand were found to be the most successful countries throughout the process.
Originality: This study differs from other studies in the literature in that it considers many variables that are thought to be effective when fighting the efficiency of OECD countries in fighting the COVID-19 pandemic, examines them at certain time intervals, and determines not only their efficiency but also their efficiency rankings.
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OECD Ülkelerinde Pandemiyle Mücadele: Kaynak Verimliliği Açısından Bir Karşılaştırma
Year 2024,
, 501 - 520, 31.10.2024
Mustafa Kaya
,
Gülbiye Yenimahalleli Yaşar
Abstract
Amaç: Bu çalışmada OECD ülkelerinin COVID-19 pandemisiyle mücadelelerinin ilk bir yıllık sürecindeki kaynak verimliliklerinin aylık ve dönem boyu zaman dilimleri açısından karşılaştırmalı olarak incelenmesi amaçlanmıştır.
Yöntem: Araştırmada Veri Zaflama Analizi (VZA) kullanılmıştır. VZA ile ülkelerin aylık ve dönem boyu zaman aralıklarına ilişkin etkinlik skorları elde edilmiştir. Daha sonra ülkelerin verimlilik sıralamalarını belirlemek amacıyla süper etkinlik analizi yapılmış ve ülkelerin ele alınan zaman dilimlerindeki kendi aralarındaki verimlilik sıraları elde edilmiştir.
Bulgular: Ülkelerin COVID-19 pandemisiyle mücadele etkinlikleri zaman içerisinde değişmiş, bazı ülkelerin süreç boyunca başarısız olduğu görülmüştür. ABD, Kolombiya ve Yeni Zelanda’nın süreç boyunca en başarılı ülkeler olduğu görülmüştür.
Özgünlük: Bu çalışma, OECD ülkelerinin COVID-19 pandemisiyle mücadele verimliliğini karşılaştırırken etkili olacağı düşünülen birçok değişkeni ele alması, belirli zaman aralıklarıyla incelemesi ve sadece verimliliklerinin değil, verimlilik sıralamalarının da belirlenmesi açısından literatürdeki diğer çalışmalardan ayrışmaktadır.
Ethical Statement
Yazarlar tarafından bu çalışmada bilimsel ve etik ilkelere uyulduğu ve yararlanılan tüm çalışmaların kaynakçada belirtildiği beyan edilmiştir.
Supporting Institution
Destekleyen kurum bulunmamaktadır.
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- Atmaca, E., Turan F., Kartal G. ve Çiğdem E.S. (2012). “Ankara ili özel hastanelerinin veri zarflama analizi ile etkinlik ölçümü”, Çukurova Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 16(2), 135-153.
- Ayan, S. (2016). “Veri Zarflama Analizi ile İmalat Sanayi Sektörünün Finansal Performans Etkinliğinin Ölçülmesi: Borsa İstanbul`da Bir Araştırma”, Yayımlanmamış Yüksek Lisans Tezi, Mehmet Akif Ersoy Üniversitesi Sosyal Bilimler Enstitüsü, Burdur.
- Aydın, N., Yurdakul, G. (2020). “Assessing Countries’ Performances Against COVID-19 via WSIDEA and Machine Learning Algorithms”, Applied Soft Computing, 97, 1-18, 106792.
- Bakhshoodeh, M. ve Thomson K.J. (2001). “Input and Output Technical Efficiencies of Wheat Production in Kerman, Iran”, Agricultural Economics, 24(3), 307-313.
- Balmford, B., Annan, J.D., Hargreaves, J.C., Altoe, M., ve Bateman I.J. (2020). “Cross-Country Comparisons of COVID-19: Policy, Politics and the Price of Life” Environmental and Resource Economics, 76(4), 525-551.
- Banker, R.D., Charnes, A. ve Cooper, W.W. (1984). “Some models for estimating technical and scale inefficiencies in data envelopment analysis”, Management Science, 30(9), 1078-1092
- Batty, M. (2020). “The Coronavirus Crisis: What Will the Post-Pandemic City Look Like?”, Environment and Planning B: Urban Analytics and City Science, 47(4), 547-552.
- Bayraktutan, Y ve Pelivanoğlu, F. (2012). “Sağlık İşletmelerinde Etkinlik Analizi: Kocaeli Örneği”, Kocaeli Üniversitesi Sosyal Bilimler Dergisi, 23, 127-162.
- Berkowitz, S.A. ve Basu, S. (2021). “Unemployment Insurance, Health-Related Social Needs, Health Care Access, and Mental Health During the COVID-19 Pandemic”, JAMA Internal Medicine, 181(5), 699-702.
- Breitenbach M.C., Ngobeni, V. ve Aye, G.C. (2021). “Global Healthcare Resource Efficiency in the Management of COVID-19 Death and Infection Prevalence Rates”, Frontiers in Public Health, 9, 638481.
- Cansever, İ.H. ve Şenol, O. (2022). “Gelişmiş ülkelerin sağlık sistemleri verimlilikleri ile COVID-19 performansları ilişkisi üzerine bir araştırma”, Anadolu Üniversitesi Sosyal Bilimler Dergisi, 22(2), 611-628.
- CDC (Centers for Disease Control and Prevention). (2005). “National Strategy for Pandemic Influenza Homeland Security”, https://www.cdc.gov/flu/pandemic-resources/pdf/pandemic-influenza-strategy-2005.pdf, (Erişim Tarihi 07.05.2024).
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- Charnes, A., Cooper, W., Lewin, A.Y. ve Seiford, L.M. (1997). “Data Envelopment Analysis Theory, Methodology and Spplications”, Journal of the Operational Research Society, 48(3), 332-333.
- Chen, C., Shi, Y., Zhang, P. ve Ding, C. (2021a). “A Cross-Country Comparison of Fiscal Policy Responses to the COVID-19 Global Pandemic”, Journal of Comparative Policy Analysis: Research and Practice, 23(2), 262-273.
- Chen, C.W., Lee, S., Dong, M.C. ve Taniguchi, M. (2021b). “What Factors Drive the Satisfaction of Citizens with Governments’ Responses to COVID-19?”, International Journal of Infectious Diseases, 102, 327-331.
- Ciotti, M., Ciccozzi, M., Terrinoni, A., Jiang, W.C., Wang, C.B. ve Bernardini, S. (2020). “The COVID-19 Pandemic”, Critical Reviews in Clinical Laboratory Sciences, 57(6), 365-388.
- Cooper, W.W., Seiford, L.M. ve Zhu J. (2011). “Handbook on Data Envelopment Analysis”. 2nd Ed. Springer, New York.
- Çavmak, Ş. (2017). “Sağlık Hizmetlerinde Veri Zarflama Analizi ve Modelleri”, Sağlık Yönetimi Dergisi, 1(1), 35-47.
- Dağcıoğlu, B.F. ve Keskin, A. (2020).” COVID-19 Pandemisi Sürecinde Türkiye, Avrupa ve Amerika Verilerinin Karşılaştırılması: Kesitsel Bir Çalışma”, Ankara Medical Journal, 20(2), 360-369.
- Dapke, K., Phadke, R., Rocha, I.C.N., Costa A.C.S., Ahmad, S., Essar M.Y., Menon, V., Bassey, E.E., Malhotra, K. ve Shah, J. (2021). “Drug Supply Shortage in India During COVID-19 Pandemic: Efforts and Challenges”, Harvard Public Health Review, 31, DOI:10.54111/0001/EE7
- Das, P., Bisai, S., Ghosh, S. (2021). Impact of Pandemics on Income Inequality: Lessons from the Past”, International Review of Applied Economics, 35(6), 832-850.
- Dinc, M. ve Haynes, K.E. (1999). “Sources of Regional Inefficiency An Integrated Shift-Share, Data Envelopment Analysis and Input-Output Approach”, The Annals of Regional Science, 33(4), 469-489.
- Doğan, M.İ., Özsoy, V.S. ve Örkcü, H.H. (2021). “Performance Management of OECD Countries on Covid-19 Pandemic: A Criticism Using Data Envelopment Analysis Models”, Journal of Facilities Management, 19(4), 479-499.
- Ersoy, Y. ve Aktaş, A. (2022). “Health System Efficiency of OECD Countries with Data Envelopment Analysis”, Problemy Zarządzania - Management İssues, 20(4), 90-109
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