G20 ÜLKELERİNİN YETENEK REKABETÇİLİĞİ PERFORMANSLARININ ANALİZİ: CRITIC TABANLI COCOSO YÖNTEMİ İLE BİR UYGULAMA

Büyük ekonomilere sahip olan ülkelerin yetenek rekabetçiliği konusundaki faaliyetleri, küresel sermayeyi ve ekonomiye etkileyebilmektedir. Dolayısıyla büyük ekonomilerin yetenek rekabetçiliği performanslarının ölçümü büyük önem arz etmektedir. Bu kapsamda araştırmada, dünyanın en büyük ekonomileri olan G20 grubunda yer alan 19 ülkenin 2021 yılı için Küresel Yetenek Rekabetçilik Endeksi (GTCI) bileşenlerine ait değerler üzerinden ülkelerin yetenek rekabetçiliği performansları CRITIC tabanlı COCOSO yöntemi ölçülmüştür. Bulgulara göre, en iyi yetenek rekabetçiliği performansı gösteren ilk üç ülkenin sırasıyla ABD, Avustralya ve Almanya olduğu tespit edilmiştir. Araştırmada ayrıca CRITIC tabanlı COCOSO yöntemi kapsamında ortalama yetenek rekabetçiliği performans değerlerinin üstünde olan ülkelerin ABD, Avustralya, Almanya, Fransa, Güney Kore ve Çin olduğu belirlenmiştir. Buna göre, ortalama değerin altında kalan ülkelerin küresel ekonomiye olan katkılarını artırmak için yetenek rekabetçiliği performanslarını artırmaları gerektiği sonucuna ulaşılmıştır. Yöntem açısından ise tespit edilen bulguya göre ülkelerin GTCI değerlerinin CRITIC tabanlı COCOSO yöntemi ile genel anlamda açıklanabileceği değerlendirilmiştir.

ANALYSIS OF TALENT COMPETITIVENESS PERFORMANCES OF G20 COUNTRIES: AN APPLICATION WITH CRITIC-BASED COCOSO METHOD

The activities of countries with large economies on talent competitiveness can affect global capital and the economy. Therefore, the measurement of talent competitiveness performances of large economies is of great importance. In this context, the CRITIC-based COCOSO method measured the talent competitiveness performances of 19 countries in the G20 group, the world's largest economies, over the values of the Global Talent Competitiveness Index (GTCI) components for 2021. According to the findings, it has been determined that the top three countries with the best talent competitiveness performance are the USA, Australia and Germany, respectively. In the study, it was also determined that the countries with above average talent competitiveness performance values within the scope of the CRITIC-based COCOSO method are the USA, Australia, Germany, France, South Korea and China. Accordingly, it was concluded that countries below the average value should increase their talent competitiveness performance in order to increase their contribution to the global economy. In terms of the method, it was evaluated that the GTCI values of the countries could be explained in general terms with the CRITIC-based COCOSO method, according to the findings.

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  • Akbulut, O. Y. (2019). CRITIC VE EDAS Yöntemleri ile İş Bankasi’nin 2009-2018 Yılları Arasındaki Performansının Analizi. Ekonomi, Politika & Finans Araştırmaları Dergisi, 4(2), 249-263.
  • Arslan, R. (2020). Critic Yöntemi. H. Bircan içinde, Çok Kriterli Karar Verme Problemlerinde Kriter Ağırlıklandırma Yöntemleri (s. 120-122). Ankara: Nobel Yayıncılık.
  • Ayçin, E. (2019). Çok Kriterli Karar Verme . Ankara: Nobel Yayın.
  • Barua, A., Jeet, S., Bagal, D. K., Satapathy, P., & Agrawal, P. K. (2019). Evaluation of Mechanical Behavior ofHybrid Natural Fiber Reinforced Nano Sic Particles Composite using Hybrid Taguchi-Cocoso Method. International Journal of Innovative Technology and Exploring Engineering, 8(10), 3341-3345.
  • Bayraktutan , Y., & Bıdırdı, H. (2016). Teknoloji ve Rekabetçilik:Temel Kavramlar ve Endeksler Bağlamında Bir Değerlendirme. Akademik Araştırmalar ve Çalışmalar Dergisi, 8(14), 1-24.
  • Buracas, A., & Navickas, V. (2014). Contents of Global Talent Evaluations: Baltics & Serbia. TEM Journal, 3, 1-9.
  • Chen, Y. (2017). Research on the Innovative Ability of Green Chemical Technology in Eastern Region of China - Based on the Perspective of Talent Competitiveness. Chemical Engineering Transactions, 62, 1573-1578.
  • Cunicica, E. (2019). Analysis of Moldova’s Talent Competitiveness Index Based on the Global Talent Competitiveness Index Model. Annals of the Constantin Brâncuşi University of Târgu Jiu, Economy Series(6), 238-243.
  • Diakoulaki, D., Mavratos, G., & Papayannakis, L. (1995). Determining Objective Weights in Multiple Criteria Promlems: The Critic Method. Computers & Operations Researchq, 22(7), 763-770.
  • Du, H., & Xu, Y. (2012). Evaluation on the Talent's Ecological Environmental Competitiveness of Shandong Peninsula Blue Economic Zone. 2012 IEEE International Conference on Computer Science and Automation Engineering). Zhangjiajie, 567-569.
  • Ecer, F. (2020). Çok Kriterli Karar Verme. Ankara: Seçkin Yayıncılık.
  • Hashemkhani Zolfani, S., Chatterjee, P., & Yazdani, M. (2019). A Structured Framework for Sustainable Supplier Selection Using a Combined BWM-COCOSO Model. International Scientific Conference „Contemporary Issues in Business, Management and Economics Engineering (s. 797-804). Vilnius: Vilnius Gediminas Technical University.
  • INSEAD. (2016). The Global Talent Competitiveness Index. Fontainebleau: INSEAD, Adecco, and HCLI.
  • INSEAD. (2016). The JRC Statistical Audit of the Global Talent Competitiveness Index 2017. M. Saisana, W. Becker, & M. Domínguez-Torreiro içinde, The Global Talent Competitiveness Index 2017. Fontainebleau: INSEAD, Adecco, and HCLI, 85-96.
  • INSEAD. (2021). The Global Talent Competitiveness Index 2021: Talent Competitiveness in Times of COVID. Fontainebleau: INSEAD, Portulans Institute, and Accenture.
  • Kazan, H., & Özdemir, Ö. (2014). Financial Performance Assessment of Large Scale Conglomerates via TOPSIS and CRITIC Methods. International Journal of Management and Sustainability, 3(4), 203-224.
  • Kiraci, K., & Bakır, M. (2018). Critic Temelli Edas Yöntemİ İle Havayolu İşletmelerinde Performans Ölçümü Uygulamasi. Pamukkale Üniversitesi Sosyal Bilimler Enstitüsü Dergisi(35), 157-174.
  • Kumar, V., Kalita, K., Chatterjee, P., Zavadskas, E. K., & Chakraborty, S. (2021). A SWARA-CoCoSo-Based Approach for Spray Painting Robot Selection. INFORMATICA(Special Issue), 1–20.
  • Lai, H., Liao, H., Wen, Z., Zavadskas, E. K., & Al-Barakati, A. (2020). An Improved CoCoSo Method with a Maximum Variance Optimization Model for Cloud Service Provider Selection. Inzinerine Ekonomika-Engineering Economics, 31(4), 411–424.
  • Leikuma-Rimicane, L., Komarova, V., Lonska, J., Selivanova-Fyodorova, N., & Ostrovska, I. (2021). The Role of Talent in the Economic Eevelopment of Countries in the Modern World. Entrepreneurship and Sustainability Issues, 9(2), 488-507.
  • Luo, Y., Zhang, X., Qin, Y., Yang, Z., & Liang, Y. (2021). Tourism Attraction Selection with Sentiment Analysis of Online Reviews Based on Probabilistic Linguistic Term Sets and the IDOCRIW-COCOSO Model. Int. J. Fuzzy Syst., 23(1), 295–308.
  • Naqvi, S. R. (2016). Comparison of India and China Based on Global Talent Competitiveness Index. 2nd International Conference on Lates Innovations in Science,Engineering and Management. Goa, 230-238.
  • Ņikadimovs, O., & Ivanchenko, T. (2020). Soft Skills Gap and Improving Business Competitiveness by Managing Talent in the Hospitality Industry. Management Economics & Education , 5(1), 36-48.
  • Oliinyk, O., Bilan, Y., Mishchuk, H., Akimov, O., & Vasa, L. (2021). The Impact of Migration of Highly Skilled Workers on The Country’s Competitiveness and Economic Growth. Montenegrin Journal of Economics, 17(3), 7-19.
  • Özdağoglu, A., Ulutaş, A., & Keleş, M. K. (2020). The Ranking of Turkish Universities with COCOSO and MARCOS. Journal of Economics, Business & Organizastion Research(Özel Sayı), 374-392.
  • Öztel, A., & Alp, İ. (2020). Çok Kriterli Karar Verme Seçiminde Yeni Bir Yaklaşım. İstanbul: Kriter Yayıncılık.
  • Peng, X., Zhang, X., & Luo, Z. (2020). Pythagorean fuzzy MCDM method based on CoCoSo and CRITIC with score function for 5G industry evaluation. Artificial Intelligence Review, 53, 3813–3847.
  • Popović, M. (2021). An MCDM Approach for Personnel Selection Using The COCOSO Method. Journal of Process Management and New Technologies, 9(3-4), 78-88.
  • Satıcı, S. (2021). Ülkelerin İnovasyon Performansının CRITIC Temelli WASPAS Yöntemiyle Değerlendirilmesi. Girişimcilik ve Kalkınma Dergisi |, 16(2), 91-104.
  • Serbana, A., & Andanut, M. (2014). Talent Competitiveness and Competitiveness through Talent. Procedia Economics and Finance, 16, 506–511.
  • Sharma, D., Taggar, R., & Jain, D. (2018). Enhancing Talent Competitiveness in The Technological Era. AIMS Journal of Research, 13(2), 18-22.
  • Shikweni, S., Schurink, W., & Wyk, R. (2019). Talent Management in the South African Construction Industry. HomeSA Journal of Human Resource Management, 17(1), 1-12.
  • Silvanto, S., & Ryan, J. (2018). An Investigation into the Core Appeals for Nation Branding to Attract and Retain Talent to Enhance a Country’s Competitiveness. Competitiveness Review, 28(5), 584-604.
  • Sipa, M. (2019). Diversification of Capabilities of Economies in the Field of Talent Management. Poland Against theBackground of the European Union. European Journal of Sustainable Development, 8(2), 268-278.
  • Topal, A. (2021). Çok Kriterli Karar Verme Analizi ile Elektrik Üretim Şirketlerinin Finansal Performans Analizi: Entropi Tabanlı Cocoso Yöntemi. BMIJ, 9(2), 532-546.
  • Torkayesh, A. E., Ecer, F., Pamucar, D., & Karamaşa, Ç. (2021). Comparative Assessment of Social Sustainability Performance: Integrated Data-driven Weighting System and CoCoSo Model. Sustainable Cities and Society, 71, 1-14.
  • Ulutaş, A., Balo, F., Sua, L., Karabasevic, D., Stanujkic, D., & Popovic, G. (2021). Selection of Insulation Materials with PSI-CRITIC Based CoCoSo Method. Revista de la Construcción, 20(2), 382-392.
  • Xu, X., Arshad, M. A., & Mahmood, A. (2021). Talent Competitiveness Evaluation of the Chongqing Intelligent Industry Based on Using the Entropy TOPSIS Method. Information 2021, 12(288), 1-14.
  • Yazdani, M., Zarate, P., Zavadskas, E., & Turskis, Z. (2019). A Combined Compromise Solution (CoCoSo) Method for Multi-Criteria Decision-Making Problems. Management Decision, 1-19.
  • Zeshuang, L., & Yao, X. (2013). Guan-tian Economic Zone Talent Competitiveness Present Situation. 2013 Fourth International Conference on Digital Manufacturing & Automation. Shangdong: CPS Publisching, 653-656.
  • Zhu, L., & Kong, X. (2018). Research on Evaluation System of University's Talent Competitiveness: A Case Study of 211 Colleges and Universities in Jiangsu Province. Advances in Social Science, Education and Humanities Research, 237, 341-344.