Affiliation:
1. Jandarma Genel Komutanlığı
Abstract
Especially countries with large economies can increase their contribution to the global economy by improving their productive capacities. For this, it is of great importance to measure the productive capacity performance of the countries in order to raise awareness about the productive capacity performances of the countries and to create strategies according to the current productive capacity. In this context, the aim of the research is to evaluate the productive capacity performances of 19 countries in the G20 group, which has the world's largest economies, over the values of the United Nationals Conference on Trade and Development (UNCTAD) Productive Capacities Index – PCI components between the years 2000-2018, which is the most recent and current, using the ENTROPI-based TOPSIS method. to measure with. According to the findings, it has been determined that the most important productive capacity component within the scope of the ENTROPY method in terms of countries is "transportation". Afterwards, it was observed that the top three countries with the highest productive capacity performances according to the ENTROPY-based TOPSIS method were Germany, the USA and South Korea. In addition, by calculating the average productive performance value of the countries, it was concluded that the countries with a lower value than the said value should increase their productive capacity performance in order to contribute more to the global economy. Apart from these, the productive capacity performance values of the countries within the scope of the method were measured with some ENTROPI-based Multi-Criteria Decision Making methods (ÇKKV: ARAS, COPRAS, EDAS, WASPAS, ROV, Gray Relational Analysis) and the relations between these values were measured with the Pearson correlation coefficient. According to this measurement, it has been evaluated that PCI can be explained by other ENTROPI-based MCDM methods, especially the ENTROPY-based TOPSIS method.
Publisher
19 Mayis Sosyal Bilimler Dergisi
Reference40 articles.
1. Aksakal, E., Çalışkan, E. (2020). Olimpiyatlarda Aday Şehirlerin Seçim Sürecinde Dİkkate Alınacak Kriterlerin Entropi Yönetimi ile Değerlendirilmesi. M. Kabak, & Y. Çınar içinde, Çok Kriterli Karar Verme Yöntemleri MS Excel Çözümlü Uygulamalar. Ankara: Nobel, 169-179.
2. Ayçin, E. (2019). Çok Kriterli Karar Verme. Ankara: Nobel Yayın.
3. Aytekin, A., Karamaşa, Ç. (2017). Analyzing Financial Performance of Insurance Companies Traded In BIST via Fuzzy Shannon’s Entropy Based Fuzzy TOPSIS Methodology. The Journal of Operations Research, Statistics, Econometrics and Management Information Systems, 5(1), 71-84.
4. Balac, M. (2015). Productive Capacities in Developing Countries Does Foreign Direct Investment Matter?, Unpublished Master's thesis, Universite d'Auvergne, Clermont-Ferrand.
5. Balcerzak, A. P. (2020). Quality of Institutions in the European Union Countries Quality of Institutions in the European Union Application of TOPSIS Based on Entropy Measure for Objective Weighting. Acta Polytechnica Hungarica, 17(1), 101-122.