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G20 GRUBU ÜLKELERİN ÜRETKENLİK KAPASİTESİTELERİNİN DEĞERLENDİRİLMESİ

Year 2022, , 138 - 152, 30.06.2022
https://doi.org/10.52835/19maysbd.1071564

Abstract

Özellikle büyük ekonomilere sahip ülkeler üretim kapasitelerini iyileştirerek küresel ekonomiye katkılarını artırabilmektedirler. Bunun için ülkelerin üretim kapasitesi performansları konusunda farkındalık kazanması ve mevcut üretim kapasitesine göre stratejiler oluşturması için ülkelerin üretim kapasitesi performanslarının ölçümü büyük önem arz etmektedir. Bu kapsamda araştırmanın amacı, dünyanın en büyük ekonomilerine sahip olan G20 grubunda yer alan 19 ülkenin en son ve güncel olan 2000-2018 yıl aralığındaki Birleşmiş Milletler Ticaret ve Kalkınma Konferansı Üretim Kapasitesi Endeksi (PCI) bileşenlerine ait değerler üzerinden üretim kapasitesi performanslarını ENTROPİ tabanlı TOPSIS yöntemi ile ölçmektir. Bulgulara göre, ülkeler açısından ENTROPİ yöntemi kapsamında en önemli üretim kapasitesi bileşeninin ‘‘ulaşım’’ olduğu tespit edilmiştir. Devamında ülkelerin ENTROPİ tabanlı TOPSIS yöntemine göre üretim kapasitesi performansları en fazla olan ilk üç ülkenin Almanya, ABD ve Güney Kore olduğu gözlenmiştir. Ayrıca ülkelerin ortalama üretim performans değeri hesaplanarak söz konusu değerden düşük olan ülkelerin küresel ekonomiye katkılarının daha fazla olması için üretim kapasite performanslarını artırması gerektiği sonucuna ulaşılmıştır. Bunların dışında, yöntem kapsamında ülkelerin üretim kapasite performans değerleri ENTROPİ tabanlı bazı Çok Kriterli Karar Verme yöntemleri (ÇKKV: ARAS, COPRAS, EDAS, WASPAS, ROV, Gri İlişkisel Analiz) ile ölçülerek söz konusu değerler arasındaki ilişkiler Pearson korelasyon katsayısı ile ölçülmüştür. Bu ölçüme göre, PCI’nın başta ENTROPİ tabanlı TOPSIS yöntemi olmak üzere diğer ENTROPİ tabanlı ÇKKV yöntemleri ile açıklanabileceği değerlendirilmiştir.

References

  • 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.
  • Ayçin, E. (2019). Çok Kriterli Karar Verme. Ankara: Nobel Yayın.
  • 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.
  • Balac, M. (2015). Productive Capacities in Developing Countries Does Foreign Direct Investment Matter?, Unpublished Master's thesis, Universite d'Auvergne, Clermont-Ferrand.
  • 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.
  • Barukab, O., Abdullah, S., Ashraf, S., Arif, M., Khan, S. A. (2019). A New Approach to Fuzzy TOPSIS Method Based on Entropy Measure under Spherical Fuzzy Information. Entropy, 21, 1-30.
  • Bulut, Z. A. (2004). İşletmeler Açısından Kapasite Planlaması ve Kapasite Planlamasına Etki eden faktörler. Mevzuat Dergisi(80), 1-10.
  • Chen, P. (2019). Effects of Normalization on the Entropy-based TOPSIS Method. Expert Systems With Applications, 136, 33–41.
  • Cornia, G. A., Scognamillo, A. (2016). Clusters of Least Developed Countries, Their Evolution between 1993 and 2013, and Policies to Expand Their Productive Capacity. Department of Economic & Social Affairs(33), 1-35.
  • Çelikbilek, Y. (2018). Çok Kriterli Karar Verme Yöntemleri. Ankara: Nobel Akademik Yayıncılık.
  • Demiral, M., Demiral, Ö. (2021). Socio economic Productive Capacities and Energy Efficiency: Global Evidence by Income Level and Resource Dependence. Environmental Science and Pollution Research/DOI: 10.1007/s11356-021-17266-z, 1-25.
  • Ding, L., Shao, Z., Zhang, H., Xu, C., Wu, D. (2016). A Comprehensive Evaluation of Urban Sustainable Development in China Based on the TOPSIS-Entropy Method. Sustainability, 8, 1-23.
  • Ecer, F. (2020). Çok Kriterli Karar Verme. Ankara: Seçkin Yayıncılık.
  • ESCAP. (2011). Economic and Social Survey of Asia and The Pacific 2011. Thailand: United Nations publication.
  • Freire, C. (2011). Productive Capacities in Asia and the Pacific. Bangkok: Macroeconomic Policy and Development Division (MPDD).
  • Gnangnon, S. K. (2021). Effect of Productive Capacities on Economic Complexity: Do Aid for Trade flows Matter? Journal of Economic Integration, 36(4), 626-688.
  • Gnangnon, S. K. (2021). Productive Capacities, Economic Growth and Economic Growth Volatility in Developing Countries: Does Structural Economic Vulnerability Matter?, DOI: doi.org/10.1142/S1793993325500012C.
  • González-Blanco, J., Vila-Alonso, M., Guisado-González, M. (2019). Exploring the Complementarity between Foreign Technology, Embedded Technology and Increase of Productive Capacity. Technological and Economic Development of Economy, 25(1), 39–58.
  • Hsu, P.-F., Hsu, M.-G. (2008). Optimizing the Information Outsourcing Practices of Primary Care Medical Organizations Using Entropy and TOPSIS. Quality & Quantity, 42, 181–201.
  • Huang, W., Shuai, B., Sun, Y., Wang, Y., Antwi, E. (2018). Using Entropy-TOPSIS Method to Evaluate Urban Rail Transit System Operation Performance: The China Case. Transportation Research Part, A 111, 292–303.
  • Koç, E., Şenel, M. C., Kaya, K. (2017). Türkiye’de Ekonomik Göstergeler - İmalat Sanayi Kapasite Kullanım Oranı. Mühendis ve Makina, 58(689), 1-22.
  • Li, X., Wang, K., Liu, L., Xin, J., Yang, H., Gao, C. (2011). Application of the Entropy Weight and TOPSIS Method in Safety Evaluation of Coal Mines. Procedia Engineering, 26, 2085-2091.
  • Li, Y., Zhao, L., Suo, J. (2014). Comprehensive Assessment on Sustainable Development of Highway Transportation Capacity Based on Entropy Weight and TOPSIS. Sustainability, 6, 4685-4693.
  • Liu, X., Zhou, X., Zhu, B., He, K., Wang, P. (2019). Measuring the Maturity of Carbon Market in China: An Entropy-Based TOPSIS Approach. Journal of Cleaner Production(229), 94-103.
  • Mian, A., Sufi, A., Verner, E. (2020). How Does Credit Supply Expansion Affect the Real Economy? The Productive Capacity and Household Demand Channels. The Journal of Finance, 75(2), 949-994.
  • Molua, E. L., Benhin, J., Kabubo-Mariara, J., Ouedraogo, M., El-Marsafawy, S. (2010). Global Climate Change and Vulnerability of African Agriculture: Implications for Resilience and Sustained Productive Capacity. Quarterly Journal of International Agriculture , 49(3), 183-211.
  • Olarte, S. H., Villarreal, F., Torrent, J. (2021). Is Productive Capacity A Key Factor to Reduce Inequalities in South America? Development Studies Research, 8(1), 94–108.
  • Öztel, A., Alp, İ. (2020). Çok Kriterli Karar Verme Seçiminde Yeni Bir Yaklaşım. İstanbul: Kriter Yayıncılık.
  • Öztel, A., Aydın, B., Köse, M. (2018). Entropi Tabanlı TOPSIS Yöntemi İle Enerji Sektöründe Kurumsal Sürdürülebilirlik Performansının Ölçümü: Akenerji Örneği. Gümüşhane Üniversitesi Sosyal Bilimler Enstitüsü Elektronik Dergisi, 9(24), 1-24.
  • Paksoy, S. (2017). Çok Kriterli Karar Vermede Güncel Yaklaşımlar. Adana: Karahan Kitapevi.
  • Salim, R. A. (2008). Differentials at Firm Level Productive Capacity Realization in Bangladesh Food Manufacturing: An Empirical Analysis. Applied Economics, 40, 3111–3126.
  • Sun, F., Yu, J. (2021). Improved Energy Performance Evaluating and Ranking Approach for Office Buildings Using Simple-Normalization, Entropy-Based TOPSIS and K-means Method. Energy Reports, 7, s. 1560–1570.
  • Therkildsen, O. (2008). United Nations Conference on Trade and Development (UNCTAD), Background Paper No:1, Geneva. UNCTAD The Least Developed Countries Report 2009: The State and Development Governance.
  • Ulutaş, A., Topal, A. (2020). Bütünleştirilmiş Çok Kriterli Karar Verme Yöntemlerinin Üretim Sektörü Uygulamaları. Ankara: Akademisyen Kitapevi.
  • UNCTAD. (2006). The Least Developed Countries Report 2006: Developing Productive Capacities . New York: United Nations Publication.
  • UNCTAD. (2020). UNCTAD Productive Capacities Index Focus on Landlocked Developing Countries. New York: United Nations Publication.
  • Wilson, J. (2021). Inflation and Productive Capacity - An Empirical Risk Reduction Model. SSRN, 1-14. DOI: https://ssrn.com/abstract=3912154.
  • Yang, W., Xu, K., Lian, J., Ma, C., Bin, L. (2018). Integrated Flood Vulnerability Assessment Approach Based on TOPSIS and Shannon Entropy Methods. Ecological Indicators, 89, 269–280.
  • Zhang, H., Gu, C.-l., Gu, L.-w., 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, 443-451.
  • Zhao, D., Li, C., Wang, Q., Yuan, J. (2020). Comprehensive Evaluation of National Electric Power Development Based on Cloud Model and Entropy Method and TOPSIS: A Case Study in 11 Countries. Journal of Cleaner Production, 277, 1-14.

PRODUCTIVE CAPACITY PERFORMANCE ANALYSIS OF G20 GROUP COUNTRIES: AN APPLICATION WITH ENTROPY BASED TOPSIS METHOD

Year 2022, , 138 - 152, 30.06.2022
https://doi.org/10.52835/19maysbd.1071564

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.

References

  • 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.
  • Ayçin, E. (2019). Çok Kriterli Karar Verme. Ankara: Nobel Yayın.
  • 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.
  • Balac, M. (2015). Productive Capacities in Developing Countries Does Foreign Direct Investment Matter?, Unpublished Master's thesis, Universite d'Auvergne, Clermont-Ferrand.
  • 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.
  • Barukab, O., Abdullah, S., Ashraf, S., Arif, M., Khan, S. A. (2019). A New Approach to Fuzzy TOPSIS Method Based on Entropy Measure under Spherical Fuzzy Information. Entropy, 21, 1-30.
  • Bulut, Z. A. (2004). İşletmeler Açısından Kapasite Planlaması ve Kapasite Planlamasına Etki eden faktörler. Mevzuat Dergisi(80), 1-10.
  • Chen, P. (2019). Effects of Normalization on the Entropy-based TOPSIS Method. Expert Systems With Applications, 136, 33–41.
  • Cornia, G. A., Scognamillo, A. (2016). Clusters of Least Developed Countries, Their Evolution between 1993 and 2013, and Policies to Expand Their Productive Capacity. Department of Economic & Social Affairs(33), 1-35.
  • Çelikbilek, Y. (2018). Çok Kriterli Karar Verme Yöntemleri. Ankara: Nobel Akademik Yayıncılık.
  • Demiral, M., Demiral, Ö. (2021). Socio economic Productive Capacities and Energy Efficiency: Global Evidence by Income Level and Resource Dependence. Environmental Science and Pollution Research/DOI: 10.1007/s11356-021-17266-z, 1-25.
  • Ding, L., Shao, Z., Zhang, H., Xu, C., Wu, D. (2016). A Comprehensive Evaluation of Urban Sustainable Development in China Based on the TOPSIS-Entropy Method. Sustainability, 8, 1-23.
  • Ecer, F. (2020). Çok Kriterli Karar Verme. Ankara: Seçkin Yayıncılık.
  • ESCAP. (2011). Economic and Social Survey of Asia and The Pacific 2011. Thailand: United Nations publication.
  • Freire, C. (2011). Productive Capacities in Asia and the Pacific. Bangkok: Macroeconomic Policy and Development Division (MPDD).
  • Gnangnon, S. K. (2021). Effect of Productive Capacities on Economic Complexity: Do Aid for Trade flows Matter? Journal of Economic Integration, 36(4), 626-688.
  • Gnangnon, S. K. (2021). Productive Capacities, Economic Growth and Economic Growth Volatility in Developing Countries: Does Structural Economic Vulnerability Matter?, DOI: doi.org/10.1142/S1793993325500012C.
  • González-Blanco, J., Vila-Alonso, M., Guisado-González, M. (2019). Exploring the Complementarity between Foreign Technology, Embedded Technology and Increase of Productive Capacity. Technological and Economic Development of Economy, 25(1), 39–58.
  • Hsu, P.-F., Hsu, M.-G. (2008). Optimizing the Information Outsourcing Practices of Primary Care Medical Organizations Using Entropy and TOPSIS. Quality & Quantity, 42, 181–201.
  • Huang, W., Shuai, B., Sun, Y., Wang, Y., Antwi, E. (2018). Using Entropy-TOPSIS Method to Evaluate Urban Rail Transit System Operation Performance: The China Case. Transportation Research Part, A 111, 292–303.
  • Koç, E., Şenel, M. C., Kaya, K. (2017). Türkiye’de Ekonomik Göstergeler - İmalat Sanayi Kapasite Kullanım Oranı. Mühendis ve Makina, 58(689), 1-22.
  • Li, X., Wang, K., Liu, L., Xin, J., Yang, H., Gao, C. (2011). Application of the Entropy Weight and TOPSIS Method in Safety Evaluation of Coal Mines. Procedia Engineering, 26, 2085-2091.
  • Li, Y., Zhao, L., Suo, J. (2014). Comprehensive Assessment on Sustainable Development of Highway Transportation Capacity Based on Entropy Weight and TOPSIS. Sustainability, 6, 4685-4693.
  • Liu, X., Zhou, X., Zhu, B., He, K., Wang, P. (2019). Measuring the Maturity of Carbon Market in China: An Entropy-Based TOPSIS Approach. Journal of Cleaner Production(229), 94-103.
  • Mian, A., Sufi, A., Verner, E. (2020). How Does Credit Supply Expansion Affect the Real Economy? The Productive Capacity and Household Demand Channels. The Journal of Finance, 75(2), 949-994.
  • Molua, E. L., Benhin, J., Kabubo-Mariara, J., Ouedraogo, M., El-Marsafawy, S. (2010). Global Climate Change and Vulnerability of African Agriculture: Implications for Resilience and Sustained Productive Capacity. Quarterly Journal of International Agriculture , 49(3), 183-211.
  • Olarte, S. H., Villarreal, F., Torrent, J. (2021). Is Productive Capacity A Key Factor to Reduce Inequalities in South America? Development Studies Research, 8(1), 94–108.
  • Öztel, A., Alp, İ. (2020). Çok Kriterli Karar Verme Seçiminde Yeni Bir Yaklaşım. İstanbul: Kriter Yayıncılık.
  • Öztel, A., Aydın, B., Köse, M. (2018). Entropi Tabanlı TOPSIS Yöntemi İle Enerji Sektöründe Kurumsal Sürdürülebilirlik Performansının Ölçümü: Akenerji Örneği. Gümüşhane Üniversitesi Sosyal Bilimler Enstitüsü Elektronik Dergisi, 9(24), 1-24.
  • Paksoy, S. (2017). Çok Kriterli Karar Vermede Güncel Yaklaşımlar. Adana: Karahan Kitapevi.
  • Salim, R. A. (2008). Differentials at Firm Level Productive Capacity Realization in Bangladesh Food Manufacturing: An Empirical Analysis. Applied Economics, 40, 3111–3126.
  • Sun, F., Yu, J. (2021). Improved Energy Performance Evaluating and Ranking Approach for Office Buildings Using Simple-Normalization, Entropy-Based TOPSIS and K-means Method. Energy Reports, 7, s. 1560–1570.
  • Therkildsen, O. (2008). United Nations Conference on Trade and Development (UNCTAD), Background Paper No:1, Geneva. UNCTAD The Least Developed Countries Report 2009: The State and Development Governance.
  • Ulutaş, A., Topal, A. (2020). Bütünleştirilmiş Çok Kriterli Karar Verme Yöntemlerinin Üretim Sektörü Uygulamaları. Ankara: Akademisyen Kitapevi.
  • UNCTAD. (2006). The Least Developed Countries Report 2006: Developing Productive Capacities . New York: United Nations Publication.
  • UNCTAD. (2020). UNCTAD Productive Capacities Index Focus on Landlocked Developing Countries. New York: United Nations Publication.
  • Wilson, J. (2021). Inflation and Productive Capacity - An Empirical Risk Reduction Model. SSRN, 1-14. DOI: https://ssrn.com/abstract=3912154.
  • Yang, W., Xu, K., Lian, J., Ma, C., Bin, L. (2018). Integrated Flood Vulnerability Assessment Approach Based on TOPSIS and Shannon Entropy Methods. Ecological Indicators, 89, 269–280.
  • Zhang, H., Gu, C.-l., Gu, L.-w., 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, 443-451.
  • Zhao, D., Li, C., Wang, Q., Yuan, J. (2020). Comprehensive Evaluation of National Electric Power Development Based on Cloud Model and Entropy Method and TOPSIS: A Case Study in 11 Countries. Journal of Cleaner Production, 277, 1-14.
There are 40 citations in total.

Details

Primary Language Turkish
Subjects Business Administration
Journal Section Research Articles
Authors

Furkan Fahri Altıntaş 0000-0002-0161-5862

Publication Date June 30, 2022
Submission Date February 10, 2022
Acceptance Date April 7, 2022
Published in Issue Year 2022

Cite

APA Altıntaş, F. F. (2022). G20 GRUBU ÜLKELERİN ÜRETKENLİK KAPASİTESİTELERİNİN DEĞERLENDİRİLMESİ. 19 Mayıs Sosyal Bilimler Dergisi, 3(2), 138-152. https://doi.org/10.52835/19maysbd.1071564