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G7 Ülkeleri Mali Performanslarının CRITIC Esaslı Gri İlişkisel Analiz Yöntemiyle Değerlendirilmesi

Year 2025, Volume: 10 Issue: 2, 727 - 752, 30.06.2025
https://doi.org/10.25229/beta.1625353

Abstract

Bu çalışmanın amacı, 2011-2023 yılları arasında 4 ayrı yıl baz alınarak (2011-2015-2019-2023) G7 ülkelerinin mali performansını ölçmek, sıralamak ve değerlendirmektir. Çalışmada Çok Kriterli Karar Verme tekniklerinden CRITIC esaslı Gri İlişkisel Analiz yöntemi kullanılmıştır. Bu yöntem, karar alıcıların farklı kriterler arasında dengeli bir değerlendirme yapmalarına olanak sağlamaktadır. Mali performansın ölçülmesinde kullanılan kriterler; kamu gelirleri, kamu harcamaları ve kamu borçlarıdır. Yapılan analiz sonucunda elde edilen bulgular; tüm periyotlarda mali performansı en iyi ülkelerin sırasıyla Almanya ve Kanada, en kötü sonuçlara sahip ülkenin ise, tüm periyotlarda Japonya olduğunu göstermektedir. 3-4-5 ve 6. sıradaki ülkeler yıllara göre değişmektedir. Kriter ağırlıklarına göre en önemli değişim, Genel Kamu Gelirleri ve Cari Hesap Dengesi kriterlerinin artan ağırlıklarıdır.

References

  • Afonso, A., Schuknecht, L., & Tanzi, V. (2005). Public sector efficiency: an international comparison. Public Choice, 123, 321-347. https://doi.org/10.1007/s11127-005-7165-2
  • Allen, R., & Tommasi, D. (2001). Managing public expenditure: a reference book for transition countries. OECD Publishing.
  • Aydemir, E., & Şahin, Y. (2019). Evaluation of healthcare service quality factors using grey relational analysis in a dialysis center. Grey Systems: Theory and Application, 9(4), 432-448. https://doi.org/10.1108/GS-01-2019-0001
  • Baležentis, А., Baležentis, T., & Misiūnas, A. (2012). An integrated assessment of lithuanian economic sectors based on financial ratios and fuzzy MCDM methods. Technological and Economic Development of Economy, 18(1), 34-53. https://doi.org/10.3846/20294913.2012.656151
  • Baydaş, M., & Elma, O. E. (2021). An objectıve criteria proposal for the comparison of MCDM and weighting methods in financial performance measurement: An application in Borsa Istanbul. Decision Making: Applications in Management and Engineering, 4(2), 257–279. https://doi.org/10.31181/dmame210402257b
  • Belke, M. (2020). CRITIC ve MAIRCA yöntemleriyle G7 ülkelerinin makroekonomik performansının değerlendirilmesi. İstanbul Ticaret Üniversitesi Sosyal Bilimler Dergisi, 19(Temmuz 2020 (Özel Ek)):120– 139.
  • Bergman, U. M., Hutchison, M. M., & Jensen, S. E. H. (2016). Promoting sustainable public finances in the European Union: The role of fiscal rules and government efficiency. European Journal of Political Economy, 42, 17-35. https://doi.org/10.1016/j.ejpoleco.2016.01.001
  • Blanchard, O. (2019). Public debt and low interest rates. American Economic Review, 109(4), 1197-1229.
  • Bohn, H. (1998). The behavior of U.S. public debt and deficits. The Quarterly Journal of Economics, 113(3), 949-963.
  • Černevičienė, J. and Kabašinskas, A. (2022). Review of multi-criteria decision-making methods in finance using explainable artificial intelligence. Frontiers in Artificial Intelligence, 5. https://doi.org/10.3389/frai.2022.827584
  • Çakır, E., & Akel, G. (2017). Evaluation of service quality of hotel and holiday reservation web sites in Turkey by integrated swara-grey relationship analysis method. PressAcademia Procedia, 3(1), 81-95. https://doi.org/10.17261/Pressacademia.2017.395
  • Deng, J. L. (1982). Control problems of grey systems. Systems & Control Letters.
  • Diakoulaki, D., Mavrotas, G., & Papayannakis, L. (1995), Determining objective weights in multiple criteria problems: The CRITIC method. Computers & Operations Research, 22(7), 763-770. https://doi.org/10.1016/0305-0548(94)00059-H
  • Erdoğan, H., H., & Kırbaç, G. (2021). Financial performance measurement of logistics companies based on entropy and waspas methods. Journal of Business Research-Turk, 13(2), 1093-1106. https://doi.org/10.20491/isarder.2021.1186
  • Ghadikolaei, A., S., & Esbouei, S., K. (2014). Integrating fuzzy ahp and fuzzy aras for evaluating financial performance. Boletim Da Sociedade Paranaense De Matemática, 32(2), 163-174. https://doi.org/10.5269/bspm.v32i2.21378
  • Ghorabaee, M. K., Amiri, M., Zavadskas, E. K., & Antucheviciene, J., (2017). Supplier evaluation and selection using CRITIC–COPRAS framework. Economic Research-Ekonomska Istraživanja, 30(1), 1073-1118. http://dx.doi.org/10.1080/1331677X.2017.1314828
  • He, R. S., & Hwang, S. F. (2007). Damage detection by a hybrid real-parameter genetic algorithm under the assistance of grey relation analysis. Engineering Applications of Artificial Intelligence, 20(7), 980-992. https://doi.org/10.1016/j.engappai.2006.11.020
  • İç, Y., Çelik, B., Kavak, S., & Baki, B. (2020). Development of a multi-criteria decision-making model for comparing the performance of turkish commercial banks. Journal of Advances in Management Research, 18(2), 250-272. https://doi.org/10.1108/jamr-05-2020-0083
  • Javadin, S., R., S., Esbouei, S., K., & Rajabani, N. (2016). An integrated assessment of companies based on value based measures in fuzzy environment. Boletim Da Sociedade Paranaense De Matemática, 34(2), 87-98. https://doi.org/10.5269/bspm.v34i2.27025
  • Johnsen, A. (2005). What does 25 years of experience tell us about the state of performance measurement in public policy and management?. Public Money and Management, 25(1), 9-17. https://doi.org/10.1111/j.1467-9302.2005.00445.x
  • Karaoğlan, S., & Şahin, S. (2018). Bı̇stxkmya işletmelerinin finansal performanslarının çok kriterli karar verme yöntemleri ı̇le ölçümü ve yöntemlerin karşılaştırılması. Ege Akademik Bakış (Ege Academic Review), 18(1), 63-80. https://doi.org/10.21121/eab.2018135912
  • Kaya, H., & Belke, M. (2024). Assessing the fiscal performance of türkiye using a multi- criteria decision making approach. Theory and Applied Fiscal Policy Empirical and Theoretical Studies, Peterlang Publishing. https://doi.org/10.3726/b22634
  • Kazan, H., Ertok, M., & Çiftçi, C. (2015). Application of a hybrid method in the financial analysis of firm performance. Procedia - Social and Behavioral Sciences, 195, 403-412. https://doi.org/10.1016/j.sbspro.2015.06.482
  • Kopits, G., & Symansky, S. (1998). Fiscal policy rules. IMF Occasional Paper, 162.
  • Kou, G., Ergu, D., & Shang, J. (2014). Enhancing data consistency in decision matrix: adapting hadamard model to mitigate judgment contradiction. European Journal of Operational Research, 236(1), 261-271. https://doi.org/10.1016/j.ejor.2013.11.035
  • Kumar, S., & Gulati, R. (2010). Measuring efficiency, effectiveness and performance of Indian public sector banks. International Journal of Productivity and Performance Management, 59(1), 57-74. https://doi.org/10.1108/17410401011006112
  • Kuo, T., & Huang, G. (2008). The use of grey relational analysis in solving multiple attribute decision-making problems. Computers & Industrial Engineering, 55(1), 80-93. https://doi.org/10.1016/j.cie.2007.12.002
  • Liu, D. (2011). E-commerce system security assessment based on grey relational analysis comprehensive evaluation. International Journal of Digital Content Technology and its Applications, 5(10), 279-284.
  • Mikesell, J. L., & Mullins, D. R. (2011). Reforms for improved efficiency in public budgeting and finance: Improvements, disappointments, and work‐in‐progress. Public Budgeting & Finance, 31(4), 1-30. https://doi.org/10.1111/j.1540-5850.2011.00998.x
  • OECD. (2019). Government at a glance. OECD Publishing.
  • Opricovic, S., & Tzeng, G. H. (2004). Compromise solution by MCDM methods: A comparative analysis of VIKOR and TOPSIS. European Journal of Operational Research, 156(2), 445-455. https://doi.org/10.1016/S0377-2217(03)00020-1
  • Ostry, J. D., Ghosh, A. R., & Kim, J. I. (2010). Fiscal space. IMF Staff Position Note, 10/11.
  • Örtlek, Z., Demirtaş, C., & Ilıkkan, Ö., M. (2023). Environmental performance: Evidence from level-2 regions. Fiscaoeconomia, 7(1), 406-443. https://doi.org/10.25295/fsecon.1160081
  • Özdemir, A. I., & Deste M. (2009). Multicriteria supplier selection by grey relational analysis: a case study in automotive industry. Istanbul University Journal of the School of Business Administration, 38(2), 147-156.
  • Reinhart, C. M., & Rogoff, K. S. (2010). Growth in a time of debt. American Economic Review, 100(2), 573-578. https://doi.org/10.1257/aer.100.2.573
  • Smith, P. C., & Street, A. (2005). Measuring the efficiency of public services: the limits of analysis. Journal of the Royal Statistical Society Series A: Statistics in Society, 168(2), 401-417. https://doi.org/10.1111/j.1467-985X.2005.00355.x
  • Şahin, Y., & Aydemir, E. (2019). An AHP-Weighted grey relational analysis method to determine the technical characteristics' importance levels of the smartphone, Eskişehir Osmangazi University Journal of Economics and Administrative Sciences, 14(1), 225-238.
  • Triantaphyllou, E. (2000). Multi-criteria decision making methods: a comparative study. Springer US, 5-21.
  • Turhan, T. & Aydemir, E. (2021). A financial ratio analysis on bist information and technology index (xutek) using ahp-weighted grey relational analysis. Düzce Üniversitesi Bilim ve Teknoloji Dergisi, 9(6), 195-209. https://doi.org/10.29130/dubited.1011252
  • Türegün, N. (2022). Financial performance evaluation by multi-criteria decision-making techniques. Heliyon, 8(5), e09361. https://doi.org/10.1016/j.heliyon.2022.e09361
  • Wang, J. J., Jing, Y. Y., Zhang, C. F., & Zhao, J. H. (2009). Review on multi-criteria decision analysis aid in sustainable energy decision-making. Renewable and Sustainable Energy Reviews,13(9),2263-2278. https://doi.org/10.1016/j.rser.2009.06.021
  • Wang, T. C., & Lee, H. D. (2009). Developing a fuzzy TOPSIS approach based on subjective weights and objective weights. Expert Systems with Applications, 36(5), 8980-8985. https://doi.org/10.1016/j.eswa.2008.11.035
  • Wu, H. Y., Tsai, A., & Wu, H. S. (2019). A hybrid multi-criteria decision analysis approach for environmental performance evaluation: an example of the tft-lcd manufacturers in Taiwan. Environmental Engineering & Management Journal (EEMJ), 18(3), 597-616.
  • Yang C. C., & Chen, B. S. (2006). Supplier selection using combined analytical hierarchy process and grey relational analysis. Journal of Manufacturing Technology Management, 17(7), 926-941. https://doi.org/10.1108/17410380610688241
  • Yeh, C. H., Deng, H., & Chang, Y. H. (2000). Fuzzy multicriteria analysis for performance evaluation. International Journal of Production Economics, 126(3), 459-473. https://doi.org/10.1016/S0377-2217(99)00315-X Zavadskas, E. K., Kaklauskas, A., Peldschus, F., & Turskis, Z. (2007). Multi-Attribute assessment of road design solutions based on the COPRAS method. The Baltic Journal of Road and Bridge Engineering, 2(4), 195-203.
  • Zavadskas, E. K., Turskis, Z., & Tamošaitiene, J. (2010). Risk assessment of construction projects. Journal of Civil Engineering and Management, 16(1), 33–46. https://doi.org/10.3846/jcem.2010.03
  • Zhou, P., Ang, B. W., & Poh, K. L. (2006). Comparing aggregating methods for constructing the composite environmental index: An objective measure. Ecological Economics, 59(3), 305-311.
  • Zopounidis, C., & Doumpos, M. (2002). Multi‐criteria decision aid in financial decision making: methodologies and literature review. Journal of Multi-Criteria Decision Analysis, 11(4-5), 167-186. https://doi.org/10.1002/mcda.333

Assessment of Financial Performances of G7 Countries with CRITIC Based Grey Relational Analysis Method

Year 2025, Volume: 10 Issue: 2, 727 - 752, 30.06.2025
https://doi.org/10.25229/beta.1625353

Abstract

This study aims to assess, rank, and evaluate the fiscal performance of G7 nations over four selected years from 2011 to 2023. Utilizing the CRITIC-based Grey Relational Analysis method—a Multi-Criteria Decision Making technique—this research enables decision-makers to effectively balance evaluations across various criteria. The criteria used for assessing fiscal performance include public revenues, public expenditures, and public debts. The analysis demonstrates that Germany and Canada consistently achieve the best fiscal performance throughout the entire period examined, while Japan is identified as the lowest performer. The rankings for countries in positions three through six fluctuate from year to year. Additionally, a significant shift in criteria weights is observed, highlighting the increasing importance of General Government Revenues and Current Account Balance.

References

  • Afonso, A., Schuknecht, L., & Tanzi, V. (2005). Public sector efficiency: an international comparison. Public Choice, 123, 321-347. https://doi.org/10.1007/s11127-005-7165-2
  • Allen, R., & Tommasi, D. (2001). Managing public expenditure: a reference book for transition countries. OECD Publishing.
  • Aydemir, E., & Şahin, Y. (2019). Evaluation of healthcare service quality factors using grey relational analysis in a dialysis center. Grey Systems: Theory and Application, 9(4), 432-448. https://doi.org/10.1108/GS-01-2019-0001
  • Baležentis, А., Baležentis, T., & Misiūnas, A. (2012). An integrated assessment of lithuanian economic sectors based on financial ratios and fuzzy MCDM methods. Technological and Economic Development of Economy, 18(1), 34-53. https://doi.org/10.3846/20294913.2012.656151
  • Baydaş, M., & Elma, O. E. (2021). An objectıve criteria proposal for the comparison of MCDM and weighting methods in financial performance measurement: An application in Borsa Istanbul. Decision Making: Applications in Management and Engineering, 4(2), 257–279. https://doi.org/10.31181/dmame210402257b
  • Belke, M. (2020). CRITIC ve MAIRCA yöntemleriyle G7 ülkelerinin makroekonomik performansının değerlendirilmesi. İstanbul Ticaret Üniversitesi Sosyal Bilimler Dergisi, 19(Temmuz 2020 (Özel Ek)):120– 139.
  • Bergman, U. M., Hutchison, M. M., & Jensen, S. E. H. (2016). Promoting sustainable public finances in the European Union: The role of fiscal rules and government efficiency. European Journal of Political Economy, 42, 17-35. https://doi.org/10.1016/j.ejpoleco.2016.01.001
  • Blanchard, O. (2019). Public debt and low interest rates. American Economic Review, 109(4), 1197-1229.
  • Bohn, H. (1998). The behavior of U.S. public debt and deficits. The Quarterly Journal of Economics, 113(3), 949-963.
  • Černevičienė, J. and Kabašinskas, A. (2022). Review of multi-criteria decision-making methods in finance using explainable artificial intelligence. Frontiers in Artificial Intelligence, 5. https://doi.org/10.3389/frai.2022.827584
  • Çakır, E., & Akel, G. (2017). Evaluation of service quality of hotel and holiday reservation web sites in Turkey by integrated swara-grey relationship analysis method. PressAcademia Procedia, 3(1), 81-95. https://doi.org/10.17261/Pressacademia.2017.395
  • Deng, J. L. (1982). Control problems of grey systems. Systems & Control Letters.
  • Diakoulaki, D., Mavrotas, G., & Papayannakis, L. (1995), Determining objective weights in multiple criteria problems: The CRITIC method. Computers & Operations Research, 22(7), 763-770. https://doi.org/10.1016/0305-0548(94)00059-H
  • Erdoğan, H., H., & Kırbaç, G. (2021). Financial performance measurement of logistics companies based on entropy and waspas methods. Journal of Business Research-Turk, 13(2), 1093-1106. https://doi.org/10.20491/isarder.2021.1186
  • Ghadikolaei, A., S., & Esbouei, S., K. (2014). Integrating fuzzy ahp and fuzzy aras for evaluating financial performance. Boletim Da Sociedade Paranaense De Matemática, 32(2), 163-174. https://doi.org/10.5269/bspm.v32i2.21378
  • Ghorabaee, M. K., Amiri, M., Zavadskas, E. K., & Antucheviciene, J., (2017). Supplier evaluation and selection using CRITIC–COPRAS framework. Economic Research-Ekonomska Istraživanja, 30(1), 1073-1118. http://dx.doi.org/10.1080/1331677X.2017.1314828
  • He, R. S., & Hwang, S. F. (2007). Damage detection by a hybrid real-parameter genetic algorithm under the assistance of grey relation analysis. Engineering Applications of Artificial Intelligence, 20(7), 980-992. https://doi.org/10.1016/j.engappai.2006.11.020
  • İç, Y., Çelik, B., Kavak, S., & Baki, B. (2020). Development of a multi-criteria decision-making model for comparing the performance of turkish commercial banks. Journal of Advances in Management Research, 18(2), 250-272. https://doi.org/10.1108/jamr-05-2020-0083
  • Javadin, S., R., S., Esbouei, S., K., & Rajabani, N. (2016). An integrated assessment of companies based on value based measures in fuzzy environment. Boletim Da Sociedade Paranaense De Matemática, 34(2), 87-98. https://doi.org/10.5269/bspm.v34i2.27025
  • Johnsen, A. (2005). What does 25 years of experience tell us about the state of performance measurement in public policy and management?. Public Money and Management, 25(1), 9-17. https://doi.org/10.1111/j.1467-9302.2005.00445.x
  • Karaoğlan, S., & Şahin, S. (2018). Bı̇stxkmya işletmelerinin finansal performanslarının çok kriterli karar verme yöntemleri ı̇le ölçümü ve yöntemlerin karşılaştırılması. Ege Akademik Bakış (Ege Academic Review), 18(1), 63-80. https://doi.org/10.21121/eab.2018135912
  • Kaya, H., & Belke, M. (2024). Assessing the fiscal performance of türkiye using a multi- criteria decision making approach. Theory and Applied Fiscal Policy Empirical and Theoretical Studies, Peterlang Publishing. https://doi.org/10.3726/b22634
  • Kazan, H., Ertok, M., & Çiftçi, C. (2015). Application of a hybrid method in the financial analysis of firm performance. Procedia - Social and Behavioral Sciences, 195, 403-412. https://doi.org/10.1016/j.sbspro.2015.06.482
  • Kopits, G., & Symansky, S. (1998). Fiscal policy rules. IMF Occasional Paper, 162.
  • Kou, G., Ergu, D., & Shang, J. (2014). Enhancing data consistency in decision matrix: adapting hadamard model to mitigate judgment contradiction. European Journal of Operational Research, 236(1), 261-271. https://doi.org/10.1016/j.ejor.2013.11.035
  • Kumar, S., & Gulati, R. (2010). Measuring efficiency, effectiveness and performance of Indian public sector banks. International Journal of Productivity and Performance Management, 59(1), 57-74. https://doi.org/10.1108/17410401011006112
  • Kuo, T., & Huang, G. (2008). The use of grey relational analysis in solving multiple attribute decision-making problems. Computers & Industrial Engineering, 55(1), 80-93. https://doi.org/10.1016/j.cie.2007.12.002
  • Liu, D. (2011). E-commerce system security assessment based on grey relational analysis comprehensive evaluation. International Journal of Digital Content Technology and its Applications, 5(10), 279-284.
  • Mikesell, J. L., & Mullins, D. R. (2011). Reforms for improved efficiency in public budgeting and finance: Improvements, disappointments, and work‐in‐progress. Public Budgeting & Finance, 31(4), 1-30. https://doi.org/10.1111/j.1540-5850.2011.00998.x
  • OECD. (2019). Government at a glance. OECD Publishing.
  • Opricovic, S., & Tzeng, G. H. (2004). Compromise solution by MCDM methods: A comparative analysis of VIKOR and TOPSIS. European Journal of Operational Research, 156(2), 445-455. https://doi.org/10.1016/S0377-2217(03)00020-1
  • Ostry, J. D., Ghosh, A. R., & Kim, J. I. (2010). Fiscal space. IMF Staff Position Note, 10/11.
  • Örtlek, Z., Demirtaş, C., & Ilıkkan, Ö., M. (2023). Environmental performance: Evidence from level-2 regions. Fiscaoeconomia, 7(1), 406-443. https://doi.org/10.25295/fsecon.1160081
  • Özdemir, A. I., & Deste M. (2009). Multicriteria supplier selection by grey relational analysis: a case study in automotive industry. Istanbul University Journal of the School of Business Administration, 38(2), 147-156.
  • Reinhart, C. M., & Rogoff, K. S. (2010). Growth in a time of debt. American Economic Review, 100(2), 573-578. https://doi.org/10.1257/aer.100.2.573
  • Smith, P. C., & Street, A. (2005). Measuring the efficiency of public services: the limits of analysis. Journal of the Royal Statistical Society Series A: Statistics in Society, 168(2), 401-417. https://doi.org/10.1111/j.1467-985X.2005.00355.x
  • Şahin, Y., & Aydemir, E. (2019). An AHP-Weighted grey relational analysis method to determine the technical characteristics' importance levels of the smartphone, Eskişehir Osmangazi University Journal of Economics and Administrative Sciences, 14(1), 225-238.
  • Triantaphyllou, E. (2000). Multi-criteria decision making methods: a comparative study. Springer US, 5-21.
  • Turhan, T. & Aydemir, E. (2021). A financial ratio analysis on bist information and technology index (xutek) using ahp-weighted grey relational analysis. Düzce Üniversitesi Bilim ve Teknoloji Dergisi, 9(6), 195-209. https://doi.org/10.29130/dubited.1011252
  • Türegün, N. (2022). Financial performance evaluation by multi-criteria decision-making techniques. Heliyon, 8(5), e09361. https://doi.org/10.1016/j.heliyon.2022.e09361
  • Wang, J. J., Jing, Y. Y., Zhang, C. F., & Zhao, J. H. (2009). Review on multi-criteria decision analysis aid in sustainable energy decision-making. Renewable and Sustainable Energy Reviews,13(9),2263-2278. https://doi.org/10.1016/j.rser.2009.06.021
  • Wang, T. C., & Lee, H. D. (2009). Developing a fuzzy TOPSIS approach based on subjective weights and objective weights. Expert Systems with Applications, 36(5), 8980-8985. https://doi.org/10.1016/j.eswa.2008.11.035
  • Wu, H. Y., Tsai, A., & Wu, H. S. (2019). A hybrid multi-criteria decision analysis approach for environmental performance evaluation: an example of the tft-lcd manufacturers in Taiwan. Environmental Engineering & Management Journal (EEMJ), 18(3), 597-616.
  • Yang C. C., & Chen, B. S. (2006). Supplier selection using combined analytical hierarchy process and grey relational analysis. Journal of Manufacturing Technology Management, 17(7), 926-941. https://doi.org/10.1108/17410380610688241
  • Yeh, C. H., Deng, H., & Chang, Y. H. (2000). Fuzzy multicriteria analysis for performance evaluation. International Journal of Production Economics, 126(3), 459-473. https://doi.org/10.1016/S0377-2217(99)00315-X Zavadskas, E. K., Kaklauskas, A., Peldschus, F., & Turskis, Z. (2007). Multi-Attribute assessment of road design solutions based on the COPRAS method. The Baltic Journal of Road and Bridge Engineering, 2(4), 195-203.
  • Zavadskas, E. K., Turskis, Z., & Tamošaitiene, J. (2010). Risk assessment of construction projects. Journal of Civil Engineering and Management, 16(1), 33–46. https://doi.org/10.3846/jcem.2010.03
  • Zhou, P., Ang, B. W., & Poh, K. L. (2006). Comparing aggregating methods for constructing the composite environmental index: An objective measure. Ecological Economics, 59(3), 305-311.
  • Zopounidis, C., & Doumpos, M. (2002). Multi‐criteria decision aid in financial decision making: methodologies and literature review. Journal of Multi-Criteria Decision Analysis, 11(4-5), 167-186. https://doi.org/10.1002/mcda.333
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Details

Primary Language Turkish
Subjects Policy of Treasury, Public Economy
Journal Section Research Article
Authors

Uğur Çiçek 0000-0003-1357-2561

Submission Date January 22, 2025
Acceptance Date May 17, 2025
Early Pub Date June 30, 2025
Publication Date June 30, 2025
Published in Issue Year 2025 Volume: 10 Issue: 2

Cite

APA Çiçek, U. (2025). G7 Ülkeleri Mali Performanslarının CRITIC Esaslı Gri İlişkisel Analiz Yöntemiyle Değerlendirilmesi. Bulletin of Economic Theory and Analysis, 10(2), 727-752. https://doi.org/10.25229/beta.1625353

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