Araştırma Makalesi
BibTex RIS Kaynak Göster

RANKING OF THE MEMBER COUNTRIES IN THE BLACK SEA ECONOMIC COOPERATION ORGANIZATION USING MULTI-CRITERIA DECISION-MAKING METHODS

Yıl 2024, Cilt: 12 Sayı: 2, 326 - 343, 01.06.2024
https://doi.org/10.36306/konjes.1328033

Öz

The objective of the study is to measure and rank the performance of the Black Sea Economic Cooperation Organization (BSECO) member countries for the different four years using Multi-Criteria Decision Making (MCDM) techniques widely used in performance measurement. This is the first study using CRITIC (Criteria Importance through Intercritera Correlation), COPRAS (Compress PRoportional ASssessment- Complex Relative Assessment) and Borda Count Methods to rank countries on basic energy indicators using MCDM. The CRITIC method was used to calculate the critical weights of the criteria established in the first stage of the three-stage work. It is an objective method of MCDM. The performance of BSECO member countries is ranked using the COPRAS method. The weights calculated in the second stage are used for the ranking. In the last stage, using the Borda count method, which is a data fusion technique, a single ranking was obtained by integrating the rankings obtained under different scenarios. According to this result, Albania was the first, Georgia was the second and Armenia was the third. The last place was taken by Türkiye. Thus, MCDM techniques can provide effective and comprehensive results in this kind of problems. It can be observed that the unbiased results are objective measures of the criteria used.

Kaynakça

  • International Energy Agency, “Energy Efficiency Indicators data collection.” Available: https://www.iea.org/media/training/presentations/escoct2013/Presentation_Energy_Efficiency_Indicators.pdf [Accessed: July 24, 2018].
  • F. Unander, “Energy indicators and sustainable development: The International Energy Agency approach,” Natural Resources Forum, vol. 29, pp. 377–391, 2005.
  • R. Ramanathan, “A multi- factor efficiency perspective to the relationships among world GDP, energy consumption, and carbondioxide emissions,” Technological Forecasting and Social Change, vol. 73, no. 5, pp. 483- 494, 2006.
  • A. Sözen, and M. Nalbant, “Situation of Turkey’s energy indicators among the EU member states,” Energy Policy, vol. 35, no. 10, pp. 4993- 5002, 2007.
  • G. Liu, “Development of a general sustainability indicator for renewable energy systems: A review,” Renewable and Sustainable Energy Reviews, vol. 31, pp. 611-621, 2014.
  • G. S. Mensah, F. Kemausuor, and A. Brew-Hammond, “Energy access indicators and trends in Ghana,” Renewable and Sustainable Energy Reviews, vol. 30, pp. 317- 323, 2014.
  • I. Iddrisu, and S. C. Bhattacharyya, “Sustainable energy development index: a multi-dimensional indicator for measuring sustainable energy development,” Renewable and Sustainable Energy Reviews, vol. 50, pp. 513-530, 2015.
  • M. T. Garcia-Alvarez, B. Moreno, and I. Soares, “Analyzing the sustainable energy development in the EU-15 by an aggregated synthetic index,” Ecological Indicators, vol. 60, pp. 996-1007, 2016.
  • P. Ogonowski, “Application of VMCM, to assess of renewable energy impact in European Union Countries,” Procedia Computer Science, vol. 192, pp. 4762-4769, 2021.
  • M. Kamali Saraji, D. Streimikiene, and R. Ciegis, “A novel Pythagorean fuzzy-SWARA-TOPSIS framework for evaluating the EU progress towards sustainable energy development,” Environmental Monitoring and Assessment, vol. 194, no. 42, pp. 1-19, 2022.
  • H. Hasheminasab, D. Streimikiene, and M. Pishahang, “A novel energy poverty evaluation: Study of the European Union countries,” Energy, vol. 264, pp. 1-9, 2023.
  • A. Sarucan, M. E. Baysal, and O. Engin, “A spherical fuzzy TOPSIS method for solving the physician selection problem,” Journal of Intelligent & Fuzzy Systems, vol. 42, pp. 181-194, 2022.
  • A. Sarucan, M. E. Baysal, and O. Engin, “Physician selection with a neutrosophic multi-criteria decision making method,” Intelligent and Fuzzy Techniques: Smart and Innovative Solutions- Proceedings of the INFUS 2020 Conference, 2021, pp. 319-327.
  • T. Ertay, C. Kahraman, and I. Kaya, “Evaluation of renewable energy alternatives using MACBETH and fuzzy AHP multicriteria methods: the case of Turkey,” Technological and Economic Development of Economy, vol. 19, no. 1, pp. 38- 62, 2013.
  • E. Wang, “Benchmarking whole-building energy performance with multi-criteria technique for order preference by similarity to ideal solution using a selective objective-weighting approach,” Applied Energy, vol. 146, pp. 92- 103, 2015.
  • S. Malkawi, M. Al-Nimr, and D. Azizi, “A multi-criteria optimization analysis for Jordan’s energy mix,” Energy, vol. 127, pp. 680- 969, 2017.
  • B. Cayir Ervural, R. Evren, and D. Delen, “A multi-objective decision-making approach for sustainable energy investment planning,” Renewable Energy, vol. 126, pp. 387- 402, 2018.
  • G. Vasic, “Application of multi criteria analysis in the design of energy policy: space and water heating in households-city Novi Sad, Serbia,” Energy Policy, vol. 113, pp. 410-419, 2018.
  • A. Sarucan, M. E. Baysal, and O. Engin, “A comparison of member countries in black sea economic cooperation organization with COPRAS method in terms of basic energy ındicators,” International GAP Renewable Energy and Energy Efficiency Congress-GAPYENEV, 2018, pp. 109-113.
  • O. Engin, A. Sarucan, and M. E. Baysal, “Analysis of renewable energy alternatives with the multi-criteria decision making methods for Turkey,” Journal of Social and Humanities Science Research, vol. 5, no. 23, pp. 1223-1231, 2018.
  • F. Rao, Y. M. Tang, K. Y. Chau, W. Iqbal, and M. Abbas, “Assessment of energy poverty and key influencing factors in N11 countries,” Sustainable Production and Consumption, vol. 30, pp. 1- 15, 2022.
  • S. T. Onifade, “Environmental impacts of energy indicators on ecological footprints of oil-exporting African countries: Perspectives on fossil resources abundance amidst sustainable development quests,” Resources Policy, vol. 82, 103481, 2023.
  • Organization of the Black Sea Economic Cooperation, Available: http://www.bsec-organization.org/ [Accessed: March 09, 2023].
  • Republic of Turkey Ministry of Foreign Affairs, Available: http://www.mfa.gov.tr/the-black-sea-economic-cooperation-organization-_bsec_.en.mfa [Accessed: March 09, 2023].
  • D. Diakoulaki, G. Mavrotas, and L. Papayannakis, “Determining objective weights in multiple criteria problems: the CRITIC method,” Computers & Operations Research, vol. 22, no. 7, pp. 763-770, 1995.
  • C. Guo, Y. Wang, and W. Jiang, “An empirical study of evaluation index system and measure method on city’s soft power: 17 cities in Shandong Province,” Cross-Cultural Communication, vol. 9, no. 6, pp. 27-31, 2013.
  • A. Jahan, F. Mustapha, S. M. Sapuan, M. Y. Ismail, and M. Bahraminasab, “A framework for weighting of criteria in ranking stage of material selection process,” The International Journal of Advanced Manufacturing Technology, vol. 58, pp. 411–420, 2012.
  • N. Ersoy, “Measuring corporate sustainability performance in the rubber coating industry: an integrated multicriterion framework,” The Online Journal of Science and Technology, vol. 7, no. 4, pp. 146-161, 2017.
  • V. Podvezko, “The comparative analysis of MCDA methods SAW and COPRAS,” Engineering Economics, vol. 22, no. 2, pp. 134-146, 2011.
  • A. Bakhouyi, R. Dehbi, and M. Talea, “Multiple criteria comparative evaluation on the interoperability of LMS by applying COPRAS method,” 2016 Future Technologies Conference (FTC), 2016, pp. 361-366.
  • N. Kundakçı, and A. Tuş Işık, “Integration of MACBETH and COPRAS methods to select air compressor for a textile company,” Decision Science Letters, vol. 5, no. 3, pp. 381-394, 2016.
  • C. Şahin, and A. Öztel, “Comparative analysis of habitability levels of countries with COPRAS method: BRICS countries and Turkey,” International Journal of Western Black Sea Social and Humanities Sciences, vol. 1, no. 1, pp. 75-84, 2017.
  • C. Lamboray, “A comparison between the prudent order and the ranking obtained with Borda’s, Copeland’s, Slater’s and Kemeny’s rules,” Mathematical Social Sciences, vol. 54, pp. 1-16, 2007.
  • R. Nuray, and F. Can, “Automatic ranking of information retrieval systems using data fusion,” Information Processing and Management, vol. 42, no. 3, pp. 595-614, 2006.
  • J. Asafu-Adjaye, “The relationship between energy consumption, energy prices, and economic growth: time series evidence from Asian developing countries,” Energy Economics, vol. 22, no. 6, pp. 615-625, 2000.
  • P. Mozumder, and A. Marathe, “Causality relationship between electricity consumption and GDP in Bangladesh,” Energy Policy, vol. 35, no. 1, pp. 395-402, 2007.
  • A. Belke, F. Dobnik, and C. Dreger, “Energy consumption and economic growth – new insights into the cointegration relationship,” Energy Economics, vol. 33, no. 5, pp. 782-789, 2011.
  • M. Gök, “Ranking G20 countries with regard to energy indicators via multiple criteria decision making techniques,” M. S. thesis, Ankara University, Ankara, 2015.
  • International Energy Agency, “Key world energy statistics, 2017.” Available: http://www.iea.org/statistics/statisticssearch/report/?country=TURKEY&product=indicators&year=2010 [Accessed: July 26, 2018].
  • Y. M. Wang, and Y. Luo, “Integration of correlations with standard deviationsfor determining attribute weights in multiple attribute decision making,” Mathematical and Computer Modeling, vol. 51, no. 12, pp. 1-12, 2010.
  • M. T. Sarımermer, “Girişim sermayesi yatırım ortaklıklarının finansal performanslarının CRITIC ve PROMETHEE yöntemleriyle değerlendirilmesi,” M. S. thesis, Marmara University, İstanbul, 2022.
  • J. Ramík, and R. Perzina, “A method for solving fuzzy multicriteria decision problems with dependent criteria,” Fuzzy Optimization and Decision Making, vol. 9 pp. 123–141, 2010.
Yıl 2024, Cilt: 12 Sayı: 2, 326 - 343, 01.06.2024
https://doi.org/10.36306/konjes.1328033

Öz

Kaynakça

  • International Energy Agency, “Energy Efficiency Indicators data collection.” Available: https://www.iea.org/media/training/presentations/escoct2013/Presentation_Energy_Efficiency_Indicators.pdf [Accessed: July 24, 2018].
  • F. Unander, “Energy indicators and sustainable development: The International Energy Agency approach,” Natural Resources Forum, vol. 29, pp. 377–391, 2005.
  • R. Ramanathan, “A multi- factor efficiency perspective to the relationships among world GDP, energy consumption, and carbondioxide emissions,” Technological Forecasting and Social Change, vol. 73, no. 5, pp. 483- 494, 2006.
  • A. Sözen, and M. Nalbant, “Situation of Turkey’s energy indicators among the EU member states,” Energy Policy, vol. 35, no. 10, pp. 4993- 5002, 2007.
  • G. Liu, “Development of a general sustainability indicator for renewable energy systems: A review,” Renewable and Sustainable Energy Reviews, vol. 31, pp. 611-621, 2014.
  • G. S. Mensah, F. Kemausuor, and A. Brew-Hammond, “Energy access indicators and trends in Ghana,” Renewable and Sustainable Energy Reviews, vol. 30, pp. 317- 323, 2014.
  • I. Iddrisu, and S. C. Bhattacharyya, “Sustainable energy development index: a multi-dimensional indicator for measuring sustainable energy development,” Renewable and Sustainable Energy Reviews, vol. 50, pp. 513-530, 2015.
  • M. T. Garcia-Alvarez, B. Moreno, and I. Soares, “Analyzing the sustainable energy development in the EU-15 by an aggregated synthetic index,” Ecological Indicators, vol. 60, pp. 996-1007, 2016.
  • P. Ogonowski, “Application of VMCM, to assess of renewable energy impact in European Union Countries,” Procedia Computer Science, vol. 192, pp. 4762-4769, 2021.
  • M. Kamali Saraji, D. Streimikiene, and R. Ciegis, “A novel Pythagorean fuzzy-SWARA-TOPSIS framework for evaluating the EU progress towards sustainable energy development,” Environmental Monitoring and Assessment, vol. 194, no. 42, pp. 1-19, 2022.
  • H. Hasheminasab, D. Streimikiene, and M. Pishahang, “A novel energy poverty evaluation: Study of the European Union countries,” Energy, vol. 264, pp. 1-9, 2023.
  • A. Sarucan, M. E. Baysal, and O. Engin, “A spherical fuzzy TOPSIS method for solving the physician selection problem,” Journal of Intelligent & Fuzzy Systems, vol. 42, pp. 181-194, 2022.
  • A. Sarucan, M. E. Baysal, and O. Engin, “Physician selection with a neutrosophic multi-criteria decision making method,” Intelligent and Fuzzy Techniques: Smart and Innovative Solutions- Proceedings of the INFUS 2020 Conference, 2021, pp. 319-327.
  • T. Ertay, C. Kahraman, and I. Kaya, “Evaluation of renewable energy alternatives using MACBETH and fuzzy AHP multicriteria methods: the case of Turkey,” Technological and Economic Development of Economy, vol. 19, no. 1, pp. 38- 62, 2013.
  • E. Wang, “Benchmarking whole-building energy performance with multi-criteria technique for order preference by similarity to ideal solution using a selective objective-weighting approach,” Applied Energy, vol. 146, pp. 92- 103, 2015.
  • S. Malkawi, M. Al-Nimr, and D. Azizi, “A multi-criteria optimization analysis for Jordan’s energy mix,” Energy, vol. 127, pp. 680- 969, 2017.
  • B. Cayir Ervural, R. Evren, and D. Delen, “A multi-objective decision-making approach for sustainable energy investment planning,” Renewable Energy, vol. 126, pp. 387- 402, 2018.
  • G. Vasic, “Application of multi criteria analysis in the design of energy policy: space and water heating in households-city Novi Sad, Serbia,” Energy Policy, vol. 113, pp. 410-419, 2018.
  • A. Sarucan, M. E. Baysal, and O. Engin, “A comparison of member countries in black sea economic cooperation organization with COPRAS method in terms of basic energy ındicators,” International GAP Renewable Energy and Energy Efficiency Congress-GAPYENEV, 2018, pp. 109-113.
  • O. Engin, A. Sarucan, and M. E. Baysal, “Analysis of renewable energy alternatives with the multi-criteria decision making methods for Turkey,” Journal of Social and Humanities Science Research, vol. 5, no. 23, pp. 1223-1231, 2018.
  • F. Rao, Y. M. Tang, K. Y. Chau, W. Iqbal, and M. Abbas, “Assessment of energy poverty and key influencing factors in N11 countries,” Sustainable Production and Consumption, vol. 30, pp. 1- 15, 2022.
  • S. T. Onifade, “Environmental impacts of energy indicators on ecological footprints of oil-exporting African countries: Perspectives on fossil resources abundance amidst sustainable development quests,” Resources Policy, vol. 82, 103481, 2023.
  • Organization of the Black Sea Economic Cooperation, Available: http://www.bsec-organization.org/ [Accessed: March 09, 2023].
  • Republic of Turkey Ministry of Foreign Affairs, Available: http://www.mfa.gov.tr/the-black-sea-economic-cooperation-organization-_bsec_.en.mfa [Accessed: March 09, 2023].
  • D. Diakoulaki, G. Mavrotas, and L. Papayannakis, “Determining objective weights in multiple criteria problems: the CRITIC method,” Computers & Operations Research, vol. 22, no. 7, pp. 763-770, 1995.
  • C. Guo, Y. Wang, and W. Jiang, “An empirical study of evaluation index system and measure method on city’s soft power: 17 cities in Shandong Province,” Cross-Cultural Communication, vol. 9, no. 6, pp. 27-31, 2013.
  • A. Jahan, F. Mustapha, S. M. Sapuan, M. Y. Ismail, and M. Bahraminasab, “A framework for weighting of criteria in ranking stage of material selection process,” The International Journal of Advanced Manufacturing Technology, vol. 58, pp. 411–420, 2012.
  • N. Ersoy, “Measuring corporate sustainability performance in the rubber coating industry: an integrated multicriterion framework,” The Online Journal of Science and Technology, vol. 7, no. 4, pp. 146-161, 2017.
  • V. Podvezko, “The comparative analysis of MCDA methods SAW and COPRAS,” Engineering Economics, vol. 22, no. 2, pp. 134-146, 2011.
  • A. Bakhouyi, R. Dehbi, and M. Talea, “Multiple criteria comparative evaluation on the interoperability of LMS by applying COPRAS method,” 2016 Future Technologies Conference (FTC), 2016, pp. 361-366.
  • N. Kundakçı, and A. Tuş Işık, “Integration of MACBETH and COPRAS methods to select air compressor for a textile company,” Decision Science Letters, vol. 5, no. 3, pp. 381-394, 2016.
  • C. Şahin, and A. Öztel, “Comparative analysis of habitability levels of countries with COPRAS method: BRICS countries and Turkey,” International Journal of Western Black Sea Social and Humanities Sciences, vol. 1, no. 1, pp. 75-84, 2017.
  • C. Lamboray, “A comparison between the prudent order and the ranking obtained with Borda’s, Copeland’s, Slater’s and Kemeny’s rules,” Mathematical Social Sciences, vol. 54, pp. 1-16, 2007.
  • R. Nuray, and F. Can, “Automatic ranking of information retrieval systems using data fusion,” Information Processing and Management, vol. 42, no. 3, pp. 595-614, 2006.
  • J. Asafu-Adjaye, “The relationship between energy consumption, energy prices, and economic growth: time series evidence from Asian developing countries,” Energy Economics, vol. 22, no. 6, pp. 615-625, 2000.
  • P. Mozumder, and A. Marathe, “Causality relationship between electricity consumption and GDP in Bangladesh,” Energy Policy, vol. 35, no. 1, pp. 395-402, 2007.
  • A. Belke, F. Dobnik, and C. Dreger, “Energy consumption and economic growth – new insights into the cointegration relationship,” Energy Economics, vol. 33, no. 5, pp. 782-789, 2011.
  • M. Gök, “Ranking G20 countries with regard to energy indicators via multiple criteria decision making techniques,” M. S. thesis, Ankara University, Ankara, 2015.
  • International Energy Agency, “Key world energy statistics, 2017.” Available: http://www.iea.org/statistics/statisticssearch/report/?country=TURKEY&product=indicators&year=2010 [Accessed: July 26, 2018].
  • Y. M. Wang, and Y. Luo, “Integration of correlations with standard deviationsfor determining attribute weights in multiple attribute decision making,” Mathematical and Computer Modeling, vol. 51, no. 12, pp. 1-12, 2010.
  • M. T. Sarımermer, “Girişim sermayesi yatırım ortaklıklarının finansal performanslarının CRITIC ve PROMETHEE yöntemleriyle değerlendirilmesi,” M. S. thesis, Marmara University, İstanbul, 2022.
  • J. Ramík, and R. Perzina, “A method for solving fuzzy multicriteria decision problems with dependent criteria,” Fuzzy Optimization and Decision Making, vol. 9 pp. 123–141, 2010.
Toplam 42 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Çok Ölçütlü Karar Verme
Bölüm Araştırma Makalesi
Yazarlar

Ahmet Sarucan 0000-0001-5582-2456

Mehmet Emin Baysal 0000-0002-1023-4009

Orhan Engin 0000-0002-7250-0317

Yayımlanma Tarihi 1 Haziran 2024
Gönderilme Tarihi 15 Temmuz 2023
Kabul Tarihi 26 Şubat 2024
Yayımlandığı Sayı Yıl 2024 Cilt: 12 Sayı: 2

Kaynak Göster

IEEE A. Sarucan, M. E. Baysal, ve O. Engin, “RANKING OF THE MEMBER COUNTRIES IN THE BLACK SEA ECONOMIC COOPERATION ORGANIZATION USING MULTI-CRITERIA DECISION-MAKING METHODS”, KONJES, c. 12, sy. 2, ss. 326–343, 2024, doi: 10.36306/konjes.1328033.