Araştırma Makalesi
BibTex RIS Kaynak Göster

OPEC Ülkelerinin Lojistik Performanslarının Birleşik ÇKKV Yöntemleri ile Değerlendirilmesi

Yıl 2025, Cilt: 29 Sayı: 2, 112 - 136, 29.12.2025
https://doi.org/10.51945/cuiibfd.1836821

Öz

Ekonomileri büyük ölçüde petrol ihracatına dayanan OPEC üyesi ülkeler için, etkili lojistik sistemleri istikrar ve büyümeyi sürdürmek için kritik öneme sahiptir. Birçok çalışma lojistik performansı bileşik endeksler veya ekonometrik modeller kullanarak analiz ederken, çok azı farklı ÇKKV ağırlıklandırma ve sıralama tekniklerinin değerlendirme sonuçları üzerindeki etkisini incelemiştir. Bu çalışma, iki nesnel ağırlıklandırma yöntemini (Entropy ve CRITIC) karşılaştırarak ve bu metotları yaygın olarak kullanılan iki ÇKKV sıralama yöntemlerinden olan TOPSIS ve CoCoSo ile entegre ederek bu boşluğu doldurmayı amaçlamaktadır. İlk aşamada, Entropy ve CRITIC yöntemleri lojistik performans göstergelerinin ağırlıklarını belirlemek için uygulanmaktadır. Sonuçlar, Entropy'nin altyapı gibi yapısal, bilgi yoğun kriterlere öncelik verdiğini, CRITIC'in ise standart sapmaya ve korelasyona duyarlılığı nedeniyle sevkiyat verimliliği ve zamanında teslimat gibi performansa dayalı göstergelere daha fazla ağırlık verdiğini göstermektedir. İkinci aşamada, ülke sıralamaları oluşturmak için TOPSIS ve CoCoSo yöntemleri kullanılmıştır. Analiz sonuçları, CoCoSo metodunun daha istikrarlı ve dengeli bir performansa sahip olduğunu göstermektedir.

Kaynakça

  • Abara, Y. (2021). The impact of logistics performance on foreign trade volume. Journal of Industrial Policy and Technology Management, 4(2), 133-144. https://www.jipat.org/index.php/jipat/article/view/69/pdf_49
  • Akandere, G. (2021). Kuşak yol ülkelerinin lojistik ve cevresel perfromansının analizi. Gaziantep University Journal of Social Sciences, 20(4), 1893–1915. https://doi.org/10.21547/jss.927509
  • Alinezhad, A., & Khalili, J. (2019). Decision making methods based on multi-criteria decision making (MCDM) methods. Springer.
  • Apergis, N., & Payne, James E. (2009). Energy consumption and economic growth: Evidence from the commonwealth of independent states. Energy Economics, 31(5), 641-647. https://doi.org/10.1016/j.eneco.2009.01.011
  • Aruldoss, M., Lakshmi, T. M., & Venkatesan, V. P. (2013). A survey on multi-criteria decision-making methods and its applications. American Journal of Information Systems, 1(1), 31-43. https://doi.org/10.12691/ajis-1-1-5
  • Arvis, J.-F., Saslavsky, D., Ojala, L., Shepherd, B., Busch, C., & Raj, A. (2013). Connecting to compete: Trade logistics in the global economy. World Bank. https://documents.worldbank.org/en/publication/documents-reports/documentdetail/099042123145531599
  • BP. (2023). Statistical Review of World Energy. Energy Institute, 72nd Edition, 1-64. https://www.connaissancedesenergies.org/sites/connaissancedesenergies.org/files/pdf-actualites/Statistical%20Review%20of%20World%20Energy.pdf
  • Devlin, J., & Yee, P. (2005). Trade logistics in developing countries: The case of the Middle East and North Africa. World Economy, 28(3), 435-456. https://doi.org/10.1111/j.1467-9701.2005.00620.x
  • 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
  • Hwang, C. L., & Yoon, K. (1981). Multiple attribute decision making: Methods and applications. Springer-Verlag.
  • IEA. (2024). Oil Market Report – April 2024. International Energy Agency. https://www.iea.org/reports/oil-market-report-december-2024
  • Jian, J., Fan, X., He, P., Xiong, H., & Shen, H. (2019). The effects of energy consumption, economic growth and financial development on CO2 emissions in China: A VECM Approach. Sustainability, 11(18), 4850. https://doi.org/10.3390/su11184850
  • Ju, M., Mirović, I., Petrović, V., Erceg, Ž., & Stević, Ž. (2024). A novel approach for the assessment of logistics performance index of EU countries. Economics, 18(1), 1-15. https://doi.org/10.1515/econ-2022-0074
  • Keleş, N., & Kahveci, A. (2025). Evaluating the logistics performance of the EU candidate and member countries using the WENSLO and ARTASI methods. Pamukkale University Journal of Social Sciences Institute, 68, 43-66. http://doi.org/10.30794/pausbed.1594714
  • OPEC. (2022). OPEC Annual Statistical Bulletin 2022. Annual Statistical Bulletin, 57th Edition. https://www.opec.org/assets/assetdb/asb-2022.pdf
  • OPEC. (2024). 2024 OPEC Annual Statistical Bulletin. Annual Statistical Bulletin, 59th Edition. https://www.opec.org/assets/assetdb/asb-2024.pdf
  • Özdağoğlu, A., Ustaömer, T.C. & Keleş, M.K. (2022). Performance evaluation in airline industry with critic and MEREC based MAUT and PSI methods. Transport & Logistics: The International Journal, 22(52). https://people.fberg.tuke.sk/tnl/index.php/tnl/article/view/98/70
  • Özekenci, E. K. (2023). Assessing the logistics market performance of developing countries by SWARA-CRITIC based CoCoSo method. LogForum, 19(3), 375-394, http://doi.org/10.17270/J.LOG.2023.857
  • Özekenci, E. K. (2025). Evaluation of the Logistics Performance Index of OECD Countries Based on Hybrid MCDM Methods. Marmara Üniversitesi İktisadi ve İdari Bilimler Dergisi, 47(1), 47–76. http://doi.org/10.14780/muiibd.1469898
  • Öztürk, E., & Kaya, T. (2020). CRITIC-WASPAS application in logistics performance analysis of OECD countries. Operational Research in Logistics, 27(1), 134-156.
  • Rashidi, K., & Cullinane, K. (2019). Evaluating the sustainability of national logistics performance using Data Envelopment Analysis. Transport Policy, 74(C), 35-46. https://doi.org/10.1016/j.tranpol.2018.11.014
  • World Bank. (2018). Connecting to Compete 2018 Trade Logistics in the Global Economy The Logistics Performance Index and Its Indicators. https://openknowledge.worldbank.org/server/api/core/bitstreams/628a4f9d-7faa-54bf-97b0-f6080c6d46cd/content
  • World Bank. (2022). World Development Indicators. https://databank.worldbank.org/source/world-development-indicators
  • Yazar Okur, İ. G., Doganer Duman, B., Demirci, E., & Yıldırım, B. F. (2025). Evaluating logistics sector sustainability indicators using multi-expert Fermatean fuzzy entropy and WASPAS methodology. Journal of International Logistics and Trade, 23(2), 94–117. doi: https://doi.org/10.1108/JILT-10-2024-0078
  • Yazdani, M., Zarate, P., Coulibaly, A., & Zavadskas, E. K. (2017). A group decision making support system in logistics and supply chain management. Expert Systems with Applications, 88, 376-392. https://doi.org/10.1016/j.eswa.2017.07.014.
  • Yazdani, M., Zarate, P., Kazimieras Zavadskas, E., & Turskis, Z. (2019). A combined compromise solution (CoCoSo) method for multi-criteria decision-making problems. Management Decision, 57(9), 2501-2519. https://doi.org/10.1108/MD-05-2017-0458
  • Yildirim, B. F., Adiguzel Mercangoz, B. (2020). Evaluating the logistics performance of OECD countries by using fuzzy AHP and ARAS-G. Eurasian Econ Rev, 10, 27–45. https://doi.org/10.1007/s40822-019-00131-3
  • Zhu, Y., Tian, D., & Yan, F. (2020). Effectiveness of Entropy weight method in decision-making. Mathematical Problems in Engineering. https://doi.org/10.1155/2020/3564835

Assessment of the Logistics Performance of OPEC Countries with Integrated MCDM Methods

Yıl 2025, Cilt: 29 Sayı: 2, 112 - 136, 29.12.2025
https://doi.org/10.51945/cuiibfd.1836821

Öz

For OPEC member states—whose economies heavily rely on oil exports—effective logistics systems are critical for maintaining stability and growth. While many studies analyze logistics performance using composite indices or econometric models, few have examined the impact of different MCDM weighting and ranking techniques on the evaluation results. This study aims to fill this gap by comparing two objective weighting methods—Entropy and CRITIC—and integrating them with two widely used MCDM ranking techniques, TOPSIS and CoCoSo. In the first stage, Entropy and CRITIC methods were applied to determine the weights of logistics performance indicators. The results show that Entropy prioritizes structural, information-intensive criteria such as infrastructure, while CRITIC gives more weight to performance-based indicators like shipment efficiency and on-time delivery due to its sensitivity to standard deviation and correlation. In the second stage, TOPSIS and CoCoSo methods were used to generate country rankings. CoCoSo results demonstrated more stable and balanced performance.

Kaynakça

  • Abara, Y. (2021). The impact of logistics performance on foreign trade volume. Journal of Industrial Policy and Technology Management, 4(2), 133-144. https://www.jipat.org/index.php/jipat/article/view/69/pdf_49
  • Akandere, G. (2021). Kuşak yol ülkelerinin lojistik ve cevresel perfromansının analizi. Gaziantep University Journal of Social Sciences, 20(4), 1893–1915. https://doi.org/10.21547/jss.927509
  • Alinezhad, A., & Khalili, J. (2019). Decision making methods based on multi-criteria decision making (MCDM) methods. Springer.
  • Apergis, N., & Payne, James E. (2009). Energy consumption and economic growth: Evidence from the commonwealth of independent states. Energy Economics, 31(5), 641-647. https://doi.org/10.1016/j.eneco.2009.01.011
  • Aruldoss, M., Lakshmi, T. M., & Venkatesan, V. P. (2013). A survey on multi-criteria decision-making methods and its applications. American Journal of Information Systems, 1(1), 31-43. https://doi.org/10.12691/ajis-1-1-5
  • Arvis, J.-F., Saslavsky, D., Ojala, L., Shepherd, B., Busch, C., & Raj, A. (2013). Connecting to compete: Trade logistics in the global economy. World Bank. https://documents.worldbank.org/en/publication/documents-reports/documentdetail/099042123145531599
  • BP. (2023). Statistical Review of World Energy. Energy Institute, 72nd Edition, 1-64. https://www.connaissancedesenergies.org/sites/connaissancedesenergies.org/files/pdf-actualites/Statistical%20Review%20of%20World%20Energy.pdf
  • Devlin, J., & Yee, P. (2005). Trade logistics in developing countries: The case of the Middle East and North Africa. World Economy, 28(3), 435-456. https://doi.org/10.1111/j.1467-9701.2005.00620.x
  • 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
  • Hwang, C. L., & Yoon, K. (1981). Multiple attribute decision making: Methods and applications. Springer-Verlag.
  • IEA. (2024). Oil Market Report – April 2024. International Energy Agency. https://www.iea.org/reports/oil-market-report-december-2024
  • Jian, J., Fan, X., He, P., Xiong, H., & Shen, H. (2019). The effects of energy consumption, economic growth and financial development on CO2 emissions in China: A VECM Approach. Sustainability, 11(18), 4850. https://doi.org/10.3390/su11184850
  • Ju, M., Mirović, I., Petrović, V., Erceg, Ž., & Stević, Ž. (2024). A novel approach for the assessment of logistics performance index of EU countries. Economics, 18(1), 1-15. https://doi.org/10.1515/econ-2022-0074
  • Keleş, N., & Kahveci, A. (2025). Evaluating the logistics performance of the EU candidate and member countries using the WENSLO and ARTASI methods. Pamukkale University Journal of Social Sciences Institute, 68, 43-66. http://doi.org/10.30794/pausbed.1594714
  • OPEC. (2022). OPEC Annual Statistical Bulletin 2022. Annual Statistical Bulletin, 57th Edition. https://www.opec.org/assets/assetdb/asb-2022.pdf
  • OPEC. (2024). 2024 OPEC Annual Statistical Bulletin. Annual Statistical Bulletin, 59th Edition. https://www.opec.org/assets/assetdb/asb-2024.pdf
  • Özdağoğlu, A., Ustaömer, T.C. & Keleş, M.K. (2022). Performance evaluation in airline industry with critic and MEREC based MAUT and PSI methods. Transport & Logistics: The International Journal, 22(52). https://people.fberg.tuke.sk/tnl/index.php/tnl/article/view/98/70
  • Özekenci, E. K. (2023). Assessing the logistics market performance of developing countries by SWARA-CRITIC based CoCoSo method. LogForum, 19(3), 375-394, http://doi.org/10.17270/J.LOG.2023.857
  • Özekenci, E. K. (2025). Evaluation of the Logistics Performance Index of OECD Countries Based on Hybrid MCDM Methods. Marmara Üniversitesi İktisadi ve İdari Bilimler Dergisi, 47(1), 47–76. http://doi.org/10.14780/muiibd.1469898
  • Öztürk, E., & Kaya, T. (2020). CRITIC-WASPAS application in logistics performance analysis of OECD countries. Operational Research in Logistics, 27(1), 134-156.
  • Rashidi, K., & Cullinane, K. (2019). Evaluating the sustainability of national logistics performance using Data Envelopment Analysis. Transport Policy, 74(C), 35-46. https://doi.org/10.1016/j.tranpol.2018.11.014
  • World Bank. (2018). Connecting to Compete 2018 Trade Logistics in the Global Economy The Logistics Performance Index and Its Indicators. https://openknowledge.worldbank.org/server/api/core/bitstreams/628a4f9d-7faa-54bf-97b0-f6080c6d46cd/content
  • World Bank. (2022). World Development Indicators. https://databank.worldbank.org/source/world-development-indicators
  • Yazar Okur, İ. G., Doganer Duman, B., Demirci, E., & Yıldırım, B. F. (2025). Evaluating logistics sector sustainability indicators using multi-expert Fermatean fuzzy entropy and WASPAS methodology. Journal of International Logistics and Trade, 23(2), 94–117. doi: https://doi.org/10.1108/JILT-10-2024-0078
  • Yazdani, M., Zarate, P., Coulibaly, A., & Zavadskas, E. K. (2017). A group decision making support system in logistics and supply chain management. Expert Systems with Applications, 88, 376-392. https://doi.org/10.1016/j.eswa.2017.07.014.
  • Yazdani, M., Zarate, P., Kazimieras Zavadskas, E., & Turskis, Z. (2019). A combined compromise solution (CoCoSo) method for multi-criteria decision-making problems. Management Decision, 57(9), 2501-2519. https://doi.org/10.1108/MD-05-2017-0458
  • Yildirim, B. F., Adiguzel Mercangoz, B. (2020). Evaluating the logistics performance of OECD countries by using fuzzy AHP and ARAS-G. Eurasian Econ Rev, 10, 27–45. https://doi.org/10.1007/s40822-019-00131-3
  • Zhu, Y., Tian, D., & Yan, F. (2020). Effectiveness of Entropy weight method in decision-making. Mathematical Problems in Engineering. https://doi.org/10.1155/2020/3564835
Toplam 28 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Matematiksel İktisat
Bölüm Araştırma Makalesi
Yazarlar

Semin Topaloğlu Paksoy 0000-0003-1693-0184

Roya Karamat 0000-0003-1519-2538

Gönderilme Tarihi 5 Aralık 2025
Kabul Tarihi 25 Aralık 2025
Yayımlanma Tarihi 29 Aralık 2025
Yayımlandığı Sayı Yıl 2025 Cilt: 29 Sayı: 2

Kaynak Göster

APA Topaloğlu Paksoy, S., & Karamat, R. (2025). Assessment of the Logistics Performance of OPEC Countries with Integrated MCDM Methods. Çukurova Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 29(2), 112-136. https://doi.org/10.51945/cuiibfd.1836821