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Dergiler / İktisadi İdari ve Siyasal Araştırmalar Dergisi / 2024 / Cilt: 9 Sayı: 25

EATWOS, OCRA ve REF III Teknikleriyle Ülkelerin Lojistik Performans İndeksine Dayalı Etkinliklerinin İncelenmesi

Examining the Efficiency of Countries Based on the Logistics Performance Index Using EATWOS, OCRA and REF III Techniques

Erhan Orakçı(HAKKARİ ÜNİVERSİTESİ)0000-0001-8468-5710
Sayfa
590–611
Yayın Tarihi
2024-10-31
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⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

Sonuçlar, bu teknikler arasında neredeyse mükemmel bir uyum olduğunu göstermektedir.

📌 3 Maddede Bu Makale

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Amaç & Hipotez:Bu çalışma, Avrupa Birliği (AB) üye ve aday ülkelerinin lojistik performanslarına bağlı ekonomik etkinliklerini OCRA, EATWOS ve REF-III gibi üç Çok Kriterli Karar Verme (ÇKKV) tekniğini kullanarak incelemeyi amaçlamaktadır.
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Temel Bulgular & Veri:Bu çerçevede, Lojistik Performans İndeksi (LPI) göstergeleri ve Gayri Safi Yurt İçi Hasıla (GSYİH) verileri birlikte değerlendirilerek analiz edilmiştir.
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Sonuç & Katkı:Sonuçlar, bu teknikler arasında neredeyse mükemmel bir uyum olduğunu göstermektedir.
🔬Tür:Araştırma Makalesi
📍Kapsam:Genişletilmiş Akademik Örneklem
⚙️Değişkenler:Etkinlik Analizi · EATWOS · ÇKKV

Özet

Bu çalışma, Avrupa Birliği (AB) üye ve aday ülkelerinin lojistik performanslarına bağlı ekonomik etkinliklerini OCRA, EATWOS ve REF-III gibi üç Çok Kriterli Karar Verme (ÇKKV) tekniğini kullanarak incelemeyi amaçlamaktadır. Bu çerçevede, Lojistik Performans İndeksi (LPI) göstergeleri ve Gayri Safi Yurt İçi Hasıla (GSYİH) verileri birlikte değerlendirilerek analiz edilmiştir. Sonuçlar, bu teknikler arasında neredeyse mükemmel bir uyum olduğunu göstermektedir. Kuzey Avrupa ülkeleri (örneğin, Danimarka, İsveç, Finlandiya) ve Lüksemburg ile İrlanda, yüksek lojistik performansları ile öne çıkarken, Güney ve Doğu Avrupa ülkeleri (örneğin, Yunanistan, İtalya, Bulgaristan) daha düşük sıralamalarda yer almıştır. AB aday ülkeleri arasında Türkiye en iyi performansı gösteren ülke olmasına rağmen genel sıralamada düşük kalmıştır. Bu bulgular, lojistik altyapı ve operasyonların iyileştirilmesi gerektiğini vurgulamaktadır. Çalışma, lojistik performansın değerlendirilmesinde kullanılan metodolojilerin etkinliğini ve güvenilirliğini doğrulamakta ve gelecekteki lojistik geliştirme stratejileri için önemli veriler sunmaktadır. Analiz ayrıca LPI puanları ile GSYİH arasında pozitif bir korelasyon olduğunu ortaya koymakta ve lojistik etkinliğin ekonomik büyüme için önemini vurgulamaktadır.

Abstract

This study aims to examine the economic efficiency of European Union (EU) member and candidate countries based on their logistics performance using three multi-criteria decision-making (MCDM) techniques: OCRA, EATWOS, and REF-III. In this context, Logistics Performance Index (LPI) indicators and Gross Domestic Product (GDP) data were analyzed together. The results show almost perfect concordance among these techniques. Northern European countries (e.g., Denmark, Sweden, Finland) and Luxembourg and Ireland stand out with their high logistics performance, while Southern and Eastern European countries (e.g., Greece, Italy, Bulgaria) are ranked lower. Among the EU candidate countries, Turkey performs the best but still ranks low overall. These findings highlight the need for improvement in logistics infrastructure and operations. The study confirms the effectiveness and reliability of the methodologies used in evaluating logistics performance and provides valuable insights for future logistics development strategies. The analysis also reveals a positive correlation between LPI scores and GDP, emphasizing the importance of logistics efficiency for economic growth.

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Bu Makaleye Atıf Yap

Orakçı, E. (2024). EATWOS, OCRA ve REF III Teknikleriyle Ülkelerin Lojistik Performans İndeksine Dayalı Etkinliklerinin İncelenmesi. İktisadi İdari ve Siyasal Araştırmalar Dergisi, Cilt: 9 Sayı: 25, 590–611. https://doi.org/10.25204/iktisad.1486017

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Kaynakça (109)

  1. Ababou, M. ve Benomar, I. (2024). Insights into the interplay between macroeconomic factors and logistics performance index. Journal of Namibian Studies: History Politics Culture, 40, 413-435. https://doi.org/10.59670/jsf7q813 https://doi.org/10.59670/jsf7q813
  2. Aksungur, M. ve Bekmezci, M. (2020). Türkiye’nin lojistik performansının değerlendirilmesi boylamsal bir araştırma. Toros Üniversitesi İİSBF Sosyal Bilimler Dergisi, 7(12), 19-40. https://dergipark.org.tr/tr/pub/iisbf/issue/54695/647883
  3. Alnıpak, S. (2022). Liman operasyonel verimliliğinin karlılık ile ilişkisi: TCDD limanları üzerine bir araştırma. Maliye ve Finans Yazıları, (118), 239-256. https://doi.org/10.33203/mfy.1150928
  4. Alnıpak, S., Isikli, E. ve Apak, S. (2023). The propellants of the Logistics Performance Index: an empirical panel investigation of the European region. International Journal of Logistics Research and Applications, 26(7), 894-916. https://doi.org/10.1080/13675567.2021.1998397
  5. Aytekin, A. (2020). Çok kriterli karar problemine uzaklık ve referans temelli çözüm yaklaşımı. https://hdl.handle.net/11494/2558
  6. Aytekin, A. (2020). Türkiye’de önde gelen şirketlerin etkinlik, farklılık ve performans ölçümü. Anadolu Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 21(4), 19-35. https://dergipark.org.tr/tr/pub/anadoluibfd/issue/59038/827385
  7. Aytekin, A. (2022). Çok kriterli karar analizi. https://hdl.handle.net/11494/4808
  8. Aytekin, A. ve Durucasu, H. (2021). Nearest solution to references method for multicriteria decision-making problems. Decision Science Letters, 10(2), 111-128. https://hdl.handle.net/11494/2830
  9. Aytekin, A., Ecer, F., Korucuk, S. ve Karamaşa, Ç. (2022). Global innovation efficiency assessment of EU member and candidate countries via DEA-EATWIOS multi-criteria methodology. Technology in Society, 68, 101896. https://doi.org/10.1016/j.techsoc.2022.101896
  10. Aytekin, A., Görçün, Ö. F., Ecer, F., Pamucar, D. ve Karamaşa, Ç. (2023b). Foreign market selection of suppliers through a novel REF-Sort technique. Kybernetes, 52(11), 4958-4992. https://doi.org/10.1108/K-03-2022-0459
  11. Aytekin, A., Korucuk, S. ve Karamaşa, Ç. (2023). Ranking countries according to logistics and international trade efficiencies via REF-III. J. Intell. Manag. Decis, 2, 74-84. https://doi.org/10.56578/jimd020204
  12. Bakucs, Z., Fertő, I., Fogarasi, J., Tóth, J. ve Latruffe, L. (2011, February). Assessment of the impact of EU accession upon farms’ performance in the New Member States with special emphasis on the farm type. (FACEPA Deliverable No. D 5.3). http://prodinra.inra.fr/ft/47343A34-EC0F-4B67-AA00-11C5788D3248
  13. Bansal, A., Kr. Singh, R., Issar, S. ve Varkey, J. (2014). Evaluation of vendors ranking by EATWOS approach. Journal of Advances in Management Research, 11(3), 290-311. https://doi.org/10.1108/JAMR-02-2014-0009
  14. Barakat, M., Madkour, T. ve Moussa, A. M. (2023). The role of logistics performance index on trade openness in Europe. International Journal of Economics and Business Research, 25(3), 379-394. https://doi.org/10.1504/IJEBR.2023.129967
  15. Beškovnik, B. (2010). Managing and organizational changes of intermodal network in transition regions: the case of South-East Europe. Transport problems, 5(2), 37-47.
  16. Beškovnik, B. ve Twrdy, E. (2015). Developing regional approach for transport industry: the role of port system in the Balkans. Transport, 30(4), 437-447. https://doi.org/10.3846/16484142.2014.938696
  17. Beysenbaev, R. ve Dus, Y. (2020). Proposals for improving the Logistics Performance Index. Asian Journal of Shipping and Logistics, 36(1), 34-42. https://doi.org/10.1016/j.ajsl.2019.10.001
  18. Bilgin, T. ve Sunaoğlu, Ş. K. (2022). Lojistik performans ve uluslararası ticaret ilişkisi üzerine alanyazın incelemesi. Pamukkale Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, (53), 325-344. https://doi.org/10.30794/pausbed.1105239
  19. Bozkurt, C. ve Mermertaş, F. (2019). Türkiye ve G8 ülkelerinin lojistik performans endeksine göre karşılaştırılması. İşletme ve İktisat Çalışmaları Dergisi, 7(2), 107-117. https://dergipark.org.tr/tr/download/article-file/840193
  20. Bugarčić, F. Ž., Mićić, V. ve Stanišić, N. (2023). The role of logistics in economic growth and global competitiveness. Zbornik Radova Ekonomski Fakultet u Rijeka, 41(2), 499-520. https://doi.org/10.18045/zbefri.2023.2.499
  21. Cakranegara, P. A., Budiastuti, A. ve Simanjorang, T. M. (2022). Determining the company marketing sales perfomance using the operational competitiveness rating analysis (OCRA) method. Enrichment: Journal of Management, 12(5), 3996-4002. https://doi.org/10.35335/enrichment.v12i5.986
  22. Chatterjee, P. (2013). Applications of preference ranking-based methods for decision-making in manufacturing environment. PhD Thesis, Jadavpur University. Kolkata. http://hdl.handle.net/10603/175990
  23. Chatterjee, P. ve Chakraborty, S. (2012). Material selection using preferential ranking methods. Material and Design, 35, 384-393. https://doi.org/10.1016/j.matdes.2011.09.027
  24. Chatterjee, P. ve Chakraborty, S. (2014). Flexible manufacturing system selection using preference ranking methods: A comparative study. International Journal of Industrial Engineering Computations, 5, 315–338. http://dx.doi.org/10.14743/apem2014.1.172
  25. Coto-Millán, P., Agüeros, M., Casares-Hontañón, P. ve Pesquera, M. Á. (2013). Impact of logistics performance on world economic growth (2007–2012). World Review of Intermodal Transportation Research, 4(4), 300-310. https://doi.org/10.1504/WRITR.2013.059857
  26. Çaloğlu Büyükselçuk, E. ve Tozan, H. (2022). Elektrikli araçların performanslarının CRITIC-EATWIOS ile değerlendirilmesi. Düzce Üniversitesi Bilim ve Teknoloji Dergisi, 10(4), 1670-1688. https://dergipark.org.tr/tr/pub/dubited/issue/73115/1002851
  27. Çanakçıoğlu, M. (2019). Borsa İstanbul’da işlem gören çimento firmalarının Entropi-EATWIOS bütünleşik yaklaşımı ile finansal performanslarının değerlendirmesi. Yaşar Üniversitesi E-Dergisi, 14(56), 407-421. https://dergipark.org.tr/tr/pub/jyasar/issue/49978/570324
  28. Çelebi, Ü., Civelek, M. E., ve Çemberci, M. (2015). The mediator effect of foreign direct investments on the relation between logistics performance and economic growth. Journal of Global Strategic Management, 17. https://ssrn.com/abstract=3338308
  29. Çilek, A. ve Karavardar, A. (2023). Hibrit Entropi ve EATWIOS teknikleri ile Türk kamu bankalarının verimlilik analizi. Business & Management Studies: An International Journal, 11(1), 136-151. https://doi.org/10.15295/bmij.v11i1.2185
  30. Darji, V. P. ve Rao, R. V. (2014). Intelligent multi criteria decision making methods for material selection in sugar industry. Procedia Materials Science, 5, 2585-2594. https://doi.org/10.1016/j.mspro.2014.07.519
  31. Doğan, H. (2020). Türkiye ve AB ülkelerinin AR-GE verimliliklerinin ENTROPİ-EATWOS yöntemleri ile karşılaştırılması. Karadeniz Sosyal Bilimler Dergisi, 12(23), 515-533. https://doi.org/10.38155/ksbd.792763
  32. Duleba, S. ve Moslem, S. (2018). Sustainable urban transport development with stakeholder participation, an AHP-Kendall model: A case study for Mersin. Sustainability, 10(10), 3647. https://doi.org/10.3390/su10103647
  33. Emirkadı, Ö. ve Balcı, H. (2018). Lojistik sektörü ve Türkiye dış ticaretine etkileri. Journal of Institute of Economic Development and Social Researches, 4(8), 123-132. https://dergipark.org.tr/tr/pub/iksad/issue/51695/671144
  34. Erdoğan, A. (2024). Türkiye’de lojistik sektörünün SWOT analizi. The Journal of Social Sciences, (47), 108-116. http://dx.doi.org/10.29228/SOBIDER.45558
  35. Eurostat. (2024, 7 Mayıs). Real GDP per capita. https://doi.org/10.2908/SDG_08_10
  36. Gani, A. (2017). The logistics performance effect in international trade. The Asian journal of shipping and logistics, 33(4), 279-288. https://doi.org/10.1016/j.ajsl.2017.12.012
  37. Göçer, A., Özpeynirci, Ö. ve Semiz, M. (2022). Logistics performance index-driven policy development: An application to Turkey. Transport Policy, 124, 20-32. https://doi.org/10.1016/j.tranpol.2021.03.007
  38. Görçün, Ö. F. (2019). Orta Asya Türk Cumhuriyetlerinin lojistik ve taşımacılık performansları ve verimliliklerinin analizi için hibrid birçok kriterli karar verme modeli. MANAS Sosyal Araştırmalar Dergisi, 8(3), 2775-2798. https://doi.org/10.33206/mjss.511522
  39. Gürler, H. E., Özçalıcı, M. ve Pamucar, D. (2024). Determining criteria weights with genetic algorithms for multi-criteria decision making methods: The case of logistics performance index rankings of European Union countries. Socio-Economic Planning Sciences, 91, 101758. https://doi.org/10.1016/j.seps.2023.101758
  40. Jayathilaka, R., Jayawardhana, C., Embogama, N., Jayasooriya, S., Karunarathna, N., Gamage, T. ve Kuruppu, N. (2021). Gross domestic product and logistics performance index drive the world trade: A study based on all continents. PLoS ONE, 17(2), e0264474. https://doi.org/10.1371/journal.pone.0264474
  41. Kahsai, M. S. ve Eyob, E. (2022). Causal relationship of logistics performance gross domestic product and governance. Journal of Applied Business and Economics, 24(4). https://articlearchives.co/index.php/JABE/article/view/5264/5225
  42. Kalansuriya, N., De Silva, S., Perera, N., Wanigarathna, B., Jayathilaka, R., Paranavitana, P. ve Arachchige, S. C. (2023). Analysing the influence of logistics, corruption, FDI and GDP on global competitiveness: A cross-sectional study. Journal of the Knowledge Economy, 1-20. https://doi.org/10.1007/s13132-023-01615-z
  43. Kálmán, B. ve Tóth, A. (2021). Links between the economy competitiveness and logistics performance in the Visegrád Group countries: Empirical evidence for the years 2007-2018. Entrepreneurial Business and Economics Review, 9(3), 169-190. https://doi.org/10.15678/eber.2021.090311
  44. Karaman Kabadurmuş, F. N. (2019). The relationship between logistics performance and innovation: An empirical study of Turkish firms. Alphanumeric Journal, 7(2), 157-172. https://doi.org/10.17093/alphanumeric.614170
  45. Karp, P. (2024). Components of the polish LPI in relation to macroeconomic variables. Cointegration analysis. Zeszyty Naukowe. Organizacja i Zarządzanie/Politechnika Śląska. http://dx.doi.org/10.29119/1641-3466.2024.191.17
  46. Kendall, M. G. (1948). Rank correlation methods. https://doi.org/10.2307/2333282
  47. Khan, S. A. R., Qianli, D., SongBo, W., Zaman, K. ve Zhang, Y. (2017). Travel and tourism competitiveness index: The impact of air transportation, railways transportation, travel and transport services on international inbound and outbound tourism. Journal of Air Transport Management, 58, 125-134. https://doi.org/10.1016/j.jairtraman.2016.10.006
  48. Koç, E., Desticioğlu, B. ve Şimşek, A. İ. (2021). ABD konteyner limanlarının toplam faktör verimliliklerinin karşılaştırılması. Avrupa Bilim ve Teknoloji Dergisi, (27), 823-831. https://doi.org/10.31590/ejosat.992850
  49. Kumari, M. ve Bharti, N. (2021). Trade and logistics performance: does country size matter?. Maritime Economics & Logistics, 23, 401-423. https://doi.org/10.1057/s41278-021-00188-5
  50. Kundakcı, N. (2019). A comparative analyze based on EATWOS and OCRA methods for supplier evaluation. Alphanumeric Journal, 7(1), 103-112. https://doi.org/10.17093/alphanumeric.477322
  51. Küçük, Ü. (2022). Lojistik faaliyetlerde yaşanan sorunlar ve çözüm önerileri gıda firması örneği. Eğitim Yayınevi.
  52. Larson, P. D. (2021). Relationships between logistics performance and aspects of sustainability: A cross-country analysis. Sustainability, 13(1), 623. https://doi.org/10.3390/su13020623
  53. Leal, E. (2011). Logistics platforms as a pivotal element in competitiveness and sustainability. Facilitation of Transport and Trade in Latin America and the Caribbean, FAL Bulletin, 302(10), 1–9. https://repositorio.cepal.org/server/api/core/bitstreams/6eaaa54b-5761-4750-a119-46e84817b5ed/content
  54. Lukić, R. (2024). Application of the REF method in the evaluation of trade efficiency in Serbia. Review of International Comparative Management, 25(1), 51-69. https://doi.org/10.24818/RMCI.2024.1.51
  55. Lukić, R. ve Zekić, B. H. (2021, 7-8 Ekim). Evaluation of transportation and storage efficiency in Serbia based on ratio analysis and the OCRA method. 21st International Scientific Conference Business Logistics in Modern Management içinde (s. 189-200). Osijek, Croatia. https://www.efos.unios.hr/repec/osi/bulimm/PDF/BusinessLogisticsinModernManagement21/blimm2111.pdf
  56. Madić, M., Petković, D. ve Radovanović, M. (2015). Selection of non-conventional machining processes using the OCRA method. Serbian Journal of Management, 10(1), 61-73. https://doi.org/10.5937/sjm10-6802
  57. Martí, L., Puertas, R. ve García, L. (2014). The importance of the logistics performance index in international trade. Applied Economics, 46(24), 2982-2992. https://doi.org/10.1080/00036846.2014.916394
  58. Mhlanga, S, T. ve Lall, M. (2021, 3-6 Aralık). Influence of normalization technique on multi-criteria decision-making methods. 2nd International Symposium on Automation, Information and Computing (ISAIC 2021) içinde (s. 1-12). Online. https://doi.org/10.1088/1742-6596/2224/1/012076
  59. Mishra, A. R., Rani, P., Cavallaro, F., Hezam, I. M. ve Lakshmi, J. (2023). An integrated intuitionistic fuzzy closeness coefficient-based OCRA method for sustainable urban transportation options selection. Axioms, 12(2), 144. https://doi.org/10.3390/axioms12020144
  60. Nguyen, T. C. ve Le, T. H. (2024). Financial crises and the national logistics performance: Evidence from emerging and developing countries. International Journal of Finance & Economics, 29(2), 1834-1855. https://doi.org/10.1002/ijfe.2768
  61. Özbek, A. (2015a). Performance analysis of public banks in Turkey. International Journal of Business Management and Economic Research, 6(3), 178-186. https://www.ijbmer.com/docs/volumes/vol6issue3/ijbmer2015060303.pdf
  62. Özbek, A. (2015b). Efficiency analysis of foreign-capital banks in Turkey by OCRA and MOORA environment. Research Journal of Finance and Accounting, 6(13), 21-31. https://core.ac.uk/download/pdf/234630854.pdf
  63. Özbek, A. (2015c). Efficiency analysis of the Turkish red crescent between 2012 and 2014. International Journal of Economics and Finance, 7(9), 322-334. http://dx.doi.org/10.5539/ijef.v7n9p322
  64. Özbek, A. Ş. I. R. (2015c). Operasyonel rekabet değerlendirmesi (OCRA) yöntemiyle mevduat bankalarının etkinlik ölçümü. Social Sciences, 10(3), 120-134. https://doi.org/10.12739/nwsa.2015.10.3.3c0132
  65. Özdağoğlu, A. (2018). BİST sınai işletmelerinin Gri Entropi-EATWIOS bütünleşik yaklaşımı ile performans değerlendirmesi. Dokuz Eylül Üniversitesi İşletme Fakültesi Dergisi, 19(2), 271-299. https://doi.org/10.24889/ifede.415061
  66. Özdemir, M. H. (2021). Effizienzanalyse für laptops mit der integrierten Entropie-EATWIOS-methode. Nevşehir Hacı Bektaş Veli Üniversitesi SBE Dergisi, 11(2), 717-736. http://hdl.handle.net/20.500.11787/6055
  67. Özgür, M. I., Demirtaş, C., Bağcı, H., Yıldırım, E. S. ve Ertuğrul, G. (2023). Türk kamu ve özel şeker fabrikalarının etkinlik ve verimlilik analizi: CRITIC VE EATWIOS Yönteminden Kanıtlar1. https://acikerisim.aksaray.edu.tr/dx.doi.org/10.25287/ohuiibf.1160049
  68. Pala, O. (2023). MEREC-CORR ve SAW temelli lojistik performans değerlendirme. Dicle Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 13(25), 117-135. https://doi.org/10.53092/duiibfd.1130928
  69. Parkan, C. (1994). Operational competitiveness ratings of production units. Managerial and Decision Economics, 15(3), 201-221. https://doi.org/10.1002/mde.4090150303
  70. Parkan, C. (1996a). Performance measurement for a subway system in Hong Kong. The Georgia Productivity Workshop II, Athens, GA.
  71. Parkan, C. (1996b). Measuring the performance of hotel operations. Socio-Economic Planning Sciences, 30(4), 257–292. https://doi.org/10.1108/01443570210427695
  72. Parkan, C. (2002). Measuring the operational performance of public transit company. International Journal of Operations & Production Management, 22(6), 693-720. https://doi.org/10.1108/01443570210427695
  73. Parkan, C. (2003). Measuring the effect of a new point of sale system on the performance of drugstore operations. Computers & Operations Research, 30(4), 729-744. https://doi.org/10.1016/S0305-0548(02)00047-3
  74. Parkan, C. (2005). Benchmarking operational performance: the case of two hotels. International Journal of Productivity and Performance Management, 54(8), 679-696. https://doi.org/10.1108/17410400510627525
  75. Parkan, C. ve Wu, M. L. (1996, 18-20 Ağustos). Selection of a manufacturing process with multiple benefit attributes. International Conference on Engineering and Technology Management. Managing Virtual Enterprises: A Convergence of Communications, Computing, and Energy Technologies (IEMC) içinde (s. 447-452). Vancouver, Canada. https://doi.org/10.1109/IEMC.1996.547858
  76. Parkan, C. ve Wu, M. L. (1997). On the equivalence of operational performance measurement and multiple attribute decision making. International Journal of Production Research, 35(11), 2963-2988. https://doi.org/10.1080/002075497194246
  77. Parkan, C. ve Wu, M.L. (1998). Process selection with multiple objective and subjective attributes. Production Planning & Control, 9(2), 189–200. https://doi.org/10.1080/095372898234415
  78. Parkan, C. ve Wu, M.L. (1999a). Measurement of the performance of an investment bank using the operational competitiveness rating procedure. Omega, 27(2), 201-217. https://doi.org/10.1016/S0305-0483(98)00041-3
  79. Parkan, C. ve Wu, M.L. (1999b). Measuring the performance of operations of Hong Kong’s manufacturing industries. European Journal of Operational Research, 118(2), 235-258. https://doi.org/10.1016/S0377-2217(99)00023-5
  80. Parkan, C. ve Wu, M.L. (1999c). Decision-making and performance measurement models with applications to robot selection. Computers & Industrial Engineering, 36(3), 503–523. https://doi.org/10.1016/S0360-8352(99)00146-1
  81. Parkan, C. ve Wu, M.L. (2000). Comparison of three modern multicriteria decision-making tools. International Journal of Systems Science, 31(4), 497-517. https://doi.org/10.1080/002077200291082
  82. Parkan, C., Lam, K. ve Hang, G. (1997). Operational competitiveness analysis on software development. The Journal of the Operational Research Society, 48(9), 892-905. https://doi.org/10.1057/palgrave.jors.2600446
  83. Pesquera, M. A. (2021). Efficiency of scale of logistics in the production of the world’s countries (2007–2018). Transportation Research Procedia, 58, 150-157. https://doi.org/10.1016/j.trpro.2021.11.021
  84. Peters, M. L. ve Zelewski, S. (2006, 28 Nisan - 1 Mayıs). Efficiency analysis under consideration of satisficing levels for output quantities. 17th Annual Conference of the Production and Operations Management Society – Operations Management in the New World Uncertainties içinde (s. 1-18). Boston (Mass.), ABD. https://www.pomsmeetings.org/confpapers/004/004-0236.pdf
  85. Peters, M. L., Zelewski, S. ve Bruns, A. S. (2012). Extended version of EATWOS concerning satisficing levels for input quantities. Thorsten Blecker, Wolfgang Kersten & Christian M. Ringle (Ed.), Pioneering supply chain design–a comprehensive insight into emerging trends, technologies and applications içinde (s. 303-318). Josef Eul Verlag GmbH. https://www.malte-peters.de/publi_fi/bkps_2012.pdf
  86. Polat, M., Kara, K. ve Yalcin, G. C. (2022). Clustering countries on logistics performance and carbon dioxide (CO2) emission efficiency: An empirical analysis. Business and Economics Research Journal, 13(2), 221-238. https://doi.org/10.20409/berj.2022.370
  87. Qazi, A. (2021). Adoption of a probabilistic network model investigating country risk drivers that influence logistics performance indicators. Environmental Impact Assessment Review, 94, 106760. https://doi.org/10.1016/j.eiar.2022.106760
  88. Rashidi, K. ve Cullinane, K. (2019). Evaluating the sustainability of national logistics performance using Data Envelopment Analysis. Transport Policy, 74, 35-46. https://doi.org/10.1016/j.tranpol.2018.11.014
  89. Roman-Liu, D., Groborz, A. ve Tokarski, T. (2013). Comparison of risk assessment procedures used in OCRA and ULRA methods. Ergonomics, 56(10), 1584-1598. https://doi.org/10.1080/00140139.2013.829923
  90. Roy, V., Mitra, S. K., Chattopadhyay, M. ve Sahay, B. S. (2022). Facilitating the extraction of extended insights on logistics performance from the logistics performance index dataset: A two-stage methodological framework and its application. Research in Transportation Business & Management, 28, 23-32. https://doi.org/10.1016/j.rtbm.2017.10.001
  91. Saini, M. ve Hrusecka, D. (2021). Comparative impact of logistics performance index, ease of doing business and logistics cost on economic development: A fuzzy QCA analysis. Journal of Business Economics and Management, 22(6), 1577-1592. https://doi.org/10.3846/jbem.2021.15586
  92. Saputri, E. G. ve Widodo, W. (2023). The effect of logistics performance on manufacturing exports: a case study of Asia Pacific Economic Cooperation (APEC) countries 2010-2018. Jurnal Ilmu Ekonomi Terapan, 8(1), 116-128. https://doi.org/10.20473/jiet.v8i1.42638
  93. Sergi, B. S., D’Aleo, V., Konecka, S., Depczynska, K. S., Dembinska, I. ve Ioppolo, G. (2021). Competitiveness and the Logistics Performance Index: The ANOVA method application for Africa, Asia, and the EU regions. Sustainable Cities and Society, 69, 102845. https://doi.org/10.1016/j.scs.2021.102845
  94. Shepherd, B. ve Sriklay, T. (2021). Extending and understanding: An application of machine learning to the World Bank’s logistics performance index. International Journal of Physical Distribution & Logistics Management, 53(8), 985-1014. https://doi.org/10.1108/IJPDLM-06-2022-0180
  95. Sofyalıoğlu, Ç. ve Kartal, B. (2013, 17-18 Eylül). Türkiye ve Avrasya ekonomik topluluğu ülkelerinin lojistik performans indekslerinin karşılaştırılması ve bazı çıkarımlar. International Conference on Eurasian Economies içinde (s. 524-531). St. Petersburg, Rusya. https://doi.org/10.36880/C04.00766
  96. Song, M. J. ve Lee, H. Y. (2022). The relationship between international trade and logistics performance: A focus on the South Korean industrial sector. Research in Transportation Business & Management, 44, 100786. https://doi.org/10.1016/j.rtbm.2022.100786
  97. Stanujkic, D., Zavadskas, E. K., Liu, S., Karabasevic, D. ve Popovic, G. (2017). Improved OCRA method based on the use of interval grey numbers. The Journal of Grey System, 29(4), 49-60.
  98. Stojanovic, D. ve Ivetic, J. (2020). Possibilities of using Incoterms clauses in a country logistics performance assessment and benchmarking. Transportation Policy, 98, 217-228. https://doi.org/10.1016/j.tranpol.2020.03.012
  99. Tuş Işık, A. ve Aytaç Adalı, E. (2016). A new integrated decision making approach based on SWARA and OCRA methods for the hotel selection problem. International Journal of Advanced Operations Management, 8(2), 140-151. https://doi.org/10.1504/IJAOM.2016.079681
  100. Türkoğlu, M. ve Duran, G. (2023). G20 ülkelerinin lojistik performanslarının CRITIC tabanlı GİA ve WASPAS uygulaması ile değerlendirilmesi. Hukuk ve İktisat Araştırmaları Dergisi, 15(1), 50-72. https://doi.org/10.53881/hiad.1247196
  101. Uca, N., Civelek, M. E. ve Çemberci, M. (2015). The effect of the components of logistics performance index on gross domestic product: conceptual model proposal. Eurasian Academy of Sciences Eurasian Business & Economic Journal, 1, 86-93. https://dx.doi.org/10.17740/eas.econ.2015-V1-04
  102. Ulkhaq, M. M. (2023). Clustering countries according to the logistics performance index. Journal of Technical Informatics and System Information, 10(4), 1010-1018. https://doi.org/10.35957/jatisi.v10i1.4755.
  103. Varma, S. ve Shah, B. (2021, 16-18 Ağustos). A Study of the relationship between logistics performance and human development. 1st Indian International Conference on Industrial Engineering and Operations Management içinde (s. 833-845). Bangalore, Hindistan. https://doi.org/10.46254/IN01.20210244
  104. Wang, M. L. ve Choi, C. H. (2018). How logistics performance promote the international trade volume? A comparative analysis of developing and developed countries. International Journal of Logistics Economics and Globalisation, 7(1), 49-70. https://doi.org/10.1504/IJLEG.2018.090504
  105. World Bank. (2024, 7 Mayıs). Logistic performance index (LPI). https://lpi.worldbank.org/sites/default/files/2023-04/LPI_2023_report_with_layout.pdf
  106. Yurdakul, E. M. (2020). Türkiye’de lojistik sektörü ve ekonomik büyüme arasındaki ilişkinin VAR analizi ile incelenmesi. Sosyal Ekonomik Araştırmalar Dergisi, 20(40), 174-185. https://doi.org/10.30976/susead.707425
  107. Yusufkhonov, Z., Ravshanov, M., Kamalov, A. ve Kamalov, E. (2021). Improving the position of the logistics performance index of Uzbekistan. E3S Web of Conferences, 264, 05028. https://doi.org/10.1051/e3sconf/202126405028
  108. Yüksekyıldız, E. (2021). ENTROPİ ve EATWOS yöntemleri ile Türkiye konteyner limanlarının verimlilik analizi. Verimlilik Dergisi, (2), 3-24. https://doi.org/10.51551/verimlilik.660708
  109. Zolfani, S. H., Görçün, Ö. F., Çanakçıoğlu, M. ve Tirkolaee, E. B. (2023). Efficiency analysis technique with input and output satisficing approach based on Type-2 Neutrosophic Fuzzy Sets: A case study of container shipping companies. Expert Systems with Applications, 218: 119596. https://doi.org/10.1016/j.eswa.2023.119596