Research Article
BibTex RIS Cite

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

Year 2024, , 590 - 611, 31.10.2024
https://doi.org/10.25204/iktisad.1486017

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.

References

  • 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
  • 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
  • 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
  • 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
  • Aytekin, A. (2020). Çok kriterli karar problemine uzaklık ve referans temelli çözüm yaklaşımı. https://hdl.handle.net/11494/2558
  • 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
  • Aytekin, A. (2022). Çok kriterli karar analizi. https://hdl.handle.net/11494/4808
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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.
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • Eurostat. (2024, 7 Mayıs). Real GDP per capita. https://doi.org/10.2908/SDG_08_10
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • Kendall, M. G. (1948). Rank correlation methods. https://doi.org/10.2307/2333282
  • 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
  • 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
  • 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
  • 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
  • Küçük, Ü. (2022). Lojistik faaliyetlerde yaşanan sorunlar ve çözüm önerileri gıda firması örneği. Eğitim Yayınevi.
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • Parkan, C. (1994). Operational competitiveness ratings of production units. Managerial and Decision Economics, 15(3), 201-221. https://doi.org/10.1002/mde.4090150303
  • Parkan, C. (1996a). Performance measurement for a subway system in Hong Kong. The Georgia Productivity Workshop II, Athens, GA.
  • Parkan, C. (1996b). Measuring the performance of hotel operations. Socio-Economic Planning Sciences, 30(4), 257–292. https://doi.org/10.1108/01443570210427695
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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.
  • 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
  • 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
  • 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
  • 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
  • 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.
  • 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
  • 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
  • World Bank. (2024, 7 Mayıs). Logistic performance index (LPI). https://lpi.worldbank.org/sites/default/files/2023-04/LPI_2023_report_with_layout.pdf
  • 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
  • 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
  • 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
  • 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

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

Year 2024, , 590 - 611, 31.10.2024
https://doi.org/10.25204/iktisad.1486017

Abstract

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.

References

  • 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
  • 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
  • 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
  • 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
  • Aytekin, A. (2020). Çok kriterli karar problemine uzaklık ve referans temelli çözüm yaklaşımı. https://hdl.handle.net/11494/2558
  • 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
  • Aytekin, A. (2022). Çok kriterli karar analizi. https://hdl.handle.net/11494/4808
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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.
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • Eurostat. (2024, 7 Mayıs). Real GDP per capita. https://doi.org/10.2908/SDG_08_10
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • Kendall, M. G. (1948). Rank correlation methods. https://doi.org/10.2307/2333282
  • 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
  • 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
  • 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
  • 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
  • Küçük, Ü. (2022). Lojistik faaliyetlerde yaşanan sorunlar ve çözüm önerileri gıda firması örneği. Eğitim Yayınevi.
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • Parkan, C. (1994). Operational competitiveness ratings of production units. Managerial and Decision Economics, 15(3), 201-221. https://doi.org/10.1002/mde.4090150303
  • Parkan, C. (1996a). Performance measurement for a subway system in Hong Kong. The Georgia Productivity Workshop II, Athens, GA.
  • Parkan, C. (1996b). Measuring the performance of hotel operations. Socio-Economic Planning Sciences, 30(4), 257–292. https://doi.org/10.1108/01443570210427695
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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.
  • 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
  • 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
  • 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
  • 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
  • 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.
  • 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
  • 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
  • World Bank. (2024, 7 Mayıs). Logistic performance index (LPI). https://lpi.worldbank.org/sites/default/files/2023-04/LPI_2023_report_with_layout.pdf
  • 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
  • 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
  • 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
  • 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
There are 110 citations in total.

Details

Primary Language Turkish
Subjects European Union Economy, Statistics (Other)
Journal Section Research Papers
Authors

Erhan Orakçı 0000-0001-8468-5710

Early Pub Date October 25, 2024
Publication Date October 31, 2024
Submission Date May 17, 2024
Acceptance Date October 8, 2024
Published in Issue Year 2024

Cite

APA Orakçı, E. (2024). EATWOS, OCRA ve REF III Teknikleriyle Ülkelerin Lojistik Performans İndeksine Dayalı Etkinliklerinin İncelenmesi. İktisadi İdari Ve Siyasal Araştırmalar Dergisi, 9(25), 590-611. https://doi.org/10.25204/iktisad.1486017
AMA Orakçı E. EATWOS, OCRA ve REF III Teknikleriyle Ülkelerin Lojistik Performans İndeksine Dayalı Etkinliklerinin İncelenmesi. İKTİSAD. October 2024;9(25):590-611. doi:10.25204/iktisad.1486017
Chicago Orakçı, Erhan. “EATWOS, OCRA Ve REF III Teknikleriyle Ülkelerin Lojistik Performans İndeksine Dayalı Etkinliklerinin İncelenmesi”. İktisadi İdari Ve Siyasal Araştırmalar Dergisi 9, no. 25 (October 2024): 590-611. https://doi.org/10.25204/iktisad.1486017.
EndNote Orakçı E (October 1, 2024) EATWOS, OCRA ve REF III Teknikleriyle Ülkelerin Lojistik Performans İndeksine Dayalı Etkinliklerinin İncelenmesi. İktisadi İdari ve Siyasal Araştırmalar Dergisi 9 25 590–611.
IEEE E. Orakçı, “EATWOS, OCRA ve REF III Teknikleriyle Ülkelerin Lojistik Performans İndeksine Dayalı Etkinliklerinin İncelenmesi”, İKTİSAD, vol. 9, no. 25, pp. 590–611, 2024, doi: 10.25204/iktisad.1486017.
ISNAD Orakçı, Erhan. “EATWOS, OCRA Ve REF III Teknikleriyle Ülkelerin Lojistik Performans İndeksine Dayalı Etkinliklerinin İncelenmesi”. İktisadi İdari ve Siyasal Araştırmalar Dergisi 9/25 (October 2024), 590-611. https://doi.org/10.25204/iktisad.1486017.
JAMA Orakçı E. EATWOS, OCRA ve REF III Teknikleriyle Ülkelerin Lojistik Performans İndeksine Dayalı Etkinliklerinin İncelenmesi. İKTİSAD. 2024;9:590–611.
MLA Orakçı, Erhan. “EATWOS, OCRA Ve REF III Teknikleriyle Ülkelerin Lojistik Performans İndeksine Dayalı Etkinliklerinin İncelenmesi”. İktisadi İdari Ve Siyasal Araştırmalar Dergisi, vol. 9, no. 25, 2024, pp. 590-11, doi:10.25204/iktisad.1486017.
Vancouver Orakçı E. EATWOS, OCRA ve REF III Teknikleriyle Ülkelerin Lojistik Performans İndeksine Dayalı Etkinliklerinin İncelenmesi. İKTİSAD. 2024;9(25):590-611.


Creative Commons Lisansı

Bu dergide yayınlanan tüm makaleler Creative Commons Atıf-GayriTicari 4.0 Uluslararası Lisansı ile lisanslanmıştır.