International Transaction Journal of Engineering, Management, & Applied Sciences & Technologies


:: International Transaction Journal of Engineering, Management, & Applied Sciences & Technologies TuEngr+QR-Code

ISSN 2228-9860
eISSN 1906-9642


Vol.12(7) (2021)


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  4. Benotmane, Z., Belalem, G., & Neki, A. (2018). Towards a cloud computing in the service of green logistics. International Journal of Logistics Systems and Management, 29(1), 37-61. doi: 10.1504/ijlsm.2018.088579
  5. Beysenbaev, R., & Dus, Y. (2020). , Proposals for improving the Logistics Performance Index. Asian journal of Shipping and Logistics, pp.34-42.
  6. Bindra, K., & Mishra, A. (2017). A detailed study of clustering algorithms. 6th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO), pp. 371-376, Noida.
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  9. Isik O., Aydin Y., Kosaroglu S.M. (2020). The Assessment of The Logistics Performance Index of CEE Countries with the New Combination of SV and MABAC Methods. LogForum, 16(4), 549-559, DOI: 10.17270/J.LOG.2020.504.
  10. Ittmann, H. (2018). Logistics performance in South Africa). Journal of Transport and Supply Chain Management, pp. 1-3.
  11. Jain, A. K. (2010). Data clustering: 50 years beyond K-means. Pattern Recognit. Letters, 31(8), pp. 651-666.
  12. Janno J., Mochalina E.P., Ivankova G.V., Labanova O., Latonina M., Safulina E., Uukkivi A., 2020. The Impact of Initial Data on the Logistics Performance Index Estimation: Estonian and Russian Study. LogForum, 17(1), 147-156, DOI: 10.17270/J.LOG.2021.554
  13. Kisa A.C.G., Aycin E., 2019. Evaluation of the Logistics Performance of OECD Countries with EDAS Method Based on SWARA. Cankiri Karatekin University Faculty of Economics and Administrative Sciences Journal, 9(1), 301-325, DOI: 10.18074/ckuiibfd.500320.
  14. Li, M., & Wu, X. (2012). Application and research on Information delivering in logistics information portal under a cloud computing enviroment. International Conference on Systems and Informatics (ICSAI2012). DOI: 10.1109/icsai.2012.6223138
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  17. Orhan M. (2019). Comparison of the Logistics Performance Between Turkey and European Union Member Countries with ENTROPY Weighted EDAS Method. European Journal of Science and Technology, (17), 1222-1238, DOI: 10.31590/ejosat.657693.
  18. Ouyang, L. Y.-Y. (2019). A Blockchain-based Framework for Collaborative Production in Distributed and Social Manufacturing. 2019 IEEE International Conference on Service Operations and Logistics, and Informatics (SOLI). doi: 10.1109/soli.
  19. Ouyang, L., Yuan, Y., & & Wang, F.-Y. (2019). A Blockchain-based Framework for Collaborative Production in Distributed and Social Manufacturing. 2019 IEEE International Conference on Service Operations and Logistics, and Informatics (SOLI).
  20. Oyelade, J., Isewon, I., Oladipupo, O., Emebo, O., Omogbadegun, Z., Aromolaran, O., & Olawole, O. (2019). Data Clustering: Algorithms and Its Applications. 19th International Conference on Computational Science and Its Applications (ICCSA). (pp. 71-81). IEEE.
  21. Senir G., 2021. Comparison of domestic logistics performances of Turkey And European Union countries in 2018 with an integrated model. LogForum, 17(2), 193-204, DOI: 10.17270/J.LOG.2021.576
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  23. Ulutas, A., & Karakoy, C. (2019). An analysis of the logistics performance index of EU countries with an integrated MCDM model. Economics and Business Review, 5(19), 49-69.
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