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An Evaluation of the logistics Performance Index Using the ENTROPY-based ORESTE Method

Year 2024, , 68 - 82, 17.05.2024
https://doi.org/10.26650/JTL.2024.1437070

Abstract

Logistics performance measurement has become increasingly important for countries as the competitive environment has increased. For this purpose, the World Bank has begun publishing logistics performance index (LPI) reports. The LPI ranking of countries is determined by the experts’ scoring system. By re-analyzing this scoring and reevaluating it without the need for expert opinion, this study analyzed the evaluation of country rankings according to criteria weights from several different angles. This study aims to provide a detailed analysis of the World Bank’s 2023 report using the ENTROPY-based ORESTE method, which has not previously been used in LPI evaluation and provides a more accurate and robust approach to the research. Although several studies have explored this similar topic in the literature, using a new method and comparing the criteria weights by including them in the analysis gave the present study a broader perspective. LPI analysis is an important tool for assessing and improving a country’s competitiveness, and it can help investors compare logistics infrastructure and processes across countries. This can help stakeholders to better plan and make direct investments. Logistics researchers can use the LPI to examine sectoral and economic trends and forecast future developments. Furthermore, the LPI can be used in academia to train and raise awareness about assessment, logistics, and supply chain management programs. This is an important resource for training future logistics professionals and managers and providing policymakers and practitioners with a more refined tool for identifying areas for improvement and investment in logistics infrastructure.

References

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  • Karaköy, Ç., & Ölmez, U. (2019). Balkan ülkelerinde lojistik performans endeksi değerlendirilmesi. Uluslararası Sosyal, Beşeri ve İdari Bilimlerde Yenilikçi Yaklaşımlar Sempozyumu, 178-180. google scholar
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  • Özdemir, L. (2017). Relationship between financial development and logistics performance and their effects on the competitiveness: an empirical cross-country study. google scholar
  • Rezaei, J., van Roekel, W. S., & Tavasszy, L. (2018). Measuring the relative importance of the logistics performance index indicators using Best Worst Method. Transport Policy, 68, 158-169. google scholar
  • Sh Shang, K. C., & Marlow, P. B. (2007). The effects of logistics competency on performance. Journal of international logistics and Trade, 5(2), 45-66. google scholar
  • Szita, I., & Lörincz, A. (2006). Learning Tetris using the noisy cross-entropy method. Neural computation, 18(12), 2936-2941. google scholar
  • TÜRKOĞLU, M., & DURAN, G. (2023).Çok kriterli karar verme yöntemleri ile bölgesel kapsamli ekonomik ortaklik (rcep) ülkelerinin lojistik performanslarinin değerlendirilmesi. Ekonomi Bilimleri Dergisi, 15(1), 45-69. google scholar
  • The World Bank (2023), The International Bank for Reconstruction and Development, website https://lpi.worldbank.org/ . google scholar
  • Ulutaş, A., & Karaköy, Ç. (2019). An analysis of the logistics performance index ofEU countries with an integrated MCDM model. Economics and Business Review, 5(4), 49-69. google scholar
  • Wu, X., & Liao, H. (2018). An approach to quality function deployment based on probabilistic linguistic term sets and ORESTE method for multi-expert multi-criteria decision making. Information Fusion, 43, 13-26. google scholar
  • Yusufkhonov, Z., Ravshanov, M., Kamolov, A., & Kamalova, E. (2021). Improving the position of the logistics performance index of Uzbekistan. In E3S Web of Conferences (Vol. 264, p. 05028). EDP Sciences. google scholar
  • Zolfani, S. H., Aghdaie, M. H., Derakhti, A., Zavadskas, E. K., & Varzandeh, M. H. M. (2013). Decision making on business issues with foresight perspective; an application of new hybrid MCDM model in shopping mall locating. Expert systems with applications, 40(17), 7111-7121. google scholar
Year 2024, , 68 - 82, 17.05.2024
https://doi.org/10.26650/JTL.2024.1437070

Abstract

References

  • Adali, E. A., & IŞIK, A. T. (2017). Ranking web design firms with the ORESTE method. Ege Academic Review, 17(2), 243-254. google scholar
  • Beysenbaev, R., & Dus, Y. (2020). Proposals for improving the logistics performance index. The Asian Journal of Shipping and Logistics, 36(1), 34-42. google scholar
  • Boer, E. R., & Rakauskas, J. E. (2005, June). Steering entropy revisited. In Driving Assessment Conference (Vol. 3, No. 2005). University of Iowa. google scholar
  • Bozkurt, C., & Mermertaş, F. (2019). Türkiye ve G8 ülkelerinin lojistik performans endeksine göre karşılaştırılması. İşletme ve İktisat Çalışmaları Dergisi, 7(2), 107-117. google scholar
  • Civelek, M. E., Çemberci, M., Artar, O. K., & Uca, N. (2015). Key factors of sustainable firm performance: A strategic approach. google scholar
  • Çetinkaya, C., Özceylan, E., Erbaş, M., & Kabak, M. (2016). GIS-based fuzzy MCDA approach for siting refugee camp: A case study for southeastern Turkey. International Journal of Disaster Risk Reduction, 18, 218-231. google scholar
  • Faria, R. N. D., Souza, C. S. D., & Vieira, J. G. V. (2015). Evaluation of logistic performance indexes of brazil in the international trade. RAM. Revista de Administraçâo Mackenzie, 16, 213-235. google scholar
  • Gavin, M., & Rodrik, D. (1995). The World Bank in historical perspective. The American Economic Review, 85(2), 329-334. google scholar
  • Gergin, R. E., & Baki, B. (2015). Evaluation by integrated AHP and TOPSIS Method of Logistics Performance in Turkey’s Regions. Business and economics research Journal, 6(4), 115. google scholar
  • Guner, S., & Coskun, E. (2012). Comparison of impacts of economic and social factors on countries’ logistics performances: a study with 26 OECD countries. Research in logistics & production, 2(4), 330-343. google scholar
  • Hayaloğlu, P. (2015). The impact of developments in the logistics sector on economic growth: the case of OECD countries. International Journal of Economics and Financial Issues, 5(2), 523-530. google scholar
  • Jafari, H. (2013). Identification and prioritization of grain discharging operations risks by using ORESTE method. American Journal of Public Health Research, 1(8), 214-220. google scholar
  • Karaköy, Ç., & Ölmez, U. (2019). Balkan ülkelerinde lojistik performans endeksi değerlendirilmesi. Uluslararası Sosyal, Beşeri ve İdari Bilimlerde Yenilikçi Yaklaşımlar Sempozyumu, 178-180. google scholar
  • Kisa, A. C. G., & Ayçin, E. (2019). Evaluation of logistics performances of OECD countries with SWARA-based EDAS method. Journal of Çankırı Karatekin University Faculty of Economics and Administrative Sciences, 9(1), 301-325. google scholar
  • Kunadhamraks, P., & Hanaoka, S. (2008). Evaluating the logistics performance of intermodal transportation in Thailand. Asia Pacific Journal of Marketing and Logistics, 20(3), 323-342. google scholar
  • Levy, R., LeBlanc, J. P. F., & Gull, E. (2017). Implementation of the maximum entropy method for analytic continuation. Computer Physics Communications, 215, 149-155. google scholar
  • Liao, H., Wu, X., Liang, X., Xu, J., & Herrera, F. (2018). A new hesitant fuzzy linguistic ORESTE method for hybrid multicriteria decision making. IEEE Transactions on Fuzzy Systems, 26(6), 3793-3807. google scholar
  • Luo, S., Liang, W., & Zhao, G. (2020). Likelihood-based hybrid ORESTE method for evaluating the thermal comfort in underground mines. Applied Soft Computing, 87, 105983. google scholar
  • Mannor, S., Peleg, D., & Rubinstein, R. (2005, August). The cross-entropy method for classification. In Proceedings of the 22nd international conference on Machine learning (pp. 561-568). google scholar
  • Marti, L., Puertas, R., & Garma, L. (2014). The importance of the Logistics Performance Index in International trade. Applied economics, 46(24), 2982-2992. google scholar
  • Marti, L., Puertas, R., & Garma, L. (2014). The importance of the Logistics Performance Index in international trade. Applied economics, 46(24), 2982-2992. google scholar
  • Ojala, L., & Celebi, D. (2015). The World Bank’s Logistics Performance Index (LPI) and drivers of logistics performance. Proceeding of MAC-EMM, OECD, 3-30. google scholar
  • Özdemir, L. (2017). Relationship between financial development and logistics performance and their effects on the competitiveness: an empirical cross-country study. google scholar
  • Rezaei, J., van Roekel, W. S., & Tavasszy, L. (2018). Measuring the relative importance of the logistics performance index indicators using Best Worst Method. Transport Policy, 68, 158-169. google scholar
  • Sh Shang, K. C., & Marlow, P. B. (2007). The effects of logistics competency on performance. Journal of international logistics and Trade, 5(2), 45-66. google scholar
  • Szita, I., & Lörincz, A. (2006). Learning Tetris using the noisy cross-entropy method. Neural computation, 18(12), 2936-2941. google scholar
  • TÜRKOĞLU, M., & DURAN, G. (2023).Çok kriterli karar verme yöntemleri ile bölgesel kapsamli ekonomik ortaklik (rcep) ülkelerinin lojistik performanslarinin değerlendirilmesi. Ekonomi Bilimleri Dergisi, 15(1), 45-69. google scholar
  • The World Bank (2023), The International Bank for Reconstruction and Development, website https://lpi.worldbank.org/ . google scholar
  • Ulutaş, A., & Karaköy, Ç. (2019). An analysis of the logistics performance index ofEU countries with an integrated MCDM model. Economics and Business Review, 5(4), 49-69. google scholar
  • Wu, X., & Liao, H. (2018). An approach to quality function deployment based on probabilistic linguistic term sets and ORESTE method for multi-expert multi-criteria decision making. Information Fusion, 43, 13-26. google scholar
  • Yusufkhonov, Z., Ravshanov, M., Kamolov, A., & Kamalova, E. (2021). Improving the position of the logistics performance index of Uzbekistan. In E3S Web of Conferences (Vol. 264, p. 05028). EDP Sciences. google scholar
  • Zolfani, S. H., Aghdaie, M. H., Derakhti, A., Zavadskas, E. K., & Varzandeh, M. H. M. (2013). Decision making on business issues with foresight perspective; an application of new hybrid MCDM model in shopping mall locating. Expert systems with applications, 40(17), 7111-7121. google scholar
There are 32 citations in total.

Details

Primary Language English
Subjects Industrial Engineering, Manufacturing and Industrial Engineering (Other)
Journal Section Research Article
Authors

Deniz Çıray 0009-0000-9986-4359

Ümit Özdemir 0000-0001-7045-9608

Süleyman Mete 0000-0001-7631-5584

Early Pub Date July 5, 2024
Publication Date May 17, 2024
Submission Date February 14, 2024
Acceptance Date March 15, 2024
Published in Issue Year 2024

Cite

APA Çıray, D., Özdemir, Ü., & Mete, S. (2024). An Evaluation of the logistics Performance Index Using the ENTROPY-based ORESTE Method. Journal of Transportation and Logistics, 9(1), 68-82. https://doi.org/10.26650/JTL.2024.1437070
AMA Çıray D, Özdemir Ü, Mete S. An Evaluation of the logistics Performance Index Using the ENTROPY-based ORESTE Method. JTL. May 2024;9(1):68-82. doi:10.26650/JTL.2024.1437070
Chicago Çıray, Deniz, Ümit Özdemir, and Süleyman Mete. “An Evaluation of the Logistics Performance Index Using the ENTROPY-Based ORESTE Method”. Journal of Transportation and Logistics 9, no. 1 (May 2024): 68-82. https://doi.org/10.26650/JTL.2024.1437070.
EndNote Çıray D, Özdemir Ü, Mete S (May 1, 2024) An Evaluation of the logistics Performance Index Using the ENTROPY-based ORESTE Method. Journal of Transportation and Logistics 9 1 68–82.
IEEE D. Çıray, Ü. Özdemir, and S. Mete, “An Evaluation of the logistics Performance Index Using the ENTROPY-based ORESTE Method”, JTL, vol. 9, no. 1, pp. 68–82, 2024, doi: 10.26650/JTL.2024.1437070.
ISNAD Çıray, Deniz et al. “An Evaluation of the Logistics Performance Index Using the ENTROPY-Based ORESTE Method”. Journal of Transportation and Logistics 9/1 (May 2024), 68-82. https://doi.org/10.26650/JTL.2024.1437070.
JAMA Çıray D, Özdemir Ü, Mete S. An Evaluation of the logistics Performance Index Using the ENTROPY-based ORESTE Method. JTL. 2024;9:68–82.
MLA Çıray, Deniz et al. “An Evaluation of the Logistics Performance Index Using the ENTROPY-Based ORESTE Method”. Journal of Transportation and Logistics, vol. 9, no. 1, 2024, pp. 68-82, doi:10.26650/JTL.2024.1437070.
Vancouver Çıray D, Özdemir Ü, Mete S. An Evaluation of the logistics Performance Index Using the ENTROPY-based ORESTE Method. JTL. 2024;9(1):68-82.



The JTL is being published twice (in April and October of) a year, as an official international peer-reviewed journal of the School of Transportation and Logistics at Istanbul University.