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AN ANALYSIS OF THE LOGISTICS AND ENVIRONMENTAL PERFORMANCE OF BRI COUNTRIES

Year 2021, Volume: 20 Issue: 4, 1893 - 1915, 29.10.2021
https://doi.org/10.21547/jss.927509

Abstract

The purpose of this research is to evaluate the rankings of Belt Road countries in terms of Logistics Performance Index (LPI) score and Environmental Performance Index (EPI) score. In the research, the performance evaluations of the countries that handle five hundred thousand TEU containers annually within the scope of the Belt Road project in 2014, 2016 and 2018 were made. Performance of Belt and Road countries will be evaluated through integrated Entropy-TOPSIS methods. As a result of the study, it was determined that Portugal, Slovenia, Italy, Singapore, Greece, Israel, Russia, Malaysia, Jordan and Romania were successful countries in performance evaluation due to their high LPI and EPI scores. Kuwait, Egypt, Malaysia, Jordan, Turkey, Algeria, Saudi Arabia, United Arab Emirates and Philippines in the LPI and EPI performance evaluation scores in the intermediate level has been moderate due to the successful countries. China, Hong Kong, India, Indonesia, Thailand, Vietnam, Kenya, Myanmar and Pakistan were the least successful countries in performance evaluation due to low LPI and EPI scores.

References

  • Aboul-Dahab, K. ve Ibrahim, M. A. (2020). Investigating the efficiency of the logistics performance ındex (LPI) weighting system using the technique for order of preference by similarity to ıdeal solution (TOPSIS) method, International Journal of Science and Research, 9, 269-277.
  • Antão, P., Calderón, M., Puig, M., Michail, A., Wooldridge, C. ve Darbra, R. M. (2016). ıdentification of occupational health, safety, security (OHSS) and environmental performance ındicators ın port areas, Safety Science, 85, 266–275.
  • Ayçin, E. ve Çakın, E. (2019). Ülkelerin çevresel performanslarının çok kriterli karar verme yöntemleri ve bulanık mantık tabanlı bir yaklaşım ile bütünleşik olarak değerlendirilmesi, Eskişehir Osmangazi Üniversitesi İktisadi ve İdari Bilimler Dergisi, 14(3), 631-656.
  • Bilbao-Terol, A., Arenas-Parra, M., Cañal-Fernández, V. ve Antomil-Ibias, J. (2014). Using TOPSIS for assessing the sustainability of government bond funds. Omega, 49, 1-17.
  • BRI Big Data Report. (2017). Big Data Report of the Trade Cooperation under the Belt and Road Initiative. Erişim Tarihi: 15. 02. 2021, https://eng.yidaiyilu.gov.cn/qwyw/rdxw/2201.htm.
  • Cansız, Ö. F. ve Ünsalan, K. (2020). Yapay zekâ ve istatistiksel yöntemler ile küresel ticarette rekabet ölçütü olan lojistik performans endeksine (LPI) etken parametrelerin ülke bazlı incelenmesi ve tahmin modellerinin geliştirilmesi, Fırat Üniversitesi Mühendislik Bilimleri Dergisi, 32(2), 571-582.
  • Çakır, S. (2017). Measuring logistics performance of OECD countries via fuzzy linear regression, Journal of Multi Criteria Decision Analysis, 24(3-4), 177-186.
  • Dianawati, F. ve Perdana, W. S. (2019). Analytic hierarchy process (AHP) and topsıs for designing green public procurement indicator on trans-java toll rest area, In Proceedings of the 2019 5th International Conference on Industrial and Business Engineering, 237-242.
  • EPI, (2021). Environmental Performance Index Rankings, Erişim Tarihi: 10. 02. 2021, www.epi.yale.edu
  • EPI, (2020b). Environmental Performance Index 2020 Report, Erişim Tarihi: 22. 02. 2021, https://epi.yale.edu/downloads/epi2020report20210112.pdf
  • Gallego-Alvarez, I., Vicente-Galindo, M., Galindo-Villardón, M. ve Rodríguez-Rosa, M. (2014). Environmental performance in countries worldwide: determinant factors and multivariate analysis, Sustainability, 6(11), 7807-7832.
  • Jin, H., Qian, X., Chin, T. ve Zhang, H. (2020). A global assessment of sustainable development based on modification of the human development index via the entropy method, Sustainability, 12(8), 3251.
  • Karaköy, Ç. ve Ölmez, U. (2019). Balkan ülkelerinde lojistik performans endeksi değerlendirilmesi, SETSCI Conference Proceedings
4 (8), 178-180,.
  • Kumar, S. ve Barman, A. G. (2021). Fuzzy TOPSIS and FUZZY vıkor ın selecting green suppliers for sponge ıron and steel manufacturing, Soft Computing, 25(8), 6505-6525.
  • Li, W., Xi, Y., Liu, S., Q., Li, M., Chen, L., Wu, X. ve Masoud, M. (2020). An ımproved evaluation framework for industrial green development: considering the underlying conditions, Ecological Indicators, 112, 106044.
  • LPI, (2021). Logistics Performance Index Rankings, Erişim Tarihi: 09. 02. 2021, https://lpi.worldbank.org/
  • Mercangoz, B. A., Yildirim, B. F. ve Yildirim, S. K. (2020). Time period based COPRAS-G method: application on the logistics performance index, LogForum, 16(2).
  • Oğuz S., Alkan, G. Ve Yılmaz, B. (2019). Seçilmiş asya ülkelerinin lojistik performanslarının TOPSIS yöntemi ile değerlendirilmesi, IBAD Sosyal Bilimler Dergisi, 497-507.
  • Ozmen, M. (2019). Logistics competitiveness of OECD countries using an improved TODIM method, Sādhanā, 44(5), 108.
  • Rezaei, J., van Roekel, W. S. ve Tavasszy, L. (2018). Measuring the relative importance of the logistics performance index indicators using best worst method, Transport Policy, 68, 158-169.
  • Sahin, A. ve Pehlivan, N. Y. (2017). Comparative analysis of multi-criteria decision making methods: a case study of the countries’ environmental performance index, In 3rd Internatıonal Researchers, Statıstıcıans And Young Statıstıcıans Congress.
  • Stojanović, I. ve Puška, A. (2021). Logistics performances of gulf cooperation council’s countries in global supply chainsi Decision Making: Applications in Management and Engineering, 4(1), 174-193.
  • Tang, J., Zhu, H. L., Liu, Z., Jia, F. ve Zheng, X. X. (2019). Urban sustainability evaluation under the modified TOPSIS based on grey relational analysis. International Journal Of Environmental Research And Public Health, 16(2), 256.
  • Tian, R., Yang, Z. ve Shao, Q. (2019). China’s arable land ınvestment in the “belt and road” region: an empirical study of overseas arable land resources, Sustainability, 12(1), 1-1.
  • Ulutaş A. ve Karaköy, C. (2019). An analysis of the logistics performance index of EU countries with an integrated MCDM model, Economics and Business Review, 5(4), 49-69.
  • Ulutaş, A. ve Karaköy, Ç. (2021). Evaluation of LPI values of transition economies countries with a grey MCDM model. In Handbook of Research on Applied AI for International Business and Marketing Applications, 499-511, IGI Global.
  • Ustalı, N. K. ve Tosun, Ö. (2020). Investıgatıon of logıstıc performance of G-20 countries using data envelopment analysis and malmquist total factor productivity analysis, Mehmet Akif Ersoy Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 7 (3), 755-781.
  • Yalçın, B. ve Ayvaz, B. (2020). Çok kriterli karar verme teknikleri ile lojistik performansın değerlendirilmesi, İstanbul Ticaret Üniversitesi Fen Bilimleri Dergisi, 19(38), 117-138.
  • Yildirim, B. F. ve Mercangoz, B. A. (2020). Evaluating the logistics performance of OECD countries by using Fuzzy AHP and ARAS-G, Eurasian Economic Review, 10(1), 27-45.
  • Zheng, B. ve Bedra, K. B. (2018). Recent sustainability performance in china: strength-weakness analysis and ranking of provincial cities, Sustainability, 10(9), 3063.

KUŞAK YOL ÜLKELERİNİN LOJİSTİK VE ÇEVRESEL PERFORMANSININ ANALİZİ

Year 2021, Volume: 20 Issue: 4, 1893 - 1915, 29.10.2021
https://doi.org/10.21547/jss.927509

Abstract

Bu araştırmanın amacı, Kuşak Yol ülkeleri sıralamalarını Lojistik Performans Endeksi (LPI) puanı ve Çevresel Performans Endeksi (EPI) puanı açısından değerlendirmektir. Araştırmada Kuşak Yol projesi kapsamında yıllık beş yüz bin TEU konteyner elleçleyen ülkelerin 2014, 2016 ve 2018 yılları performans değerlendirmesi yapılmıştır. Kuşak Yol ülkelerinin performansı, bütünleşik Entropi-TOPSIS yöntemleri aracılığıyla değerlendirilecektir. Araştırmanın sonucunda, Portekiz, Slovenya, İtalya, Singapur, Yunanistan, İsrail, Rusya, Malezya Ürdün ve Romanya’nın LPI ve EPI skorlarının yüksek olması sebebiyle performans değerlendirmesinde başarılı ülkeler olduğu saptanmıştır. Kuveyt, Mısır, Malezya, Ürdün, Türkiye, Cezayir, Sudi Arabistan, Birleşik Arap Emirlikleri ve Filipinlerin LPI ve EPI skorlarının orta seviyede olması sebebiyle performans değerlendirmesinde ılımlı başarılı ülkeler olmuştur. Çin, Hong Kong, Hindistan, Endonezya, Tayland, Vietnam, Kenya, Myanmar ve Pakistan LPI ve EPI skorlarının düşük seviyede olması sebebiyle performans değerlendirmesinde en az başarılı ülkeler olmuştur.

References

  • Aboul-Dahab, K. ve Ibrahim, M. A. (2020). Investigating the efficiency of the logistics performance ındex (LPI) weighting system using the technique for order of preference by similarity to ıdeal solution (TOPSIS) method, International Journal of Science and Research, 9, 269-277.
  • Antão, P., Calderón, M., Puig, M., Michail, A., Wooldridge, C. ve Darbra, R. M. (2016). ıdentification of occupational health, safety, security (OHSS) and environmental performance ındicators ın port areas, Safety Science, 85, 266–275.
  • Ayçin, E. ve Çakın, E. (2019). Ülkelerin çevresel performanslarının çok kriterli karar verme yöntemleri ve bulanık mantık tabanlı bir yaklaşım ile bütünleşik olarak değerlendirilmesi, Eskişehir Osmangazi Üniversitesi İktisadi ve İdari Bilimler Dergisi, 14(3), 631-656.
  • Bilbao-Terol, A., Arenas-Parra, M., Cañal-Fernández, V. ve Antomil-Ibias, J. (2014). Using TOPSIS for assessing the sustainability of government bond funds. Omega, 49, 1-17.
  • BRI Big Data Report. (2017). Big Data Report of the Trade Cooperation under the Belt and Road Initiative. Erişim Tarihi: 15. 02. 2021, https://eng.yidaiyilu.gov.cn/qwyw/rdxw/2201.htm.
  • Cansız, Ö. F. ve Ünsalan, K. (2020). Yapay zekâ ve istatistiksel yöntemler ile küresel ticarette rekabet ölçütü olan lojistik performans endeksine (LPI) etken parametrelerin ülke bazlı incelenmesi ve tahmin modellerinin geliştirilmesi, Fırat Üniversitesi Mühendislik Bilimleri Dergisi, 32(2), 571-582.
  • Çakır, S. (2017). Measuring logistics performance of OECD countries via fuzzy linear regression, Journal of Multi Criteria Decision Analysis, 24(3-4), 177-186.
  • Dianawati, F. ve Perdana, W. S. (2019). Analytic hierarchy process (AHP) and topsıs for designing green public procurement indicator on trans-java toll rest area, In Proceedings of the 2019 5th International Conference on Industrial and Business Engineering, 237-242.
  • EPI, (2021). Environmental Performance Index Rankings, Erişim Tarihi: 10. 02. 2021, www.epi.yale.edu
  • EPI, (2020b). Environmental Performance Index 2020 Report, Erişim Tarihi: 22. 02. 2021, https://epi.yale.edu/downloads/epi2020report20210112.pdf
  • Gallego-Alvarez, I., Vicente-Galindo, M., Galindo-Villardón, M. ve Rodríguez-Rosa, M. (2014). Environmental performance in countries worldwide: determinant factors and multivariate analysis, Sustainability, 6(11), 7807-7832.
  • Jin, H., Qian, X., Chin, T. ve Zhang, H. (2020). A global assessment of sustainable development based on modification of the human development index via the entropy method, Sustainability, 12(8), 3251.
  • Karaköy, Ç. ve Ölmez, U. (2019). Balkan ülkelerinde lojistik performans endeksi değerlendirilmesi, SETSCI Conference Proceedings
4 (8), 178-180,.
  • Kumar, S. ve Barman, A. G. (2021). Fuzzy TOPSIS and FUZZY vıkor ın selecting green suppliers for sponge ıron and steel manufacturing, Soft Computing, 25(8), 6505-6525.
  • Li, W., Xi, Y., Liu, S., Q., Li, M., Chen, L., Wu, X. ve Masoud, M. (2020). An ımproved evaluation framework for industrial green development: considering the underlying conditions, Ecological Indicators, 112, 106044.
  • LPI, (2021). Logistics Performance Index Rankings, Erişim Tarihi: 09. 02. 2021, https://lpi.worldbank.org/
  • Mercangoz, B. A., Yildirim, B. F. ve Yildirim, S. K. (2020). Time period based COPRAS-G method: application on the logistics performance index, LogForum, 16(2).
  • Oğuz S., Alkan, G. Ve Yılmaz, B. (2019). Seçilmiş asya ülkelerinin lojistik performanslarının TOPSIS yöntemi ile değerlendirilmesi, IBAD Sosyal Bilimler Dergisi, 497-507.
  • Ozmen, M. (2019). Logistics competitiveness of OECD countries using an improved TODIM method, Sādhanā, 44(5), 108.
  • Rezaei, J., van Roekel, W. S. ve Tavasszy, L. (2018). Measuring the relative importance of the logistics performance index indicators using best worst method, Transport Policy, 68, 158-169.
  • Sahin, A. ve Pehlivan, N. Y. (2017). Comparative analysis of multi-criteria decision making methods: a case study of the countries’ environmental performance index, In 3rd Internatıonal Researchers, Statıstıcıans And Young Statıstıcıans Congress.
  • Stojanović, I. ve Puška, A. (2021). Logistics performances of gulf cooperation council’s countries in global supply chainsi Decision Making: Applications in Management and Engineering, 4(1), 174-193.
  • Tang, J., Zhu, H. L., Liu, Z., Jia, F. ve Zheng, X. X. (2019). Urban sustainability evaluation under the modified TOPSIS based on grey relational analysis. International Journal Of Environmental Research And Public Health, 16(2), 256.
  • Tian, R., Yang, Z. ve Shao, Q. (2019). China’s arable land ınvestment in the “belt and road” region: an empirical study of overseas arable land resources, Sustainability, 12(1), 1-1.
  • Ulutaş A. ve Karaköy, C. (2019). An analysis of the logistics performance index of EU countries with an integrated MCDM model, Economics and Business Review, 5(4), 49-69.
  • Ulutaş, A. ve Karaköy, Ç. (2021). Evaluation of LPI values of transition economies countries with a grey MCDM model. In Handbook of Research on Applied AI for International Business and Marketing Applications, 499-511, IGI Global.
  • Ustalı, N. K. ve Tosun, Ö. (2020). Investıgatıon of logıstıc performance of G-20 countries using data envelopment analysis and malmquist total factor productivity analysis, Mehmet Akif Ersoy Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 7 (3), 755-781.
  • Yalçın, B. ve Ayvaz, B. (2020). Çok kriterli karar verme teknikleri ile lojistik performansın değerlendirilmesi, İstanbul Ticaret Üniversitesi Fen Bilimleri Dergisi, 19(38), 117-138.
  • Yildirim, B. F. ve Mercangoz, B. A. (2020). Evaluating the logistics performance of OECD countries by using Fuzzy AHP and ARAS-G, Eurasian Economic Review, 10(1), 27-45.
  • Zheng, B. ve Bedra, K. B. (2018). Recent sustainability performance in china: strength-weakness analysis and ranking of provincial cities, Sustainability, 10(9), 3063.
There are 30 citations in total.

Details

Primary Language Turkish
Subjects Finance
Journal Section Business
Authors

Gökhan Akandere 0000-0002-5051-1154

Publication Date October 29, 2021
Submission Date April 25, 2021
Acceptance Date June 15, 2021
Published in Issue Year 2021 Volume: 20 Issue: 4

Cite

APA Akandere, G. (2021). KUŞAK YOL ÜLKELERİNİN LOJİSTİK VE ÇEVRESEL PERFORMANSININ ANALİZİ. Gaziantep University Journal of Social Sciences, 20(4), 1893-1915. https://doi.org/10.21547/jss.927509