LOGISTIC PERFORMANCE INDEX OF OECD MEMBERS

Year 2020, Volume: 12 Issue: 23, 598 - 608, 26.11.2020

Abdulkadir Atalan

https://doi.org/10.20990/kilisiibfakademik.720604

Cited By: 2

Abstract

Logistics Performance Index (LPI) values of the countries are considered in order to show the development levels of the countries' logistics infrastructure. In this study, the LPI values of the next period were calculated by considering the current LPI values of OECD members. Estimation series method was developed by using nonlinear equations for this study. The estimation data differed according to the degree of reliability of the equations. Estimated LPI data ranged from 2.869 to 4.206 with an average value of 3.611 based on equations. According to developed method of the study, the maximum value of LPI was estimated for Sweden, while the lowest value of LPI was determined for Slovenia among the members of OECD. In brief, a significant decrease in the estimated LPI values was observed in the majority of OECD members.

Keywords

Logistics Performance Index, OECD Members, Estimation Series, Degree of Reliability

OECD ÜYELERİNİN LOJİSTİK PERFORMANS İNDEKSİ

Abstract

Ülkelerin lojistik altyapılarının gelişmişlik düzeylerini göstermek için ülkelere ait Lojistik Performans İndeks (LPİ) değerleri dikkate alınmaktadır. Bu çalışmada OECD üyelerinin mevcut LPİ değerleri göz önünde bulundurularak bir sonraki döneme ait LPİ değerleri hesaplanmıştır. Bu çalışma için geliştirilen yöntem ile doğrusal olmayan denklemler kullanılarak tahmin serisi metodu geliştirilmiştir. Tahmin verileri, denklemlerin güvenilirlik derecesine göre farklılık göstermiştir. Tahmini LPİ verileri 2,869 ile 4,206 arasında yer almıştır ve ortalama değer 3.611 olarak hesaplanmıştır. İsveç maksimum LPİ değerine sahip olurken Slovenya’nın en düşük LPİ değerine sahip olduğu tespit edilmiştir. Sonuç olarak, tahmini LPİ değerlerinde OECD üyelerinin büyük bir kısmında düşüş olduğu gözlemlenmiştir.

Keywords

Lojistik Performans İndeksi, OECD üyeleri, Tahmin Serisi, Güvenirlilik Derecesi

References

• ARVIS, J. F., MUSTRA, M. A., OJALA, L., SHEPHERD, B., & SASLAVSKY, D. (2010). Connecting to Compete 2010:Trade Logistics in the Global Economy-The Logistics Performance Index and Its Indicators. In The World Bank. Washington (DC).
• ARVIS, J. F., MUSTRA, M. A., OJALA, L., SHEPHERD, B., & SASLAVSKY, D. (2012). Connecting to Compete 2012:Trade Logistics in the Global Economy-The Logistics Performance Index and Its Indicators.
• ARVIS, J. F., OJALA, L., WIEDERER, C., SHEPHERD, B., RAJ, A., DAIRABAYEVA, K., & KIISKI, T. (2018). Connecting to Compete 2018:Trade Logistics in the Global Economy-The Logistics Performance Index and Its Indicators. World Bank.
• ARVIS, J. F., SASLAVSKY, D., OJALA, L., SHEPHERD, B., BUSCH, C., & RAJ, A. (2014). Connecting to Compete 2014:Trade Logistics in the Global Economy-The Logistics Performance Index and Its Indicators. In The World Bank.
• ARVIS, JEAN-FRANCOIS, ALINA MUSTRA, M., PANZER, J., OJALA, L., & NAULA, T. (2007). Connecting to Compete 2007:Trade Logistics in the Global Economy. The Logistics Performance Index and Its Indicators. In Connecting to Compete 2007.
• ARVIS, JEAN-FRANÇOIS, SASLAVSKY, D., OJALA, L., SHEPHERD, B., BUSCH, C., RAJ, A., & NAULA, T. (2016). Connecting to Compete 2010:Trade Logistics in the Global Economy-The Logistics Performance Index and Its Indicators.
• ATALAN, A. (2018). Türkiye Sağlık Ekonomisi için İstatistiksel Çok Amaçlı Optimizasyon Modelinin Uygulanması. İşletme Ekonomi ve Yönetim Araştırmaları Dergisi, 1(1), 34–51.
• ATALAN, A. (2019). The Impacts of Healthcare Resources on Services of Emergency Department: Discrete Event Simulation with Box-Behnken Design. PONTE International Scientific Researchs Journal, 75(6), 12–23.
• CHAPMAN, R. L., SOOSAY, C., & KANDAMPULLY, J. (2003). Innovation in logistic services and the new business model: a conceptual framework. International Journal of Physical Distribution & Logistics Management, 33(7), 630–650.
• CHILDERLEY, A. (1980). The importance of logistics in the UK economy. International Journal of Physical Distribution & Materials Management, 10(4), 185–192.
• DAVIDSON, A. L. (2006). Key performance indicators in humanitarian logistics. Massachusetts Institute of Technology.
• DEVKOTA, K. C., REGMI, A. D., POURGHASEMI, H. R., YOSHIDA, K., PRADHAN, B., RYU, I. C., … ALTHUWAYNEE, O. F. (2013). Landslide susceptibility mapping using certainty factor, index of entropy and logistic regression models in GIS and their comparison at Mugling–Narayanghat road section in Nepal Himalaya. Natural Hazards, 65(1), 135–165.
• HOLLWEG, C., & WONG, M.-H. (2009). Measuring regulatory restrictions in logistics services. ERIA Discussion Paper Series, 14.
• KARMARKAR, U. S., & APTE, U. M. (2007). Operations management in the information economy: Information products, processes, and chains. Journal of Operations Management, 25(2), 438–453.
• KOVÁCS, G., & KOT, S. (2016). New logistics and production trends as the effect of global economy changes. Polish Journal of Management Studies, 14.
• LAN, S. L., & ZHONG, R. Y. (2018). Coordinated development between metropolitan economy and logistics for sustainability. Resources, Conservation and Recycling, 128, 345–354.
• LAN, S., YANG, C., & HUANG, G. Q. (2017). Data analysis for metropolitan economic and logistics development. Advanced Engineering Informatics, 32, 66–76.
• MARTÍ, L., PUERTAS, R., & GARCÍA, L. (2014). The importance of the Logistics Performance Index in international trade. Applied Economics. PUERTAS, R., MARTÍ, L., & GARCÍA, L. (2014). Logistics performance and export competitiveness: European experience. Empirica, 41(3), 467–480.
• 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.
• THE WORLD BANK. (2018). The Lojistic Performance Index.
• TSENG, Y., YUE, W. L., & TAYLOR, M. A. P. (2005). The role of transportation in logistics chain. Eastern Asia Society for Transportation Studies.