Orta Asya Türk Cumhuriyetlerinin Lojistik ve Taşımacılık Performansları ve Verimliliklerinin Analizi için Hibrid bir Çok Kriterli Karar Verme Modeli

Year 2019, Volume: 8 Issue: 3, 2775 - 2798, 16.07.2019

Ömer Faruk Görçün

https://doi.org/10.33206/mjss.511522

Cited By: 12

Abstract

Bağımsızlıklarını
elde ettiklerinden beri, Avrupa ve Asya arasında önemli bir geçiş güzergâhı
olan Orta Asya Türk Cumhuriyetlerinin küresel ticaretin yanı sıra, uluslararası
taşımacılık ve lojistik operasyonlar açısından önemleri giderek artmaktadırlar.
Bu ülkeler geçiş ülkeleri olmalarına ek olarak, lojistik ve ulaştırma alanında
yaptıkları yatırımlar sayesinde küresel ticarette birer lojistik hub ülke
olabilme çabası göstermektedirler. Öte yandan ulusal gelirlerinin artmasına
bağlı olarak, bu ülkelerin ithalatı da artış gösterirken, aynı zamanda ihracatlarına
konu olan ürünlerin çeşitlilikleri ve artan ihracata bağlı olarak elde
ettikleri gelirler artmaktadır. Söz konusu ülkelerin küresel rekabette önemli
bir aktör haline gelebilmeleri için lojistik ve ulaştırma faaliyetlerine
ilişkin verimliliklerinin, etkinliklerinin ve performanslarının farkında
olmaları ve alacakları kararları bu faktörlere dayandırmaları son derece önem
arz eden bir konudur. Bu nedenle Orta Asya Türk Cumhuriyetlerinin lojistik ve
taşımacılık alanında performanslarını değerlendirebilmek için sistematik ve
yapısal nitelikte çözüm yolu öneren bir metodolojiye ve modele gereksinim
duyulmaktadır. Bu çalışmada söz konusu ülkelerin lojistik verimliliklerini
analiz edebilmek için entegre entropi ve EATWOS yöntemlerinden oluşan hibrid
bir model önerilmektedir. Seçilen model ülkelerin lojistik alanında
kullandıkları girdi ve çıktı faktörlerine odaklanarak, verimlilik değerlerinin
hesaplanmasına olanak sağlarken, aynı zamanda ülkelerin lojistik ve ulaştırma
alanında performanslarını ve verimliliklerini karşılaştırma olanağı da
sağlamaktadır. 

Keywords

Entropi, EATWOS Yöntemi, Verimlilik Analizi, Lojistik, Ulaştırma Sistemleri

A Hybrid MCDM Model for Performance and Productivity Analysis of Logistics and Transportation Performance of Central Asian Turk Republics

Abstract

Since their independence, the importance of Central Asian Turk Republics in the perspective of international transportation and logistics operations in addition to global trade has been increasing. Especially, in addition to being a country of transit, each of them tries to be hub countries in the international trade thanks to investments, which were made in the fields of transportation and logistics by themselves. At the same time, while the import volume of these countries is shown an increase depending on their national incomes. As well as the range of products that subject to the export, total revenue of countries is also increased day by day. In order to be important actors in international trade, they should be aware of their productivity, effectivity, and performance and should base on their decisions to these factors. Therefore, it is needed a methodology and model, which suggest systematic and structural solution way in order to evaluate the performance of the Republics of Central Asia in the fields of logistics and transportation. In this study, a hybrid model, which consist of integrated entropy and EATWOS methods is proposed in order to analyze the logistical effectivities of these countries. While the selected model can provide the calculation of the logistic performance scores of countries and it provides an opportunity of comparison of logistics effectivity and performance of these countries by focusing the output and input factors.

Keywords

Entropy, EATWOS Method, Productivity Analysis, Logistics, Transportation Systems

References

• Referans1 Banister, D., Berechman, Y. (2001). Transport Investment and The Promotion of Economic Growth. Journal of Transport Geography, 9, (3), 209-218.
• Referans2 Brockett, P.L., Golany, B., Li, S. (1998). Analysis of Intertemporal Efficiency Trends Using Rank Statistics with an Application Evaluating the Macro Economic Performance of OECD Nations. Journal of Productivity Analysis, 11, 169-182.
• Referans3 Caplice, C., Sheffi, Y. (1994). A Review and Evaluation of Logistics Metrics. The International Journal of Logistics, 15, (3), 280-290.
• Referans4 Chow, G., Heaver, T.D., Henriksson, L.E. (1994). Logistics Performance: Definition and Measurement. International Journal of Physical Distribution & Logistics Management, 24, (1), 17-28.
• Referans5 Coelli, T., Estache, A., Perelman, S., Trujillo, L. (2003). A Primer On Efficiency Measurement for Utilities and Transport Regulators. The World Bank. Washington, D.C.
• Referans6 Cullinane, K., T.F., Wang, D.W., Song, Ji, P. (2006). The Technical Efficiency of Container Ports: Comparing Data Envelopment Analysis and Stochastic Frontier Analysis. Transportation Research Part A: Policy and Practice, 40, 4, 354-374.
• Referans7 Erkan, B. (2014). The Importance and Determinants of Logistics Performance of Selected Countries. Journal of Emerging Issues in Economics. Finance and Banking (JEIEFB), 3, (6), 1237-1254.
• Referans8 Gogoneata, B. (2008). An Analysis of Explanatory Factors of Logistics Performance of a Country. The AMFITEATRU ECONOMIC Journal, Academy of Economic Studies - Bucharest, Romania, 10, 24, 143-156.
• Referans9 Hausman, W.H., Lee, H.L. Subramanian, U. (2005). The Impact of Logistics Performance on Trade. 22, (2), 236-252.
• Referans10 Heikkilä, J. (2002). From Supply to Demand Chain Management: Efficiency and Customer Satisfaction. Journal of Operations Management, 20, (6), 747-767.
• Referans11 Hwang, C.L., Yoon, K. (1981). Multiple Attribute Decision Making – Methods and Applications – A State-Of-The-Art Survey. Springer-Verlag, Berlin, Heidelberg, New York, NY.
• Referans12 Jaramillo, C.F., Freund, C., Reis, J.G., Arvis, J. F., Wiederer, C.K., Ojala, L.M., Shepherd, B.A., Raj, A.U.L., Dairabayeva, K.S., Kiiski, T.M.M. (2018). Connecting to Compete 2018: Trade Logistics in The Global Economy - The Logistics Performance Index and Its Indicators. World Bank Group, Washington, D.C.
• Referans13 Karami, A., Johansson, R. (2014). Utilization of Multi Attribute Decision Making Techniques to Integrate Automatic and Manual Ranking of Options. Journal of Information Science and Engineering, 30, 519-534.
• Referans14 Layard, R. (1994). Cost-Benefit Analysis, Cambridge University Press, Cambridge.
• Referans15 Li, X., Wang, K., Liu, L., Xin, J., Yang, H., Gao, C. (2011). Application of The Entropy Weight and TOPSIS Method in Safety Evaluation of Coal Mines. Procedia Engineering, 26, 2085-2091.
• Referans16 Liu, C.L; Lyons, A.C; (2011). An Analysis of Third-Party Logistics Performance and Service Provision. Transportation Research Part E: Logistics and Transportation Review, 47, (4), 547-570.
• Referans17 Martí, L., Puertas, R., García L. (2014). The Importance of the Logistics Performance Index in International Trade. Applied Economics, 46, (24), 2982-2992.
• Referans18 Özbek, A. (2015a). Çok Ölçütlü Karar Verme Yöntemleriyle Hayırsever Kuruluşlarında Verimlilik Analizi Efficiency Analysis in Charity Organizations by Multiple Criteria Decision. Anadolu Üniversitesi Sosyal Bilimler Dergisi, 18, (2), 99-114.
• Referans19 Özbek, A. (2015b). Efficiency Analysis of the Turkish Red Crescent Between 2012 And 2014. International Journal of Economics and Finance, 7, (9), 322-334.
• Referans20 Özbek, A. (2015c). Analysis of Private Pension Companies in Turkey by EATWOS. European Journal of Business and Management, 7, (26), 31-43.
• Referans21 Özbek, A. (2015d). Efficiency Analysis of Non-Governmental Organizations Based in Turkey. International Business Research, 8, (9), 95-104.
• Referans22 Özbek, A. (2015e). Efficiency Analysis of the Turkish Red Crescent Between 2012 And 2014. International Journal of Economics and Finance, 7, (9), 322-334.
• Referans23 Özbek, A. (2015f). Gönüllü Kuruluşlarda Çalışanların Electre Yöntemine Göre Değerlendirilmesi. Electronic Journal of Social Sciences, 14, (54), 221-233.
• Referans24 Özbek, A. (2016). Efficiency Analysis of Gold Mining Companies Through Financial Statements. International Journal of Academic Research in Business and Social Sciences, 6, (10), 273-290.
• Referans25 Özbek, A. (2017). İlkokul Öğretmenleri Sağlik Ve Sosyal Yardim Sandiği'nin Finansal Performans Analizi. Çankırı Karatekin Üniversitesi İİBF Dergisi, 7, (1), 1-31.
• Referans26 Puertas, R., Martí, L., García, L. (2014). Logistics Performance and Export Competitiveness: European Experience. Empirica, 41, 467.
• Referans27 Ruamsook, K., Russell, D.M., Thomchick, E.A. (2009). Sourcing from Low‐Cost Countries: Identifying Sourcing Issues and Prioritizing Impacts On Logistics Performance. The International Journal of Logistics Management, 20, (1), 79-96.
• Referans28 Shepherd, Günter. (2010). Measuring Supply Chain Performance: Current Research and Future Directions. International Journal of Productivity and Performance Management, 55, (3/4), 242-258.
• Referans29 Soni, V., Singh, S., & Banwet, D. (2016). Precise Decisions in Indian Energy Sector by Imprecise Evaluation. International Journal of Energy Sector Management, 10, (1), 111-118.
• Referans30 Tongzon, J., Heng, W. (2005). Port Privatization, Efficiency and Competitiveness: Some Empirical Evidence from Container Ports (Terminals). Transportation Research Part A: Policy and Practice, 39, (5), 405-424.
• Referans31 Töyli, J., Häkkinen, L., Ojala, L., Naula, T. (2008). Logistics and Financial Performance: An Analysis of 424 Finnish Small and Medium‐Sized Enterprises. International Journal of Physical Distribution & Logistics Management, 38, (1), 57-80.
• Referans32 Vining, A.R; Boardman, E.A. (1992). Ownership Versus Competition: Efficiency in Public Enterprise. Public Choice, 73, (2), 205-239.
• Referans33 Wang, T.C., Lee, H.D. (2009). Developing A Fuzzy TOPSIS Approach Based On Subjective Weights and Objective Weights. Expert Systems with Applications, 36, (5), 8980-8985.
• Referans34 Yuen, C., Zhang, A., Cheung, W. (2012). Port Competitiveness from The Users' Perspective: An Analysis of Major Container Ports in China and Its Neighboring Countries. Research in Transportation Economics, 35, (1), 34-40.