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Veri zarflama analizi ile Avrupa geçiş ekonomilerinin lojistik performans endeksi kullanılarak değerlendirilmesi

Year 2023, Volume: 12 Issue: 1, 30 - 51, 30.06.2023
https://doi.org/10.47934/tife.12.01.02

Abstract

Rekabetin her geçen gün daha yoğun yaşandığı günümüz kapitalizminde, performans ile onun unsurları olan etkinlik ve verimlilik artan önemini korumaktadır. Üretim sisteminde yüksek bir performans gerçekleştirmek için tüm süreçte optimal kaynak kullanımının sağlanması, maliyetlerin düşürülmesi gerekmektedir. Malzeme arzı, malzeme tedariki ve lojistik süreci boyunca tüm aşama optimum uyum içinde gerçekleştirilmelidir. Dolayısıyla performans artışında, lojistik sektörlerinin etkinliğinin ve verimliliğinin sağlanması önem kazanmaktadır. Bu çalışmada, Avrupa Geçiş Ekonomisi Ülkeleri içinde geçişi tamamlamış olan 11 ülkenin etkinlik ve verimlilik analizi, Lojistik Performans Endeksi alt boyutlarına ait veriler kullanılarak Girdi Odaklı Ölçeğe Göre Sabit Getiri (CCR) ve Girdi Odaklı Ölçeğe Göre Değişken Getiri (BCC) Modellerine göre yapılmıştır. Lojistik Performans Endeksinin altı alt boyutundan üçü (gümrük, altyapı ve lojistik kalite) girdi olarak kullanılırken, diğer üçü ise (uluslararası gönderiler, izleme-takip ve zamanında teslimat) çıktı olarak ele alınmıştır. Veri Zarflama Analizi ile yapılan çalışmada “EMS Paket Programı” kullanılarak etkinlik değerlendirilmesi yapılmıştır. Analiz bulgularından elde edilen sonuçlara göre etkin ve verimli olan ülkeler bulunmuştur. Aynı zamanda etkinsiz ve verimsiz olan ülkeler de bulunarak, etkin olmayan ülkelerin ideal etkinlik düzeyine çıkabilmesi için girdi değişkenlerin iyileştirme oranları hesaplanmıştır.

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Evaluation of European transition economies using the logistics performance index with data envelopment analysis

Year 2023, Volume: 12 Issue: 1, 30 - 51, 30.06.2023
https://doi.org/10.47934/tife.12.01.02

Abstract

In today's capitalism, where competition is more intense day by day, performance and its elements, efficiency, and productivity, remain of increasing importance. In order to realise a high performance in the production system, it is necessary to ensure optimal resource utilisation in the whole process and to reduce costs. The entire stage during the material supply, material procurement and logistics process should be carried out in optimal harmony. Therefore, ensuring the activity and efficiency of logistics sectors has come into prominence in performance improvement. In this study, the efficiency and productivity analysis of 11 countries that have completed the transition within the European Transition Economy Countries were made according to the Input-Oriented Constant Return to Scale Model and Input-Oriented Variable Returns to Scale Model by using the data belonging to the Logistics Performance Index sub-dimensions. Three of the six sub-dimensions of the Logistics Performance Index (customs, infrastructure, and logistics quality) were used as inputs, while the other three (international shipments, tracking / tracking, and on-time delivery) were considered as outputs. In the study conducted with Data Envelopment Analysis, the efficiency evaluation was made by using the "EMS Package Program". According to the results acquired from the analysis findings, efficient and productive countries were found. At the same time, ineffective and nonproductive countries were found and the improvement rates of the input variables have been calculated so that the inefficient countries can reach the ideal efficiency level.

References

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  • Acer, A. (2021). Lojistik faaliyetlerde antrepoların etkinliğinin veri zarflama analizi ile belirlenmesi. İşletme Araştırmaları Dergisi, 13(4), 2976-2989.
  • Aigner, D. J. ve Chu, S. F. (1968). On estimating the industry production function. The American Economic Review, 58(4), 826-839.
  • Altıntaş, F. F. (2022, Ocak) . G7 ülkelerinin lojistik etkinlik ve verimlilik performanslarının değerlendirilmesi. Verimlilik Dergisi, (1), 78-93.
  • Altuğ, F. N. (2005). Ekonomide devletin yeri. Toprak İşveren (Türkiye Toprak, Seramik, Çimento ve Cam Sanayii İşverenleri Sendikası Yayın Organı), 68, 11-19.
  • Asker, V. (2018). Veri zarflama analizi ile finansal ve operasyonel etkinlik ölçümü: geleneksel havayolu işletmelerinde bir uygulama. Anadolu Üniversitesi Sosyal Bilimler Dergisi, 18(1), 153-172.
  • Bakırcı, F. (2006). Sektörel bazda bir etkinlik ölçümü: VZA ile bir analiz. Atatürk Üniversitesi İktisadi ve İdari Bilimler Dergisi, 20(2), 199-217.
  • Baležentis, A., & Baležentis, T. (2011). Assessing the efficiency of Lithuanian transport sector by applying the methods of MULTIMOORA and data envelopment analysis. Transport, 26(3), 263-270.
  • Banker, R. D., Charnes, A. ve Cooper W. W. (1984). Some models for estimating technical and scale inefficiencies in data envelopment analysis management science. Management Science, 30(9), 1078-1092.
  • Bayrak, R., & Bahar, O. (2018). Economic efficiency analysis of tourism sector in OECD countries: An emprical study with DEA. Uluslararası İktisadi ve İdari İncelemeler Dergisi, (20), 83-100.
  • Biloslavo, R., Bagnoli, C. ve Figelj, R. R. (2013). Managing dualities for efficiency and effectiveness of organisations. Industrial Management ve Data Systems, 113(3), 423-442. Doi: 10.1108/02635571311312695
  • Charnes, A., Cooper, W.W. ve Rhodes, E. (1978). Measuring the efficiency of decision making units. European Journal of Operational Research, 2(6), 429-444. Doi: 10.1016/0377-2217(78)90138-8
  • Chen, X., Miao, Z., Wang, K., & Sun, C. (2020). Assessing eco-performance of transport sector: Approach framework, static efficiency and dynamic evolution. Transportation Research Part D: Transport and Environment, 85, 102414.
  • Coelli, T., Estache, A., Perelman, S. ve Trujillo, L. (2003). A primer on efficiency measurement for utilities and transport regulators. WBI Development Studies.
  • Coelli, T. (1996). A guide to DEAP version 2.1: a data envelopment analysis (computer) program. Centre for Efficiency and Productivity Analysis, University of New England, Australia, 96(08), 1-49.
  • Cook, W. D. ve Seiford, L. M. (2009). Data envelopment analysis (DEA)-thirty years on. European Journal of Operational Research, 192(1), 1-17. Doi:10.1016/j.ejor.2008.01.032
  • Çemberci, M, Civelek, M.E. ve Canbolat, N. (2015). The moderator effect of global competitiveness index on dimensions of logistics performance index. Procedia-Social and Behavioral Sciences, 195, 1514–1524.
  • Daştan, H. (2018). Türkiye şeker sanayinin etkinlik ve verimlilik analizi. Gazi Üniversitesi Sosyal Bilimler Dergisi, 5(14), 478-498.
  • De Melo, M., Denizer, C., Gelb, A., ve Tenev, S. (2001). Circumstance and choice: The role of initial conditions and policies in transition economies. The World Bank Economic Review, 15(1), 1-31.
  • Debreu, G. (1951). The coefficient of resource utilization. Econometrica, 19(3), 273-292.
  • Erturan, M. B., & Merdivenci, F. (2021). LPI based two stage network DEA model to measure logistics efficiency: An application on OECD countries. İşletme Araştırmaları Dergisi, 13(2), 1187-1199.
  • Fanchon, P. (2003). Variable selection for dynamic measures of efficiency in the computer industry. International Advances in Economic Research, 9(3), 175-188.
  • Farrell, M. J. (1957). The measurement of productive efficiency. Journal of the Royal Statistical Society, Series A (General), 120 (3), 253-290.
  • Fischer, S. ve Sahay, R. (2004). Transition economies: the role of institutions and initial conditions. Calvo Conference-April 1-4.
  • Florensa, J. P. ve Simar, L. (2005). Parametric approximations of nonparametric frontiers. Journal of Econometrics, 124(1), 91-116. Doi:10.1016/j.jeconom.2004.02.012
  • Gattoufi, S., Wang, Y., Reisman, A. ve Oral, M. (2007). An interpretation of the technical efficiency as the "best possible deviation" from the conditions defined by the weak axiom of profit maximization. International Business ve Economics Research Journal, 6(2), 49-58.
  • Gökgöz, F. (2009). Veri zarflama analizi ve finans alanına uygulanması. Ankara Üniversitesi Siyasal Bilgiler Fakültesi Yayını, (597).
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  • Jiang, C. & Fu, P. (2009, October). Evaluating efficiency and effectiveness of logistics infrastructure based on PCA-DEA approach in China. In 2009 Second International Conference on Intelligent Computation Technology and Automation, 3, (pp. 62-66). IEEE.
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  • Koopmans, T. C. (1951), An Analysis of production as an efficient combination of activities. T.C. Koopmans (Ed.). Activity Analysis of Production and Allocation, Cowles Commission for Research in Economics, Monograph No. 13, (ss. 33-98). London: John Wiley and Sons Inc.
  • Kuah, C. T., Wong, K. Y. ve Behrouzi, F. (2010). A review on data envelopment analysis (DEA). Fourth Asia International Conference on Mathematical/Analytical Modelling and Computer Simulation, IEEE, (ss. 168-173). Doi: 10.1109/AMS.2010.45
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  • Kutlar, A. & Babacan, A. (2008). Türkiye’deki kamu üniversitelerinde CCR etkinliği-ölçek etkinliği analizi: DEA tekniği uygulaması. Kocaeli Üniversitesi Sosyal Bilimler Dergisi, (15), 148-172.
  • Kutlar, A. ve Kartal, M. (2004). Cumhuriyet Üniversitesinin verimlilik analizi: fakülteler düzeyinde veri zarflama yöntemiyle bir uygulama. Kocaeli Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, (8), 49-79.
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Details

Primary Language Turkish
Subjects International Logistics
Journal Section Research Article
Authors

Kadir Kaan Göncü 0000-0002-4810-6336

Duygu Yücel 0000-0002-2665-6732

Early Pub Date June 15, 2023
Publication Date June 30, 2023
Submission Date March 10, 2022
Published in Issue Year 2023 Volume: 12 Issue: 1

Cite

APA Göncü, K. K., & Yücel, D. (2023). Veri zarflama analizi ile Avrupa geçiş ekonomilerinin lojistik performans endeksi kullanılarak değerlendirilmesi. Trakya Üniversitesi İktisadi Ve İdari Bilimler Fakültesi E-Dergi, 12(1), 30-51. https://doi.org/10.47934/tife.12.01.02

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