KONTEYNER TERMİNALLERİNDE HEDEF ÇIKTININ BELİRLENMESİ: YÖNTEMSEL BİR KATKI

Yıl 2019, Cilt: 7 Sayı: 1, 80 - 92, 26.06.2019

Egemen Ertürk Bayram Bilge Sağlam Abdullah Açık

Öz

Sermaye
yoğun tabiatından ötürü, konteyner terminallerinin etkin yönetimi, yapılan
yatırımlardan optimal faydanın sağlanması açısından oldukça önemlidir. Her ne
kadar konteyner terminallerine yapılan yatırımlar operasyonel yönetimin
etkinliğini artırmak amacıyla yapılıyorsa da, hedeflenen elleçleme hacimlerine
erişilemediği halde, yapılan yatırımların beklenen faydayı sağlamaması riski
mevcuttur. Bu sebeple karar vericilerin yük potansiyeli konusundaki görüşleri
önemli olsa da, eldeki kaynakların bu görüşlere uygun şekilde değerlendirilmesi
de bir o kadar önemlidir. Bu yolda karar vericilere, etkinliği zedelemeden
hedef çıktıyı belirleme konusunda yardımcı olacak metodolojik araçlara ihtiyaç
vardır. Bu çalışmada, süper etkinlik veri zarflama analizi ve regresyon
analizinin birlikte kullanılması ile konteyner terminallerinin etkin olması
için çıktı seviyesini tespit eden bir model geliştirilmiştir. Model, Türkiye’de
2016 yılında 50000 TEU üstü konteyner elleçlemesi olan 17 konteyner terminaline
uygulanmış ve seçilen terminallerin hedef çıktıları yatırım senaryolarına göre
sonraki aşamada hesaplanmıştır. Çalışmanın sonuçlarında, seçilen terminaller
arasında Marport, TCE Ege ve MIP terminalleri süper etkinlik modeline göre
sıralama listesinin en başında yer bulmuşlardır. Etkinlik analizini takiben
uygulanan regresyon analizi girdilerin katsayılarını ortaya koyarak potansiyel
yatırım değerlerinin girilmesinden sonra hedef çıktıların hesaplanmasını
sağlamaktadır. 17 konteyner terminalinin etkinlik verilerinden oluşturulan bu
regresyon modeli hedef çıktıların değerlendirilmesi için kullanılacak bir araç
niteliğindedir. Bu araç, girdilerde yapılan değişikliklere bağlı olarak yeni
hedef çıktıları sağlayacağından, liman yöneticileri tarafından yatırım
kararlarının doğrulanmasında kullanılabilecektir.

Anahtar Kelimeler

Hedef çıktı, etkinlik, yatırım, konteyner terminalleri

DETERMINING THE TARGET OUTPUT IN CONTAINER TERMINALS: A METHODOLOGICAL CONTRIBUTION

Öz

Due to its capital intensive nature, the efficient management of container terminals is essential in achieving the optimal benefit from the investments made. Albeit the investments in container terminal are made to improve the efficient management of the operations, when the expected handling volumes are not met, there is a risk that said investments can be rendered obsolete. Thereby while the outlook of the decision makers on the cargo potential is important, arrangement of the resources at hand in accordance with this outlook is also crucial. However, there is a need for methodological tools that can help the decision makers set the target output without hampering the efficiency. In this study, through the combined application of super efficiency data envelopment analysis and regression analysis, a model for determining the output level for efficient container terminals was developed. The model was applied to 17 container terminals in Turkey that had over 50000 TEU of container throughput in the year of 2016 and target outputs were evaluated thereafter according to several investment scenarios. Findings of this study reveal that among the selected ports, Marport, TCE Ege and MIP are at the top of the ranking list based on the super efficiency model. The regression analysis applied subsequent to efficiency analysis provides coefficients of the inputs, enabling the calculation of the target outputs after inserting the potential investment values. The regression model that has emerged from efficiency data of 17 container terminals can be used as a tool to evaluate target outputs. It is believed that port managers can validate their investment decisions based on this tool as it would provide the new target output after the changes in inputs.

Anahtar Kelimeler

Target output, efficiency, investment, container terminals

Kaynakça

• Ablanedo‐Rosas, J. H., Gao, H., Zheng, X., Alidaee, B. and Wang, H. (2010). “A Study of The Relative Efficiency of Chinese Ports: A Financial Ratio‐Based Data Envelopment Analysis Approach”. Expert systems, 27 (5), 349-362.
• Al-Eraqi, A. S., Mustafa, A., Khader, A. T. and Barros, C. P. (2008). “Efficiency of Middle Eastern and East African Seaports: Application of DEA Using Window Analysis”. European Journal of Scientific Research, 23 (4), 597-612.
• Andersen, P., Petersen, N.C. (1993). “A Procedure For Ranking Efficient Units in Data Envelopment Analysis”. Management Science, 39, 1261–1264.
• Ateş, A., Esmer, S., Çakir, E. and Balci, K. (2013). “Karadeniz Konteyner Terminallerinin Göreceli Etkinlik Analizi”. Journal of Maritime Faculty, 5 (1), 1-22.
• Barros, C. P. and Athanassiou, M. (2015). Efficiency in European Seaports with DEA: Evidence from Greece and Portugal. In Port Management (pp. 293-313). Palgrave Macmillan, London.
• Charnes, A., Cooper, W.W. and Rhodes, E. (1978). “Measuring the Efficiency of Decision Making Units”. European Journal of Operational Research, 2 (6), 429–444.
• Chatterjee, S., & Hadi, A. S. (2015). Regression Analysis by Example. New Jersey, John Wiley & Sons.
• Coto-Millan, P., Banos-Pino, J. and Rodriguez-Alvarez, A. (2000). “Economic Efficiency in Spanish Ports: Some Empirical Evidence. Maritime Policy & Management, 27 (2), 169-174.
• Cullinane, K., Ji, P. and Wang, T. F. (2005). “The Relationship between Privatization and DEA Estimates of Efficiency in the Container Port İndustry”. Journal of Economics and Business, 57 (5), 433-462.
• Esquerdo, P. J. R. and Welc, J. (2018). Applied Regression Analysis for Business. Switzerland, Springer.
• Farrell, M.J. (1957). “The Measurement of Productive Efficiency”. Journal of the Royal Statistical Society, 120 (3), 253-290.
• Garcia-Alonso, L. and Martin-Bofarull, M. (2007). “Impact of Port Investment on Efficiency and Capacity to Attract Traffic in Spain: Bilbao versus Valencia. Maritime Economics & Logistics, 9 (3), 254-267.
• Güner, S. (2015). “Investigating İnfrastructure, Superstructure, Operating and Financial Efficiency in the Management of Turkish Seaports Using Data Envelopment Analysis. Transport Policy, 40, 36-48.
• Itoh, H. (2002). Effeciency Changes at Major Container Ports in Japan: A Window Application of Data Envelopment Analysis. Review of Urban & Regional Development Studies, 14 (2), 133-152.
• Lee, H. S., Chu, C. W. and Zhu, J. (2011). “Super-Efficiency DEA in The Presence of Infeasibility”. European Journal of Operational Research, 212 (1), 141-147.
• Lee, T., Yeo, G. T. and Thai, V. V. (2014). “Environmental Efficiency Analysis of Port Cities: Slacks-Based Measure Data Envelopment Analysis Approach”. Transport Policy, 33, 82-88.
• Lirn, T. C., Thanopoulou, H. A., Beynon, M. J. and Beresford, A. K. (2015). An Application of AHP on Transshipment Port Selection: A Global Perspective. In Port Management (pp. 314-338), Palgrave Macmillan, London.
• Pagan, A. R. and Hall, A.D. (1983). “Diagnostic Tests as Residual Analysis”. Econometric Reviews, 2 (2), 159-218.
• Roll, Y. and Hayuth, Y. (1993). “Port Performance Comparison Applying Data Envelopment Analysis (DEA)”. Maritime Policy and Management. 20 (2), 153-161.
• Sağlam, B. B., Açık, A. and Ertürk, E. (2018). “Evaluation of Investment Impact on Port Efficiency: Berthing Time Difference as A Performance Indicator. Journal of Eta Maritime Science, 6 (1), 37-46.
• Schellinck, T. and Brooks, M. R. (2016). “Does Superior Service Performance Provided to Shipping Lines Improve The Perceived Value of a Port?”. International Journal of Shipping and Transport Logistics, 8 (2), 175-193.
• Schøyen, H. and Odeck, J. (2013). “The Technical Efficiency of Norwegian Container Ports: A Comparison to Some Nordic and UK Container Ports Using Data Envelopment Analysis (DEA). Maritime Economics & Logistics, 15 (2), 197-221.
• Slack, B. (1985). “Containerization, Inter-Port Competition, and Port Selection”. Maritime Policy and Management, 12 (4), 293-303.
• Sohn, J. R. and Jung, C. M. (2009). “The Size Effect of a Port on the Container Handling Efficiency Level and Market Share in Internation Transshipment Flow”. Maritime Policy & Management, 36 (2), 117-129.
• Thai, V. V. (2016). “The Impact of Port Service Quality on Customer Satisfaction: The Case of Singapore”. Maritime Economics & Logistics, 18 (4), 458-475.
• Tongzon, J. (2001). “Efficiency Measurement of Selected Australian and Other International Ports Using Data Envelopment Analysis”. Transportation Research Part A: Policy and Practice, 35 (2), 107-122.
• Tongzon, J. and 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.
• Ugboma, C., Ogwude, I. C., Ugboma, O. and Nnadi, K. (2007). “Service Quality and Satisfaction Measurements in Nigerian Ports: An Exploration”. Maritime Policy & Management, 34 (4), 331-346.
• Woo, S. H., Pettit, S. and Beresford, A. K. (2011). “Port Evolution and Performance in Changing Logistics Environments”. Maritime Economics & Logistics, 13 (3), 250-277.
• Yeo, G. T., Thai, V. V. and Roh, S. Y. (2015). “An Analysis of Port Service Quality and Customer Satisfaction: The Case of Korean Container Ports”. The Asian Journal of Shipping and Logistics, 31 (4), 437-447.
• Zhu, J. (2014). Quantitative Models for Performance Evaluation and Benchmarking: Data Envelopment Analysis with Spreadsheets. Switzerland, Springer.