Konteyner taşımacılığında navlun oranlarının nasıl değişeceğini sektördeki paydaşların öngörebilmesi oldukça önemlidir. Bu çalışma, literatürde ilk defa olmak üzere, konteyner taşımacılığında navlun oranlarının değişimini gösteren en önemli göstergelerden biri olan CCFI (Çin Konteyner Navlun Endeksi) 'nin tahmini için toplu zaman serisi modelleri sunmaktadır. Çalışmanın sonuçları, modellerin CCFI’nin tahmininde oldukça iyi sonuçlar verdiğini ve önemli bir karar destek sistemi olarak kullanılabileceğini göstermektedir.
Stakeholders in the sector need to be able to predict how freight rates will change in container transportation. For the first time in the literature, this study presents aggregate time series models for the prediction of CCFI (China Container Freight Index), one of the most critical indicators showing the change of freight rates in container shipping. The study results show that the models provide promising results in forecasting CCFI and can be used as an essential decision support system.
Primary Language | English |
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Subjects | Maritime Transportation and Freight Services |
Journal Section | Research Article |
Authors | |
Early Pub Date | October 27, 2023 |
Publication Date | December 30, 2023 |
Published in Issue | Year 2023 Volume: 8 Issue: 2 |
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