Purpose

The purpose of this paper is to present an integrated model to measure the operational efficiency of the top 40 container ports in the world for a five-year continuous period using a two-stage uncertainty data envelopment analysis (UDEA) combined with fuzzy C-means clustering method (FCM).

Design/methodology/approach

UDEA model is adopted for measuring the efficiency of container ports to overcome the limitation of the basic model, which is unable to handle uncertain data that are easy to meet in practice. FCM algorithm is implemented to find similar distribution efficiency scores of two stages and the cluster similar efficiency scores of container ports into various groups.

Findings

The combination of the two-stage UDEA model and the FCM algorithm provided a more comprehensive view when evaluating the performance of container ports. The UDEA results show that most of the container ports have reduced their profitability level in the second stage and most of the efficient container ports have turned into inefficient ones because of their small scale.

Originality/value

This paper proposes using the two-stage UDEA model to evaluate port efficiency based on two main aspects of productivity and profitability. Moreover, it combines DEA and FCM algorithms to offer a more comprehensive view when measuring the performance of container ports.

中文翻译：

---

基于两阶段不确定性DEA模型和​​FCM的世界顶级集装箱港口效率分析

目的

本文的目的是提供一个综合模型，该模型使用两阶段不确定性数据包络分析（UDEA）与模糊C均值相结合来连续五年来衡量世界排名前40位集装箱港口的运营效率聚类方法（FCM）。

设计/方法/方法

UDEA模型用于衡量集装箱港口的效率，克服了基本模型的局限性，该模型无法处理在实践中容易满足的不确定数据。实施FCM算法以找到两个阶段的相似的分配效率得分，并将集装箱港口的相似的效率得分聚类为各个组。

发现

在评估集装箱港口的性能时，两阶段UDEA模型和​​FCM算法的结合提供了更全面的视图。UDEA的结果表明，大多数集装箱港口在第二阶段都降低了盈利水平，并且大多数高效的集装箱港口由于规模小而变成了低效率的港口。

创意/价值

本文提出了基于生产率和获利能力两个主要方面的两阶段UDEA模型来评估港口效率。此外，它结合了DEA和FCM算法，可在测量集装箱港口的性能时提供更全面的视图。