Efficiency Of Container Ports Research Articles

Productive Efficiency of World Container Ports

This study evaluates the productive efficiency of 140 global hub and national gateway container ports in almost all countries of the world for the years 1991 and 2004. It adopts diverse models of data envelopment analysis (DEA), including two specific cases of DEA window analysis: intertemporal and contemporaneous. The study finds that world ports have experienced inter- and intraregional efficiency gaps, which have not lessened over time. In general, the larger-scale ports are more efficient because they drive technological development and adopt better managerial practices. However, many large ports operate under decreasing returns-to-scale at each port level. This implies a potential for interport competition as a way to increase port efficiency at an aggregated regional level. In addition, port size is not the sole factor in determining port efficiency. Newly developed ports in Asia and the Middle East and small Central American ports operate efficiently. They have created strong partnerships with emerging, globally franchised terminal operators. With small hinterlands, Oceanian ports have tried to improve efficiency by reforming institutional structures and managerial practices. However, they have not fully overcome the disadvantages of the lack of economies of scale. For them, interport competition may not be an effective means to improve efficiency.

Operational performance evaluation of major container ports in the Asia-Pacific region

If international container ports are to gain a proper appreciation of their various advantages, disadvantages and potential opportunities in a globally competitive environment, it is essential that they conduct effective evaluation of their operational performance. The present study applies five models of data envelopment analysis (DEA) to acquire a variety of complementary information about the operational efficiency of major container ports in the Asia-Pacific region and to identify trends in port efficiency. The study first establishes the causes of inefficiency on the basis of efficiency value analysis. Slack variable analysis is then used to identify potential areas of improvement for inefficient ports. This is followed by the utilization of return to scale analysis to assess whether each port is in a state of increasing, decreasing, or constant return to scale. Finally, a sensitivity analysis is conducted to identify which input or output variables have larger weights in terms of efficiency. The results provide valuable information for port managements in their attempts to establish competitive strategies for the future and to improve their resource utilization for ongoing improvements in operational efficiency.

The efficiency of European container ports: A cross-sectional data envelopment analysis

This paper focuses on measuring the efficiency of container terminals in Europe using the data envelopment analysis (DEA) approach. Container terminals in Europe play an important role in the region’s economic development and, as the result of their geographic concentration, face fierce competition compared with the rest of the world. Despite this, studies of the efficiency of container terminals in the region are minimal. As a basis for further research, this paper serves to supplement existing studies by deriving estimates of relative efficiency for a sample comprising 69 of Europe’s container terminals with annual throughput of over 10,000 TEUs. The scale properties of container terminal production are also considered as part of the study, as is the relationship of efficiency to geographical influence.

The technical efficiency of container ports: Comparing data envelopment analysis and stochastic frontier analysis

The efficiency of the container port industry has been variously studied utilising either Data Envelopment Analysis (DEA) or Stochastic Frontier Analysis (SFA). Given the strengths and weaknesses associated with these two approaches, the efficiency estimates and scale properties derived from these analyses are not always convincing. This paper applies both approaches to the same set of container port data for the world’s largest container ports and compares the results obtained. A high degree of correlation is found between the efficiency estimates derived from all the models applied, suggesting that results are relatively robust to the DEA models applied or the distributional assumptions under SFA. High levels of technical efficiency are associated with scale, greater private-sector participation and with transhipment as opposed to gateway ports. In analysing the implications of the results for management and policy makers, a number of shortcomings of applying a cross-sectional approach to an industry characterised by significant, lumpy and risky investments are identified and the potential benefits of a dynamic analysis, based on panel data, are enumerated.

The relationship between privatization and DEA estimates of efficiency in the container port industry

A major objective of port privatization is to improve the efficiency of the sector. This paper presents the pros and cons of port privatization and provides an empirical examination of the relationship between privatization and relative efficiency within the container port industry. Data envelopment analysis (DEA) is justified as the chosen methodology for analysing the relative efficiency of container ports and is applied in a variety of configurations to industry panel data. The paper concludes with the rejection of the hypothesis that greater private sector involvement in the container port sector irrevocably leads to improved efficiency.

An Application of DEA Windows Analysis to Container Port Production Efficiency

There have been various analyses of the efficiency of container port (or terminal) production using Data Envelopment Analysis (DEA) based on cross-sectional data. When time is not considered, the efficiency results derived using this approach can be biased. In order to overcome this problem, this paper applies DEA windows analysis, utilising panel data, to a sample of the world’s major container ports in order to deduce their relative efficiency. The results suggest that estimates of container port efficiency fluctuate over time. The paper concludes that existing programming methods for estimating efficiency are inadequate in capturing the long-term increased efficiency and competitiveness that accrue from significant investments.