컨테이너 항만의 효율성 분석에 관한 연구

Abstract

This paper presents a approach to the measurement of efficiency. Data envelopment analysis(DEA), as it is called, has particular applicability in the service sector. Applying mathematical programming techniques, DEA enables relative efficiency ratings to be derived within a set of analysed units. Thus it does not require the development of 'standard' against which efficiency is measured. although such standards can be incorporated in the DEA analysis. The efficiency of units is compared with an 'efficiency envelope' that contains the most efficient units in the group. The DEA efficient ratings can be a useful tool for port managers and for researchers, providing a deeper insight into port performance.

Malmquist analysis is effciency measurement techniques for the measurement of productivity change. The DEA-based Malmquist productivity index has several advantages when compared with other methodologies. Some of them refer to the problems mentioned previously. The DEA-based Malmquist index is non-parametric, and thus it does not suffer the problem of an inappropriate functional form, and it easily tackles multiple outputs and multiple inputs. It allows a decomposition of the cause of change in productivity: both measurable technical change and efficiency change.

This paper investigates the efficiency employing DEA-CCR Model and DEA-BCC Model on data for 53 container ports and 53 container terminals covering 1995~2001 in the world. also, investigates the change in productivity employing Malmquist Indices as changing years for 7 years.

Efficiency of ports and terminals can be affected by characteristics such as region, size of ports, economic conditions of a country, length of berths and so on. In this paper, 53 ports and 53 termials devide according to its characteristics. and compare to differences of efficiency and the change of effciency between each group. This paper presents a clear characterization of areas with greater technical progress and the region with technical regress.