Measuring Productivity and Efficiency of Seaports in India using DEA technique

Abstract

Aim: In this paper we are looking at the seaports (in India called ‘major ports’) from the context of its trade and India’s strategic importance in trade world after the initiation of economic reforms in 1991. It empirically estimates the levels of productivity and efficiency of seaports in India. This paper applies DEA technique to assess productivity and efficiency of seaports in India. Design/Research methods: DEA technique is extensively used in the literature of economics to provide measures of firms’ technical efficiency. These measures rank the firms by looking at their apparent performances over a period of time. DEA is a frontier model which is non-parametric since no functional specification or form is required to be mentioned. Conclusions/Findings: The DEA results as discussed and reported in the paper have shown how Indian ports are performing over the years. This investigation alone is not sufficient to develop a benchmark in the port system of India. Rather it will do well to have a closer look at the Indian ports from the physical and financial performance point of view. This study made use of data envelopment analysis (DEA) to generate what we call an efficiency benchmarks and assessment of the Indian ports sector. With this modest attempt to investigate the port sector of India several issues are in the open one can further analyze and come to desired conclusions. Originality/value of the paper: The main role of a port is to transfer goods between two transport modes. As far as Indian ports are concerned, there are few studies with regard to productivity and efficiency of the port sector. Since, there is an attempt in recent years to overhaul the infrastructure sectors of the Indian economy and especially seaports. There is a need to look at issues in port sector as well. Productivity and efficiency concerns should be the main aspect of the benchmarking of the performance of today’s Indian ports. Limitations of the research: Second stage DEA, distance function approach, Bayesian techniques, Carlo Monte techniques, can be alternatively used.