Data Envelopment Analysis (DEA) Based Study of Major Sea Ports of India

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Abstract

India is one of the biggest peninsulas in the world. A major part of trading, both by volume and value, is done through maritime transport in India. There are twelve major government owned ports that service this transport. Efficiency evaluation of these ports is crucial for the operators and managers to analyse their performance for further improvements. The present study uses the non parametric efficiency evaluation technique of data envelopment analysis (DEA) to measure the performance of these ports for the year 2019-2020. Technical, Pure Technical, scale and super efficiencies have been evaluated for the twelve major ports. Three out of twelve ports turned out to be efficient when evaluated by using the constant returns to scale model and six turned to be efficient when evaluated using variable returns to scale model. In order to give benchmarks to the inefficient ports, potential improvements in the input and output variables have also been discussed. It was observed that Kamarajar port in Tamil Nadu is the best performer while Mormugao in Goa is the least.
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基于数据包络分析(DEA)的印度主要海港研究
印度是世界上最大的半岛之一。从数量和价值来看,印度的大部分贸易都是通过海运完成的。有十二个主要的政府拥有的港口为这种运输服务。对这些港口的效率评估对于运营商和管理者分析其业绩以进一步改进至关重要。本研究使用数据包络分析(DEA)的非参数效率评估技术来衡量这些港口在2019-2020年的表现。对十二个主要港口的技术、纯技术、规模和超效率进行了评估。十二个端口中有三个在使用恒定比例回报率模型进行评估时是有效的,六个在使用可变比例回报率模式进行评估时也是有效的。为了给低效端口提供基准,还讨论了输入和输出变量的潜在改进。据观察,泰米尔纳德邦的Kamarajar港表现最好,而果阿的Mormugao表现最少。
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