R. N. Joshi, S.P. Singh


In the garment industry, performance of a firm is generally measured by using conventional ratios such as number of garments per machine and per operator. These ratios cannot reflect the firm’s performance completely as the firm does not use only a single input to produce a single output. In this context, Data Envelopment Analysis (DEA) is an appropriate technique as it considers multiple inputs and outputs to measure the production efficiency of a firm. This paper, therefore, applies this technique to estimate the production efficiency of ready-made garment firms. The study is based on the primary data collected from eight ready-made garment firms located in Bangalore, India. To measure the efficiency, we consider the number of stitching machines and number of operators as input-variables and the number of pieces of garment produced as an output-variable. The DEA results show that under the CRS technology assumption, average production efficiency score in the garment firms works out to be 0.75. This indicates that on an average, the firms could increase their output by 25 percent with the existing level of inputs. When the aggregate production efficiency is decomposed into pure production efficiency and scale efficiency using VRS production function, it is found that on an average, the firms are 17 percent inefficient in pure production efficiency and 9 percent in scale efficiency. Most of the firms are found operating under decreasing return to scale. This indicates that the production efficiency of the firms could be improved by adjusting the plant-size at the optimum level. The study also concludes that the DEA is superior to the ratio analysis for performance evaluation of the garment industry.

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