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Venkatesh Bhagavath


There has been an ever-growing concern to measure efficiency of decision-making units (DMUs). Regression and Stochastic frontier analysis have been the popular methods of measuring the same. Data Envelopment Analysis (DEA) is one of the latest additions to the bracket of these techniques. DEA is essentially an op- timization algorithm, which develops efficiency scores for all DMUs on a scale of zero to 100%, with units receiving 100% efficiency score being called efficient. Further a simple modification in the DEA model also accounts for scaling efficiencies especially for large sized DMUs. In this study, technical efficiency measure- ment of State Road Transport Undertakings (STUs) was done using the data on a sample of 44 Indian state road transport undertakings. Using a variable return to scale model, efficiency scores were developed for all the state road transport undertakings. The study has revealed that only eight out of 44 STUs were scale efficient. One of the interesting findings of the study is that STUs operating as companies were relatively more technically efficient than others.


There is an increasing concern among organizations to study level of efficiency with which they work relative to their competitors. Traditional performance mea- surement system provides a very unbalanced picture of performance that can lead managers to miss impor- tant opportunities for improvement. The most com- mon methods of comparison or performance evalua- tion were regression analysis and stochastic frontier analysis. These measures are often inadequate due to the multiple inputs and outputs related to different re- sources, activities and environmental factors. Data En- velopment Analysis (DEA) provides a means of calcu- lating apparent efficiency levels with in a group of or- ganizations. In DEA study, efficiency of an organiza- tion is calculated relative to the group’s observed best practice. In this study a review of DEA methodology is done and with the help of an example, the working methodology, results of DEA are explained. Section 1 deals with different efficiency concepts and section 2 gives a detailed description of DEA model. Section 3 gives an illustration of DEA with the help of the data collected on a sample of state transport undertakings and Section 4 gives the summary of findings of this empirical work.

Data Envelopment Analysis and Concepts of Effec- tiveness, Efficiency and Productivity

Effectiveness is the extent to which outputs of service providers meet the objectives set for them. Efficiency is the success with which an organization uses its re- sources to produce outputs — that is the degree to which the observed use of resources to produce out- puts of a given quality matches the optimal use of re- sources to produce outputs of a given quality. This can be assessed in terms of technical, allocative, cost and dynamic efficiency.

Improving the performance of an organizational unit relies on both efficiency and effectiveness. A govern- ment service provider might increase its measured ef- ficiency at the expense of the effectiveness of its ser- vice. For example, a state transport undertaking might reduce the inputs used like fleet size, cost, bus or day to carry the same number of passengers. This could increase the apparent efficiency of that state transport undertaking but reduce its effectiveness in providing satisfactory outcomes for passengers. Therefore, it is important to develop effectiveness indicators also.

All agencies use a range of inputs, including labor,

Alliance Journal of Business Research


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