The concept of efficiency is important in economic science; at present, its role in every sector of the economy is growing. Evaluating an enterprise’s efficiency makes it possible to implement a correct and profitable strategy of resource allocation, which shows its potential level Given an annual increase in the number of bankrupt enterprises, the issue of estimating the efficiency of enterprises is relevant for both their owners and managers, as well as for creditors. There are various methods and models for estimating the performance of enterprises. This work has assessed the efficiency of enterprises in the industrial sector over the period of 2017‒2018. Stochastic Frontier Analysis is based on the stochastic model of production function. The classic SFA method is based on the production function of the company, which relates the volume of output to the volume of resources consumed. At the same time, the SFA model uses several inputs (volumes of resources consumed) and only one output parameter ‒ the volume of production. In order to achieve more precise results, a given model has been modified. The model allows several key financial indicators to be taken into consideration as outputs at the same time, based on which the financial activities of the studied economic entities are assessed. The result of the work involving open sources has revealed how the efficiency of different enterprises in the same industry changes over several years. It is shown that the modified Stochastic Frontier Analysis model could be used to assess financial stability and predict bankruptcy.
Objective: To evaluate the efficiency of Russian industrial enterprises based on the stochastic method using financial indicators for 2017-2018. Method: the parametric SFA (Stochastic Frontier Analysis) method based on a stochastic model of the production function is used to assess the efficiency of enterprises. In order to achieve more accurate results, a modification of this method was performed. And also with the help of the developed modified SFA method, the bankruptcy of industrial enterprises of the Russian Federation was predicted on the basis of selected significant financial indicators. 35 bankrupt enterprises and 35 operating enterprises of the same industry were analyzed. Results: As a result of the work done using open sources, you can see how the efficiency of different enterprises in the same industry changes over several years. Conclusion: This study suggests the ability to use the Stochastic Frontier Analysis method and its modification on the studied data in the process of monitoring the dynamics of the efficiency of enterprises both bankrupt and operating. Such an assessment of efficiency can be recommended to other sectors of the economy.
At the moment, there is an increase in the importance of efficiency in another sector of the economy. Evaluating the efficiency of an enterprise makes it possible to implement a correct and profitable resource allocation strategy, which shows its potential level. In connection with the annual increase in the number of bankrupt enterprises, the problem of assessing the efficiency of enterprises' activities is relevant both for their owners and managers, and for creditors. There are various methods and models for assessing the efficiency of enterprises. One study focuses on the improvement of a parametric method for assessing the performance of objects - the SFA (Stochastic Frontier Analysis) method. The classical SFA method is based on the production function of an enterprise, linking the volume of output with the volume of consumed resources. In this case, the SFA model uses several input (volumes of consumed resources) and only one output parameter - the volume of output. The essence of the proposed modification of the model based on the SFA method is to use financial indicators of enterprises' activities instead of data on consumed resources and output, on the basis of evaluating the financial activity of the economic objects under study. The developed model of the situation for assessing the efficiency of the enterprise in terms of its financial indicators.
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