Операционная эффективность деятельности российских сталелитейных компаний: сравнение оценок по моделям SFA и DEA

The steel industry is one of the economy-forming industries in Russia. The products of this industry are used in construction, mechanical engineering, infrastructure, and household appliances. Russia has always been one of the key exporters of steel to the CIS market, and the main steel companies were vertical conglomerates that accompanied the production of steel from primary resources to the finished product.
Now the industry is especially in need of efficiency assessment for several reasons: industry 4.0 technologies are being introduced and the struggle for technological superiority in the steel market begins, prices for basic steel products are highly volatile, because of this, it is necessary to try to reduce production costs as much as possible in order to be able to withstand these shocks. It is for these reasons that steel firm managers and executives need to be efficient and make the most of resources to create economic value.
This work will concentrate on measuring technical performance, as this is the leading way to measure organizational performance. If steel production is not technically efficient, then it will lose revenue and profits, which must be invested in the digitalization of production and increased portfolio diversification. Other organizational performance metrics cannot account for the dynamics of change, and there are also difficulties in interpreting decisions to improve organizational performance. Therefore, this research will be relevant for steel companies.
The research gap which this paper tries to cover lies is that steel companies use metrics that yield quick results, but have many drawbacks, such as the difficulty of interpreting the results in a recommendation. DEA and SFA analyzes, on the other hand, can solve this problem and signal which resources should be reduced and reallocated more efficiently, that the output has remained at the same level. Many researchers have also used these methods to assess the performance of the steel industry in China, India and Vietnam, but this has never been done in the Russian market.
Theoretical contribution of this research is that we apply state-of-the-art analysis methods for multi-input and output data, using state-of-the-art analysis packages (DEA and SFA), and for the first time use these tools to analyze the effectiveness of the Russian steel industry together with the formation of practical recommendations for market participants.
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The main aim of this paper is evaluating the effectiveness of Russian steel companies by comparing their operating results with each other and identify the best performers using SFA and DEA methods.
This paper aims to accomplish the following research objectives to reach the abovementioned goal:
1. What is the performance metric for a typical Russian steel company?
2. Who in the Russian steel market shows the best results in terms of the
aforementioned efficiency?
3. Does the size of a steel company affect its performance?
4. Does the number of factories affect the efficiency of a steel company?
5. Does the type of product a steel company makes on efficiency?
6. What actions will allow Russian steel companies to improve their efficiency?
Summarizing, this work presents: a brief introduction to the steel industry, as well as the main trends that will affect this industry in the future. Thereafter, various definitions of effectiveness were reviewed to avoid ambiguity and the basics were defined. In addition, a detailed literary analysis of a short list of works devoted to the effectiveness of steel companies was carried out, the most popular models were identified, and a gap in Russian studies on this topic was discovered. data selection and time interval, including the specification of variables that will be selected as input and output data. The pros and cons of choosing quantitative analysis as the primary method have also been described. DEA and SFA were described and proven as the methods of analysis used, including the various pros and cons of one and the other method of analysis. The specifications of each of the models were also selected based on logic and previous experience from the literature. The data were analyzed in several ways of DEA and SFA, and the results were compared with each other, then subgroups were determined for answers to the main research questions. At the end, recommendations are given to businesses that will help move away from production inefficiencies.
This study uses quantitative empirical research. This method assumes a high-quality literature analysis and a clear formation of a research gap. Collecting data from major steel companies using Thomas Reuters databases. This study uses fixed assets, operating expenses and СOGS as inputs and Net Sales and Net Profits as outputs. The efficiency will be gauged with the help of an add-in plugin for Excel, called DEA-Solver. Summing it all up, this study defines the criterion for finding the best performers on the steel market.
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This research consists of several logical stages that add up to a single story. Starting with an overview of the steel market in Russia and the main trends, the definition of the concept of efficiency and a review of the literature with basic research on the efficiency of steel production. Then the main research method is determined, which consists of two modern methods of researching technical efficiency: Data Envelopment Analysis and Stochastic frontier approach. Then the specifications of these models are defined, as well as the main inputs and outputs of the model. Then a research is carried out, the main best performers are determined, and an assessment is carried out on the basis of the research questions. Finally, basic recommendations are revealed that can be useful for managers and owners of steel businesses.