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Five types of indicators to reveal a company’s competitiveness within the industry

2023-07-19 14:37:00

Indicators per employee are surprisingly less predictive of a firm's financial performance and sectoral competitiveness, while corporate income margin indicators and country effect are good predictors, according to research by the Corvinus University of Budapest.

Two researchers from Corvinus University analysed industry averages from 27 economic sectors in the Visegrad Four (V4) countries based on 25 financial indicators to find out which ones determine a firm’s competitiveness the most. Tamás Kristóf and Miklós Virág included in their study the 2016-2020 indicators of companies with annual turnover of at least one million euros from a widely used source of corporate data , Moody’s Analytics Orbis Europe, and processed the data using six different machine learning techniques. 

 

Besides country effect, it is the income margin indicators  that really matter 

In fact, the results show that one good predictor of sectoral competitiveness is the country in which the firm is located in the V4: in Poland, the Czech Republic, Slovakia or Hungary. Among the financial data, the income margin  ,  turnover and leverage ratios (which indicate the ability to meet financial obligations and the amount of firm capital that is derived from liabilities  and credit) are the most related to financial competitiveness, while shareholder liquidity ratios also have an important impact on industry performance. The researchers measured financial competitiveness using the two most widely used profitability indicators: return on assets (ROA) and return on equity (ROE).  

 

One of the surprises of the research was that financial indicators per employee did not prove to be a relevant variable in judging the competitiveness of a given firm in a given industry,” said Tamás Kristóf, associate professor at the Corvinus University of Budapest and first author of the study. He added: “All six of the machine learning models we used were able to explain and predict  return on assets more reliably than  return on equity“.  

 

The average V4 indicators by sector fall into five groups 

 

In addition to predicting financial performance, the researchers used artificial intelligence to classify the V4 economic sectors into five clusters. The similarities could be identified mainly on the basis of economies of scale and profit margin indicators. Indicators per capita have become a noticeably important factor in clustering. Unexpectedly, however, the usual indicators of financial competitiveness – e.g. ROE, ROA, liquidity ratios, net asset turnover – did not play an important role. Of the 25 indicators examined, 7 described profitability, 5 operational efficiency, 6 corporate structure and 7 financial characteristics per employee. 

  • Cluster 1 consists mainly of firms in Polish sectors with low profit margins and low  total assets volume per employee. 
  • Cluster 2 incorporates mainly of companies in Hungarian sectors with high gross profit margins and average levels of total assets volume per employee. 
  • Cluster 3 is dominated by  firms in Slovak sectors with relatively low gross profit margins and low total assets volume per employee. 
  • Cluster 4 is highly diversified for each  country, however most observations come from  companies operating in a Czech sector, with high gross profit margins and a very high level of total assets volume per employee. 
  • Cluster 5 is also diverse, with more Slovak elements than average, with  average gross profit margins and the lowest total assets per employee. 

 

“The results of the clustering have highlighted the financial combinations that can be used to distinguish sharply between the sectoral financial profiles of V4 companies, forming a manageable number of groups,” said Tamás Kristóf, first author of the paper. The study was published in December 2022 in the Journal of Competitiveness. 

 

 

 

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