1 Challenges in Identifying Fast-Growing Companies to Differentiate Government Support Measures
Elena A. Fomina Ufa branch of the Financial University under the Government of the Russian Federation, Ufa, Russia
Julia V. Khodkovskaya Ufa State Petroleum Technical University, Ufa, Russia
Ilya I. Beloliptsev Ufa branch of the Financial University under the Government of the Russian Federation, Ufa, Russia
Denis V. Chuvilin Ufa branch of the Financial University under the Government of the Russian Federation, Ufa, Russia
Introduction
Interest in rapidly growing companies (RGC) – “gazelles” – in the world and Russia is supported to a large extent due to the results of assessing their impact on indicators such as job creation and participation in income growth in the economy of a particular region or country as a whole. Since 2000, many researchers have confirmed that the RGC effect persists if it does not increase. Therefore, in the UK, 6% of all firms with 10 or more employees created 54% of jobs in 2005–2008. In Sweden, this ratio is 6–42%, in Finland 5–90% (in 2003–2006) (Goswami, 2019). In the United States, 10–15% of the total number of firms creates 50–60% of jobs. The same high results were noted in Canada, France, the Netherlands, Spain and other countries of the world. Despite the main problem of RGC – the occasional nature of periods of high growth rates – the high net contribution to job creation makes them the object of close attention of regulators in many countries of the world. RGC creates associated effects by influencing the demand for products from related industries or creating opportunities for increased production and efficiency in product chains. However, expanding business in the digital economy necessarily requires additional external financing, which, as a rule, is difficult to access, especially for young companies that are only trying to occupy their niche in the market. In this regard, the differentiated mechanism of state support measures should be implemented on the basis of high-quality identification of RGC.
Methodology
Currently, the problem of effective state support for business is of primary importance for modern society (Fomina, 2018). As world experience shows, improving the quality of life, growth in wealth directly depend on the development of the business sector, the quality of the transformations being carried out in the digital economy, which requires the use of effective tools (Fomina, 2018) state support for business, including RGC. The presence of digital technologies helps companies make operational decisions in order to increase the utilization rate of assets, reduce current costs and increase overall efficiency, and, therefore, the conditions for the growth and development of companies (Khodkovskaya, 2018). As a rule, RGC support programs are considered as an integral part of state influence on small and medium-sized enterprises (SMEs). However, government support measures in most countries are provided to SMEs, regardless of their RGC affiliation.
The methodological basis for establishing RGC identification criteria was the studies of D. Birch, OECD, the World Bank, etc. After studying the best Russian and foreign practices to determine the essence of RGC and the criteria for their identification, three approaches were identified: “absolute” (OECD criteria), “relative” (Birch index, DHS criterion) and “distributive” (Halvarson criterion). A systematic analysis of modern scientific papers (more than 20 authors) (Henreksonand, 2010) revealed the main signs of DBK growth (Baranova, 2016): indicator, measures, regularity, threshold value of the measure, process and demographics of companies. To identify DBK growth indicators, the economic growth models of companies are systematized (Poh, 2013), the analysis of which allows us to conclude that there is no typical RGC image, and the term “rapid growth” itself is a multidimensional and multifaceted object for study; Methodological approaches should be applied in a comprehensive manner using a multi-criterion RGC selection mechanism. The process of identifying RGC according to different countries shows that there is no relationship between the level of development of the country (for example, in terms of per capita income) and the share of RGC in the total number of companies, which poses additional tasks for researchers to determine how different RGC identification criteria are related to other indicators of economic growth (except for company income and number of employees). Therefore, it is advisable to structure the RGC identification process to establish the need for state support measures by creating a single vertically integrated RGC selection system based on a scientifically sound choice of growth indicators.
Results
A critical review of RGC approaches revealed the advantages of the OECD criteria and the Birch index, which is evident in the ease of application and comparability of results when comparing RGC lists across regions and countries. It should be noted that many researchers focus on their search among young companies and startups. An analysis of the reasons for the greater concentration of RGC among them shows that the main ones are the opportunities to master new markets, technologies and products, as well as the specific nature of competition in new market segments. In all countries, the majority of RGC is concentrated in a group of companies no longer than 5 years old, and in a number of countries (Brazil, Hungary, Côte d’Ivoire) the share exceeds 60%. Thus, it can be concluded that in most countries about 40% of RGC is accounted for by startups 1–2 years old. Among companies over 21 years old, the share of RGC practically does not exceed 20% (with the exception of Ethiopia – 22%). Despite the fact that the growth potential is really most often higher among young companies, this does not always mean that RGC is concentrated among small and medium-sized firms. World Bank research shows that RGC can be found among all categories of company size. In general, a review of RGC identification results using OECD criteria shows that their share in the total number of companies in developed countries varies from less than 2% (Austria, Germany, Italy, the Netherlands), to 6% (Finland, Sweden, UK, USA, Spain), to 10% (South Korea). Studies also show that using the OECD criterion (income) and the requirement of a minimum staff of 15 people, on average, the share of RGC is about 5–6% of the total number of companies. Moreover, such a conclusion is the same for developed and developing countries (African countries) (Goswami, 2019). Comparison of RGC samples obtained using different criteria leads to the need to solve the problem of taking into account the “multifactorial” economic growth in identifying RGC. In such a way, in the work (Delmar, 2013), based on the analysis of 19 growth indicators over a 10-year period, it was shown that company growth can manifest itself in different ways, in different indicators. In this regard, the use of one criterion as a measure limits the selection of RGC to only one possible option. Therefore, we also consider it possible to use the Birch index as a criterion, significantly expanding the sample of RGC compared to the OECD criterion (number). Another “stratum” in the analysis of DBK identification criteria and factors is market and industry analysis. The characteristics of market formation can influence the growth of the amount of RGC, for example, through concentration/deconcentration processes. Therefore, the concentration of the market on the principle of “grow or leave” leads to the fact that enlarging companies displace their less effective competitors, occupying their market shares and increasing their own growth rates (Kay, 2019). Reverse processes can lead to an increase in the number of companies in high-yield market segments, which causes increased competition and distribution of the overall growth potential among many companies and, as a result, a decrease in the number of potential RGC. The industry analysis of RGC composition emphasizes that individual business areas may be at different stages of the life cycle (Volovikov, 2015) and, therefore, have different growth potentials. At the same time, the widespread opinion about the greater likelihood of RGC in high-tech industries is not unequivocally confirmed (Goswami, 2019). However, these two aspects of RGC identification analysis remain little understood to date. Thus, the definitions and criteria for identifying RGC can vary significantly, focusing on certain...
