International Journal of Technology (Mar 2025)
Market Valuation of High-Tech Companies in the IT and Automotive Industries: A Regression Analysis of Key Factors
Abstract
The market value of a company is a key performance indicator for any modern business. The issue of market value growth is particularly relevant for high-tech companies, which serve as the leading drivers of digital economy development. Therefore, this study aimed to identify and analyze the key factors influencing the market value of high-tech companies. Using regression analysis tools and STATA 14.2 statistical software, econometric models were developed to describe the relationship between a company's market value and various influencing factors in two high-tech industries namely automotive and information technology (IT). To construct a multiple linear regression model, market capitalization was selected as the dependent variable (Y) while 15 indicators—including economic value added (EVA), equity capital, revenue, profit, number of employees, Research and Development (R&D) costs, goodwill, and intangible assets—were chosen as explanatory variables. Furthermore, this study was based on 10 years of panel data (2013–2022) from 25 listed automotive and IT companies each all of which were global leaders by market capitalization. Ordinary least squares regression models (OLS) with a high degree of fit were constructed for each industry. The results of the regression analysis showed that the models possessed high explanatory power with R-square values of 0.958 for the automobile industry and 0.921 for the IT industry. These figures suggested that 95.8% and 92.1% of the variance, respectively, could be explained and predicted by the obtained regression equations while avoiding issues of multicollinearity (strong linear dependence between independent variables) and heteroscedasticity in random errors. The study showed that the main common factors significantly impacting the market capitalization of high-tech IT and automotive companies were EVA and share price. However, R&D expenses and intangible assets were found to have no significant impact on market value of high-tech companies. Beyond the shared key factors, industry-specific factors influencing market capitalization were also identified for each sector. The high explanatory power of the obtained models allowed the framework to be used as an effective tool for managing, analyzing, and forecasting the value of IT and automobile companies.
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