Innovative activity is an important source of competitiveness, economic growth, as well as the image of each country. There are several ways to measure and evaluate the innovation performance of a country. Our research was focused on the summary innovation index (SII), a tool used for analysing the innovative ability of European countries. The Innovation Union is an EU initiative which monitors progress achieved in research, development, and innovation, all indicators which are included in the SII. The aim of this paper is to analyse the impact of all SII 27 indicators, which are divided into 10 main areas: human resources, research systems, innovation-friendly environment, finance and support, firm investments, innovators, linkages, intellectual assets, employment impacts, sales impacts. All these indicators are considered in creating the total value of the SII. A statistically significant relationship was determined among all the SII indicators and the total value of the SII using samples from the V4 countries of Czech Republic, Slovakia, Hungary, and Poland during the period 2010-2016. The aim of the research was to identify possible strengths and weaknesses of the national innovation systems of these countries and, thus to identify the impact of these strengths and weaknesses on the innovative position of these countries.
Research background: There are many consultative groups and market research companies on the market that have also brand valuation included in their service portfolios. Such companies tend to adopt their own unique approaches to value brands to face increasing competition, which is also reinforced by the fact that brand constitutes the company's most valuable commercial and intangible assets. The paper compares selected internationally recognized brand valuation methods, using the mathematical statistics apparatus (Pearson and Spearman correlation coefficients), on the sample of 12 global well-known brands (Apple, Google, Microsoft, Coca-Cola, Facebook, Toyota, IBM, Disney, McDonald's, General Electric, Samsung and Amazon). Purpose of the article:The aim is to analyze the brand values and the methods applied for possible deviations, and identify whether they are statistically significant and/or find any statistical correlation, or eventually recognize them as totally different and independent approaches. Methods: The analysis is carried out by pairwise comparison of selected brand values provided by selected consultative companies (Forbes, Interbrand, Brand Finance and Millward Oeconomia Copernicana, 8(1),(99)(100)(101)(102)(103)(104)(105)(106)(107)(108)(109)(110) Brown). The degree of correlation of brand values provided by respective consultative groups is calculated using the following correlation coefficients: Pearson's correlation coefficient and its modified non-parametric version involving ordinals -Spearman's rank correlation coefficient. Findings & Value added:The analysis proved the highest correlation of the brand values provided by the Forbes and Interbrand; Subsequently, a trend analysis is carried out to determine the development over time, identifying the most striking development in the brand values provided by Millward Brown (BrandZTM) for the period 2013-2016.
Brand is considered to be one of the most important assets of any company and therefore determination of its value is of a great importance. There are many methods for determining brand value. Each of them is based on different inputs that determine the resulting brand value. The aim of this paper is to test the selected financial indicators that we expect to significantly affect the resulting value of a brand. In our research, we tested whether there is a statistically significant relationship among 20 selected financial indicators and the value of the brands of five companies in the automotive industry (Honda, BMW, Toyota, Daimler, Nissan), while we took into account three different brand values calculated by three consulting groups (Interbrand, Brand Finance, Millward Brown). After application of the selected statistical methods (correlation analysis and hypothesis testing of the correlation coefficient), we concluded that there exists a strong positive linear statistical relationship between the value of brand and revenue. Also, we observed a strong negative linear statistical relationship between brand value and free cash flow. Through application of hypotheses' testing of correlation coefficients we have proved that it is inappropriate to take hasty conclusions based on the use of only one statistical method, as in the case of our research, we greatly reduced our previous results by applying an additional statistical system.
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