PurposeThe different models have been used in recent intellectual capital (IC) studies to understand better the outcome of company intangible asset components. The purpose of this paper is to develop and apply the index of IC of construction companies in relation to the growth of their net profit.Design/methodology/approachEvaluation of the relationship between an IC index and company net profit employs a scoring method of evaluation of individual components of IC, which include human capital, investment capital, process capital, relations capital and management styles. The correlation method, based on rank correlation index, has been used to calculate the strength and character of the relationships.FindingsA quantitative method of evaluation of qualitative components of IC has been developed as well as a way of finding a relationship between the quality of IC and the growth of net profit earned by a company. The obtained findings support the hypothesis: the higher the value of IC, the greater the net profit growth.Research limitations/implicationsThe paper covers the procedure of measuring IC, determination of its effect on company results and creating IC in the context of long‐term competitiveness.Practical implicationsThe method can be applied by construction companies in order to determine the value of intellectual assets and to assess how they influence profit growth.Originality/valueThe solutions presented in the paper provide an approach to qualitative assessment of intellectual assets, in the strategic and universal aspect.
It is generally agreed that successful firms need to utilize all of their assets properly in order to gain a competitive advantage. However, little attention has been paid in business to proper utilization of tacit knowledge, a subset of intangible assets, because no specialized attempt has been made to quantify it. Once a value has been assigned to an asset, it is more easily utilized in the proper way. This paper analyzes the use of tacit knowledge in pharmaceutical industry, presents a graphical model of tacit knowledge, and finally presents and uses a simplified mathematical model that could be useful in quantifying tacit knowledge. The mathematical model was applied in the empirical study of multibillion dollar acquisition of Genentech by Hoffman La-Roche AG. The model gives a good estimation of the value of the tacit knowledge contained in the firm, which is an important contribution to the field of finance. The quantification of tacit knowledge could be extremely beneficial for managers of pharmaceutical firms who have extremely high levels of tacit knowledge in the form of knowledge workers. By quantifying tacit knowledge, managers can get a better understanding of the real value of their firm or of the value of a firm that may be a target for acquisition.
This study relies on a calculable and essential analysis of a statistically oriented regression model. Ninety-five variables taken into consideration in this research were grouped into four categories. The first category covers the general macroeconomic situation, the second is devoted to crime, the third is formed by characteristics of income and living conditions, and the fourth one applies to the taxation system. The Multiple Indicators Multiple Causes (MIMIC) model was employed to measure the level of shadow economy in Poland and in Lithuania during 2000-2019. The MIMIC model depends on Structural Equation Models. The MIMIC approach allows one to assess shadow economy as a latent variable. The observed factors are government employment/labor force, tax burden, subsides/GDP, social benefits paid by government/GDP, self-employment/GDP, and unemployment rate. The Pearson correlation index was used to size up the correlation between independent variables, and Kolmogorov–Smirnov (KS) test for normality of residuals was applied. In both countries, factors affecting the shadow economy performance show great similarity. The shadow economy development in Poland and in Lithuania is fostered by many different factors, related to, but not limited to, the general macroeconomic situation. In fact, the economic situation is associated with the standard of living, income as well as the crime rate. Important factors are associated with the taxation system. The results demonstrate that the regression model can be used to predict the shadow economy development and performance in Poland and in Lithuania. Such information facilitates taking adequate steps in order to minimize the shadow economy level in both countries. Such implications are very useful for decision makers in shaping the legal and economic progress in both countries.
The purpose of this paper is to recognize the correlation among dimensions of national culture and the shadow economy. Shadow economy exists in any country and it is fostering economic development. That is why not only academics but also researchers try to identify the factors affecting the shadow economy level. In literature and research studies relatively insignificant attention is paid to the relation between national culture and shadow economy. In order to identify the relation, the correlation analysis and Hofstede's categorized national culture dimensions were used. Shadow Economy (as a percentage of the official GDP) was calculated based on the DYMIMIC and the Currency Demand Method. The Pearson's coefficient index, and t-student test were used, as well. The correlation analysis revealed the correlation between the shadow economy and the following: the dimensions of national cultural power distance, uncertainty avoidance, and individualism vs. collectivism. There is a slight correlation between the shadow economy and masculinity vs. femininity. This is a novel empirical analysis of the shadow economy existing among the dimensions of national culture. Based on the achieved results there is a requirement to shape national culture. Thanks to that the level of shadow economy might be reduced. The unexpected findings of high correlation between some national cultural dimensions suggest the need for more research in this area.
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