Search

Research background: Currently the topic of a company’s intellectual capital is being widely investigated by various researchers. Nevertheless, only a small number of studies on the compa-ny’s intellectual capital impact on its market value were conducted. What is more, the concept of a company’s intellectual capital itself is not unified. There are some discrepancies in defining a company’s intellectual capital, unifying structural model of the company’s intellectual capital, and harmonizing the research methods and models of how to evaluate a company’s intellectual capital. Purpose of the article: The aim of the article is to examine various scientific approaches of the company’s intellectual capital and its impact on the market value of a respective company; to prepare a model of company’s intellectual capital and its impact on the market value. What is more, the aim of this article is to check and test the model effectiveness using an example of the Baltic States listed companies. Methods: Data on 58 Baltic States’ companies that are listed in Nasdaq Baltic stock exchange were taken as the basis of the research. Based on four component model (human capital, structural capital, juridical capital, relational capital) a set of indicators for assessing company’s intellectual capital was formed. Expert evaluation was used in order to assign weights for different structural parts of intellectual capital. An exploratory factor analysis was conducted in order to find out what factors are the most significant for a company’s intellectual capital. In order to find out how specific elements affect company’s intellectual capital, a pair-wise multiple correlation and re-gression analysis were used. An average comparison method was used to reveal differences between companies of different countries. Findings & Value added: The study contributes to the Baltic States’ knowledge on intellectual capital. It was detected that it is appropriate to use human capital, structural capital, juridical capital, and relational capital structural parts as components of company’s intellectual capital while investigating its impact on market value of a respective company. According to the ob-tained results, the model of a company’s intellectual capital and its impact on the market value was created, optimized, and its validity checked using exploratory factor analysis. The model was used to test the Baltic States listed companies and how their intellectual capital affects the market value. It was identified that intellectual capital in the listed companies of the Baltic States has a positive impact on their market value. Nevertheless, the study revealed that intellectual capital structural parts do not equally affect the market value of listed companies. The findings support the conclusion that human capital and relational capital have the greatest influence on the market value of listed companies. Companies where structural capital comprises the largest proportion of intellectual capital had lower levels of intellectual capital aggregated index, which could be exam-ined in future studies. Keywords: intellectual capital; human capital; structural capital; juridical capital; relational capital; market value.

Research background: Importance of intangible resources for country’s economic growth is widely recognized. However, empirical evidence of this influence is hard to show due to measurement limitations of intangible resources. Majority of empirical studies concentrates on the analysis of a specific type of intangible resource’s influence on economic growth. National intellectual capital concept provides background for an integrated assessment of the country's intangible resources. This new approach enables the estimation of intangible resources’ influence to economic growth in a more complex way. Purpose of the article: a) To examine various scientific approaches of the national intellec-tual capital and its impact on the economic growth; b) to offer a measurement model of the national intellectual capital influence on economic growth; c) to evaluate the specific Euro-pean Union countries’ intellectual capital’s effect on their economic growth. Methods: Econometric analysis; refined factor value computation method using the stand-ardized regression coefficients; the SAW method; expert evaluation, cluster analysis; corre-lation and regression analyses. Findings & Value added: A review of the economic growth theories showed that structural components of intellectual capital (human capital, structural capital, social capital, relational capital) in economic growth theories are analyzed as key determinants of economic growth. Our proposed research methodology consists time lag between variables and this let us evaluate casual relation. Empirical analysis of 25 European Union countries’ intellectual capital’s effect on their economic growth rate revealed that national intellectual capital and the countries’ level of economic development have statistically significant impact on eco-nomic growth rate. The analysis of intellectual capital components’ influence on economic growth rate of 25 European Union countries showed that only human capital and the level of economic development have statistically significant influence. A more comprehensive hu-man capital’s influence on economic growth analysis revealed that 63.1 percent of the long-term economic growth rate in 25 European Union countries can be explained by differences in their economic development level and differences in educational achievement factor values. Moreover, analysis of national intellectual capital effect on economic growth in separate clusters allowed to identify influence differences in each group of countries. Keywords: national intellectual capital; human capital; structural capital; social capital; relational capital; economic growth.

The relationship between the Economic growth and Energy Sector performance is unquestionable. Honewer it is not an easy task to evaluate the strength of this relationship. The majority of scientists are investigating the impact of certain Energy Sector’s activities on the overall energy consumption, climate change or Economic growth. This article analyzes the influence of Energy Sector to GDP of Lithuania. The objective of the research is to show how the results of Lithuanian Energy Sector in 2005 – 2015 have been changed and to determine their impact on GDP. The concept of Energy Sector is presented first. Secondly, a methodology for analyzing the performance of the Economic growth and Energy Sector is described. Thirdly, the analysis of the activities of Energy Sector and its influence on GDP has been analyzed. The proposed model of the impact of the Energy Sector's activities on the growth of GDP in the article combines six main aspects of the research: participants in the Energy Sector; Energy balance indicators; Changes in energy product prices; The value added created by the Energy Sector; The main taxes paid by Energy Sector as part of the National budget revenue; The net profitability of the Energy Sector. This model is applicable for analyzing the aggregate performance indicators of Energy Sector and its impact on the growth of GDP. Hypothesis of this research - Lithuanian energy sector has a statistically significant influence on GDP. The findings showed that GDP and Energy Sector indicators, after a year of crisis, tended to grow. But the impact of these indicators on GDP is weak. However, particularly high correlation ratios between them may indirectly affect the change in GDP.

The purpose of this article is to assess exchange rate forecasting possibilities with an information flow approach model. In the model the three types of information flows are distinguished: fundamental analysis information flow through particular macroeconomic determinants, microstructure approach information flow through dealer clients’ positioning data, technical analysis information flow through technical indicators. By using regression analysis it is shown that the composed model can forecast the exchange rate, the most significant information flows are distinguished. The results lead to further development of the information flow approach as a tool to forecast exchange rate fluctuations.

The Assess Model of Intellectual Capital and a Company's Value Added CohesionNowadays intangible assets are especially important in every company and can help to increase a company's value added. The importance is so huge that many companies invest more money in intellectual capital than in material assets. Why has this happened? Scientists answer this question very quickly and easily - many companies have already been disappointed and damaged by their materials, goods, equipment, buildings, cars, machinery that cost a lot of money but do not give effective productivity. On the contrary, intellectual capital that usually costs only the salary of an employee brings significant benefits.The research purposeis to evaluate the cohesion between intellectual capital and a company's value added and to provide the model of this cohesion.The methods usedare analysis of scientific literature, GBN matrix method, expert evaluation, average comparison method, and Kendall's coefficient of concordance.Scientific aims:to reveal the cohesion between intellectual capital and a company's value added; to introduce a model of a company's value added and its intellectual capital; to demonstrate the results of expert evaluation on the model of intellectual capital and a company's value.The findingsare as follows: intellectual capital is considered as a unit of social capital, communicational capital, and psychological capital; intellectual capital has a huge influence for the growth of a company's value added; employee motivation is the most important factor either for the growth of intellectual capital or a company's value added.Conclusions:expert evaluation was performed in order to investigate the importance of intellectual capital factors for the growth of intellectual capital itself and a company's value added. Experts were taken from two areas: business environment and academic environment. It is possible that experts from other environments could answer the questions in a completely different way, and this model could be improved even more.

The importance of small and medium-sized business companies has always been indisputable. Governments are trying to facilitate the entrance into a marketplace; the activity itself and managers are able to administer their companies in their best manner. Despite these facts, the changing environment has made a strong impact on all companies all over the world. In addition to this, nowadays it is not enough just to have a sack of tangible assets in order to have huge company’s value added. The modern century of new technologies, the importance of knowledge and information brought a new attitude to the company. The value added, which is created by the company, depends not only on tangible assets but also on intangible assets, which, by the way, are among the most important in a new modern company. Intellectual capital is intangible, hardly measurable, but plays a vital role in every company’s value added. This paper is aimed at analysing this company’s value added and its intellectual capital coherence, and the model of new company’s value added and its intellectual capital coherence is proposed. &nbsp

Valstybės gebėjimas kurti inovacijas ir atlikti aukštos pridėtinės vertės funkcijas priklauso nuo valstybės intelektinio kapitalo. Nustatyti valstybės intelektinio kapitalo vertę – vis dar sudėtinga užduotis. Šiame straipsnyje analizuojama valstybės intelektinio kapitalo koncepcija ir vertinimo metodai, siekiant parodyti būdus, kaip valstybės intelektinis kapitalas gali būti įvertintas. Tyrimo rezultatai atskleidžia taikomų vertinimo modelių validumo trūkumą. Šie trūkumai naujausiuose vertinimo modeliuose minimizuojami taikant sudėtingas valstybės intelektinio kapitalo klasifikacijos sistemas ir pažangius valstybės intelektinio kapitalo vertės apibendrinimo metodus. Pasirinktų valstybės intelektinio kapitalo modelių analizė atskleidė, kad jų vertinimo sistemoje tapačių rodiklių naudojama nedaug (nuo 21 iki 60 proc.), tačiau valstybės intelektinio kapitalo vertė, nustatyta taikant skirtingus vertinimo modelius, yra panaši (rezultatai yra aukšto statistiškai reikšmingo koreliacijos lygio). National intellectual capital is regarded as an important factor of a country’s ability to perform high value added functions including the ability to create innovations. Measuring national intellectual capital is still a complicated task. In this article national intellectual capital concept and measurement models are analysed in order to show how national intellectual capital could be measured. The findings show that there are several weaknesses of measurement models validity. Those weaknesses in more recent measurement models are minimized by introducing advanced national intellectual capital structural models and more complex value approximation methods. Analysis of selected national intellectual capital measurement models has shown that there are not many similar indicators used (from 21% to 60% of matching indicators), though results obtained by using these evaluation models have high significant correlation.

The article analyses creativity and innovativeness in organisations of service business in Lithuania. Relation between creativity and innovativeness is given, and concepts of creativity and innovativeness, as well as the main research models, are presented. Statistical data and questionnaire survey data analyses are used for the research of the factors of creativity and innovativeness in Lithuania. Research results have shown that more than half of the organisations of the service sector in Lithuania are assessed as not creative; also factors that stimulate creativity are not sufficient for the development of creativity. It is necessary to create a work environment favourable for innovations that would help reveal and develop the creativity of human capital.

Straipsnyje siekiama pateikti, kaip socialinis kapitalas gali gerinti įmonės verslo procesus, kaip naudojamas verslo tikslais socialiniuose tinkluose ir kurie veiksniai naudos aspektu yra vertingiausi. Pirmojoje šio straipsnio dalyje buvo nagrinėjama socialinio kapitalo teorija ir pagrindiniai koncepciniai požiūriai. Remiantis teorine analize, buvo identifikuota socialinio kapitalo koncepcija ir veiksniai. Antrojoje straipsnio dalyje buvo tiriama socialinio kapitalo vertė įmonių verslo procesams, pabrėžiant ne tik socialinio kapitalo sukuriamą vertę, bet ir riziką, kuri gali atsirasti, jei socialinis kapitalas netinkamai naudojamas. Paskutinėje straipsnio dalyje pateiktas socialinio kapitalo įmonės verslo procesų naudos modelis ir įvertinti tiesiogiai su šiuo procesu susiję veiksniai This paper aims to present how social capital can benefit business processes of an enterprise, which uses its social networks for business purposes, and which of those benefits are the most important in this context. The first part of this article represents the theory of social capital. The main conceptual approaches to social capital were investigated. According to this, the conception of social capital and its dimensions were introduced. The second part of this paper seeks to evaluate the benefits of social capital to enterprise's business activities by mentioning not only benefits, which create social capital but also risks, which can occur if social capital is used improperly. The last part of this essay introduced the model of social capital's benefits to enterprise's business processes and evaluated, which of them are the most relevant

This paper is devoted to a review of the Multicriteria Framework of financial decisions of bank loan portfolio management as a financial model supporting financial decision-making, which builds pointed models taking into account the peculiarities of a problem. The goal here is to bridge the gap between decision-making disciplines of financial economics and the need for adequate decision support. Finance has traditionally recognized the two-objective situation of risk versus return, with the fundamental goal of wealth maximization. However, not well known are the new ways of approaching financial problems when three or more criteria exist. The modern portfolio management approach involves complex goals where they interact with one another; each has its own possible interpretation of wealth maximization, subjects to concern about risk, safety, liquidity, profitability, social responsibility, environmental protection, employee welfare, and so on. Consequently, it may well be appropriate to pursue a multiple objective approach to many financial decision-making problems. This article is concentrated upon building up a model with multicriteria analysis that provides financial decision makers and analysts with a wide-range methodology well suited to the complexity of modern bank loan portfolio management decision-making.

This research shows how U.S. and German government bond yields can determine the EUR/USD exchange rate in the short run. After presenting the discussion on fundamental, technical and microstructure approach exchange rate determination models, a conclusion is made that out of the components of fundamental models the interest rates could be the best determinants for explaining exchange rate fluctuations in the short term. For the research the mostly traded currency pair, the EUR/USD, was chosen and 2-year, 10-year U.S. and German government bond yields were selected as determinants of the exchange rate. After performing the linear regression procedure it has shown that the model can determine 5 per cent of the daily EUR/USD fluctuations with a change in 2-year U.S. government debt yield being the greatest determinant in the model. It affects the exchange rate as it is stated in the uncovered interest rate parity model – when the yield increases, the USD declines against the euro and vice versa. Another finding is that an increase in the German 10-year government bond yield increases the price of the euro and the increase in the U.S. 10-year debt yield leads to an appreciation of the USD.